{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1398fe9e",
   "metadata": {},
   "source": [
    "# Начало лабораторной работы, юху(-оперативка в конце)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef6e5d15",
   "metadata": {},
   "source": [
    "## Классификация"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0ad9916",
   "metadata": {},
   "source": [
    "### Загрузка набора данных для задачи классификации\n",
    "\n",
    "В данной лабораторной работе используется набор данных с классификацией некотрых персонажей вселенной Marvel\n",
    "\n",
    "Набор данных состоит из 5 папок с изображениями 5 персонажей сооответственно: Капитан Омерика, Мертвый Бассейн, Соколиный Глаз, Халк, Росомаха\n",
    "\n",
    "Ссылка на датасет: https://www.kaggle.com/datasets/codyfrederick/simple-marvel-characters?resource=download\n",
    "\n",
    "#### Какова задача\n",
    "\n",
    "Задача: классификация перечисленных персонажей вселенной Marvel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "edd1233f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Всего классов: 5\n",
      "Список персонажей: ['captainamerica', 'deadpool', 'hawkeye', 'hulk', 'wolverine']\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "from PIL import Image\n",
    "from sklearn.model_selection import train_test_split\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout, BatchNormalization\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "\n",
    "# Устанавливаем seed для воспроизводимости\n",
    "np.random.seed(42)\n",
    "\n",
    "# Укажите путь к вашему датасету\n",
    "dataset_path = \"./static/images/data\"\n",
    "\n",
    "# Список классов (персонажей)\n",
    "characters = os.listdir(dataset_path)\n",
    "num_classes = len(characters)\n",
    "\n",
    "print(f\"Всего классов: {num_classes}\")\n",
    "print(\"Список персонажей:\", characters)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "988a79bb",
   "metadata": {},
   "source": [
    "### Отображение данных\n",
    "\n",
    "Вывод примеров классов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b633c86c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 15 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "for i, character in enumerate(characters[:5]):\n",
    "    character_dir = os.path.join(dataset_path, character)\n",
    "    img_files = os.listdir(character_dir)[:3]\n",
    "    \n",
    "    for j, img_file in enumerate(img_files):\n",
    "        img_path = os.path.join(character_dir, img_file)\n",
    "        img = Image.open(img_path)\n",
    "        \n",
    "        plt.subplot(5, 3, i*3 + j + 1)\n",
    "        plt.imshow(img)\n",
    "        plt.title(character)\n",
    "        plt.axis('off')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "748f74fd",
   "metadata": {},
   "source": [
    "### Предобработка изображений\n",
    "\n",
    "* Конвертация в RGB на случай черно-белых изображений\n",
    "* Ресайз до 128x128 пикселей\n",
    "* Нормализация значений пикселей в диапазон [0, 1]\n",
    "* Преобразование меток в one-hot encoding\n",
    "* Разделение данных на выборки"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "67a7260e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размер обучающей выборки: (215, 128, 128, 3)\n",
      "Размер тестовой выборки: (54, 128, 128, 3)\n",
      "Количество классов: 5\n"
     ]
    }
   ],
   "source": [
    "# Путь к датасету\n",
    "dataset_path = \"./static/images/data\"\n",
    "\n",
    "# Получаем список персонажей\n",
    "characters = sorted(os.listdir(dataset_path))\n",
    "num_classes = len(characters)\n",
    "\n",
    "# Параметры изображений\n",
    "img_width, img_height = 128, 128\n",
    "input_shape = (img_width, img_height, 3)  # используем 2D-изображения для CNN\n",
    "\n",
    "# Загрузка и предобработка изображений\n",
    "X = []\n",
    "y = []\n",
    "\n",
    "for i, character in enumerate(characters):\n",
    "    character_dir = os.path.join(dataset_path, character)\n",
    "    for img_file in os.listdir(character_dir):\n",
    "        try:\n",
    "            img_path = os.path.join(character_dir, img_file)\n",
    "            img = Image.open(img_path).convert('RGB')  # Убедимся, что 3 канала\n",
    "            img = img.resize((img_width, img_height))\n",
    "            img_array = np.array(img) / 255.0  # Нормализация\n",
    "            X.append(img_array)\n",
    "            y.append(i)\n",
    "        except Exception as e:\n",
    "            print(f\"Ошибка при загрузке {img_path}: {e}\")\n",
    "\n",
    "X = np.array(X)\n",
    "y = np.array(y)\n",
    "\n",
    "# Преобразование меток в one-hot encoding\n",
    "y = to_categorical(y, num_classes=num_classes)\n",
    "\n",
    "# Разделение данных\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42, stratify=y)\n",
    "\n",
    "print(f\"Размер обучающей выборки: {X_train.shape}\")\n",
    "print(f\"Размер тестовой выборки: {X_test.shape}\")\n",
