ML.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "76fbbbfc-d9d0-454b-af7b-750863a36255",
   "metadata": {},
   "source": [
    "# 1. Импортирование библиотек и парсинг данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d6cdc242-a74f-4033-a690-9b7f156e16a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import cv2\n",
    "import torch\n",
    "import os\n",
    "from glob import glob\n",
    "from matplotlib.patches import Rectangle\n",
    "from tqdm import tqdm\n",
    "import shutil\n",
    "import codecs\n",
    "# Отключаем проверку\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "707d214f-56c0-4840-b41b-af6764f87426",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['.\\\\data\\\\test\\\\0.bmp',\n",
       " '.\\\\data\\\\test\\\\03.bmp',\n",
       " '.\\\\data\\\\test\\\\04.bmp',\n",
       " '.\\\\data\\\\test\\\\05.bmp',\n",
       " '.\\\\data\\\\test\\\\0_075.bmp',\n",
       " '.\\\\data\\\\test\\\\0_077.bmp',\n",
       " '.\\\\data\\\\test\\\\0_078.bmp',\n",
       " '.\\\\data\\\\test\\\\0_080.bmp',\n",
       " '.\\\\data\\\\test\\\\0_081.bmp',\n",
       " '.\\\\data\\\\test\\\\0_083.bmp']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_bmp = [] # Массив путей к bmp\n",
    "def parsing_bmp(dir):\n",
    "    list = os.listdir(dir) # Список всех файлов в данной директории\n",
    "    for item in glob(dir+'\\\\'+'*.bmp'):\n",
    "        list_bmp.append(item) # Добавляем в массив названий файлов типа .bmp\n",
    "    for dir_for in list:\n",
    "        if os.path.isdir(dir+'\\\\'+dir_for): # Если это директория, то запускай функцию. Рекурсия :)\n",
    "            parsing_bmp(dir+'\\\\'+dir_for)\n",
    "parsing_bmp('.')\n",
    "list_bmp[:10] # Выведем "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e9b34149-5740-42f6-a43a-1caa7a0c6a75",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Файлов формата bmp 14339\n"
     ]
    }
   ],
   "source": [
    "print(f'Файлов формата bmp {len(list_bmp)}') "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab787522-03ab-4ca8-a635-93c1633b4861",
   "metadata": {},
   "source": [
    "# 2. Чтение изображения"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0c9f7f83-7f40-4d81-9e07-338c39871570",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████| 14339/14339 [01:41<00:00, 141.75it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Прочиталось 13652 изображений\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "images = [] # Массив изображений\n",
    "for file in tqdm(list_bmp):\n",
    "    try:\n",
    "        image = cv2.imread(file, cv2.IMREAD_COLOR) # Читаем изображение\n",
    "        image = cv2.resize(image, dsize=(960, 600)) # Изменяем размер фото на 960x600\n",
    "        images.append(image)\n",
    "    except:\n",
    "        pass\n",
    "print(f'Прочиталось {len(images)} изображений')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ca42bd8-465b-4f9e-a343-6ba1a3c46a85",
   "metadata": {},
   "source": [
    "Визуализируем пример с дефектом"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "22c19d53-c728-4ad2-8ed1-968a98255b96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x18006348ed0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "image = cv2.imread('.\\\\DATASET\\\\FRAMES\\\\0\\\\1538\\\\frame0006.bmp', cv2.IMREAD_COLOR) # Читаем изображение\n",
    "image = np.array(image) # Переводим в numpy массивы\n",
    "image = image.astype('float32') # Изменяем на тип float\n",
    "image = image / 255.0 # Нормализируем пиксили\n",
    "plt.gca().add_patch (Rectangle((809-50,336-50),100,100,edgecolor='red', facecolor='none', lw= 1 )) \n",
    "plt.imshow(image)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "329b3203-f6ef-463f-9186-232defcf185b",
   "metadata": {},
   "source": [
    "# 3. Чтение выборок "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cfb59285-5840-418d-b2e6-57cbc03f5555",
   "metadata": {},
   "outputs": [],
   "source": [
    "root = 'data' # Папка с данными\n",
    "def dict_frames_maker(path, prefix, sampling, *, show=False):\n",
    "    '''\n",
    "    Функция позволяет создать директорию с выборкой и разметкой для детекции\n",
    "    Input:\n",
    "        path - путь до файла формата .cfg\n",
    "        prefix - путь до директории с фотографиями с камер\n",
    "        sampling - имя выборки\n",
    "        show - отобразить результат\n",
    "    '''\n",
    "    file = open(path, \"r\") # Открываем файл .cfg\n",
    "    with codecs.open(path, 'r', encoding='cp1251') as fdata:\n",
    "        list_lines = fdata.readlines() # Читаем построчно\n",
    "    # Создаём папки с выборкой\n",
    "    if not os.path.exists(root):\n",
    "        os.mkdir(root)\n",
    "    if not os.path.exists('.\\\\'+root+'\\\\'+sampling):\n",
    "        os.mkdir('.\\\\'+root+'\\\\'+sampling)\n",
    "    if not os.path.exists('.\\\\'+root+'\\\\' + sampling + '\\\\image\\\\'):\n",
    "        os.mkdir('.\\\\'+root+'\\\\' + sampling + '\\\\image\\\\')\n",
    "    if not os.path.exists('.\\\\'+root+'\\\\' + sampling + '\\\\label\\\\'):\n",
    "        os.mkdir('.\\\\'+root+'\\\\' + sampling + '\\\\label\\\\')\n",
    "    key = 0 #\n",
    "    dict_frames = {} # Словарь с данными\n",
    "    dict_value = [] # Список с данными по фото\n",
    "\n",
    "    # Проходимся по файлу .cfg\n",
    "    for item in list_lines:\n",
    "        item = item[:-2] # Убираем последние пустые символы\n",
    "        if item.endswith('.frame'):\n",
    "            # Если в файле нет записей, то записываем заглушку \n",
    "            if len(dict_value) == 0:\n",
    "                dict_frames[key] = '0 0.0 0.0 0.0 0.0'\n",
    "            else:\n",
    "                dict_frames[key] = dict_value\n",
    "            key = prefix+item # Путь до файла\n",
    "            key = key.replace(\".frame\", \".bmp\") # Переименуем путь до файла с формата .frame до .bmp\n",
    "            dict_value = [] # Очищаем список по фото\n",
    "        else:\n",
    "            # Если фотография не будет битой, то занесём в список\n",
    "            try:\n",
    "                height, width, channels = cv2.imread(key).shape # Получаем размеры изображения\n",
    "                items_coor = [int(i) for i in item.split(', ')] # массив детекции с X, Y, CLASS\n",
    "                # Добавляем строку формата CLASS X Y WIDTH HEIGHT\n",
    "                dict_value.append(' '.join([str(items_coor[2]), str(round((items_coor[0]) / width, 6)), \n",
    "                                            str(round((items_coor[1]) / height, 6)), str(round((items_coor[0] + 25) / width, 6)), \n",
    "                                            str(round((items_coor[1] + 25) / height, 6))]))\n",
    "            except:\n",
    "                pass\n",
    "    del dict_frames[0]\n",
    "    # Проходимся по всем файлам\n",
    "    for item in dict_frames.keys():\n",
    "        try:\n",
    "            # Копируем изображение в новое место\n",
    "            shutil.copy(item, '.\\\\'+root+'\\\\'+sampling+'\\\\'+item[item.rfind('\\\\'):])\n",
    "            # Открываем txt с таким же названием и записываем данные о дефекте \n",
    "            with open('.\\\\'+root+'\\\\'+sampling+'\\\\'+item[item.rfind('\\\\'):].replace('.bmp', '.txt'), 'w') as f:\n",
    "                for i in dict_frames[item]:\n",
    "                    f.write(i+'\\n') \n",
    "        except:\n",
    "            pass\n",
    "    # Выводим в консоль весб\n",
    "    if show:\n",
    "        for key in dict_frames: \n",
    "            print(key + ':', dict_frames[key])\n",
    "    return dict_frames"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ca1f952-4755-40a1-b606-58bb569f941f",
   "metadata": {},
   "source": [
    "Тренировочная выборка"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f5ca5c37-5740-4ef8-b6ce-1d69712601fc",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 15.9 s\n",
      "Wall time: 2min 4s\n"
     ]
    },
    {
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       " '.\\\\DATASET\\\\FRAMES\\\\2022.08.02\\\\0\\\\4_590.bmp': ['1 0.173958 0.503333 0.2 0.545',\n",
       "  '1 0.176042 0.641667 0.202083 0.683333',\n",
       "  '1 0.169792 0.381667 0.195833 0.423333',\n",
       "  '1 0.173958 0.765 0.2 0.806667',\n",
       "  '1 0.173958 0.213333 0.2 0.255',\n",
       "  '0 0.46875 0.451667 0.494792 0.493333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.08.02\\\\0\\\\4_711.bmp': ['11 0.691667 0.698333 0.717708 0.74',\n",
       "  '0 0.114583 0.7 0.140625 0.741667',\n",
       "  '0 0.161458 0.255 0.1875 0.296667',\n",
       "  '0 0.591667 0.255 0.617708 0.296667',\n",
       "  '0 0.222917 0.55 0.248958 0.591667',\n",
       "  '0 0.222917 0.746667 0.248958 0.788333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.08.02\\\\0\\\\4_756.bmp': ['0 0.428125 0.466667 0.454167 0.508333',\n",
       "  '0 0.345833 0.156667 0.371875 0.198333',\n",
       "  '0 0.776042 0.451667 0.802083 0.493333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.08.02\\\\0\\\\4_771.bmp': ['0 0.8375 0.156667 0.863542 0.198333',\n",
       "  '0 0.714583 0.255 0.740625 0.296667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.08.02\\\\0\\\\4_789.bmp': ['0 0.272917 0.701667 0.298958 0.743333',\n",
       "  '0 0.530208 0.353333 0.55625 0.395',\n",
       "  '0 0.653125 0.353333 0.679167 0.395',\n",
       "  '0 0.8375 0.451667 0.863542 0.493333',\n",
       "  '0 0.653125 0.55 0.679167 0.591667',\n",
       "  '0 0.222917 0.746667 0.248958 0.788333',\n",
       "  '0 0.407292 0.845 0.433333 0.886667',\n",
       "  '0 0.591667 0.845 0.617708 0.886667',\n",
       "  '0 0.8375 0.845 0.863542 0.886667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.08.02\\\\0\\\\4_826.bmp': ['1 0.645833 0.466667 0.671875 0.508333',\n",
       "  '1 0.645833 0.378333 0.671875 0.42',\n",
       "  '1 0.640625 0.141667 0.666667 0.183333',\n",
       "  '0 0.284375 0.648333 0.310417 0.69',\n",
       "  '0 0.407292 0.648333 0.433333 0.69'],\n",
       " ...}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "path = \".\\\\DATASET\\\\metadata\\\\set.cfg\"\n",
    "prefix = '.\\\\DATASET\\\\FRAMES\\\\'\n",
    "train_json = dict_frames_maker(path, prefix, 'train')\n",
    "train_json"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46acd720-0146-4205-a9d4-682bd0abcb4e",
   "metadata": {},
   "source": [
    "Тестовая выборка"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5f94b374-d669-4425-b03a-8930361bf140",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 6.39 s\n",
      "Wall time: 17 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538\\\\frame0007.bmp': ['3 0.694792 0.53 0.720833 0.571667',\n",
       "  '3 0.844792 0.871667 0.870833 0.913333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538\\\\frame0009.bmp': ['3 0.6 0.521667 0.626042 0.563333',\n",
       "  '3 0.754167 0.848333 0.780208 0.89'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538\\\\frame0011.bmp': ['3 0.497917 0.84 0.523958 0.881667',\n",
       "  '3 0.339583 0.536667 0.365625 0.578333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538\\\\frame0012.bmp': ['3 0.290625 0.543333 0.316667 0.585',\n",
       "  '3 0.45 0.838333 0.476042 0.88'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538\\\\frame0013.bmp': ['3 0.252083 0.551667 0.278125 0.593333',\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538\\\\frame0015.bmp': ['3 0.127083 0.593333 0.153125 0.635',\n",
       "  '3 0.245833 0.856667 0.271875 0.898333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\0_421.bmp': ['4 0.273958 0.815 0.3 0.856667',\n",
       "  '4 0.439583 0.863333 0.465625 0.905',\n",
       "  '4 0.598958 0.861667 0.625 0.903333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\0_421_1.bmp': ['3 0.369792 0.405 0.395833 0.446667',\n",
       "  '3 0.536458 0.74 0.5625 0.781667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\0_422.bmp': ['3 0.245833 0.436667 0.271875 0.478333',\n",
       "  '3 0.420833 0.776667 0.446875 0.818333'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\0_426.bmp': ['3 0.80625 0.645 0.832292 0.686667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\0_426_1.bmp': ['3 0.702083 0.221667 0.728125 0.263333',\n",
       "  '3 0.848958 0.601667 0.875 0.643333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\0_426_2.bmp': ['3 0.56875 0.233333 0.594792 0.275',\n",
       "  '3 0.726042 0.59 0.752083 0.631667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\0_545.bmp': ['3 0.851042 0.3 0.877083 0.341667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\1_425_1.bmp': ['3 0.534375 0.425 0.560417 0.466667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\1_426.bmp': ['3 0.202083 0.646667 0.228125 0.688333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\1_426_1.bmp': ['3 0.122917 0.288333 0.148958 0.33',\n",
       "  '3 0.252083 0.575 0.278125 0.616667'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\1_528.bmp': ['3 0.29375 0.706667 0.319792 0.748333'],\n",
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       "  '3 0.417708 0.8 0.44375 0.841667'],\n",
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       "  '3 0.607292 0.788333 0.633333 0.83'],\n",
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       "  '3 0.4125 0.586667 0.438542 0.628333'],\n",
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       "  '3 0.729167 0.62 0.755208 0.661667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\2_424.bmp': ['3 0.723958 0.171667 0.75 0.213333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\2_425.bmp': ['3 0.573958 0.505 0.6 0.546667',\n",
       "  '3 0.738542 0.833333 0.764583 0.875'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\2_426.bmp': ['3 0.771875 0.165 0.797917 0.206667',\n",
       "  '3 0.921875 0.528333 0.947917 0.57'],\n",
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       "  '3 0.88125 0.531667 0.907292 0.573333',\n",
       "  '5 0.414583 0.336667 0.440625 0.378333'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\2_427_2.bmp': ['3 0.771875 0.483333 0.797917 0.525',\n",
       "  '3 0.607292 0.141667 0.633333 0.183333',\n",
       "  '0 0.389583 0.211667 0.415625 0.253333'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\2_545.bmp': ['3 0.767708 0.368333 0.79375 0.41'],\n",
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       "  '3 0.094792 0.201667 0.120833 0.243333'],\n",
