{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/torchvision/transforms/functional_tensor.py:5: UserWarning: The torchvision.transforms.functional_tensor module is deprecated in 0.15 and will be **removed in 0.17**. Please don't rely on it. You probably just need to use APIs in torchvision.transforms.functional or in torchvision.transforms.v2.functional.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from handler import EndpointHandler\n",
    "import base64\n",
    "from io import BytesIO\n",
    "from PIL import Image\n",
    "import cv2\n",
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.environ[\"AWS_ACCESS_KEY_ID\"] = \"\"\n",
    "os.environ[\"AWS_SECRET_ACCESS_KEY\"] = \"\"\n",
    "os.environ[\"S3_BUCKET_NAME\"] = \"\"\n",
    "os.environ[\"TILING_SIZE\"] = \"0\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO - model_path: /workspace/real-esrgan/weights/Real-ESRGAN-x4plus.pth\n",
      "INFO - TILING_SIZE is 0, not using tiling\n",
      "INFO - initializing model\n",
      "INFO - model initialized in 1.977891206741333 seconds\n"
     ]
    }
   ],
   "source": [
    "# init handler\n",
    "my_handler = EndpointHandler(path=\".\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO - >>> 1/7: GETTING INPUTS....\n",
      "INFO - outscale: 4.0\n",
      "INFO - downloading image from URL: https://jiffy-transfers.imgix.net/2/attachments/r267odvvfmkp6c5lccj1y6f9trb0?ixlib=rb-0.3.5\n",
      "INFO - >>> 2/7: RUNNING ASSERTIONS ON IMAGE....\n",
      "INFO - image.size: (1024, 1024), image.mode: RGB\n",
      "INFO - >>> 3/7: CONVERTING IMAGE TO OPENCV BGR/BGRA FORMAT....\n",
      "INFO - converting RGB image to BGR\n",
      "INFO - >>> 4/7: UPSCALING IMAGE....\n",
      "INFO - output.shape: (4096, 4096, 3)\n",
      "INFO - >>> 5/7: CONVERTING IMAGE TO RGB/RGBA FORMAT....\n",
      "INFO - >>> 6/7: CONVERTING IMAGE TO PIL....\n",
      "INFO - >>> 7/7: UPLOADING IMAGE TO S3....\n",
      "INFO - image uploaded to s3: https://jiffy-staging-upscaled-images.s3.amazonaws.com/25b91e15-b785-47ca-81a6-ad5fbdf8b92a.png\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://jiffy-staging-upscaled-images.s3.amazonaws.com/25b91e15-b785-47ca-81a6-ad5fbdf8b92a.png 25b91e15-b785-47ca-81a6-ad5fbdf8b92a.png\n"
     ]
    }
   ],
   "source": [
    "img_dir = \"test_data/\"\n",
    "img_urls = [\"https://jiffy-transfers.imgix.net/2/attachments/r267odvvfmkp6c5lccj1y6f9trb0?ixlib=rb-0.3.5\",\n",
    "            # \"https://jiffy-staging-transfers.imgix.net/2/development/attachments/zo31eau0ykhbwoddrjtlbyz6w9mp?ixlib=rb-0.3.5\", # larger than > 1.96M pixels\n",
    "            # \"https://jiffy-staging-transfers.imgix.net/2/development/attachments/b8ecchms9rr9wk3g71kfpfprqg1v?ixlib=rb-0.3.5\" # larger than > 1.96M pixels\n",
    "           ]\n",
    "\n",
    "out_scales = [4]#, 3, 2]\n",
    "for img_url, outscale in zip(img_urls, out_scales):\n",
    "    # create payload\n",
    "    payload = {\n",
    "        \"inputs\": {\"image_url\": img_url, \n",
    "                    \"outscale\": outscale\n",
    "                    }\n",
    "            }\n",
    "    \n",
    "    output_payload = my_handler(payload)\n",
    "    print(output_payload[\"image_url\"], output_payload[\"image_key\"])\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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