    "print(f\"Количество классов: {num_classes}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97b6f189",
   "metadata": {},
   "source": [
    "### Создание модели CNN\n",
    "\n",
    "#### Архитектура CNN\n",
    "\n",
    "Слои и их назначение:\n",
    "\n",
    "1. Свёрточные блоки (Conv2D + BatchNorm + MaxPooling):\n",
    "\n",
    "    * Выделяют пространственные признаки\n",
    "\n",
    "    * BatchNorm ускоряет обучение\n",
    "\n",
    "2. Dropout:\n",
    "\n",
    "    * Борется с переобучением (0.2-0.5)\n",
    "\n",
    "3. Полносвязные слои:\n",
    "\n",
    "    * Анализируют извлечённые признаки\n",
    "\n",
    "4. Выходной слой:\n",
    "\n",
    "    * softmax для многоклассовой классификации\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "df4dcfb9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Admin\\StudioProjects\\AIM-PIbd-31-Alekseev-I-S\\aimenv\\Lib\\site-packages\\keras\\src\\layers\\convolutional\\base_conv.py:107: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
      "  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv2d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)   │           <span style=\"color: #00af00; text-decoration-color: #00af00\">896</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)   │           <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)   │         <span style=\"color: #00af00; text-decoration-color: #00af00\">9,248</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_1           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)   │           <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)     │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)     │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)     │        <span style=\"color: #00af00; text-decoration-color: #00af00\">18,496</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_2           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)     │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)     │        <span style=\"color: #00af00; text-decoration-color: #00af00\">36,928</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_3           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)     │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)     │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)     │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">73,856</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_4           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │           <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │       <span style=\"color: #00af00; text-decoration-color: #00af00\">147,584</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_5           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │           <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32768</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)            │     <span style=\"color: #00af00; text-decoration-color: #00af00\">8,388,864</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_6           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)            │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)            │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">5</span>)              │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,285</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv2d (\u001b[38;5;33mConv2D\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m32\u001b[0m)   │           \u001b[38;5;34m896\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m32\u001b[0m)   │           \u001b[38;5;34m128\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_1 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m32\u001b[0m)   │         \u001b[38;5;34m9,248\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_1           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m32\u001b[0m)   │           \u001b[38;5;34m128\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d (\u001b[38;5;33mMaxPooling2D\u001b[0m)    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m32\u001b[0m)     │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m32\u001b[0m)     │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_2 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m)     │        \u001b[38;5;34m18,496\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_2           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m)     │           \u001b[38;5;34m256\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_3 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m)     │        \u001b[38;5;34m36,928\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_3           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m)     │           \u001b[38;5;34m256\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_1 (\u001b[38;5;33mMaxPooling2D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m)     │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_1 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m64\u001b[0m)     │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_4 