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       "  '3 0.69375 0.546667 0.719792 0.588333'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\3_427.bmp': ['3 0.4625 0.738333 0.488542 0.78'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\3_533.bmp': ['3 0.697917 0.61 0.723958 0.651667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\4_532.bmp': ['3 0.244792 0.363333 0.270833 0.405'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\4_533.bmp': ['3 0.103125 0.733333 0.129167 0.775'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\1538mov\\\\5_422.bmp': ['3 0.915625 0.48 0.941667 0.521667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\d\\\\0.bmp': ['6 0.701042 0.548333 0.727083 0.59'],\n",
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       "  '0 0.127083 0.501667 0.153125 0.543333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\d\\\\5.bmp': ['0 0.3625 0.393333 0.388542 0.435',\n",
       "  '6 0.377083 0.775 0.403125 0.816667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\miss\\\\0_489.bmp': ['0 0.208333 0.206667 0.234375 0.248333',\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\miss\\\\0_656.bmp': ['0 0.159375 0.336667 0.185417 0.378333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\miss\\\\0_802.bmp': ['0 0.544792 0.376667 0.570833 0.418333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\miss\\\\0_872.bmp': ['5 0.458333 0.621667 0.484375 0.663333'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\miss\\\\3_517.bmp': ['0 0.28125 0.528333 0.307292 0.57'],\n",
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       "  '4 0.121875 0.066667 0.147917 0.108333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\miss\\\\3_780.bmp': ['4 0.094792 0.536667 0.120833 0.578333',\n",
       "  '4 0.280208 0.626667 0.30625 0.668333',\n",
       "  '4 0.320833 0.731667 0.346875 0.773333',\n",
       "  '4 0.120833 0.706667 0.146875 0.748333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\mv_1\\\\frame0004.bmp': ['4 0.559375 0.851667 0.585417 0.893333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\mv_1\\\\frame0012.bmp': ['4 0.591667 0.216667 0.617708 0.258333',\n",
       "  '4 0.454167 0.216667 0.480208 0.258333',\n",
       "  '4 0.735417 0.22 0.761458 0.261667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\n1\\\\frame0003.bmp': ['4 0.663542 0.53 0.689583 0.571667'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\0\\\\n1\\\\frame0004.bmp': ['4 0.640625 0.323333 0.666667 0.365',\n",
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       "  '4 0.946875 0.28 0.972917 0.321667'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\2022.10.27\\\\4_172.bmp': ['0 0.372917 0.511667 0.398958 0.553333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.10.27\\\\4_201.bmp': ['0 0.591667 0.746667 0.617708 0.788333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.10.27\\\\4_648.bmp': ['0 0.345833 0.156667 0.371875 0.198333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.10.27\\\\4_743.bmp': ['0 0.653125 0.648333 0.679167 0.69'],\n",
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       "  '7 0.58125 0.456667 0.607292 0.498333'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\2022.10.27\\\\5_729.bmp': ['5 0.5625 0.856667 0.588542 0.898333',\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\2022.10.27\\\\5_831.bmp': ['0 0.284375 0.746667 0.310417 0.788333'],\n",
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       "  '0 0.714583 0.353333 0.740625 0.395'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.10.27\\\\t11_dist_2_frame_1.bmp': ['6 0.441667 0.511667 0.467708 0.553333',\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\2022.10.31\\\\2_592.bmp': ['13 0.366667 0.371667 0.392708 0.413333'],\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\2022.11.22\\\\3_866.bmp': ['6 0.436458 0.336667 0.4625 0.378333'],\n",
       " '.\\\\DATASET\\\\FRAMES\\\\2022.11.22\\\\3_879.bmp': ['5 0.413542 0.431667 0.439583 0.473333',\n",
       "  '5 0.485417 0.53 0.511458 0.571667',\n",
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       " '.\\\\DATASET\\\\FRAMES\\\\2022.11.22\\\\4_275.bmp': ['0 0.714583 0.746667 0.740625 0.788333'],\n",
       " ...}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "path = \".\\\\DATASET\\\\metadata\\\\test_set.cfg\"\n",
    "prefix = '.\\\\DATASET\\\\FRAMES\\\\'\n",
    "test_json = dict_frames_maker(path, prefix, 'test')\n",
    "test_json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ca7af56d-7502-4867-acca-d24142dd5765",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Изображений в тренировочной выборке: 7566\n",
      "Изображений в тестовой выборке 5500\n"
     ]
    }
   ],
   "source": [
    "count_train = len(os.listdir('.\\\\'+root+'\\\\train\\\\')) # Количество фото в тренировочной выборке\n",
    "count_test = len(os.listdir('.\\\\'+root+'\\\\test\\\\')) # Количество фото в тестовой выборке\n",
    "print(f\"Изображений в тренировочной выборке: {count_train}\\nИзображений в тестовой выборке {count_test}\")\n",
    "del count_test, count_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1e6124dc-b50e-41bd-9a17-dd9f28187555",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'names': ['не дефект',\n",
       "  'потертость',\n",
       "  'черная точка',\n",
       "  'плена',\n",
       "  'маркер',\n",
       "  'грязь',\n",
       "  'накол',\n",
       "  'н.д. накол',\n",
       "  'микровыступ',\n",
       "  'н.д. микровыступ',\n",
       "  'вмятина',\n",
       "  'мех.повреждение',\n",
       "  'риска',\n",
       "  'царапина с волчком'],\n",
       " 'train': 'C:\\\\Users\\\\k1rsn\\\\Notebook\\\\Defect-Detection\\\\data\\\\train',\n",
       " 'val': 'C:\\\\Users\\\\k1rsn\\\\Notebook\\\\Defect-Detection\\\\data\\\\test',\n",
       " 'nc': 14}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Формируем словарь\n",
    "json_yalm = {\n",
    "    \"names\": \"DATASET\",\n",
    "    \"train\": \"C:\\\\Users\\\\k1rsn\\\\Notebook\\\\Defect-Detection\\\\data\\\\train\",\n",
    "    \"val\": \"C:\\\\Users\\\\k1rsn\\\\Notebook\\\\Defect-Detection\\\\data\\\\test\",\n",
    "}\n",
    "\n",
    "def dict_classes_maker(path):\n",
    "    '''\n",
    "    Функция позволяет спарсить классы дефектов \n",
    "    Input:\n",
    "        path - путь до конфига \n",
    "    '''\n",
    "    # Читаем файл\n",
    "    with codecs.open(path, 'r', encoding='cp1251') as fdata:\n",
    "        list_lines = fdata.readlines() # Читаем по строкам файлы \n",
    "        my_dict = {} # Словарь классов \n",
    "        # Запустем цикл по всем строкам файла .cfg\n",
    "        for line in list_lines:\n",
    "            items = line.split(', ')\n",
    "            my_dict[items[0].split()[1]] = items[-1][:-2]\n",
    "        return my_dict\n",
    "\n",
    "ded = dict_classes_maker('./DATASET/metadata/classes.cfg')\n",
    "\n",
    "# Запишем в словарь\n",
    "json_yalm['nc'] = len(list(ded.values()))\n",
    "json_yalm['names'] = list(ded.values())\n",
    "json_yalm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a786c0b5-12b7-49d8-890b-b373db96ff71",
   "metadata": {},
   "outputs": [],
   "source": [
    "import yaml\n",
    "\n",
    "# Преобразование данных в формат YAML\n",
    "yaml_data = yaml.dump(json_yalm)\n",
    "\n",
    "# Запись данных в файл в формате YAML\n",
    "with open('yaml_format.yaml', 'w', encoding='utf-8') as file:\n",
    "    file.write(yaml_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24c31b06-4303-4617-895f-82c2a3c59c04",
   "metadata": {},
   "source": [
    "# 4. Обучение нейросети"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cd4ad6c2-aad1-411a-a74b-80123f075c2f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                   from  n    params  module                                       arguments                     \n",
      "  0                  -1  1       928  ultralytics.nn.modules.conv.Conv             [3, 32, 3, 2]                 \n",
      "  1                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]                \n",
      "  2                  -1  1     29056  ultralytics.nn.modules.block.C2f             [64, 64, 1, True]             \n",
      "  3                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]               \n",
      "  4                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]           \n",
      "  5                  -1  1    295424  ultralytics.nn.modules.conv.Conv             [128, 256, 3, 2]              \n",
      "  6                  -1  2    788480  ultralytics.nn.modules.block.C2f             [256, 256, 2, True]           \n",
      "  7                  -1  1   1180672  ultralytics.nn.modules.conv.Conv             [256, 512, 3, 2]              \n",
      "  8                  -1  1   1838080  ultralytics.nn.modules.block.C2f             [512, 512, 1, True]           \n",
      "  9                  -1  1    656896  ultralytics.nn.modules.block.SPPF            [512, 512, 5]                 \n",
      " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 12                  -1  1    591360  ultralytics.nn.modules.block.C2f             [768, 256, 1]                 \n",
      " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 15                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]                 \n",
      " 16                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]              \n",
      " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 18                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]                 \n",
      " 19                  -1  1    590336  ultralytics.nn.modules.conv.Conv             [256, 256, 3, 2]              \n",
      " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 21                  -1  1   1969152  ultralytics.nn.modules.block.C2f             [768, 512, 1]                 \n",
      " 22        [15, 18, 21]  1   2147008  ultralytics.nn.modules.head.Detect           [80, [128, 256, 512]]         \n",
      "YOLOv8s summary: 225 layers, 11166560 parameters, 11166544 gradients, 28.8 GFLOPs\n",
      "\n",
      "Transferred 355/355 items from pretrained weights\n"
     ]
    }
   ],
   "source": [
    "from ultralytics import YOLO\n",
    "model = YOLO('yolov8n.yaml').load('yolov8n.pt')  #  загружаем стандартные веса"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "210430b6-34cf-4009-b1a1-a63c2f90287c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ultralytics YOLOv8.0.227 🚀 Python-3.11.5 torch-2.1.1+cu118 CUDA:0 (NVIDIA GeForce RTX 3050 Laptop GPU, 4096MiB)\n",
      "\u001b[34m\u001b[1mengine\\trainer: \u001b[0mtask=detect, mode=train, model=yolov8s.yaml, data=yaml_format.yaml, epochs=100, patience=50, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train65, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0, cfg=None, tracker=botsort.yaml, save_dir=runs\\detect\\train65\n",
      "Overriding model.yaml nc=80 with nc=14\n",
      "\n",
      "                   from  n    params  module                                       arguments                     \n",
      "  0                  -1  1       928  ultralytics.nn.modules.conv.Conv             [3, 32, 3, 2]                 \n",
      "  1                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]                \n",
      "  2                  -1  1     29056  ultralytics.nn.modules.block.C2f             [64, 64, 1, True]             \n",
      "  3                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]               \n",
      "  4                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]           \n",
      "  5                  -1  1    295424  ultralytics.nn.modules.conv.Conv             [128, 256, 3, 2]              \n",
      "  6                  -1  2    788480  ultralytics.nn.modules.block.C2f             [256, 256, 2, True]           \n",
      "  7                  -1  1   1180672  ultralytics.nn.modules.conv.Conv             [256, 512, 3, 2]              \n",
      "  8                  -1  1   1838080  ultralytics.nn.modules.block.C2f             [512, 512, 1, True]           \n",
      "  9                  -1  1    656896  ultralytics.nn.modules.block.SPPF            [512, 512, 5]                 \n",
      " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 12                  -1  1    591360  ultralytics.nn.modules.block.C2f             [768, 256, 1]                 \n",
      " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 15                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]                 \n",
      " 16                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]              \n",
      " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 18                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]                 \n",
      " 19                  -1  1    590336  ultralytics.nn.modules.conv.Conv             [256, 256, 3, 2]              \n",
      " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 21                  -1  1   1969152  ultralytics.nn.modules.block.C2f             [768, 512, 1]                 \n",
      " 22        [15, 18, 21]  1   2121466  ultralytics.nn.modules.head.Detect           [14, [128, 256, 512]]         \n",
      "YOLOv8s summary: 225 layers, 11141018 parameters, 11141002 gradients, 28.7 GFLOPs\n",
      "\n",
      "Transferred 349/355 items from pretrained weights\n",
      "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs\\detect\\train65', view at http://localhost:6006/\n",
      "Freezing layer 'model.22.dfl.conv.weight'\n",
      "\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks with YOLOv8n...\n",
