{ "cells": [ { "cell_type": "code", "source": [ "from google.colab import drive\n", "drive.mount('/content/drive')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1mu8Zf6eBLZn", "outputId": "5c667be6-8fe1-4706-fe3b-23f0a33dd2f8" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n" ] } ] }, { "cell_type": "code", "source": [ "%pip install efficientnet-pytorch" ], "metadata": { "id": "a1Gp5qitBoGu", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "073c089a-02ac-438f-e029-d71d68c1ce3b" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Collecting efficientnet-pytorch\n", " Downloading efficientnet_pytorch-0.7.1.tar.gz (21 kB)\n", " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "Requirement already satisfied: torch in /usr/local/lib/python3.9/dist-packages (from efficientnet-pytorch) (2.0.0+cu118)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.9/dist-packages (from torch->efficientnet-pytorch) (3.11.0)\n", "Requirement already satisfied: networkx in /usr/local/lib/python3.9/dist-packages (from torch->efficientnet-pytorch) (3.1)\n", "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.9/dist-packages (from torch->efficientnet-pytorch) (2.0.0)\n", "Requirement already satisfied: sympy in /usr/local/lib/python3.9/dist-packages (from torch->efficientnet-pytorch) (1.11.1)\n", "Requirement already satisfied: jinja2 in /usr/local/lib/python3.9/dist-packages (from torch->efficientnet-pytorch) (3.1.2)\n", "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.9/dist-packages (from torch->efficientnet-pytorch) (4.5.0)\n", "Requirement already satisfied: lit in /usr/local/lib/python3.9/dist-packages (from triton==2.0.0->torch->efficientnet-pytorch) (16.0.1)\n", "Requirement already satisfied: cmake in /usr/local/lib/python3.9/dist-packages (from triton==2.0.0->torch->efficientnet-pytorch) (3.25.2)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.9/dist-packages (from jinja2->torch->efficientnet-pytorch) (2.1.2)\n", "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.9/dist-packages (from sympy->torch->efficientnet-pytorch) (1.3.0)\n", "Building wheels for collected packages: efficientnet-pytorch\n", " Building wheel for efficientnet-pytorch (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for efficientnet-pytorch: filename=efficientnet_pytorch-0.7.1-py3-none-any.whl size=16444 sha256=f66c80f53cbcc0f56a272a760e469ac08d2c560303071f28a51cc6b97573dffa\n", " Stored in directory: /root/.cache/pip/wheels/29/16/24/752e89d88d333af39a288421e64d613b5f652918e39ef1f8e3\n", "Successfully built efficientnet-pytorch\n", "Installing collected packages: efficientnet-pytorch\n", "Successfully installed efficientnet-pytorch-0.7.1\n" ] } ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "3_jQKJwUAqnv" }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import os\n", "from PIL import Image\n", "import torch\n", "from torch import nn, optim\n", "import torch.nn.functional as F\n", "from torch.utils.data import DataLoader, Dataset\n", "import albumentations as A\n", "from albumentations.pytorch import ToTensorV2 \n", "from tqdm import tqdm\n", "from torchvision import models\n", "from efficientnet_pytorch import EfficientNet\n", "from sklearn import metrics" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "Ue18ORtKAqn0" }, "outputs": [], "source": [ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 424 }, "id": "c1gGDtOcAqn0", "outputId": "de9f9219-2603-4452-cf37-f8daec79d12b" }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " id label\n", "0 0.jpg 1\n", "1 1.jpg 1\n", "2 2.jpg 1\n", "3 3.jpg 0\n", "4 4.jpg 1\n", "... ... ...\n", "15820 15820.jpg 1\n", "15821 15821.jpg 0\n", "15822 15822.jpg 0\n", "15823 15823.jpg 0\n", "15824 15824.jpg 1\n", "\n", "[15825 rows x 2 columns]" ], "text/html": [ "\n", "
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