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │        \u001b[38;5;34m73,856\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_4           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │           \u001b[38;5;34m512\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_5 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │       \u001b[38;5;34m147,584\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_5           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │           \u001b[38;5;34m512\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_2 (\u001b[38;5;33mMaxPooling2D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_2 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten (\u001b[38;5;33mFlatten\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32768\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense (\u001b[38;5;33mDense\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m)            │     \u001b[38;5;34m8,388,864\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_6           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m)            │         \u001b[38;5;34m1,024\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_3 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m)            │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_1 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m5\u001b[0m)              │         \u001b[38;5;34m1,285\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">8,679,973</span> (33.11 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m8,679,973\u001b[0m (33.11 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">8,678,565</span> (33.11 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m8,678,565\u001b[0m (33.11 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">1,408</span> (5.50 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m1,408\u001b[0m (5.50 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def create_cnn_model(input_shape, num_classes):\n",
    "    model = Sequential()\n",
    "    \n",
    "    # Первый сверточный блок\n",
    "    model.add(Conv2D(32, (3, 3), activation='relu', padding='same', input_shape=input_shape))\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(Conv2D(32, (3, 3), activation='relu', padding='same'))\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(MaxPooling2D((2, 2)))\n",
    "    model.add(Dropout(0.2))\n",
    "    \n",
    "    # Второй сверточный блок\n",
    "    model.add(Conv2D(64, (3, 3), activation='relu', padding='same'))\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(Conv2D(64, (3, 3), activation='relu', padding='same'))\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(MaxPooling2D((2, 2)))\n",
    "    model.add(Dropout(0.3))\n",
    "    \n",
    "    # Третий сверточный блок\n",
    "    model.add(Conv2D(128, (3, 3), activation='relu', padding='same'))\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(Conv2D(128, (3, 3), activation='relu', padding='same'))\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(MaxPooling2D((2, 2)))\n",
    "    model.add(Dropout(0.4))\n",
    "    \n",
    "    # Полносвязные слои\n",
    "    model.add(Flatten())\n",
    "    model.add(Dense(256, activation='relu'))\n",
    "    model.add(BatchNormalization())\n",
    "    model.add(Dropout(0.5))\n",
    "    model.add(Dense(num_classes, activation='softmax'))\n",
    "    \n",
    "    # Компиляция модели\n",
    "    model.compile(optimizer=Adam(learning_rate=0.0001),\n",
    "                 loss='categorical_crossentropy',\n",
    "                 metrics=['accuracy'])\n",
    "    \n",
    "    return model\n",
    "\n",
    "model = create_cnn_model(input_shape, num_classes)\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "669e0d73",
   "metadata": {},
   "source": [
    "### Аугментация данных и обучение"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40c13ba2",
   "metadata": {},
   "source": [
    "Эффекты для аугментации:\n",
    "\n",
    "* Повороты на ±20°\n",
    "\n",
    "* Сдвиги по ширине/высоте на 20%\n",
    "\n",
    "* Горизонтальное отражение\n",
    "\n",
    "Для обучения возьмем 50 эпох"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2437db11",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Admin\\StudioProjects\\AIM-PIbd-31-Alekseev-I-S\\aimenv\\Lib\\site-packages\\keras\\src\\trainers\\data_adapters\\py_dataset_adapter.py:121: UserWarning: Your `PyDataset` class should call `super().__init__(**kwargs)` in its constructor. `**kwargs` can include `workers`, `use_multiprocessing`, `max_queue_size`. Do not pass these arguments to `fit()`, as they will be ignored.\n",
      "  self._warn_if_super_not_called()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 683ms/step - accuracy: 0.2191 - loss: 2.8230 - val_accuracy: 0.2500 - val_loss: 1.6083 - learning_rate: 1.0000e-04\n",
      "Epoch 2/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 39ms/step - accuracy: 0.2188 - loss: 2.1692 - val_accuracy: 0.1875 - val_loss: 1.6186 - learning_rate: 1.0000e-04\n",