      "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mtrain: \u001b[0mScanning C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train.cache... 3782 images, 0 backgrounds, 271 corrupt: 1\u001b[0m"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_086_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_087.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_087_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_095.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_104.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_111.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_114.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_116.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_117.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_123.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_132.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_134.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_144.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_152.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_175.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_182.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_183.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_195.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_225.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_226.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_258.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_260.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_271.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_278.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_293.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_333.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_339.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_375.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_379.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_388.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_394.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_410.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_417.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_424.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_458.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_481.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_494.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_496.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_524.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_599.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_614.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_621.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_622.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_685.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_686.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_726.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_741.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_746.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_769.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_771.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_859.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_891.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_086.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_087.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_087_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_114_.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_115_.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_141.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_166.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_174.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_265.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_290.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_295.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_305.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_333.bmp: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0031]\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_343.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_380.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_406.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_435.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_458.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_470.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_498.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_533.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_539.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_561.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_568.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_584.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_608.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_615.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_672.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_800.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_879.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2 раковины.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_118.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_139.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_141.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_161.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_166.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_175.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_201.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_209.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_264.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_283.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_310.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_338.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_351.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_359.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_418.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_490.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_530.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_588.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_627.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_637.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_660.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_713.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_756.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_793.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_796.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_800.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_812.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_900.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_086_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_098.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_103.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_128.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_171.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_197.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_198.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_242.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_264.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_281.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_292.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_303.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_325.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_335.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_336.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_340.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_342.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_351.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_360.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_362.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_370.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_388.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_400.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_484.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_501.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_552.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_582.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_586.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_587.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_615.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_630.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_638.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_653.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_671.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_681.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_692.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_755.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_768.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_774.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_780.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_784.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_792.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_793.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_804.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_820.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_822.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_880.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_072.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_133.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_142.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_172.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_185.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_206.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_212.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_214.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_215.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_250.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_257.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_258.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_270.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_349.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_381.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_390.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_437.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_480.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_549.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_556.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_579.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_585.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_596.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_615.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_623.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_636.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_638.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_670.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_691.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_717.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_741.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_746.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_761.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_768.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_788.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_823.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_843.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_845.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_864.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_870.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_875.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_907.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_072.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_098.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_111.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_127.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_135.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_163.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_177.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_191.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_216.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_293.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_296.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_314.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_336.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_350.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_369.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_370.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_384.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_396.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_411.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_429.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_466.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_467.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_501.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_537.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_545.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_577.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_592.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_598.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_709.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_714.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_721.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_733.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_766.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_770.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_787.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_802.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_803.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_815.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_816_0.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_872.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_895.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0002.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0005.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0006.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0007.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0008.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0009.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0010.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0011.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0012.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0013.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0014.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0015.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\t6_dist_1_frame_2.bmp: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0167]\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\кольцо 38 мкм.