{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hLUuW5pTJuPT",
        "outputId": "42b83dd7-f75c-48da-cdc9-bd76ebd7512c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Collecting wandb==0.15.12\n",
            "  Using cached wandb-0.15.12-py3-none-any.whl (2.1 MB)\n",
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            "\u001b[?25hCollecting docker-pycreds>=0.4.0 (from wandb==0.15.12)\n",
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            "  Downloading pathtools-0.1.2.tar.gz (11 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting setproctitle (from wandb==0.15.12)\n",
            "  Downloading setproctitle-1.3.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (30 kB)\n",
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            "Collecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->GitPython!=3.1.29,>=1.0.0->wandb==0.15.12)\n",
            "  Downloading smmap-5.0.1-py3-none-any.whl (24 kB)\n",
            "Building wheels for collected packages: pathtools\n",
            "  Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pathtools: filename=pathtools-0.1.2-py3-none-any.whl size=8791 sha256=64de6a66e8b36654f7a0eedc926778646639da9d0872a196c03ba200aab96057\n",
            "  Stored in directory: /root/.cache/pip/wheels/e7/f3/22/152153d6eb222ee7a56ff8617d80ee5207207a8c00a7aab794\n",
            "Successfully built pathtools\n",
            "Installing collected packages: pathtools, smmap, setproctitle, sentry-sdk, docker-pycreds, gitdb, GitPython, wandb\n",
            "Successfully installed GitPython-3.1.43 docker-pycreds-0.4.0 gitdb-4.0.11 pathtools-0.1.2 sentry-sdk-2.2.1 setproctitle-1.3.3 smmap-5.0.1 wandb-0.15.12\n",
            "Collecting ultralytics==8.0.186\n",
            "  Using cached ultralytics-8.0.186-py3-none-any.whl (618 kB)\n",
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            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (3.3)\n",
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            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (2023.6.0)\n",
            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
            "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
            "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
            "Collecting nvidia-nccl-cu12==2.20.5 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
            "Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics==8.0.186) (2.3.0)\n",
            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.8.0->ultralytics==8.0.186)\n",
            "  Using cached nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from cycler>=0.10->matplotlib>=3.3.0->ultralytics==8.0.186) (1.16.0)\n",
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            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.8.0->ultralytics==8.0.186) (1.3.0)\n",
            "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, ultralytics\n",
            "Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105 ultralytics-8.0.186\n"
          ]
        }
      ],
      "source": [
        "!pip install roboflow\n",
        "!pip install wandb==0.15.12\n",
        "!pip install ultralytics==8.0.186"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W4bpYoXPdICN"
      },
      "source": [
        "# Download Dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k2a4POcLdKPd"
      },
      "source": [
        " I downloaded the dataset from Kaggle, and re-upload it to Roboflow. This dataset contains 807 images with 3,856 bounding boxes of 3 classes:\n",
        "* `mask_weared_incorrect`\n",
        "* `with_mask`\n",
        "* `without_mask`\n",
        "\n",
        "After augmentations, the adataset are multiplied 3x into a total of 1,937 images.\n",
        "\n",
        "**Note**: You need to insert your Roboflow API key to run the cell below."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "hK2DcESMHFwD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "55b5b3ab-c530-4b69-d4eb-1a21a25f7ffc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "··········\n",
            "loading Roboflow workspace...\n",
            "loading Roboflow project...\n",
            "Dependency ultralytics==8.0.196 is required but found version=8.0.186, to fix: `pip install ultralytics==8.0.196`\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading Dataset Version Zip in Face-Mask-Detection-1 to yolov8:: 100%|██████████| 122925/122925 [00:07<00:00, 15438.04it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "Extracting Dataset Version Zip to Face-Mask-Detection-1 in yolov8:: 100%|██████████| 3886/3886 [00:01<00:00, 2398.11it/s]\n"
          ]
        }
      ],
      "source": [
        "from getpass import getpass\n",
        "from roboflow import Roboflow\n",
        "\n",
        "rf = Roboflow(api_key=getpass())\n",
        "project = rf.workspace(\"manfred-michael\").project(\"face-mask-detection-4zoki\")\n",
        "version = project.version(1)\n",
        "dataset = version.download(\"yolov8\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VAvLch8RecBl"
      },
      "source": [
        "The dataset would be splitted into 3 parts when we download it."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9j2UItKteX5Q"
      },
      "source": [
        "![image.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SofVDqFBw5Oq"
      },
      "source": [
        "All images in this dataset are already resized into 640x640 and it also includes augmented samples. So, I don't need to do any data preparation. Roboflow handled everything for me.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zO5bJpTMw5Oo"
      },
      "source": [
        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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JCYjNpydw5Os"
      },
      "source": [
        "# Model Training"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9eJha2Kyw5Os"
      },
      "source": [
        "I will use ultralytics to train YOLOv8, and WandB to monitor the training process. This wandb tracking implementation includes some advanced features that we will see shortly."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# !pip install wandb"
      ],
      "metadata": {
        "id": "bOs6W9wX763m"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "A79lfQaaQxY4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ca66bfda-aef9-4865-ee23-646227e0d39e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING ⚠️ 'ultralytics.yolo.v8' is deprecated since '8.0.136' and will be removed in '8.1.0'. Please use 'ultralytics.models.yolo' instead.\n",
            "WARNING ⚠️ 'ultralytics.yolo.utils' is deprecated since '8.0.136' and will be removed in '8.1.0'. Please use 'ultralytics.utils' instead.\n",
            "Note this warning may be related to loading older models. You can update your model to current structure with:\n",
            "    import torch\n",
            "    ckpt = torch.load(\"model.pt\")  # applies to both official and custom models\n",
            "    torch.save(ckpt, \"updated-model.pt\")\n",
            "\n"
          ]
        }
      ],
      "source": [
        "import wandb\n",
        "from wandb.integration.ultralytics import add_wandb_callback\n",
        "from PIL import Image\n",
        "\n",
        "from ultralytics import YOLO"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310,
          "referenced_widgets": [
            "2146f10769064170acce6e7e8335cebd",
            "be657624c5ea43c199921c4382f7a958",
            "ae90885359d24008a3fd13e846a22246",
            "9b71788bd91f46269093c90e8fb71c0c",
            "fd1ba992d244494c972f0f97b775a0a7",
            "f9879c9d97704b37b8d6c1fff1677d97",
            "be3b792ad0714dfda173bd1a08979f74",
            "86eaffd1aa4c47c0ba920352eb4551a5"
          ]
        },
        "id": "mZzOItry66VU",
        "outputId": "75f83701-6ed4-4760-e822-03eae536adce"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Finishing last run (ID:bw243key) before initializing another..."