      "Epoch 3/50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Admin\\StudioProjects\\AIM-PIbd-31-Alekseev-I-S\\aimenv\\Lib\\site-packages\\keras\\src\\trainers\\epoch_iterator.py:107: UserWarning: Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches. You may need to use the `.repeat()` function when building your dataset.\n",
      "  self._interrupted_warning()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 591ms/step - accuracy: 0.3167 - loss: 2.2168 - val_accuracy: 0.1875 - val_loss: 1.6216 - learning_rate: 1.0000e-04\n",
      "Epoch 4/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 32ms/step - accuracy: 0.3125 - loss: 2.0393 - val_accuracy: 0.2812 - val_loss: 1.5984 - learning_rate: 1.0000e-04\n",
      "Epoch 5/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 553ms/step - accuracy: 0.4306 - loss: 2.0434 - val_accuracy: 0.2188 - val_loss: 1.7040 - learning_rate: 1.0000e-04\n",
      "Epoch 6/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 29ms/step - accuracy: 0.5000 - loss: 1.6092 - val_accuracy: 0.2500 - val_loss: 1.6702 - learning_rate: 1.0000e-04\n",
      "Epoch 7/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 568ms/step - accuracy: 0.3554 - loss: 1.9729 - val_accuracy: 0.2188 - val_loss: 1.8088 - learning_rate: 1.0000e-04\n",
      "Epoch 8/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 29ms/step - accuracy: 0.3043 - loss: 2.0110 - val_accuracy: 0.1875 - val_loss: 1.8583 - learning_rate: 1.0000e-04\n",
      "Epoch 9/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 542ms/step - accuracy: 0.4436 - loss: 1.6193 - val_accuracy: 0.1875 - val_loss: 1.9989 - learning_rate: 1.0000e-04\n",
      "Epoch 10/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 28ms/step - accuracy: 0.4375 - loss: 1.8523 - val_accuracy: 0.1875 - val_loss: 2.0222 - learning_rate: 1.0000e-05\n",
      "Epoch 11/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 534ms/step - accuracy: 0.3894 - loss: 1.9038 - val_accuracy: 0.2500 - val_loss: 2.0370 - learning_rate: 1.0000e-05\n",
      "Epoch 12/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 33ms/step - accuracy: 0.4688 - loss: 1.5261 - val_accuracy: 0.1250 - val_loss: 2.3184 - learning_rate: 1.0000e-05\n",
      "Epoch 13/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 568ms/step - accuracy: 0.4809 - loss: 1.5141 - val_accuracy: 0.1875 - val_loss: 2.2570 - learning_rate: 1.0000e-05\n",
      "Epoch 14/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 29ms/step - accuracy: 0.5938 - loss: 1.3917 - val_accuracy: 0.1875 - val_loss: 2.3324 - learning_rate: 1.0000e-05\n"
     ]
    }
   ],
   "source": [
    "# Создаем генератор аугментированных данных\n",
    "train_datagen = ImageDataGenerator(\n",
    "    rotation_range=20,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    shear_range=0.2,\n",
    "    zoom_range=0.2,\n",
    "    horizontal_flip=True,\n",
    "    fill_mode='nearest'\n",
    ")\n",
    "\n",
    "# Генератор для тестовых данных (только нормализация)\n",
    "test_datagen = ImageDataGenerator()\n",
    "\n",
    "# Подготовка генераторов\n",
    "batch_size = 32\n",
    "train_generator = train_datagen.flow(X_train, y_train, batch_size=batch_size)\n",
    "test_generator = test_datagen.flow(X_test, y_test, batch_size=batch_size)\n",
    "\n",
    "# Коллбэки для обучения\n",
    "from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau\n",
    "\n",
    "callbacks = [\n",
    "    EarlyStopping(monitor='val_loss', patience=10, restore_best_weights=True),\n",
    "    ReduceLROnPlateau(monitor='val_loss', factor=0.1, patience=5)\n",
    "]\n",
    "\n",
    "# Обучение модели\n",
    "epochs = 50\n",
    "history = model.fit(\n",
    "    train_generator,\n",
    "    steps_per_epoch=len(X_train) // batch_size,\n",
    "    epochs=epochs,\n",
    "    validation_data=test_generator,\n",
    "    validation_steps=len(X_test) // batch_size,\n",
    "    callbacks=callbacks,\n",
    "    verbose=1\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d2949a9",
   "metadata": {},
   "source": [
    "### Оценка и визуализация результатов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "04fbc504",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Финальная точность на тестовых данных: 0.2407\n",
      "Финальные потери на тестовых данных: 1.6688\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Оценка модели на тестовых данных\n",
    "test_loss, test_acc = model.evaluate(test_generator, verbose=0)\n",
    "print(f\"\\nФинальная точность на тестовых данных: {test_acc:.4f}\")\n",
    "print(f\"Финальные потери на тестовых данных: {test_loss:.4f}\")\n",
    "\n",
    "# Графики обучения\n",
    "plt.figure(figsize=(12, 5))\n",
    "\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.plot(history.history['accuracy'], label='Обучающая точность')\n",
    "plt.plot(history.history['val_accuracy'], label='Валидационная точность')\n",
    "plt.title('Точность модели')\n",
    "plt.ylabel('Точность')\n",