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\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"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mval: \u001b[0mScanning C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test.cache... 2749 images, 0 backgrounds, 205 corrupt: 100%\u001b[0m"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_086.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_086_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_087.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_087_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_095.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_104.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_114.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_116.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_117.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_123.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_132.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_144.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_182.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_195.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_225.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_226.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_258.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_260.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_271.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_333.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_375.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_388.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_417.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_458.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_481.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_494.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_529.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_621.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_622.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_686.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_746.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_766.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_891.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_087.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_087_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_114_.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_115_.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_116.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_117.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_141.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_166.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_174.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_290.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_294.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_435.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_470.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_498.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_522.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_533.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_544.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_554.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_615.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_788.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2 раковины.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_101.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_102.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_122.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_139.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_147.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_161.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_179.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_201.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_283.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_338.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_351.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_490.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_530.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_627.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_678.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_793.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_796.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_812.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_086_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_098.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_103.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_108.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_111.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_117.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_128.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_129.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_139.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_171.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_182.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_197.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_198.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_204.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_213.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_228.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_241.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_242.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_281.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_292.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_303.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_325.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_336.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_340.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_351.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_362.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_370.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_380.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_388.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_460.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_484.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_515.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_529.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_630.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_638.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_671.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_692.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_774.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_779.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_784.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_792.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_793.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_804.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_877.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_880.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_885.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_072.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_120.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_172.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_206.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_212.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_214.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_215.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_222.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_250.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_257.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_258.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_270.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_312.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_378.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_390.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_549.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_556.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_585.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_596.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_670.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_691.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_701.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_717.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_746.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_768.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_788.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_817.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_818.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_823.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_836.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_877.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_907.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_072.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_098.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_108.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_111.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_163.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_173.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_177.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_196.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_216.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_226.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_248.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_314.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_336.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_350.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_369.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_384.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_396.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_501.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_537.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_545.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_577.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_598.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_714.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_733.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_803.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_815.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_816_0.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_872.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_893.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0002.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0006.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0010.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0011.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0014.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0015.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\t6_dist_1_frame_2.bmp: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0167]\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\кольцо 38 мкм.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting labels to runs\\detect\\train65\\labels.jpg... \n",
      "\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n",
      "\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.000556, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n",
      "Image sizes 640 train, 640 val\n",
      "Using 8 dataloader workers\n",
      "Logging results to \u001b[1mruns\\detect\\train65\u001b[0m\n",
      "Starting training for 100 epochs...\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      1/100      4.25G      2.054      3.029      2.277         87        640: 100%|██████████| 220/220 [02:52<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:49\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.373      0.257       0.09     0.0411\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      2/100      4.33G      1.545      2.371       1.92         71        640: 100%|██████████| 220/220 [03:39<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:40\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.305      0.342      0.166     0.0844\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      3/100      4.34G      1.452      2.297      1.863         91        640: 100%|██████████| 220/220 [03:21<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:50\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.316       0.25      0.116     0.0564\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      4/100      4.32G      1.387      2.252      1.823         73        640: 100%|██████████| 220/220 [04:30<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [01:52\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.269      0.397      0.227      0.132\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      5/100      4.32G      1.338      2.198      1.775         84        640: 100%|██████████| 220/220 [03:28<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:47\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.267      0.461      0.252      0.149\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      6/100      4.33G      1.308       2.17      1.754        104        640: 100%|██████████| 220/220 [04:28<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:51\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.296      0.421      0.249      0.162\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      7/100      4.32G      1.269      2.155      1.727         71        640: 100%|██████████| 220/220 [03:15<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:50\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.257      0.465      0.268      0.153\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      8/100      4.33G      1.247       2.14      1.715         74        640: 100%|██████████| 220/220 [06:30<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [01:52\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.458      0.398      0.297      0.186\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      9/100      4.32G      1.223       2.11      1.688         82        640: 100%|██████████| 220/220 [02:50<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:54\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.333       