03_b_GenerateMaskedImages.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "from datetime import datetime\n",
    "\n",
    "import tqdm\n",
    "from PIL import Image\n",
    "\n",
    "import src.data.Dataset as dt\n",
    "import src.visualization.visualization_utils as vu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PYTHONPATH: :/Users/carlos/WORKSPACE/MegaClassifier/data/external/ai4eutils:/Users/carlos/WORKSPACE/MegaClassifier/data/external/CameraTraps:/Users/carlos/WORKSPACE/MegaClassifier/data/external/yolov5\n"
     ]
    }
   ],
   "source": [
    "required_paths = [\"/ai4eutils\", \"/CameraTraps\", \"/yolov5\"]\n",
    "python_path = os.environ.get(\"PYTHONPATH\", \"\")\n",
    "root_path = os.getcwd()\n",
    "\n",
    "for path in required_paths:\n",
    "    if not any(p.endswith(path) for p in python_path.split(\":\")):\n",
    "        python_path += f\":{root_path}/data/external{path}\"\n",
    "\n",
    "os.environ[\"PYTHONPATH\"] = python_path\n",
    "\n",
    "!echo \"PYTHONPATH: $PYTHONPATH\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "DATASET_PATH:   /Users/carlos/WORKSPACE/MegaClassifier/dataset/datasetFiltered\n",
      "MASKED_PATH:      /Users/carlos/WORKSPACE/MegaClassifier/resources/masked/datasetFiltered/md_v5a\n",
      "DETECTION_JSON: /Users/carlos/WORKSPACE/MegaClassifier/resources/json/md_v5a/29618_images_0_003_threshold.json\n"
     ]
    }
   ],
   "source": [
    "DATASET_PATH = os.path.abspath(\"./dataset/datasetFiltered\")\n",
    "MASKED_PATH = os.path.abspath(\"./resources/masked\")\n",
    "DETECTION_JSON = os.path.abspath(\n",
    "    \"./resources/json/md_v5a/29618_images_0_003_threshold.json\"\n",
    ")\n",
    "\n",
    "with open(DETECTION_JSON, \"r\") as f:\n",
    "    result = json.load(f)\n",
    "\n",
    "MASKED_PATH = os.path.join(\n",
    "    MASKED_PATH,\n",
    "    os.path.basename(DATASET_PATH),\n",
    "    result[\"info\"][\"detector\"].split(\".\")[0],\n",
    ")\n",
    "\n",
    "\n",
    "print()\n",
    "print(f\"DATASET_PATH:   {DATASET_PATH}\")\n",
    "print(f\"MASKED_PATH:      {MASKED_PATH}\")\n",
    "print(f\"DETECTION_JSON: {DETECTION_JSON}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 29618/29618 [06:26<00:00, 76.65it/s]  \n"
     ]
    }
   ],
   "source": [
    "for image in tqdm.tqdm(result[\"images\"]):\n",
    "    input_file = os.path.join(DATASET_PATH, image[\"file\"])\n",
    "    output_file = os.path.join(MASKED_PATH, image[\"file\"])\n",
    "    detections = image[\"detections\"]\n",
    "\n",
    "    vu.apply_mask_on_file(input_file, output_file, detections)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of openable images: 29618\n",
      "Number of not openable images: 0\n",
      "Not openable files: []\n"
     ]
    }
   ],
   "source": [
    "from PIL import Image\n",
    "import os\n",
    "\n",
    "# Ruta base\n",
    "base_path = MASKED_PATH\n",
    "\n",
    "# Contadores para las imágenes que se pueden y no se pueden abrir\n",
    "count_openable = 0\n",
    "count_not_openable = 0\n",
    "\n",
    "# Lista para almacenar las rutas de las imágenes que no se pueden abrir\n",
    "not_openable_files = []\n",
    "\n",
    "# Iterar sobre las rutas de las imágenes en el dataset\n",
    "for image in result[\"images\"]:\n",
    "    file_path = image[\"file\"]\n",
    "    absolute_path = base_path + \"/\" + file_path\n",
    "    try:\n",
    "        # Intentar abrir la imagen\n",
    "        img = Image.open(absolute_path)\n",
    "        img.verify()  # Verificar que la imagen se puede abrir\n",
    "        count_openable += 1\n",
    "    except (IOError, SyntaxError) as e:\n",
    "        # Si hay un error, incrementar el contador de imágenes no abiertas\n",
    "        count_not_openable += 1\n",
    "        not_openable_files.append(absolute_path)\n",
    "\n",
    "# Imprimir los resultados\n",
    "print(f\"Number of openable images: {count_openable}\")\n",
    "print(f\"Number of not openable images: {count_not_openable}\")\n",
    "print(f\"Not openable files: {not_openable_files}\")"
   ]
  }
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