    "plt.xlabel('Эпоха')\n",
    "plt.legend()\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.plot(history.history['loss'], label='Обучающие потери')\n",
    "plt.plot(history.history['val_loss'], label='Валидационные потери')\n",
    "plt.title('Потери модели')\n",
    "plt.ylabel('Потери')\n",
    "plt.xlabel('Эпоха')\n",
    "plt.legend()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c6b04f8",
   "metadata": {},
   "source": [
    "Реузльтаты обученной модели оказались не самыми лучшими - 18.5% точности.\n",
    "\n",
    "Анализ проблемы:\n",
    "\n",
    "1. Недостаточная сложность модели для датасета\n",
    "\n",
    "    Так как в кадом классе датасета персонаж предосталвен во всех возможных вариациях(в супер-костюме - без костюма, в полный рост - в анфаз и т.д.), модели достаточно тяжело кооректно предугадать персонажа по изборажению\n",
    "\n",
    "2. Переобучение\n",
    "\n",
    "    Слишком большая разница между train и val accuracy\n",
    "\n",
    "3. Проблемы с данными \n",
    "\n",
    "    Неправильная предобработка или несбалансированные классы"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82e5cd48",
   "metadata": {},
   "source": [
    "### Попытка №2\n",
    "\n",
    "На основе недочетов прошлой модели попробуем создать новую, более подходящую для решения поставленной задачи\n",
    "\n",
    "#### Ключевые улучшения:\n",
    "\n",
    "1. Увеличенная емкость модели:\n",
    "\n",
    "    * Добавлено больше фильтров (64 → 128 → 256)\n",
    "\n",
    "    * Увеличен размер полносвязного слоя (512 нейронов)\n",
    "\n",
    "2. Улучшенная регуляризация:\n",
    "\n",
    "    * Добавлен L2-регуляризатор для всех слоев\n",
    "\n",
    "    * Увеличен Dropout (до 0.6 в последнем слое)\n",
    "\n",
    "    * Более агрессивная аугментация данных\n",
    "\n",
    "3. Оптимизация обучения:\n",
    "\n",
    "    * Уменьшена скорость обучения с целью рассмотрения наибольшего количества минимумов - learning rate (0.00001)\n",
    "\n",
    "    * Добавлено сохранение лучшей модели\n",
    "\n",
    "    * Увеличен patience для EarlyStopping\n",
    "\n",
    "4. Работа с дисбалансом классов:\n",
    "\n",
    "    * Добавлена визуализация распределения классов\n",
    "\n",
    "    * Реализовано автоматическое взвешивание классов\n",
    "\n",
    "5. Дополнительные улучшения:\n",
    "\n",
    "    * Вертикальное отражение в аугментации\n",
    "\n",
    "    * Регулировка яркости изображений"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "be197900",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Количество образцов в классах: [41. 44. 43. 41. 46.]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv2d_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)   │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,792</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_7           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)   │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)   │        <span style=\"color: #00af00; text-decoration-color: #00af00\">36,928</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_8           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)   │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)     │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)     │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_8 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │        <span style=\"color: #00af00; text-decoration-color: #00af00\">73,856</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_9           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │           <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_9 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │       <span style=\"color: #00af00; text-decoration-color: #00af00\">147,584</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_10          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │           <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)    │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_10 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)              │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)    │       <span style=\"color: #00af00; text-decoration-color: #00af00\">295,168</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_11          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)    │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_11 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)              │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)    │       <span style=\"color: #00af00; text-decoration-color: #00af00\">590,080</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_12          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)    │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,024</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)    │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)    │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">65536</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)            │    <span style=\"color: #00af00; text-decoration-color: #00af00\">33,554,944</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_13          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)            │         <span style=\"color: #00af00; text-decoration-color: #00af00\">2,048</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span>)            │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">5</span>)              │         <span style=\"color: #00af00; text-decoration-color: #00af00\">2,565</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv2d_6 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m)   │         \u001b[38;5;34m1,792\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_7           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m)   │           \u001b[38;5;34m256\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_7 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m)   │        \u001b[38;5;34m36,928\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_8           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m128\u001b[0m, \u001b[38;5;34m64\u001b[0m)   │           \u001b[38;5;34m256\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_3 (\u001b[38;5;33mMaxPooling2D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m)     │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_4 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m)     │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_8 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │        \u001b[38;5;34m73,856\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_9           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │           \u001b[38;5;34m512\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_9 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │       \u001b[38;5;34m147,584\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_10          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │           \u001b[38;5;34m512\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_4 (\u001b[38;5;33mMaxPooling2D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_5 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m128\u001b[0m)    │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_10 (\u001b[38;5;33mConv2D\u001b[0m)              │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m256\u001b[0m)    │       \u001b[38;5;34m295,168\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_11          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m256\u001b[0m)    │         \u001b[38;5;34m1,024\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv2d_11 (\u001b[38;5;33mConv2D\u001b[0m)              │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m256\u001b[0m)    │       \u001b[38;5;34m590,080\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_12          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m256\u001b[0m)    │         \u001b[38;5;34m1,024\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling2d_5 (\u001b[38;5;33mMaxPooling2D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m256\u001b[0m)    │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_6 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m256\u001b[0m)    │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_1 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m65536\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_2 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m)            │    \u001b[38;5;34m33,554,944\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ batch_normalization_13          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m)            │         \u001b[38;5;34m2,048\u001b[0m │\n",
       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_7 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m)            │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_3 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m5\u001b[0m)              │         \u001b[38;5;34m2,565\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">34,708,549</span> (132.40 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m34,708,549\u001b[0m (132.40 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">34,705,733</span> (132.39 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m34,705,733\u001b[0m (132.39 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">2,816</span> (11.00 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m2,816\u001b[0m (11.00 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2s/step - accuracy: 0.2254 - loss: 3.7768"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m17s\u001b[0m 2s/step - accuracy: 0.2229 - loss: 3.7817 - val_accuracy: 0.1875 - val_loss: 2.8892 - learning_rate: 1.0000e-05\n",
      "Epoch 2/50\n",
      "\u001b[1m1/6\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m10s\u001b[0m 2s/step - accuracy: 0.2188 - loss: 4.6368"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 221ms/step - accuracy: 0.2188 - loss: 4.6368 - val_accuracy: 0.2500 - val_loss: 2.8868 - learning_rate: 1.0000e-05\n",