0.52      0.352      0.239\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     10/100      4.33G      1.203      2.099      1.675         53        640: 100%|██████████| 220/220 [04:32<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [01:42\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.385      0.555      0.405      0.289\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     11/100      4.32G      1.174      2.063      1.651         98        640: 100%|██████████| 220/220 [03:51<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:59\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.312      0.567      0.365      0.248\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     12/100      4.49G      1.179      2.073      1.666        106        640: 100%|██████████| 220/220 [05:00<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:43\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.428      0.478      0.371      0.251\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     13/100      4.33G      1.148      2.048       1.64         75        640: 100%|██████████| 220/220 [03:49<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:59\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.383      0.555      0.419      0.288\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     14/100      4.33G      1.138      2.029      1.637         78        640: 100%|██████████| 220/220 [05:09<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [01:47\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.346      0.564       0.38      0.262\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     15/100      4.33G      1.116      2.019      1.616         73        640: 100%|██████████| 220/220 [04:54<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [01:46\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.431      0.625       0.46      0.348\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     16/100      4.32G      1.104      2.003      1.603         81        640: 100%|██████████| 220/220 [04:37<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [01:36"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.483      0.533      0.457      0.356\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     17/100      4.33G      1.101      2.015        1.6         92        640: 100%|██████████| 220/220 [02:42<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [01:40"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.446      0.623      0.499      0.397\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     18/100      4.32G      1.097      1.987      1.597         65        640: 100%|██████████| 220/220 [04:44<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:53"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.441       0.56      0.491      0.351\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     19/100      4.32G      1.077      1.988      1.583         85        640: 100%|██████████| 220/220 [03:56<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [02:12\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.431      0.549      0.452      0.324\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     20/100      4.32G      1.062      1.983      1.578        109        640: 100%|██████████| 220/220 [04:01<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [02:35\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.449      0.637      0.527      0.416\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     21/100      4.32G      1.055      1.971      1.571         65        640: 100%|██████████| 220/220 [06:51<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [01:14\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.436      0.598      0.501      0.384\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     22/100      4.31G      1.043      1.956      1.567        109        640: 100%|██████████| 220/220 [06:25<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:47\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.459      0.625      0.503      0.393\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     23/100      4.31G      1.045      1.937      1.561         97        640: 100%|██████████| 220/220 [06:25<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:59"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.496      0.644      0.545      0.437\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     24/100      4.31G      1.063      1.907      1.578        199        640:   2%|▏         | 5/220 [00:08<06:18,  1.\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[3], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myaml_format.yaml\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\engine\\model.py:338\u001b[0m, in \u001b[0;36mModel.train\u001b[1;34m(self, trainer, **kwargs)\u001b[0m\n\u001b[0;32m    336\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtrainer\u001b[38;5;241m.\u001b[39mmodel\n\u001b[0;32m    337\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtrainer\u001b[38;5;241m.\u001b[39mhub_session \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msession  \u001b[38;5;66;03m# attach optional HUB session\u001b[39;00m\n\u001b[1;32m--> 338\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    339\u001b[0m \u001b[38;5;66;03m# Update model and cfg after training\u001b[39;00m\n\u001b[0;32m    340\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m RANK \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m0\u001b[39m):\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\engine\\trainer.py:190\u001b[0m, in \u001b[0;36mBaseTrainer.train\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    187\u001b[0m         ddp_cleanup(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28mstr\u001b[39m(file))\n\u001b[0;32m    189\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 190\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_do_train\u001b[49m\u001b[43m(\u001b[49m\u001b[43mworld_size\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\engine\\trainer.py:337\u001b[0m, in \u001b[0;36mBaseTrainer._do_train\u001b[1;34m(self, world_size)\u001b[0m\n\u001b[0;32m    335\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mcuda\u001b[38;5;241m.\u001b[39mamp\u001b[38;5;241m.\u001b[39mautocast(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mamp):\n\u001b[0;32m    336\u001b[0m     batch \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpreprocess_batch(batch)\n\u001b[1;32m--> 337\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mloss, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mloss_items \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    338\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m RANK \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m    339\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mloss \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m=\u001b[39m world_size\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1516\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[0;32m   1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m-> 1518\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[0;32m   1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[0;32m   1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[0;32m   1525\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[0;32m   1526\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[1;32m-> 1527\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m   1530\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\nn\\tasks.py:41\u001b[0m, in \u001b[0;36mBaseModel.forward\u001b[1;34m(self, x, *args, **kwargs)\u001b[0m\n\u001b[0;32m     31\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m     32\u001b[0m \u001b[38;5;124;03mForward pass of the model on a single scale. Wrapper for `_forward_once` method.\u001b[39;00m\n\u001b[0;32m     33\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     38\u001b[0m \u001b[38;5;124;03m    (torch.Tensor): The output of the network.\u001b[39;00m\n\u001b[0;32m     39\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m     40\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mdict\u001b[39m):  \u001b[38;5;66;03m# for cases of training and validating while training.\u001b[39;00m\n\u001b[1;32m---> 41\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloss\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     42\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpredict(x, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\nn\\tasks.py:212\u001b[0m, in \u001b[0;36mBaseModel.loss\u001b[1;34m(self, batch, preds)\u001b[0m\n\u001b[0;32m    209\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcriterion \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minit_criterion()\n\u001b[0;32m    211\u001b[0m preds \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mforward(batch[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mimg\u001b[39m\u001b[38;5;124m'\u001b[39m]) \u001b[38;5;28;01mif\u001b[39;00m preds \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m preds\n\u001b[1;32m--> 212\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcriterion\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpreds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\utils\\loss.py:188\u001b[0m, in \u001b[0;36mv8DetectionLoss.__call__\u001b[1;34m(self, preds, batch)\u001b[0m\n\u001b[0;32m    185\u001b[0m \u001b[38;5;66;03m# Pboxes\u001b[39;00m\n\u001b[0;32m    186\u001b[0m pred_bboxes \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbbox_decode(anchor_points, pred_distri)  \u001b[38;5;66;03m# xyxy, (b, h*w, 4)\u001b[39;00m\n\u001b[1;32m--> 188\u001b[0m _, target_bboxes, target_scores, fg_mask, _ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massigner\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    189\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpred_scores\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdetach\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msigmoid\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mpred_bboxes\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdetach\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mstride_tensor\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtype\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgt_bboxes\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    190\u001b[0m \u001b[43m    \u001b[49m\u001b[43manchor_points\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mstride_tensor\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgt_labels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgt_bboxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmask_gt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    192\u001b[0m target_scores_sum \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmax\u001b[39m(target_scores\u001b[38;5;241m.\u001b[39msum(), \u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m    194\u001b[0m \u001b[38;5;66;03m# Cls loss\u001b[39;00m\n\u001b[0;32m    195\u001b[0m \u001b[38;5;66;03m# loss[1] = self.varifocal_loss(pred_scores, target_scores, target_labels) / target_scores_sum  # VFL way\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1516\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[0;32m   1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m-> 1518\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[0;32m   1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[0;32m   1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[0;32m   1525\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[0;32m   1526\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[1;32m-> 1527\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m   1530\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\utils\\_contextlib.py:115\u001b[0m, in \u001b[0;36mcontext_decorator.<locals>.decorate_context\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    112\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[0;32m    113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecorate_context\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m    114\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m ctx_factory():\n\u001b[1;32m--> 115\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\utils\\tal.py:115\u001b[0m, in \u001b[0;36mTaskAlignedAssigner.forward\u001b[1;34m(self, pd_scores, pd_bboxes, anc_points, gt_labels, gt_bboxes, mask_gt)\u001b[0m\n\u001b[0;32m    110\u001b[0m     device \u001b[38;5;241m=\u001b[39m gt_bboxes\u001b[38;5;241m.\u001b[39mdevice\n\u001b[0;32m    111\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m (torch\u001b[38;5;241m.\u001b[39mfull_like(pd_scores[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m0\u001b[39m], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbg_idx)\u001b[38;5;241m.\u001b[39mto(device), torch\u001b[38;5;241m.\u001b[39mzeros_like(pd_bboxes)\u001b[38;5;241m.\u001b[39mto(device),\n\u001b[0;32m    112\u001b[0m             torch\u001b[38;5;241m.\u001b[39mzeros_like(pd_scores)\u001b[38;5;241m.\u001b[39mto(device), torch\u001b[38;5;241m.\u001b[39mzeros_like(pd_scores[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m0\u001b[39m])\u001b[38;5;241m.\u001b[39mto(device),\n\u001b[0;32m    113\u001b[0m             torch\u001b[38;5;241m.\u001b[39mzeros_like(pd_scores[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m0\u001b[39m])\u001b[38;5;241m.