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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              " View run <strong style=\"color:#cdcd00\">copper-oath-3</strong> at: <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/bw243key' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/bw243key</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
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              "Find logs at: <code>./wandb/run-20240522_071908-bw243key/logs</code>"
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              "Successfully finished last run (ID:bw243key). Initializing new run:<br/>"
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              "<IPython.core.display.HTML object>"
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              "wandb version 0.17.0 is available!  To upgrade, please run:\n",
              " $ pip install wandb --upgrade"
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              "Tracking run with wandb version 0.15.12"
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              "Syncing run <strong><a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/p127dd66' target=\"_blank\">ethereal-grass-4</a></strong> to <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
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              " View run at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/p127dd66' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/p127dd66</a>"
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        "wandb.init(project=\"verihubs-tech-assessment\", job_type=\"training\")"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3QhRD12ABwT3",
        "outputId": "b7597b66-87a1-4d14-9fa7-888085361f27"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Ultralytics YOLOv8.0.186 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "Setup complete ✅ (2 CPUs, 12.7 GB RAM, 30.2/78.2 GB disk)\n"
          ]
        }
      ],
      "source": [
        "import ultralytics\n",
        "ultralytics.checks()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OjpabMQqw5Ot"
      },
      "source": [
        "I trained YOLOv8 for 10 epochs."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2iFRJbtnQ6f8",
        "outputId": "335d9641-7335-4439-f15d-9278d4bc527f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[1;30;43mOutput streaming akan dipotong hingga 5000 baris terakhir.\u001b[0m\n",
            "      28/80      8.54G       1.09      0.576      1.107         71        640: 100%|██████████| 106/106 [00:59<00:00,  1.79it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.25it/s]\n",
            "                   all        161        861      0.842      0.769      0.808      0.518\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 22 with_masks, 5 without_masks, 47.9ms\n",
            "Speed: 1.7ms preprocess, 47.9ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 1 with_mask, 7 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 with_mask, 3 without_masks, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 4 with_masks, 6 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.4ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 2 without_masks, 37.3ms\n",
            "Speed: 2.1ms preprocess, 37.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 8 with_masks, 1 without_mask, 37.3ms\n",
            "Speed: 2.3ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 12 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 5 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 4 without_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 25 with_masks, 4 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 1 without_mask, 37.3ms\n",
            "Speed: 1.9ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      29/80       8.6G      1.077     0.5726      1.101        103        640: 100%|██████████| 106/106 [00:58<00:00,  1.82it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.83it/s]\n",
            "                   all        161        861      0.881      0.753      0.825      0.539\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 38.3ms\n",
            "Speed: 5.0ms preprocess, 38.3ms inference, 9.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 2.4ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 2 mask_weared_incorrects, 10 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 2 mask_weared_incorrects, 2 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 21 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 14 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 9 without_masks, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.4ms\n",
            "Speed: 2.0ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 10 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.6ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.4ms\n",
            "Speed: 2.0ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 5 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 5 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 6 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      30/80      8.64G      1.076     0.5669      1.098         86        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.73it/s]\n",
            "                   all        161        861      0.902      0.709      0.812      0.525\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 10 with_masks, 41.6ms\n",
            "Speed: 7.2ms preprocess, 41.6ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      31/80      8.72G      1.071     0.5658      1.102        115        640: 100%|██████████| 106/106 [00:59<00:00,  1.79it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.53it/s]\n",
            "                   all        161        861      0.799      0.751      0.786      0.497\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 38.5ms\n",
            "Speed: 3.9ms preprocess, 38.5ms inference, 11.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 5.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 15 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.3ms\n",
            "Speed: 1.8ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 108 with_masks, 23 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 2 mask_weared_incorrects, 21 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 3 mask_weared_incorrects, 10 with_masks, 6 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 1.7ms preprocess, 37.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 8 with_masks, 7 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 3.0ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 9 with_masks, 4 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 2 with_masks, 1 without_mask, 38.2ms\n",
            "Speed: 1.8ms preprocess, 38.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 8 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 (no detections), 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      32/80      8.79G      1.071     0.5651      1.096        106        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.22it/s]\n",
            "                   all        161        861      0.836      0.805      0.828      0.527\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 38.5ms\n",
            "Speed: 1.7ms preprocess, 38.5ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 10 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 16 with_masks, 5 without_masks, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.5ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 2 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 38.1ms\n",
            "Speed: 1.8ms preprocess, 38.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 1.9ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 4.1ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 38.3ms\n",
            "Speed: 2.1ms preprocess, 38.3ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      33/80      8.85G      1.046     0.5498      1.083         93        640: 100%|██████████| 106/106 [01:00<00:00,  1.75it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.02it/s]\n",
            "                   all        161        861       0.87       0.79      0.824      0.519\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 2 with_masks, 44.8ms\n",
            "Speed: 1.7ms preprocess, 44.8ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 21 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 3 mask_weared_incorrects, 10 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 1 mask_weared_incorrect, 14 with_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 9 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 6 without_masks, 37.1ms\n",
            "Speed: 2.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 1 mask_weared_incorrect, 4 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 1 mask_weared_incorrect, 43 with_masks, 6 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.4ms\n",
            "Speed: 2.2ms preprocess, 37.4ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 3 without_masks, 37.1ms\n",
            "Speed: 2.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 13 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 15 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 5 without_masks, 37.2ms\n",
            "Speed: 1.6ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 11 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      34/80      8.86G      1.049     0.5441      1.084        131        640: 100%|██████████| 106/106 [01:00<00:00,  1.75it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.17it/s]\n",
            "                   all        161        861      0.821      0.718      0.785      0.507\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 20 with_masks, 2 without_masks, 51.5ms\n",
            "Speed: 1.9ms preprocess, 51.5ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 40.8ms\n",
            "Speed: 3.9ms preprocess, 40.8ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.7ms\n",
            "Speed: 1.9ms preprocess, 37.7ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 2.1ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 38.1ms\n",
            "Speed: 1.9ms preprocess, 38.1ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 4 with_masks, 2 without_masks, 38.9ms\n",
            "Speed: 2.0ms preprocess, 38.9ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.7ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 40.9ms\n",
            "Speed: 1.8ms preprocess, 40.9ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 6 with_masks, 1 without_mask, 38.0ms\n",
            "Speed: 3.5ms preprocess, 38.0ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 3 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 2.4ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 3.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 19 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      35/80       8.9G       1.02     0.5384      1.081         56        640: 100%|██████████| 106/106 [00:59<00:00,  1.78it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.87it/s]\n",
            "                   all        161        861       0.84      0.787      0.827      0.518\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 2 with_masks, 38.6ms\n",
            "Speed: 1.7ms preprocess, 38.6ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 12.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 1 without_mask, 37.4ms\n",
            "Speed: 2.2ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 4.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 2 with_masks, 1 without_mask, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 17 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 3.2ms preprocess, 37.2ms inference, 4.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 1 mask_weared_incorrect, 11 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 11 with_masks, 10 without_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 4.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 39.2ms\n",
            "Speed: 1.7ms preprocess, 39.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 4.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 10 with_masks, 39.0ms\n",
            "Speed: 1.9ms preprocess, 39.0ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 4.9ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 4 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      36/80      9.03G      1.026     0.5305      1.074        122        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.19it/s]\n",
            "                   all        161        861      0.785      0.767      0.797      0.497\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 14 with_masks, 49.0ms\n",
            "Speed: 2.9ms preprocess, 49.0ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      37/80      9.07G      1.014     0.5258      1.072         91        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.35it/s]\n",
            "                   all        161        861      0.855      0.808      0.845      0.534\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 45.7ms\n",
            "Speed: 2.0ms preprocess, 45.7ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 14 with_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 102 with_masks, 16 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 3.1ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 3 mask_weared_incorrects, 7 with_masks, 7 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 4.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 6 with_masks, 6 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 11 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 8 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 2.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      38/80      9.11G      1.018     0.5264      1.065        132        640: 100%|██████████| 106/106 [00:59<00:00,  1.78it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.27it/s]\n",
