{
 "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\"] = \"1000\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# init handler\n",
    "my_handler = EndpointHandler(path=\".\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "image.size: (1024, 1024), image.mode: RGB, outscale: 4.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\tTile 1/4\n",
      "\tTile 2/4\n",
      "\tTile 3/4\n",
      "\tTile 4/4\n",
      "output.shape: (4096, 4096, 3)\n",
      "https://jiffy-staging-upscaled-images.s3.amazonaws.com/d91323cb-0801-45b7-8109-9739212037ed.png d91323cb-0801-45b7-8109-9739212037ed.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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "pygments_lexer": "ipython3",
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