\u001b[39mto(device))\n\u001b[1;32m--> 115\u001b[0m mask_pos, align_metric, overlaps \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_pos_mask\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpd_scores\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpd_bboxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgt_labels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgt_bboxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43manc_points\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    116\u001b[0m \u001b[43m                                                     \u001b[49m\u001b[43mmask_gt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    118\u001b[0m target_gt_idx, fg_mask, mask_pos \u001b[38;5;241m=\u001b[39m select_highest_overlaps(mask_pos, overlaps, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_max_boxes)\n\u001b[0;32m    120\u001b[0m \u001b[38;5;66;03m# Assigned target\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\utils\\tal.py:136\u001b[0m, in \u001b[0;36mTaskAlignedAssigner.get_pos_mask\u001b[1;34m(self, pd_scores, pd_bboxes, gt_labels, gt_bboxes, anc_points, mask_gt)\u001b[0m\n\u001b[0;32m    134\u001b[0m mask_in_gts \u001b[38;5;241m=\u001b[39m select_candidates_in_gts(anc_points, gt_bboxes)\n\u001b[0;32m    135\u001b[0m \u001b[38;5;66;03m# Get anchor_align metric, (b, max_num_obj, h*w)\u001b[39;00m\n\u001b[1;32m--> 136\u001b[0m align_metric, overlaps \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_box_metrics\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpd_scores\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpd_bboxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgt_labels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgt_bboxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmask_in_gts\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mmask_gt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    137\u001b[0m \u001b[38;5;66;03m# Get topk_metric mask, (b, max_num_obj, h*w)\u001b[39;00m\n\u001b[0;32m    138\u001b[0m mask_topk \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mselect_topk_candidates(align_metric, topk_mask\u001b[38;5;241m=\u001b[39mmask_gt\u001b[38;5;241m.\u001b[39mexpand(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtopk)\u001b[38;5;241m.\u001b[39mbool())\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\utils\\tal.py:158\u001b[0m, in \u001b[0;36mTaskAlignedAssigner.get_box_metrics\u001b[1;34m(self, pd_scores, pd_bboxes, gt_labels, gt_bboxes, mask_gt)\u001b[0m\n\u001b[0;32m    155\u001b[0m bbox_scores[mask_gt] \u001b[38;5;241m=\u001b[39m pd_scores[ind[\u001b[38;5;241m0\u001b[39m], :, ind[\u001b[38;5;241m1\u001b[39m]][mask_gt]  \u001b[38;5;66;03m# b, max_num_obj, h*w\u001b[39;00m\n\u001b[0;32m    157\u001b[0m \u001b[38;5;66;03m# (b, max_num_obj, 1, 4), (b, 1, h*w, 4)\u001b[39;00m\n\u001b[1;32m--> 158\u001b[0m pd_boxes \u001b[38;5;241m=\u001b[39m \u001b[43mpd_bboxes\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munsqueeze\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mexpand(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_max_boxes, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m)[mask_gt]\n\u001b[0;32m    159\u001b[0m gt_boxes \u001b[38;5;241m=\u001b[39m gt_bboxes\u001b[38;5;241m.\u001b[39munsqueeze(\u001b[38;5;241m2\u001b[39m)\u001b[38;5;241m.\u001b[39mexpand(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, na, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m)[mask_gt]\n\u001b[0;32m    160\u001b[0m overlaps[mask_gt] \u001b[38;5;241m=\u001b[39m bbox_iou(gt_boxes, pd_boxes, xywh\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, CIoU\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\u001b[38;5;241m.\u001b[39msqueeze(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m)\u001b[38;5;241m.\u001b[39mclamp_(\u001b[38;5;241m0\u001b[39m)\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "results = model.train(data='yaml_format.yaml', epochs=100) # Запускае обучение на 100 эпох"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c6674d7-c53b-4edc-803c-349caff816d2",
   "metadata": {},
   "source": [
    "Дообучение весов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "88b83c5e-3fb5-4fa6-873a-3ca064a6c741",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ultralytics YOLOv8.0.227 🚀 Python-3.11.5 torch-2.1.1+cu118 CUDA:0 (NVIDIA GeForce RTX 3050 Laptop GPU, 4096MiB)\n",
      "\u001b[34m\u001b[1mengine\\trainer: \u001b[0mtask=detect, mode=train, model=.\\runs\\detect\\train60\\weights\\best.pt, data=yaml_format.yaml, epochs=100, patience=50, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train64, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0, cfg=None, tracker=botsort.yaml, save_dir=runs\\detect\\train64\n",
      "\n",
      "                   from  n    params  module                                       arguments                     \n",
      "  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]                 \n",
      "  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]                \n",
      "  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]             \n",
      "  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]                \n",
      "  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]             \n",
      "  5                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]               \n",
      "  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]           \n",
      "  7                  -1  1    295424  ultralytics.nn.modules.conv.Conv             [128, 256, 3, 2]              \n",
      "  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]           \n",
      "  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]                 \n",
      " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 12                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]                 \n",
      " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 15                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]                  \n",
      " 16                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]                \n",
      " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 18                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]                 \n",
      " 19                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]              \n",
      " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 21                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]                 \n",
      " 22        [15, 18, 21]  1    754042  ultralytics.nn.modules.head.Detect           [14, [64, 128, 256]]          \n",
      "YOLOv8n summary: 225 layers, 3013578 parameters, 3013562 gradients, 8.2 GFLOPs\n",
      "\n",
      "Transferred 355/355 items from pretrained weights\n",
      "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs\\detect\\train64', view at http://localhost:6006/\n",
      "Freezing layer 'model.22.dfl.conv.weight'\n",
      "\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks with YOLOv8n...\n",
      "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mtrain: \u001b[0mScanning C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train.cache... 3782 images, 0 backgrounds, 271 corrupt: 1\u001b[0m"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_086_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_087.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_087_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_095.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_104.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_111.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_114.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_116.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_117.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_123.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_132.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_134.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_144.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_152.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_175.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_182.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_183.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_195.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_225.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_226.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_258.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_260.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_271.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_278.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_293.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_333.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_339.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_375.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_379.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_388.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_394.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_410.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_417.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_424.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_458.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_481.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_494.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_496.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_524.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_599.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_614.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_621.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_622.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_685.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_686.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_726.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_741.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_746.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_769.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_771.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_859.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\0_891.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_086.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_087.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_087_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_114_.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_115_.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_141.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_166.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_174.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_265.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_290.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_295.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_305.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_333.bmp: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0031]\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_343.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_380.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_406.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_435.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_458.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_470.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_498.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_533.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_539.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_561.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_568.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_584.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_608.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_615.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_672.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_800.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\1_879.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2 раковины.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_118.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_139.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_141.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_161.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_166.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_175.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_201.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_209.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_264.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_283.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_310.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_338.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_351.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_359.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_418.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_490.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_530.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_588.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_627.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_637.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_660.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_713.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_756.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_793.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_796.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_800.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_812.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\2_900.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_086_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_098.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_103.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_128.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_171.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_197.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_198.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_242.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_264.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_281.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_292.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_303.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_325.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_335.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_336.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_340.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_342.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_351.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_360.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_362.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_370.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_388.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_400.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_484.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_501.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_552.