            "                   all        161        861      0.875      0.756       0.82       0.51\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 39.4ms\n",
            "Speed: 4.1ms preprocess, 39.4ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.6ms\n",
            "Speed: 2.7ms preprocess, 37.6ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 9 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 39.4ms\n",
            "Speed: 1.9ms preprocess, 39.4ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 6 with_masks, 37.3ms\n",
            "Speed: 2.2ms preprocess, 37.3ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 5.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 10 with_masks, 5 without_masks, 37.2ms\n",
            "Speed: 5.8ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 38.7ms\n",
            "Speed: 2.0ms preprocess, 38.7ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 38.8ms\n",
            "Speed: 2.0ms preprocess, 38.8ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      39/80      9.19G      1.001     0.5244      1.059         87        640: 100%|██████████| 106/106 [00:59<00:00,  1.78it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.21it/s]\n",
            "                   all        161        861      0.886      0.748      0.812      0.516\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 1 with_mask, 43.6ms\n",
            "Speed: 1.7ms preprocess, 43.6ms inference, 6.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 19 with_masks, 1 without_mask, 44.9ms\n",
            "Speed: 1.8ms preprocess, 44.9ms inference, 10.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 11 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 7 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 2 mask_weared_incorrects, 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.4ms\n",
            "Speed: 2.0ms preprocess, 37.4ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 4 without_masks, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 51 with_masks, 2 without_masks, 37.5ms\n",
            "Speed: 2.1ms preprocess, 37.5ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 39.7ms\n",
            "Speed: 2.0ms preprocess, 39.7ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 3 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 13 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 15 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 7 with_masks, 4 without_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 10 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      40/80      9.34G     0.9872     0.5144      1.056        121        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.23it/s]\n",
            "                   all        161        861      0.836      0.754      0.819      0.532\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 16 with_masks, 1 without_mask, 38.6ms\n",
            "Speed: 1.7ms preprocess, 38.6ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 42.6ms\n",
            "Speed: 3.0ms preprocess, 42.6ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 40.6ms\n",
            "Speed: 1.8ms preprocess, 40.6ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 2.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.4ms\n",
            "Speed: 1.8ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 2.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 4 without_masks, 41.2ms\n",
            "Speed: 1.8ms preprocess, 41.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.3ms\n",
            "Speed: 2.1ms preprocess, 37.3ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.4ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 4.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 2.3ms preprocess, 37.3ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.3ms\n",
            "Speed: 2.8ms preprocess, 37.3ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 6.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 37.4ms\n",
            "Speed: 1.8ms preprocess, 37.4ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      41/80      9.29G     0.9788      0.513      1.053         77        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.89it/s]\n",
            "                   all        161        861      0.877      0.731      0.824      0.537\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 3 with_masks, 44.6ms\n",
            "Speed: 7.4ms preprocess, 44.6ms inference, 9.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 4 with_masks, 45.3ms\n",
            "Speed: 3.0ms preprocess, 45.3ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 6.5ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 2 mask_weared_incorrects, 8 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 7.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 5 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 2 mask_weared_incorrects, 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 2 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 18 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 9 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 8 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 6 with_masks, 37.3ms\n",
            "Speed: 2.7ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 5 with_masks, 37.8ms\n",
            "Speed: 2.2ms preprocess, 37.8ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 2 with_masks, 37.5ms\n",
            "Speed: 2.1ms preprocess, 37.5ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 2.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.3ms\n",
            "Speed: 1.9ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 4 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      42/80      9.42G     0.9645     0.4966      1.044        115        640: 100%|██████████| 106/106 [01:00<00:00,  1.75it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.22it/s]\n",
            "                   all        161        861      0.849      0.726      0.806      0.525\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 10 with_masks, 38.7ms\n",
            "Speed: 1.8ms preprocess, 38.7ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      43/80      9.44G     0.9858     0.4992      1.045         84        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.14it/s]\n",
            "                   all        161        861       0.89      0.773      0.825      0.544\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 38.7ms\n",
            "Speed: 13.3ms preprocess, 38.7ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 45.6ms\n",
            "Speed: 5.4ms preprocess, 45.6ms inference, 7.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 16 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 1 mask_weared_incorrect, 102 with_masks, 25 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 22 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 3 mask_weared_incorrects, 6 with_masks, 7 without_masks, 37.1ms\n",
            "Speed: 4.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 1 mask_weared_incorrect, 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 7 with_masks, 7 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 10 with_masks, 37.2ms\n",
            "Speed: 1.5ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 2 mask_weared_incorrects, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 9 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 2.4ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      44/80      9.47G     0.9401     0.4742      1.035        100        640: 100%|██████████| 106/106 [01:00<00:00,  1.77it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.15it/s]\n",
            "                   all        161        861      0.872      0.744      0.806      0.518\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 38.6ms\n",
            "Speed: 1.7ms preprocess, 38.6ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 2.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 6 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 11 with_masks, 5 without_masks, 37.7ms\n",
            "Speed: 1.8ms preprocess, 37.7ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.6ms\n",
            "Speed: 1.9ms preprocess, 37.6ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 4.3ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 1 mask_weared_incorrect, 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      45/80      9.59G     0.9338     0.4761      1.031         96        640: 100%|██████████| 106/106 [01:01<00:00,  1.74it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.19it/s]\n",
            "                   all        161        861      0.892      0.786      0.824      0.533\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 1 with_mask, 46.7ms\n",
            "Speed: 1.9ms preprocess, 46.7ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 20 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 18 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 6 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 38.2ms\n",
            "Speed: 1.8ms preprocess, 38.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 9 with_masks, 7 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 3.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 42 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 2 without_masks, 38.0ms\n",
            "Speed: 2.2ms preprocess, 38.0ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 13 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 14 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 7 with_masks, 4 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 3.7ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 5.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 9 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 3 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      46/80      9.62G     0.9246     0.4633      1.025         88        640: 100%|██████████| 106/106 [01:03<00:00,  1.66it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.93it/s]\n",
            "                   all        161        861      0.894      0.784      0.829      0.529\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 17 with_masks, 1 without_mask, 47.0ms\n",
            "Speed: 1.9ms preprocess, 47.0ms inference, 7.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 2.4ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.4ms\n",
            "Speed: 2.1ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.4ms\n",
            "Speed: 1.8ms preprocess, 37.4ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.3ms\n",
            "Speed: 1.7ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      47/80      9.57G     0.9267     0.4664      1.031        118        640: 100%|██████████| 106/106 [01:02<00:00,  1.71it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.25it/s]\n",
            "                   all        161        861      0.876      0.819      0.845      0.552\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 48.9ms\n",
            "Speed: 5.5ms preprocess, 48.9ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 3 with_masks, 39.8ms\n",
            "Speed: 1.9ms preprocess, 39.8ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 7 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 5 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 with_mask, 1 without_mask, 37.3ms\n",
            "Speed: 2.7ms preprocess, 37.3ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 18 with_masks, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 10 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 12 with_masks, 8 without_masks, 37.2ms\n",
            "Speed: 1.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 5.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 8 with_masks, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 3.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 4.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.2ms\n",
            "Speed: 6.6ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      48/80      9.73G     0.9063      0.461      1.019        164        640: 100%|██████████| 106/106 [01:06<00:00,  1.60it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.82it/s]\n",
            "                   all        161        861      0.891      0.762      0.832      0.534\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 13 with_masks, 40.0ms\n",
            "Speed: 4.0ms preprocess, 40.0ms inference, 15.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      49/80      9.67G     0.8964     0.4531      1.017         86        640: 100%|██████████| 106/106 [01:10<00:00,  1.50it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.91it/s]\n",
            "                   all        161        861      0.915      0.764      0.846       0.54\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 38.8ms\n",
            "Speed: 5.5ms preprocess, 38.8ms inference, 11.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 2 with_masks, 37.4ms\n",
            "Speed: 5.1ms preprocess, 37.4ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.9ms\n",
            "Speed: 1.8ms preprocess, 37.9ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 11 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 101 with_masks, 20 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 4.2ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 2 mask_weared_incorrects, 6 with_masks, 8 without_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 5.4ms preprocess, 37.3ms inference, 3.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 1 mask_weared_incorrect, 7 with_masks, 7 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 9 with_masks, 4 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 2.6ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 41.5ms\n",
            "Speed: 1.9ms preprocess, 41.5ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      50/80      9.77G     0.8982     0.4541      1.022         55        640: 100%|██████████| 106/106 [01:06<00:00,  1.59it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.87it/s]\n",
            "                   all        161        861      0.851      0.805      0.842      0.541\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 38.5ms\n",
            "Speed: 1.6ms preprocess, 38.5ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 8 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 13 with_masks, 4 without_masks, 37.2ms\n",
            "Speed: 3.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 11 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 4.8ms preprocess, 37.2ms inference, 6.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      51/80      9.85G     0.8893     0.4496      1.017        135        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.22it/s]\n",
            "                   all        161        861      0.875      0.763      0.812      0.525\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 1 with_mask, 50.9ms\n",
            "Speed: 7.3ms preprocess, 50.9ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 18 with_masks, 1 without_mask, 37.3ms\n",
            "Speed: 4.9ms preprocess, 37.3ms inference, 3.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 4 mask_weared_incorrects, 9 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 14 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 5 with_masks, 37.3ms\n",
            "Speed: 1.8ms preprocess, 37.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 7 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 3 with_masks, 37.6ms\n",
            "Speed: 3.9ms preprocess, 37.6ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 42 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 4.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 3 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 14 with_masks, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 15 with_masks, 37.3ms\n",
            "Speed: 2.9ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 1 mask_weared_incorrect, 7 with_masks, 4 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 10 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.2ms\n",
            "Speed: 2.6ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      52/80      9.87G     0.8786     0.4452      1.011        154        640: 100%|██████████| 106/106 [01:04<00:00,  1.65it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.70it/s]\n",
            "                   all        161        861      0.829      0.775      0.825      0.526\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 19 with_masks, 1 without_mask, 65.3ms\n",
            "Speed: 1.8ms preprocess, 65.3ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 38.5ms\n",
            "Speed: 1.9ms preprocess, 38.5ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 2 with_masks, 37.8ms\n",
            "Speed: 6.6ms preprocess, 37.8ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 3.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 3 with_masks, 39.4ms\n",
            "Speed: 1.8ms preprocess, 39.4ms inference, 7.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 3.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 4.1ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 5 with_masks, 1 without_mask, 37.4ms\n",
            "Speed: 2.4ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.8ms\n",
            "Speed: 1.8ms preprocess, 37.8ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 2.5ms preprocess, 37.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 2 without_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 4.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 23 with_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 1 without_mask, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.4ms\n",
            "Speed: 2.0ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      53/80      9.99G     0.8738     0.4471      1.004        112        640: 100%|██████████| 106/106 [01:00<00:00,  1.74it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.19it/s]\n",
            "                   all        161        861      0.824       0.78      0.823      0.532\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 48.8ms\n",
            "Speed: 2.2ms preprocess, 48.8ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 5 with_masks, 37.3ms\n",
            "Speed: 1.9ms preprocess, 37.3ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 5 with_masks, 37.4ms\n",
            "Speed: 2.8ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 5 with_masks, 1 without_mask, 37.6ms\n",
            "Speed: 1.8ms preprocess, 37.6ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 with_mask, 1 without_mask, 38.6ms\n",
            "Speed: 1.8ms preprocess, 38.6ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 1 mask_weared_incorrect, 12 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 12 with_masks, 8 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.3ms\n",
            "Speed: 2.1ms preprocess, 37.3ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 10 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 39.9ms\n",
            "Speed: 1.9ms preprocess, 39.9ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      54/80        10G     0.8735     0.4425      1.002        120        640: 100%|██████████| 106/106 [01:05<00:00,  1.63it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.60it/s]\n",
            "                   all        161        861      0.867      0.773      0.826      0.542\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 11 with_masks, 42.7ms\n",
            "Speed: 8.2ms preprocess, 42.7ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      55/80        10G     0.8592     0.4363     0.9941         89        640: 100%|██████████| 106/106 [01:08<00:00,  1.55it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.08it/s]\n",
            "                   all        161        861      0.829      0.807      0.816      0.531\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 48.0ms\n",
            "Speed: 7.0ms preprocess, 48.0ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.6ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 13 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 8.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 2.5ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 104 with_masks, 15 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 21 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 3 mask_weared_incorrects, 6 with_masks, 8 without_masks, 37.1ms\n",
            "Speed: 2.4ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 3.1ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.2ms\n",
            "Speed: 3.1ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 7 with_masks, 7 without_masks, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 8 with_masks, 38.0ms\n",
            "Speed: 1.9ms preprocess, 38.0ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.4ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 10 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      56/80      10.1G     0.8384     0.4295     0.9918         90        640: 100%|██████████| 106/106 [01:11<00:00,  1.49it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.83it/s]\n",
            "                   all        161        861      0.893      0.781      0.841      0.551\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 38.6ms\n",
            "Speed: 1.9ms preprocess, 38.6ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.3ms\n",
            "Speed: 2.5ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 1 mask_weared_incorrect, 11 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 9 with_masks, 2 without_masks, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 10 with_masks, 4 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 9 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 4.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 4.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 2 mask_weared_incorrects, 37.2ms\n",
            "Speed: 6.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 6 with_masks, 1 without_mask, 37.6ms\n",
            "Speed: 1.9ms preprocess, 37.6ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 5.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      57/80      10.2G     0.8435     0.4276      0.991         72        640: 100%|██████████| 106/106 [01:09<00:00,  1.53it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.79it/s]\n",
            "                   all        161        861      0.856      0.799      0.813      0.525\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 2 with_masks, 40.5ms\n",
            "Speed: 2.1ms preprocess, 40.5ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 19 with_masks, 1 without_mask, 39.4ms\n",
            "Speed: 2.5ms preprocess, 39.4ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 3 mask_weared_incorrects, 8 with_masks, 2 without_masks, 38.5ms\n",
            "Speed: 2.5ms preprocess, 38.5ms inference, 6.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 6 with_masks, 37.3ms\n",
            "Speed: 2.2ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 9 with_masks, 6 without_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.6ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 41 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 39.7ms\n",
            "Speed: 2.1ms preprocess, 39.7ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 3 with_masks, 37.4ms\n",
            "Speed: 2.2ms preprocess, 37.4ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 3 without_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 13 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 14 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 1 mask_weared_incorrect, 7 with_masks, 5 without_masks, 37.2ms\n",
            "Speed: 2.5ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 4.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.2ms\n",
            "Speed: 3.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      58/80      10.2G     0.8201     0.4239     0.9837         99        640: 100%|██████████| 106/106 [01:04<00:00,  1.64it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.26it/s]\n",
            "                   all        161        861      0.874      0.774      0.819      0.536\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 1 mask_weared_incorrect, 18 with_masks, 2 without_masks, 38.6ms\n",
            "Speed: 1.7ms preprocess, 38.6ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 3.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 7 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 2.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 22 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 2 without_masks, 40.6ms\n",
            "Speed: 1.9ms preprocess, 40.6ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      59/80      10.3G     0.8283     0.4195     0.9829        104        640: 100%|██████████| 106/106 [01:01<00:00,  1.71it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.64it/s]\n",
            "                   all        161        861      0.856      0.786      0.829      0.536\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 2 with_masks, 46.1ms\n",
            "Speed: 1.8ms preprocess, 46.1ms inference, 9.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 3 with_masks, 37.6ms\n",
            "Speed: 9.7ms preprocess, 37.6ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 37.1ms\n",
            "Speed: 6.1ms preprocess, 37.1ms inference, 6.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 5 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 5.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 5 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 5.2ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 1 without_mask, 40.2ms\n",
            "Speed: 1.7ms preprocess, 40.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 17 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 3.1ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 11 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 3.9ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 8 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.9ms\n",
            "Speed: 1.9ms preprocess, 37.9ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.3ms\n",
            "Speed: 1.9ms preprocess, 37.3ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      60/80      10.4G     0.8154      0.416     0.9786        102        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.26it/s]\n",
            "                   all        161        861      0.922      0.767      0.843      0.542\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 12 with_masks, 44.3ms\n",
            "Speed: 1.6ms preprocess, 44.3ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      61/80      10.4G     0.7983     0.4074     0.9735        109        640: 100%|██████████| 106/106 [00:59<00:00,  1.77it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.33it/s]\n",
            "                   all        161        861      0.882      0.765      0.836       0.54\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 44.3ms\n",
            "Speed: 4.7ms preprocess, 44.3ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 12 with_masks, 37.3ms\n",
            "Speed: 2.1ms preprocess, 37.3ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 3 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.6ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 94 with_masks, 20 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 2 mask_weared_incorrects, 6 with_masks, 7 without_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.3ms\n",
            "Speed: 2.1ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 4 with_masks, 37.4ms\n",
            "Speed: 2.1ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 7 with_masks, 7 without_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 2 mask_weared_incorrects, 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 9 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 5.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      62/80      10.5G     0.7956      0.405     0.9638         74        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.26it/s]\n",