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_582.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_586.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_587.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_615.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_630.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_638.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_653.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_671.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_681.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_692.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_755.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_768.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_774.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_780.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_784.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_792.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_793.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_804.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_820.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_822.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\3_880.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_072.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_133.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_142.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_172.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_185.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_206.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_212.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_214.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_215.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_250.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_257.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_258.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_270.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_349.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_381.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_390.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_437.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_480.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_549.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_556.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_579.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_585.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_596.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_615.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_623.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_636.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_638.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_670.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_691.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_717.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_741.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_746.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_761.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_768.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_788.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_823.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_843.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_845.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_864.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_870.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_875.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\4_907.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_072.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_098.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_111.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_127.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_135.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_163.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_177.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_191.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_216.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_293.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_296.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_314.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_336.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_350.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_369.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_370.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_384.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_396.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_411.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_429.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_466.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_467.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_501.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_537.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_545.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_577.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_592.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_598.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_709.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_714.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_721.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_733.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_766.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_770.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_787.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_802.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_803.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_815.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_816_0.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_872.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\5_895.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0002.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0005.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0006.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0007.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0008.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0009.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0010.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0011.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0012.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0013.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0014.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\frame0015.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\t6_dist_1_frame_2.bmp: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0167]\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\train\\кольцо 38 мкм.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\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"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mval: \u001b[0mScanning C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test.cache... 2749 images, 0 backgrounds, 205 corrupt: 100%\u001b[0m"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_086.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_086_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_087.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_087_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_095.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_104.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_114.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_116.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_117.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_123.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_132.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_144.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_182.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_195.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_225.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_226.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_258.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_260.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_271.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_333.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_375.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_388.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_417.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_458.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_481.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_494.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_529.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_621.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_622.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_686.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_746.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_766.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\0_891.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_087.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_087_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_114_.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_115_.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_116.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_117.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_141.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_166.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_174.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_290.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_294.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_435.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_470.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_498.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_522.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_533.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_544.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_554.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_615.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_788.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\1_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2 раковины.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_101.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_102.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_122.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_139.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_147.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_161.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_179.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_201.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_233.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_283.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_338.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_351.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_490.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_530.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_627.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_678.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_754.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_793.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_796.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\2_812.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_086_1.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_098.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_103.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_108.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_111.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_117.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_128.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_129.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_139.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_171.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_182.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_197.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_198.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_204.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_213.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_228.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_241.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_242.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_281.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_292.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_303.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_325.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_336.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_340.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_351.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_362.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_370.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_380.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_388.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_460.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_484.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_515.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_529.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_630.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_638.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_671.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_692.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_774.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_779.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_784.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_792.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_793.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_804.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_877.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_880.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\3_885.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_072.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_120.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_172.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_206.