            "                   all        161        861      0.895      0.738      0.819      0.527\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 40.1ms\n",
            "Speed: 1.9ms preprocess, 40.1ms inference, 9.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 8 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.4ms\n",
            "Speed: 2.7ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.3ms\n",
            "Speed: 1.8ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 10 with_masks, 6 without_masks, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 11 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.3ms\n",
            "Speed: 1.8ms preprocess, 37.3ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 5.1ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 39.8ms\n",
            "Speed: 1.8ms preprocess, 39.8ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.4ms\n",
            "Speed: 2.2ms preprocess, 37.4ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      63/80      10.5G     0.7792     0.3974     0.9639        100        640: 100%|██████████| 106/106 [01:00<00:00,  1.77it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.78it/s]\n",
            "                   all        161        861      0.923      0.769      0.856      0.557\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 1 with_mask, 44.6ms\n",
            "Speed: 1.8ms preprocess, 44.6ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 19 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 2 mask_weared_incorrects, 8 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 12 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 6 without_masks, 37.1ms\n",
            "Speed: 2.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 2 mask_weared_incorrects, 3 with_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 3.1ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 5 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 41 with_masks, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 6.1ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.9ms\n",
            "Speed: 1.8ms preprocess, 37.9ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 3.8ms preprocess, 37.2ms inference, 5.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 2 without_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 14 with_masks, 37.2ms\n",
            "Speed: 2.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 14 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 7 with_masks, 4 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 2.7ms preprocess, 37.2ms inference, 3.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 38.7ms\n",
            "Speed: 1.9ms preprocess, 38.7ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 9 with_masks, 37.2ms\n",
            "Speed: 4.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 12 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.7ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      64/80      10.5G      0.773     0.3889     0.9626         59        640: 100%|██████████| 106/106 [01:00<00:00,  1.76it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.91it/s]\n",
            "                   all        161        861      0.905      0.752      0.827      0.552\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 3 without_masks, 73.9ms\n",
            "Speed: 1.8ms preprocess, 73.9ms inference, 4.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 2.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.3ms\n",
            "Speed: 1.8ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.3ms\n",
            "Speed: 2.4ms preprocess, 37.3ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 6 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.3ms\n",
            "Speed: 2.3ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 3 without_masks, 37.4ms\n",
            "Speed: 1.8ms preprocess, 37.4ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 22 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 2.4ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      65/80      10.6G     0.7668      0.395     0.9549        220        640: 100%|██████████| 106/106 [01:00<00:00,  1.75it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.10it/s]\n",
            "                   all        161        861      0.901      0.769      0.832      0.551\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 101.1ms\n",
            "Speed: 1.7ms preprocess, 101.1ms inference, 5.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 2 with_masks, 39.9ms\n",
            "Speed: 1.9ms preprocess, 39.9ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.3ms\n",
            "Speed: 1.9ms preprocess, 37.3ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 37.2ms\n",
            "Speed: 2.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 4 with_masks, 1 without_mask, 37.9ms\n",
            "Speed: 1.9ms preprocess, 37.9ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 3 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 9 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 40.6ms\n",
            "Speed: 2.0ms preprocess, 40.6ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 6 with_masks, 37.1ms\n",
            "Speed: 2.5ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.8ms\n",
            "Speed: 1.9ms preprocess, 37.8ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 9 with_masks, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      66/80      10.6G     0.7636     0.3859     0.9584         89        640: 100%|██████████| 106/106 [01:04<00:00,  1.64it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:04<00:00,  1.47it/s]\n",
            "                   all        161        861      0.908      0.762      0.829      0.538\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 12 with_masks, 87.2ms\n",
            "Speed: 2.4ms preprocess, 87.2ms inference, 10.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      67/80      10.7G     0.7531     0.3801     0.9556         87        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.22it/s]\n",
            "                   all        161        861      0.851      0.792      0.835      0.547\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss107_png.rf.285757ad3a789f0d69380282b3bdb846.jpg: 640x640 1 with_mask, 80.8ms\n",
            "Speed: 4.1ms preprocess, 80.8ms inference, 10.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss569_png.rf.245d020288f15a704c2742a49eb1ca63.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 5.0ms preprocess, 37.2ms inference, 8.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss56_png.rf.ffec370c63bb3ee301d05f9ce072e3fa.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss577_png.rf.99d8deb18d344f24bb95f02394713470.jpg: 640x640 13 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.5ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss585_png.rf.16b40d54481e86f0a1434d30bc6d9c64.jpg: 640x640 4 with_masks, 2 without_masks, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss595_png.rf.f3a260412881f24273c64d6bd6e1966b.jpg: 640x640 6 with_masks, 38.3ms\n",
            "Speed: 1.7ms preprocess, 38.3ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss596_png.rf.9bf29752ebe873bc099ff9b64ddef6d1.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss603_png.rf.0d06c5299fd1cf3136e68b97a2afa4fd.jpg: 640x640 95 with_masks, 19 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss568_png.rf.a4d4a4e139954b5194617ef2e9ffc81c.jpg: 640x640 1 with_mask, 39.7ms\n",
            "Speed: 1.9ms preprocess, 39.7ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss608_png.rf.4806b67fedacda192a8448bcf3b53d64.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss623_png.rf.19a2c6b529d5478510934f467949c887.jpg: 640x640 1 mask_weared_incorrect, 21 with_masks, 3 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss626_png.rf.4a2f1a57a893fdcef400930251142f52.jpg: 640x640 1 with_mask, 37.7ms\n",
            "Speed: 1.9ms preprocess, 37.7ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss627_png.rf.81b096f6b0f9e897cc64f59880e630e0.jpg: 640x640 1 mask_weared_incorrect, 6 with_masks, 7 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss630_png.rf.d1ecd7de587fb5c2571563293babff62.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss631_png.rf.418be1a60a0224818dc54e0d2281c6f4.jpg: 640x640 11 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss636_png.rf.e6889a20be3cb52fa81b195fdef01b58.jpg: 640x640 6 with_masks, 2 without_masks, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 4.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss645_png.rf.d577b2fbdae8c09e7cb396b9c14f18d7.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss619_png.rf.bc1dcbfae2f9104ce082afe801399f54.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss646_png.rf.a434ddc2569b34a89bbb07a259996497.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 7.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss563_png.rf.dc088c07f08e5fba01fd6bddeceb27e2.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 3.7ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss554_png.rf.ba664c8fdc34b11faff3a128d06dbe9a.jpg: 640x640 5 with_masks, 42.7ms\n",
            "Speed: 1.9ms preprocess, 42.7ms inference, 4.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss473_png.rf.6de35811442245ad013a2676e2bcaa0a.jpg: 640x640 3 with_masks, 1 without_mask, 37.3ms\n",
            "Speed: 1.8ms preprocess, 37.3ms inference, 5.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss477_png.rf.0e319d347398d08b8a52fb6a152de44e.jpg: 640x640 6 with_masks, 7 without_masks, 37.2ms\n",
            "Speed: 5.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss481_png.rf.6682292ffe5179b26d46c8515797446e.jpg: 640x640 6 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss483_png.rf.4c059c2770f996153e3487a7f52f771c.jpg: 640x640 3 with_masks, 2 without_masks, 40.5ms\n",
            "Speed: 1.9ms preprocess, 40.5ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss484_png.rf.a57bfdb112b858aa9ed93bf36306ac61.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.4ms\n",
            "Speed: 3.2ms preprocess, 37.4ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss498_png.rf.095899d089070e7a5a7697113b108f8a.jpg: 640x640 10 with_masks, 3 without_masks, 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss499_png.rf.611bdf8f03aea1d86028c7b5d7d494ec.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss560_png.rf.bc8e65e2733e0f7b723391d33c380fe0.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss49_png.rf.d4077078d124ff3d3d699fc94bd06150.jpg: 640x640 7 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss509_png.rf.6470c0dd2a6a4b05117cca6aad267087.jpg: 640x640 (no detections), 37.4ms\n",
            "Speed: 1.9ms preprocess, 37.4ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss512_png.rf.8dbd72e69a164fdcdad2e220bcd0c467.jpg: 640x640 7 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      68/80      10.7G     0.7499      0.382     0.9592         66        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.11it/s]\n",
            "                   all        161        861      0.885      0.771      0.829      0.542\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss515_png.rf.9b8d660e9368ee9ccfeb977e609167ed.jpg: 640x640 1 with_mask, 76.5ms\n",
            "Speed: 1.7ms preprocess, 76.5ms inference, 6.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss529_png.rf.6ae323861cb838fc945c80ee31070c4c.jpg: 640x640 1 mask_weared_incorrect, 6 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss532_png.rf.03aa559343f932efbfa3753190291fa7.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss537_png.rf.f22f4997ea93880ebfa2cb19a893caad.jpg: 640x640 1 without_mask, 37.3ms\n",
            "Speed: 1.8ms preprocess, 37.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss551_png.rf.010062fb38326dac49ecca8d9322953f.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss501_png.rf.125122fa5a318ec6d0e27d632764f840.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 3.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss649_png.rf.5540865cd8826940d55b3b48c045183c.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss64_png.rf.4b8ca34d17365fb62029fdbee94cb0aa.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss653_png.rf.22cf40d34bad20f7f9b542b6a0a89e2f.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss787_png.rf.a7e026e8082789734a57252cf6df81e5.jpg: 640x640 8 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss793_png.rf.dd2be948b6231ceb68a6af8371f2329c.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss797_png.rf.5ead12df141e267f928b7b34c73dfb1a.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss79_png.rf.e12280d9bd602d3e52504b83921437d6.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss806_png.rf.504dc192775390a4b3f7d6b85bc58636.jpg: 640x640 6 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss808_png.rf.b2e534caaaf701b8674add21e64fd528.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss822_png.rf.8601f2a416cbe3f239fde9934f5f66d2.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 4 without_masks, 37.2ms\n",
            "Speed: 1.6ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss784_png.rf.b95afb3096062e72503f25dfdaf53f52.jpg: 640x640 11 with_masks, 2 without_masks, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss828_png.rf.ef40e6fb83c895f7c4ca491dadbcecb1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss832_png.rf.fd2d4b0fa4b62433e71f92aa8f1bc067.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss834_png.rf.c14acf559bb5531c92d3cf19a5193aa2.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss835_png.rf.b8a44eb8c868a51999b450873338a62a.jpg: 640x640 1 mask_weared_incorrect, 2 with_masks, 37.2ms\n",
            "Speed: 1.7ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss840_png.rf.78c778f16a6a87f204473b70c7e735b1.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.2ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss844_png.rf.98f015b79733ae45cfff40da2c6eb85c.jpg: 640x640 2 with_masks, 37.5ms\n",
            "Speed: 1.9ms preprocess, 37.5ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss846_png.rf.f600f86418cd50b99d7116344abfe0df.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss848_png.rf.a1793122f2a5ab2b5a3d7be92157ea6b.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss830_png.rf.c8684a6a7e69bd43d4d35d54f2004fd7.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
            "Speed: 2.2ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss761_png.rf.666e2aaecaf296dc7fe39031d857300a.jpg: 640x640 1 mask_weared_incorrect, 37.2ms\n",
            "Speed: 2.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss751_png.rf.dad3bdfd78335be99b02ca0f7f0a6679.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss748_png.rf.75b65aa87d1ab4b31a47b7e3f80a43c3.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss658_png.rf.18a299a86c94f8a6784af81f2f6b6c89.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss65_png.rf.f3dacea8ddea2ac8019c39c83bcec5c4.jpg: 640x640 2 with_masks, 1 without_mask, 40.6ms\n",
            "Speed: 1.7ms preprocess, 40.6ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss662_png.rf.0dec50b3c2f682da13df8167851159b8.jpg: 640x640 4 with_masks, 37.6ms\n",
            "Speed: 4.2ms preprocess, 37.6ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      69/80        11G     0.7407     0.3803      0.957        171        640: 100%|██████████| 106/106 [01:02<00:00,  1.68it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.20it/s]\n",
            "                   all        161        861      0.869      0.767      0.806      0.531\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss664_png.rf.d7257f69f379e30582c9d5854e4bb093.jpg: 640x640 2 with_masks, 50.2ms\n",
            "Speed: 4.5ms preprocess, 50.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss674_png.rf.7848cd9439fa5dc0f5b03471912cdd27.jpg: 640x640 19 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss680_png.rf.6430e43e329f2bd17482dab5d188875a.jpg: 640x640 3 mask_weared_incorrects, 8 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss691_png.rf.68076bbedb2a9c8ce1c37ba0bc259d8c.jpg: 640x640 10 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss694_png.rf.92b3468ed6b2d74d6e8e47c151e871a0.jpg: 640x640 5 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss708_png.rf.0b01c6531d4980ea30cfde314a37ac52.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss714_png.rf.c59ce90ae182b29cc037c99b47028dd2.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss723_png.rf.4f8f04c5a74149652aaa8862ac9acb2a.jpg: 640x640 8 with_masks, 6 without_masks, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss725_png.rf.24ef1eeec5e346d219ce1633e649949c.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss72_png.rf.b94af68c76d704d083fc9720d480ef93.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss733_png.rf.bde25a6afb7d3fef880a5c9723c5c30d.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.7ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss73_png.rf.4f856521249c200a0dac653cddd51e50.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss744_png.rf.a8b60de6dbbfeb80df902a739b90f925.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss747_png.rf.09f39fbe610327e3092119f0e0a091ff.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss471_png.rf.c52f488eaed280f80c7d3e439c0c4e2a.jpg: 640x640 6 with_masks, 4 without_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss89_png.rf.0459d0e0116e154559a89c1975734728.jpg: 640x640 36 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss470_png.rf.3fca085941c9a6dbd4e79ea151f97079.jpg: 640x640 5 with_masks, 37.4ms\n",
            "Speed: 2.0ms preprocess, 37.4ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss461_png.rf.6316f0f312cd4c8c93c77f83f5484af9.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss230_png.rf.1fe3136ab2b6bffc7cd0b6e65101870c.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss236_png.rf.ea526bb945fec0e07973f2cd052ef688.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss241_png.rf.01c103b7f1b42f6eaaa3f4c67d5e063a.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss242_png.rf.048ddfefd131055beb8263c92bbb62a8.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss244_png.rf.f9240dd571e5670cad3b769290bbd680.jpg: 640x640 1 with_mask, 2 without_masks, 37.2ms\n",
            "Speed: 6.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss247_png.rf.f67e30adf66e59df979a1db74326bd5b.jpg: 640x640 14 with_masks, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 5.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss248_png.rf.c19d9460b893693e4b637a1f7df7008a.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss229_png.rf.45ba617a90c78bc0e8e547bffedbe3c3.jpg: 640x640 15 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss253_png.rf.93b13ca348adf361296ed659d6acfe75.jpg: 640x640 7 with_masks, 5 without_masks, 38.7ms\n",
            "Speed: 1.8ms preprocess, 38.7ms inference, 4.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss264_png.rf.7018fdf357ffc35189a710fdfc752b52.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss271_png.rf.cc2239f13f1ebcc7519a1b37fc36376a.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 3.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss277_png.rf.12d1ae22a19b53135a7172821eaf2559.jpg: 640x640 8 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss282_png.rf.32d06bf0012896891f681325fa56166d.jpg: 640x640 11 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 6.8ms preprocess, 37.1ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss289_png.rf.fee0ba4040ee03de9c67793e8127c627.jpg: 640x640 2 without_masks, 37.2ms\n",
            "Speed: 3.9ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      70/80      10.9G     0.7398     0.3749     0.9456        107        640: 100%|██████████| 106/106 [01:01<00:00,  1.73it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:02<00:00,  2.18it/s]\n",
            "                   all        161        861      0.823       0.81      0.835      0.541\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss301_png.rf.79b160619414ca6a470bd5ea8b30ef4a.jpg: 640x640 1 mask_weared_incorrect, 19 with_masks, 3 without_masks, 50.3ms\n",
            "Speed: 8.7ms preprocess, 50.3ms inference, 6.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss303_png.rf.f00ae35b4058b933e066d1d2a4d88c17.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss258_png.rf.fc7b4f2f14e1d199dce55985695d1120.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss304_png.rf.9df48cf93de57fa41d0a2b59de78a62c.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss224_png.rf.4539ed1dc0a709e4e01077ecf7bc2b22.jpg: 640x640 2 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss20_png.rf.ca394d629ffaba1fdb13e432a79a5eb9.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.6ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss109_png.rf.3c26f7537566830dffb39c47f71e574e.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss114_png.rf.c087c8382ac2542ac89314fa0bbeb4f6.jpg: 640x640 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 2.4ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss127_png.rf.1baab62c26cbf4478f2a8d99e1cf68de.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss146_png.rf.ec0da30308aa466d39bae79b0cc0e2bf.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss152_png.rf.c66bb39b29efc7503239890f834100dc.jpg: 640x640 7 with_masks, 40.8ms\n",
            "Speed: 7.7ms preprocess, 40.8ms inference, 2.7ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss154_png.rf.7512e06f4e0bd3a2185ec1867603cc8a.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss168_png.rf.3b19cb741e672eef23c3f091fd204d52.jpg: 640x640 3 with_masks, 3 without_masks, 37.3ms\n",
            "Speed: 1.9ms preprocess, 37.3ms inference, 3.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss217_png.rf.c4e305ead91154374bba4fc48e0e3b99.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss169_png.rf.49a3d702f1cd1ce83aa6cd01599e3644.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss174_png.rf.ba1760e663e246482b26e587332650b0.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 6.1ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss178_png.rf.2fd8857c96b9bed1982f78b55798a334.jpg: 640x640 2 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 5.1ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss194_png.rf.77ed2eca9fe5235cf2496449dd156996.jpg: 640x640 2 with_masks, 37.3ms\n",
            "Speed: 2.0ms preprocess, 37.3ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss197_png.rf.cd0c6b120a0fae906bb417f825daf6a1.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss1_png.rf.e41f0052ad0e49cab0887d6e50e5a7eb.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.9ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss203_png.rf.eba7307a461c6b2098593e82d2cccecc.jpg: 640x640 4 with_masks, 37.9ms\n",
            "Speed: 1.8ms preprocess, 37.9ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss206_png.rf.68794173883f5ae26e2382a3087aac0b.jpg: 640x640 7 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 3.0ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss172_png.rf.13bb93a8bf5266e0d73bab43f62e0376.jpg: 640x640 1 without_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss306_png.rf.52a38aff8eebcfb7d90d0c7cac38fdec.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 2.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss307_png.rf.93b21e5a88a625f2a9284ff6253bd417.jpg: 640x640 2 mask_weared_incorrects, 1 with_mask, 1 without_mask, 37.3ms\n",
            "Speed: 2.2ms preprocess, 37.3ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss308_png.rf.61a249cc68e67a9cf66c2393f61080f2.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss402_png.rf.adb70e16aac43aa519466a4364f99311.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss408_png.rf.bb077fd8dd6090c8f22b2dfe4fb0b2dc.jpg: 640x640 8 with_masks, 3 without_masks, 37.3ms\n",
            "Speed: 2.5ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss409_png.rf.a1da634820d49e7be38ce59f5f5887bb.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss410_png.rf.eaad04d3f7e7468f6a0a3d017306d6da.jpg: 640x640 1 mask_weared_incorrect, 20 with_masks, 3 without_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss418_png.rf.432d10d262677cb69e95be55ca0c9125.jpg: 640x640 2 with_masks, 1 without_mask, 37.3ms\n",
            "Speed: 1.8ms preprocess, 37.3ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss421_png.rf.7ecb66f6ba285fd631717a3635a7dd71.jpg: 640x640 6 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "Closing dataloader mosaic\n",
            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
            "os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      71/80      10.9G      0.714     0.3269     0.9362         44        640: 100%|██████████| 106/106 [01:03<00:00,  1.66it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.64it/s]\n",
            "                   all        161        861        0.9      0.771      0.837      0.546\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss425_png.rf.b69c6da9a6c99fd8edfdad09f10582d2.jpg: 640x640 1 with_mask, 38.6ms\n",
            "Speed: 2.0ms preprocess, 38.6ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss400_png.rf.63c84ce5e3e0391c9509f77d2244755c.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 2.7ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss429_png.rf.0f9bc0b4f072650f40e985eefdce87df.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 3.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss438_png.rf.85978160d8cedb7d56a26e0d06e41f87.jpg: 640x640 4 with_masks, 37.2ms\n",
            "Speed: 1.6ms preprocess, 37.2ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss440_png.rf.641564d43589f6344bacc5d05d51da53.jpg: 640x640 1 mask_weared_incorrect, 9 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss44_png.rf.b6697a646548922305672e657697750b.jpg: 640x640 4 with_masks, 1 without_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss450_png.rf.8f5e0ff6c7228f1180f985685beb20d5.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss457_png.rf.60b3bf773c197a83826aae38a0cf2387.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss459_png.rf.73bd4ff56e948804a4c7d5cc9e2f98ef.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.2ms\n",
            "Speed: 2.5ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss45_png.rf.3b160c8afb75253926e1abf7b4972504.jpg: 640x640 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss431_png.rf.c5e66fbd5f544edca4f20973ce5ecf08.jpg: 640x640 1 mask_weared_incorrect, 17 with_masks, 37.1ms\n",
            "Speed: 1.9ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss395_png.rf.d0fd9e7ac741d7df48a86b7f291e9b49.jpg: 640x640 1 with_mask, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss389_png.rf.11956fb49c814dab304f0006b9075f71.jpg: 640x640 9 with_masks, 2 without_masks, 37.2ms\n",
            "Speed: 1.6ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss388_png.rf.4847bd339895b2496b21a16876aca440.jpg: 640x640 1 mask_weared_incorrect, 10 with_masks, 8 without_masks, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss311_png.rf.8d4e3cc30ab76d6699d7f220a26286dd.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 1.5ms preprocess, 37.1ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss313_png.rf.0d2ede745cca1bbc73883747763be4cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss315_png.rf.bdcb0e2cde8b888d72849bbf232bc644.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss31_png.rf.f71dabc8b32a5181ae4a7ec0724d169e.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 2.3ms preprocess, 37.2ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss321_png.rf.d5ca9ccecbb235c5551003b177cd1d46.jpg: 640x640 1 mask_weared_incorrect, 1 with_mask, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss330_png.rf.ca2fe4eca45ae4b2bc6bb9fde6d39dff.jpg: 640x640 4 with_masks, 37.1ms\n",