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_212.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_214.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_215.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_222.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_250.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_257.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_258.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_270.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_312.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_323.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_378.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_390.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_549.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_556.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_585.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_596.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_670.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_691.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_701.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_717.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_736.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_746.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_768.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_788.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_817.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_818.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_823.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_836.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_868.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_877.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\4_907.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_072.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_098.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_108.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_111.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_163.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_173.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_177.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_196.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_216.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_226.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_248.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_314.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_336.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_350.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_369.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_384.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_396.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_501.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_537.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_545.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_577.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_598.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_714.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_733.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_803.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_815.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_816_0.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_869.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_872.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\5_893.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0002.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0006.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0010.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0011.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0014.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\frame0015.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\t6_dist_1_frame_2.bmp: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0167]\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ C:\\Users\\k1rsn\\Notebook\\Defect-Detection\\data\\test\\кольцо 38 мкм.bmp: ignoring corrupt image/label: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (17,) + inhomogeneous part.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting labels to runs\\detect\\train64\\labels.jpg... \n",
      "\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n",
      "\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.000556, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n",
      "Image sizes 640 train, 640 val\n",
      "Using 8 dataloader workers\n",
      "Logging results to \u001b[1mruns\\detect\\train64\u001b[0m\n",
      "Starting training for 100 epochs...\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      1/100      2.49G      0.845      1.844      1.405         87        640: 100%|██████████| 220/220 [00:53<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:21"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.558      0.743      0.631      0.545\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      2/100      2.51G      0.893      1.869      1.441         71        640: 100%|██████████| 220/220 [00:52<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.518      0.685      0.572       0.45\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      3/100      2.51G     0.9223      1.906      1.464         91        640: 100%|██████████| 220/220 [00:53<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:23\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.469      0.661      0.549      0.447\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      4/100      2.51G     0.9626       1.92      1.493         73        640: 100%|██████████| 220/220 [00:51<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:22\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.535      0.694      0.579      0.462\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      5/100      2.51G     0.9395      1.905      1.475         84        640: 100%|██████████| 220/220 [00:51<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:22\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.483      0.655      0.531      0.423\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      6/100      2.44G      0.954      1.909      1.487        104        640: 100%|██████████| 220/220 [00:51<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:22\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.506      0.664      0.566      0.458\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      7/100      2.51G     0.9618      1.923      1.495         71        640: 100%|██████████| 220/220 [00:54<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:25\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.415      0.586      0.459      0.342\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      8/100      2.51G     0.9486      1.915      1.486         74        640: 100%|██████████| 220/220 [00:52<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:21\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.531      0.611      0.554      0.454\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "      9/100      2.51G     0.9384      1.914      1.476         82        640: 100%|██████████| 220/220 [00:51<00:00,  \n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 80/80 [00:22\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   all       2544       4517      0.483      0.653      0.536      0.425\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "     10/100      2.23G     0.9545       1.92      1.481        216        640:  91%|█████████▏| 201/220 [00:48<00:04,  \n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[1], line 3\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01multralytics\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m YOLO\n\u001b[0;32m      2\u001b[0m model \u001b[38;5;241m=\u001b[39m YOLO(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mruns\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mdetect\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mtrain60\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mweights\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mbest.pt\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m----> 3\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myaml_format.yaml\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\engine\\model.py:338\u001b[0m, in \u001b[0;36mModel.train\u001b[1;34m(self, trainer, **kwargs)\u001b[0m\n\u001b[0;32m    336\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtrainer\u001b[38;5;241m.\u001b[39mmodel\n\u001b[0;32m    337\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtrainer\u001b[38;5;241m.\u001b[39mhub_session \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msession  \u001b[38;5;66;03m# attach optional HUB session\u001b[39;00m\n\u001b[1;32m--> 338\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    339\u001b[0m \u001b[38;5;66;03m# Update model and cfg after training\u001b[39;00m\n\u001b[0;32m    340\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m RANK \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m0\u001b[39m):\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\engine\\trainer.py:190\u001b[0m, in \u001b[0;36mBaseTrainer.train\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    187\u001b[0m         ddp_cleanup(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28mstr\u001b[39m(file))\n\u001b[0;32m    189\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 190\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_do_train\u001b[49m\u001b[43m(\u001b[49m\u001b[43mworld_size\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\ultralytics\\engine\\trainer.py:344\u001b[0m, in \u001b[0;36mBaseTrainer._do_train\u001b[1;34m(self, world_size)\u001b[0m\n\u001b[0;32m    340\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtloss \u001b[38;5;241m=\u001b[39m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtloss \u001b[38;5;241m*\u001b[39m i \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mloss_items) \u001b[38;5;241m/\u001b[39m (i \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtloss \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \\\n\u001b[0;32m    341\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mloss_items\n\u001b[0;32m    343\u001b[0m \u001b[38;5;66;03m# Backward\u001b[39;00m\n\u001b[1;32m--> 344\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mscaler\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mscale\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloss\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbackward\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    346\u001b[0m \u001b[38;5;66;03m# Optimize - https://pytorch.org/docs/master/notes/amp_examples.html\u001b[39;00m\n\u001b[0;32m    347\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ni \u001b[38;5;241m-\u001b[39m last_opt_step \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maccumulate:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\_tensor.py:492\u001b[0m, in \u001b[0;36mTensor.backward\u001b[1;34m(self, gradient, retain_graph, create_graph, inputs)\u001b[0m\n\u001b[0;32m    482\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m has_torch_function_unary(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m    483\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m handle_torch_function(\n\u001b[0;32m    484\u001b[0m         Tensor\u001b[38;5;241m.\u001b[39mbackward,\n\u001b[0;32m    485\u001b[0m         (\u001b[38;5;28mself\u001b[39m,),\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    490\u001b[0m         inputs\u001b[38;5;241m=\u001b[39minputs,\n\u001b[0;32m    491\u001b[0m     )\n\u001b[1;32m--> 492\u001b[0m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mautograd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbackward\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    493\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgradient\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mretain_graph\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_graph\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minputs\u001b[49m\n\u001b[0;32m    494\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\autograd\\__init__.py:251\u001b[0m, in \u001b[0;36mbackward\u001b[1;34m(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)\u001b[0m\n\u001b[0;32m    246\u001b[0m     retain_graph \u001b[38;5;241m=\u001b[39m create_graph\n\u001b[0;32m    248\u001b[0m \u001b[38;5;66;03m# The reason we repeat the same comment below is that\u001b[39;00m\n\u001b[0;32m    249\u001b[0m \u001b[38;5;66;03m# some Python versions print out the first line of a multi-line function\u001b[39;00m\n\u001b[0;32m    250\u001b[0m \u001b[38;5;66;03m# calls in the traceback and some print out the last line\u001b[39;00m\n\u001b[1;32m--> 251\u001b[0m \u001b[43mVariable\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_execution_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_backward\u001b[49m\u001b[43m(\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# Calls into the C++ engine to run the backward pass\u001b[39;49;00m\n\u001b[0;32m    252\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtensors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    253\u001b[0m \u001b[43m    \u001b[49m\u001b[43mgrad_tensors_\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    254\u001b[0m \u001b[43m    \u001b[49m\u001b[43mretain_graph\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    255\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcreate_graph\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    256\u001b[0m \u001b[43m    \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    257\u001b[0m \u001b[43m    \u001b[49m\u001b[43mallow_unreachable\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m    258\u001b[0m \u001b[43m    \u001b[49m\u001b[43maccumulate_grad\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m    259\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "model = YOLO('.\\\\runs\\\\detect\\\\train60\\\\weights\\\\best.pt') # Путь до лучших весов прошлого обучения\n",
    "results = model.train(data='yaml_format.yaml', epochs=100) # Запускаем обучение на 100 эпох"
   ]
  }
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