            "Speed: 1.8ms preprocess, 37.1ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss338_png.rf.669c284dd81181d71654743a3ca9aeb3.jpg: 640x640 5 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss339_png.rf.d26efdd756cada62599cd227994bbf56.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.0ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss343_png.rf.1c5c7bbcb828a1cf9d4d2584972083cb.jpg: 640x640 1 without_mask, 37.1ms\n",
            "Speed: 2.1ms preprocess, 37.1ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss351_png.rf.15436d1eb7080d7bae2e79d554a4d3cb.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 2.1ms preprocess, 37.2ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss364_png.rf.74e470c60f166ba4ec1a268b153fa240.jpg: 640x640 3 with_masks, 37.2ms\n",
            "Speed: 5.8ms preprocess, 37.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss366_png.rf.433ea8f6b4fcab0d951b52116611c1be.jpg: 640x640 2 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss368_png.rf.1d14fe4224d1b152c5e272d889fe3d45.jpg: 640x640 9 with_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss374_png.rf.b51c420d86fc3a474ed557b5a230b51e.jpg: 640x640 4 with_masks, 1 without_mask, 37.1ms\n",
            "Speed: 1.7ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss376_png.rf.ca418b2ffccc242892a1ab14657e8349.jpg: 640x640 8 with_masks, 37.1ms\n",
            "Speed: 2.3ms preprocess, 37.1ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss37_png.rf.60ce2ff44ae089a01d8f07ff2e0f00ad.jpg: 640x640 1 with_mask, 37.2ms\n",
            "Speed: 1.9ms preprocess, 37.2ms inference, 2.5ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss387_png.rf.6d027b3075e33a4414cc245ec7435fcc.jpg: 640x640 1 mask_weared_incorrect, 3 with_masks, 37.1ms\n",
            "Speed: 2.0ms preprocess, 37.1ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss464_png.rf.b7d07a0f6aabc271e6bfbe039246786b.jpg: 640x640 7 with_masks, 37.2ms\n",
            "Speed: 1.8ms preprocess, 37.2ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      72/80        11G     0.6901     0.3235     0.9268         48        640: 100%|██████████| 106/106 [01:02<00:00,  1.71it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.68it/s]\n",
            "                   all        161        861       0.87       0.77      0.813      0.529\n",
            "\n",
            "image 1/1 /content/Face-Mask-Detection-1/valid/images/maksssksksss90_png.rf.bb3401c96e9aba7db607a9a5ac8d8f51.jpg: 640x640 11 with_masks, 47.8ms\n",
            "Speed: 1.8ms preprocess, 47.8ms inference, 6.3ms postprocess per image at shape (1, 3, 640, 640)\n",
            "Results saved to \u001b[1mruns/detect/train\u001b[0m\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      73/80        11G     0.6748      0.318     0.9196        167        640: 100%|██████████| 106/106 [00:59<00:00,  1.78it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 6/6 [00:03<00:00,  1.90it/s]\n",
            "                   all        161        861      0.865      0.776       0.83      0.547\n"
          ]
        }
      ],
      "source": [
        "# Initialize YOLO Model\n",
        "model = YOLO(\"yolov8m.pt\")\n",
        "\n",
        "# Add Weights & Biases callback for Ultralytics\n",
        "add_wandb_callback(model, enable_model_checkpointing=True)\n",
        "\n",
        "# Train/fine-tune model\n",
        "model.train(project=\"verihubs-tech-assessment\", data='/content/Face-Mask-Detection-1/data.yaml', epochs=80, device=[0])\n",
        "model.val()\n",
        "\n",
        "# Finish the W&B run\n",
        "wandb.finish()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "93eWzFxhw5Ot"
      },
      "source": [
        "# Model Evaluation"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Evaluate on test set"
      ],
      "metadata": {
        "id": "bh2FD2tj38wQ"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "_6Hm3i4Pw5Ot"
      },
      "outputs": [],
      "source": [
        "model = YOLO('best.pt', task='detect')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eXetfgvw0gpM",
        "outputId": "08a10b3d-fd98-46fb-ebab-67ea7c4cf68c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Ultralytics YOLOv8.0.186 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "Downloading https://ultralytics.com/assets/Arial.ttf to '/root/.config/Ultralytics/Arial.ttf'...\n",
            "100%|██████████| 755k/755k [00:00<00:00, 62.4MB/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/Face-Mask-Detection-1/valid/labels... 161 images, 0 backgrounds, 0 corrupt: 100%|██████████| 161/161 [00:00<00:00, 1699.32it/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/Face-Mask-Detection-1/valid/labels.cache\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 11/11 [00:11<00:00,  1.06s/it]\n",
            "                   all        161        861        0.9      0.772      0.837      0.547\n",
            " mask_weared_incorrect        161         28      0.891      0.643      0.735      0.486\n",
            "             with_mask        161        720      0.935      0.902      0.944      0.648\n",
            "          without_mask        161        113      0.876       0.77      0.831      0.508\n",
            "Speed: 5.0ms preprocess, 22.5ms inference, 0.0ms loss, 7.2ms postprocess per image\n",
            "Results saved to \u001b[1mruns/detect/val2\u001b[0m\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ultralytics.utils.metrics.DetMetrics object with attributes:\n",
              "\n",
              "ap_class_index: array([0, 1, 2])\n",
              "box: ultralytics.utils.metrics.Metric object\n",
              "confusion_matrix: <ultralytics.utils.metrics.ConfusionMatrix object at 0x7c0dd57b3550>\n",
              "fitness: 0.5763262590985345\n",
              "keys: ['metrics/precision(B)', 'metrics/recall(B)', 'metrics/mAP50(B)', 'metrics/mAP50-95(B)']\n",
              "maps: array([     0.4858,      0.6481,     0.50819])\n",
              "names: {0: 'mask_weared_incorrect', 1: 'with_mask', 2: 'without_mask'}\n",
              "plot: True\n",
              "results_dict: {'metrics/precision(B)': 0.9004291228691308, 'metrics/recall(B)': 0.7716073384676143, 'metrics/mAP50(B)': 0.8370097832892117, 'metrics/mAP50-95(B)': 0.5473614230773481, 'fitness': 0.5763262590985345}\n",
              "save_dir: PosixPath('runs/detect/val2')\n",
              "speed: {'preprocess': 5.027679182727885, 'inference': 22.499906350366818, 'loss': 0.001861441949879901, 'postprocess': 7.183861288224689}"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "model.val()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "When I tested the model on test set, I got 83.7% mAP@50 and 54.7% map@50-95 on all classess.\n",
        "\n",
        "\n",
        "See the inference results here https://wandb.ai/anakbangkit/verihubs-tech-assessment/reports/AI-Engineer-Study-Case-Report-Manfred-Michael--Vmlldzo4MDYxNjkx"
      ],
      "metadata": {
        "id": "N9nch27T3Tox"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "> **Note**: From the wandb report above, we could see that the incorrectly weared mask is the hardest to detect."
      ],
      "metadata": {
        "id": "Mj6A1Fbc_w-M"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### WandB Tracking Results"
      ],
      "metadata": {
        "id": "DkmorRd54C86"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "You can see the full report here - https://wandb.ai/anakbangkit/verihubs-tech-assessment/reports/AI-Engineer-Study-Case-Report-Manfred-Michael--Vmlldzo4MDYxNjkx"
      ],
      "metadata": {
        "id": "SsH3PZdp7FAb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Confusion Matrix"
      ],
      "metadata": {
        "id": "b3H7GOmG4vpS"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "iiEppGVg_b-T"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### mean Average Precision"
      ],
      "metadata": {
        "id": "gqhAfDv45U72"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "G-rjoAqg5LPW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Calculate Inference Speed"
      ],
      "metadata": {
        "id": "q-H53qT45ryn"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310,
          "referenced_widgets": [
            "99f163adc5d743839dd82733209496c3",
            "8bf3e79c28314bfe92b1462ca08d65fb",
            "8edf70b4aa984bc09da31c8be7b9405b",
            "6d09eff9fa5546b592186984c5bddd86",
            "3b96f0b655104800bf2ef4504660e9fb",
            "3d8af422cf854c08b9cabcdc10f63f32",
            "1af10357ef5d4a6dac6d67277ff093b5",
            "2733a301ee7e448684399bdcb81eddc2"
          ]
        },
        "id": "9WGkhvfXSijI",
        "outputId": "dfce0c30-2e08-4d82-9c83-4c6b6930ee1d"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Finishing last run (ID:uvj29u8v) before initializing another..."
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(Label(value='0.001 MB of 0.013 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=0.094515…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "99f163adc5d743839dd82733209496c3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run <strong style=\"color:#cdcd00\">visionary-eon-7</strong> at: <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/uvj29u8v' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/uvj29u8v</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Find logs at: <code>./wandb/run-20240522_235650-uvj29u8v/logs</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Successfully finished last run (ID:uvj29u8v). Initializing new run:<br/>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "wandb version 0.17.0 is available!  To upgrade, please run:\n",
              " $ pip install wandb --upgrade"
            ]
          },
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              "<IPython.core.display.HTML object>"
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              "Tracking run with wandb version 0.15.12"
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              "Run data is saved locally in <code>/content/wandb/run-20240523_000329-47wmvauk</code>"
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              "Syncing run <strong><a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk' target=\"_blank\">fanciful-snowball-8</a></strong> to <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
            ]
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        },
        {
          "output_type": "display_data",
          "data": {
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              "<IPython.core.display.HTML object>"
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            "text/html": [
              " View project at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment</a>"
            ]
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "<IPython.core.display.HTML object>"
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              " View run at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<button onClick=\"this.nextSibling.style.display='block';this.style.display='none';\">Display W&B run</button><iframe src='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk?jupyter=true' style='border:none;width:100%;height:420px;display:none;'></iframe>"
            ],
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              "<wandb.sdk.wandb_run.Run at 0x7c0ccfee1360>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ],
      "source": [
        "wandb.init(project=\"verihubs-tech-assessment\", job_type=\"evaluation\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "Y8iCmJYpw5Ou"
      },
      "outputs": [],
      "source": [
        "model_best = YOLO('/content/best.pt', task='detect')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5AIYedpzYy6R",
        "outputId": "d38f2424-7d55-4cd9-b4e1-1b9b5f9aa57a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "0: 640x640 2 with_masks, 1: 640x640 3 with_masks, 2: 640x640 3 with_masks, 1 without_mask, 3: 640x640 1 mask_weared_incorrect, 4: 640x640 5 mask_weared_incorrects, 2 with_masks, 1 without_mask, 157.9ms\n",
            "Speed: 2.8ms preprocess, 31.6ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640)\n"
          ]
        }
      ],
      "source": [
        "import glob\n",
        "test_img_paths = glob.glob(\"/content/test-images/*\")\n",
        "\n",
        "imgs = [Image.open(path) for path in test_img_paths]\n",
        "\n",
        "results = model_best(imgs)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "20yvojD1Y8Qu",
        "outputId": "beebafab-647b-44f9-8e1f-b07ec4a8068d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/test-images/106757648-1603404475911-gettyimages-1281710356-nng_6210_2020102252211420.jpeg\n",
            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n",
            "/content/test-images/download (1).jpg\n",
            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n",
            "/content/test-images/Women-wearing-facemasks-while-walking-outdoors-Milan-Italy-February-2020-coronavirus-COVID-19.webp\n",
            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n",
            "/content/test-images/download (2).jpg\n",
            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n",
            "/content/test-images/images (5).jpg\n",
            "{'preprocess': 2.7736663818359375, 'inference': 31.577253341674805, 'postprocess': 1.3605594635009766}\n"
          ]
        }
      ],
      "source": [
        "for result in results:\n",
        "    print(result.path)\n",
        "    print(result.speed)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Here we get 31ms latency on inference"
      ],
      "metadata": {
        "id": "Gls-sFvR5y0V"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Reduce Inference Speed"
      ],
      "metadata": {
        "id": "73D6BcSl6lEH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "### Quantize the model"
      ],
      "metadata": {
        "id": "XECaJUUh7SFq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this step, I will export the model with int8 quantization."
      ],
      "metadata": {
        "id": "OCr4aSt66p1N"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "id": "_Q2VJ0QPZJaA",
        "outputId": "e91223e7-b1e9-4fbc-bc12-078d5e5a03f2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Ultralytics YOLOv8.0.186 🚀 Python-3.10.12 torch-2.3.0+cu121 CPU (Intel Xeon 2.00GHz)\n",
            "\n",
            "\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from '/content/best.pt' with input shape (1, 3, 640, 640) BCHW and output shape(s) (1, 7, 8400) (296.6 MB)\n",
            "\n",
            "\u001b[34m\u001b[1mTorchScript:\u001b[0m starting export with torch 2.3.0+cu121...\n",
            "\u001b[34m\u001b[1mTorchScript:\u001b[0m export success ✅ 8.3s, saved as '/content/best.torchscript' (99.1 MB)\n",
            "\n",
            "Export complete (11.5s)\n",
            "Results saved to \u001b[1m/content\u001b[0m\n",
            "Predict:         yolo predict task=detect model=/content/best.torchscript imgsz=640 int8 \n",
            "Validate:        yolo val task=detect model=/content/best.torchscript imgsz=640 data=/content/Face-Mask-Detection-1/data.yaml int8 \n",
            "Visualize:       https://netron.app\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/best.torchscript'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ],
      "source": [
        "model_best.export(format='torchscript', int8=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 307,
          "referenced_widgets": [
            "87507ff80bed4339b98615f17f631f9a",
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        },
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      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Finishing last run (ID:47wmvauk) before initializing another..."
            ]
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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            "text/html": [
              "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
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          "metadata": {}
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        {
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          "data": {
            "text/plain": [
              "VBox(children=(Label(value='0.001 MB of 0.001 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
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          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run <strong style=\"color:#cdcd00\">fanciful-snowball-8</strong> at: <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/47wmvauk</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
            ]
          },
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Find logs at: <code>./wandb/run-20240523_000329-47wmvauk/logs</code>"
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              "<IPython.core.display.HTML object>"
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            "text/html": [
              "Successfully finished last run (ID:47wmvauk). Initializing new run:<br/>"
            ]
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        {
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          "data": {
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              "<IPython.core.display.HTML object>"
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            "text/html": [
              "wandb version 0.17.0 is available!  To upgrade, please run:\n",
              " $ pip install wandb --upgrade"
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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            "text/html": [
              "Tracking run with wandb version 0.15.12"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "<IPython.core.display.HTML object>"
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            "text/html": [
              "Run data is saved locally in <code>/content/wandb/run-20240523_000806-tv5b30zu</code>"
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          },
          "metadata": {}
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              "<IPython.core.display.HTML object>"
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            "text/html": [
              "Syncing run <strong><a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/tv5b30zu' target=\"_blank\">divine-pond-9</a></strong> to <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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            "text/html": [
              " View project at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run at <a href='https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/tv5b30zu' target=\"_blank\">https://wandb.ai/anakbangkit/verihubs-tech-assessment/runs/tv5b30zu</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "YOLO()"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "wandb.init(project=\"verihubs-tech-assessment\", job_type=\"evaluation\")\n",
        "\n",
        "model_int8 = YOLO('/content/best.torchscript', task='detect')\n",
        "add_wandb_callback(model_int8, enable_model_checkpointing=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 138,
          "referenced_widgets": [
            "c699954b34a24c50a28c70361badd803",
            "baee1aa3f5c741e1a531846fd98ac771",
            "ab714c6388af49ee8da67cddff061443",
            "d94d1a3b8f4343bea6ff0f19b0bd4443",
            "96763df4270946caaf2961a07c699c0a",
            "c504e93947ae4a2d9ecfe2615e0c9cc6",
            "1c56b744165b4093b5941feb56a73785",
            "e4bd657fbd7d40bda45409ea8f17c27a",
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            "14199fca456249eaadcec5700d1857d3",
            "c369e26eeb36461a9a06db2ba7658472"
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        "id": "a7g50M8RaMgG",
        "outputId": "0f7bf76a-8a7f-4fb4-e3d8-342d0231e1dc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Loading /content/best.torchscript for TorchScript inference...\n",
            "\n",
            "0: 640x640 2 with_masks, 1: 640x640 3 with_masks, 2: 640x640 3 with_masks, 1 without_mask, 3: 640x640 1 mask_weared_incorrect, 4: 640x640 5 mask_weared_incorrects, 2 with_masks, 1 without_mask, 109.6ms\n",
            "Speed: 2.2ms preprocess, 21.9ms inference, 1.2ms postprocess per image at shape (1, 3, 640, 640)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/5 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c699954b34a24c50a28c70361badd803"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "imgs = [Image.open(path) for path in test_img_paths]\n",
        "results = model_int8(imgs)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P2LIaT0rWcos",
        "outputId": "a94286ba-f875-4cb3-db2c-b5db38dfc0e1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/test-images/106757648-1603404475911-gettyimages-1281710356-nng_6210_2020102252211420.jpeg\n",
            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n",
            "/content/test-images/download (1).jpg\n",
            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n",
            "/content/test-images/Women-wearing-facemasks-while-walking-outdoors-Milan-Italy-February-2020-coronavirus-COVID-19.webp\n",
            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n",
            "/content/test-images/download (2).jpg\n",
            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n",
            "/content/test-images/images (5).jpg\n",
            "{'preprocess': 2.2184371948242188, 'inference': 21.917200088500977, 'postprocess': 1.1716365814208984}\n"
          ]
        }
      ],
      "source": [
        "for result in results:\n",
        "    print(result.path)\n",
        "    print(result.speed)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "After quantization, we get 21ms on inference. 29% reduction in inference time!"
      ],
      "metadata": {
        "id": "GJ6R3zBfaOF6"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Evaluate after quantization"
      ],
      "metadata": {
        "id": "8CoxoiUI7PzH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now let's test the model after quantizatoin"
      ],
      "metadata": {
        "id": "MYH6jwg87Yhb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model_int8 = YOLO('/content/best.torchscript', task='detect')\n",
        "model_int8.val(data='/content/Face-Mask-Detection-1/data.yaml', imgsz=640)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GC23AVk_7XZI",
        "outputId": "a03a3b1d-9d64-4dab-e15d-4429bd000fef"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Ultralytics YOLOv8.0.186 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "Loading /content/best.torchscript for TorchScript inference...\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/Face-Mask-Detection-1/valid/labels.cache... 161 images, 0 backgrounds, 0 corrupt: 100%|██████████| 161/161 [00:00<?, ?it/s]\n",
            "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 11/11 [00:08<00:00,  1.28it/s]\n",
            "                   all        161        861      0.847      0.795      0.829      0.543\n",
            " mask_weared_incorrect        161         28      0.809      0.679      0.722      0.482\n",
            "             with_mask        161        720      0.912       0.91      0.939      0.639\n",
            "          without_mask        161        113      0.818      0.796      0.825      0.506\n",
            "Speed: 4.7ms preprocess, 19.8ms inference, 0.0ms loss, 1.5ms postprocess per image\n",
            "Results saved to \u001b[1mruns/detect/val3\u001b[0m\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ultralytics.utils.metrics.DetMetrics object with attributes:\n",
              "\n",
              "ap_class_index: array([0, 1, 2])\n",
              "box: ultralytics.utils.metrics.Metric object\n",
              "confusion_matrix: <ultralytics.utils.metrics.ConfusionMatrix object at 0x7c0ccecef5b0>\n",
              "fitness: 0.571245528142035\n",
              "keys: ['metrics/precision(B)', 'metrics/recall(B)', 'metrics/mAP50(B)', 'metrics/mAP50-95(B)']\n",
              "maps: array([    0.48219,     0.63923,     0.50649])\n",
              "names: {0: 'mask_weared_incorrect', 1: 'with_mask', 2: 'without_mask'}\n",
              "plot: True\n",
              "results_dict: {'metrics/precision(B)': 0.846657158388935, 'metrics/recall(B)': 0.7949851975707888, 'metrics/mAP50(B)': 0.8287328115265163, 'metrics/mAP50-95(B)': 0.5426358299882038, 'fitness': 0.571245528142035}\n",
              "save_dir: PosixPath('runs/detect/val3')\n",
              "speed: {'preprocess': 4.6583658419780845, 'inference': 19.83749052012189, 'loss': 0.03296692178856512, 'postprocess': 1.5373052277179977}"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now we get 82.9% mAP@50 and 54.4% map@50-95. A very similar performance with only 2/3 of the original inference time!"
      ],
      "metadata": {
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