      "Epoch 3/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 2s/step - accuracy: 0.2511 - loss: 3.7162 - val_accuracy: 0.2188 - val_loss: 2.8898 - learning_rate: 1.0000e-05\n",
      "Epoch 4/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 82ms/step - accuracy: 0.1739 - loss: 3.7196 - val_accuracy: 0.1562 - val_loss: 2.8895 - learning_rate: 1.0000e-05\n",
      "Epoch 5/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 2s/step - accuracy: 0.2405 - loss: 3.8828 - val_accuracy: 0.1875 - val_loss: 2.8862 - learning_rate: 1.0000e-05\n",
      "Epoch 6/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 97ms/step - accuracy: 0.3125 - loss: 4.1274 - val_accuracy: 0.1875 - val_loss: 2.8843 - learning_rate: 1.0000e-05\n",
      "Epoch 7/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 2s/step - accuracy: 0.2315 - loss: 3.7674 - val_accuracy: 0.1875 - val_loss: 2.9007 - learning_rate: 1.0000e-05\n",
      "Epoch 8/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 83ms/step - accuracy: 0.0870 - loss: 3.9548 - val_accuracy: 0.1875 - val_loss: 2.8925 - learning_rate: 1.0000e-05\n",
      "Epoch 9/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 2s/step - accuracy: 0.2102 - loss: 3.9395 - val_accuracy: 0.2500 - val_loss: 2.8799 - learning_rate: 1.0000e-05\n",
      "Epoch 10/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 85ms/step - accuracy: 0.1875 - loss: 3.4593 - val_accuracy: 0.2188 - val_loss: 2.8831 - learning_rate: 1.0000e-05\n",
      "Epoch 11/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 2s/step - accuracy: 0.2384 - loss: 3.4290 - val_accuracy: 0.1562 - val_loss: 2.9002 - learning_rate: 1.0000e-05\n",
      "Epoch 12/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 83ms/step - accuracy: 0.1875 - loss: 4.1556 - val_accuracy: 0.1250 - val_loss: 2.8989 - learning_rate: 1.0000e-05\n",
      "Epoch 13/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 2s/step - accuracy: 0.2004 - loss: 3.7011 - val_accuracy: 0.2188 - val_loss: 2.8954 - learning_rate: 1.0000e-05\n",
      "Epoch 14/50\n",
      "\u001b[1m1/6\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m9s\u001b[0m 2s/step - accuracy: 0.3438 - loss: 2.7935"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 246ms/step - accuracy: 0.3438 - loss: 2.7935 - val_accuracy: 0.2812 - val_loss: 2.8882 - learning_rate: 1.0000e-05\n",
      "Epoch 15/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 2s/step - accuracy: 0.1864 - loss: 3.8101 - val_accuracy: 0.2188 - val_loss: 2.8858 - learning_rate: 1.0000e-05\n",
      "Epoch 16/50\n",
      "\u001b[1m1/6\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m9s\u001b[0m 2s/step - accuracy: 0.2500 - loss: 3.4220"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 242ms/step - accuracy: 0.2500 - loss: 3.4220 - val_accuracy: 0.3125 - val_loss: 2.8826 - learning_rate: 1.0000e-05\n",
      "Epoch 17/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 2s/step - accuracy: 0.2332 - loss: 3.6672 - val_accuracy: 0.2500 - val_loss: 2.8784 - learning_rate: 1.0000e-05\n",
      "Epoch 18/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 85ms/step - accuracy: 0.1875 - loss: 4.1298 - val_accuracy: 0.2188 - val_loss: 2.8824 - learning_rate: 1.0000e-05\n",
      "Epoch 19/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m17s\u001b[0m 3s/step - accuracy: 0.2367 - loss: 3.9492 - val_accuracy: 0.2812 - val_loss: 2.8750 - learning_rate: 1.0000e-05\n",
      "Epoch 20/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 84ms/step - accuracy: 0.1875 - loss: 3.4662 - val_accuracy: 0.2188 - val_loss: 2.9051 - learning_rate: 1.0000e-05\n",
      "Epoch 21/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 2s/step - accuracy: 0.1641 - loss: 4.0261 - val_accuracy: 0.2812 - val_loss: 2.8953 - learning_rate: 1.0000e-05\n",
      "Epoch 22/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 85ms/step - accuracy: 0.2188 - loss: 3.5259 - val_accuracy: 0.2188 - val_loss: 2.9047 - learning_rate: 1.0000e-05\n",
      "Epoch 23/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 2s/step - accuracy: 0.2721 - loss: 3.5784 - val_accuracy: 0.2188 - val_loss: 2.9078 - learning_rate: 1.0000e-05\n",
      "Epoch 24/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 88ms/step - accuracy: 0.0938 - loss: 4.0467 - val_accuracy: 0.2812 - val_loss: 2.9002 - learning_rate: 1.0000e-05\n",
      "Epoch 25/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 6s/step - accuracy: 0.1440 - loss: 4.2750 - val_accuracy: 0.1562 - val_loss: 2.9078 - learning_rate: 1.0000e-05\n",
      "Epoch 26/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m19s\u001b[0m 1s/step - accuracy: 0.2609 - loss: 4.0810 - val_accuracy: 0.2188 - val_loss: 2.9088 - learning_rate: 1.0000e-05\n",
      "Epoch 27/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 2s/step - accuracy: 0.2099 - loss: 3.6910 - val_accuracy: 0.1875 - val_loss: 2.8969 - learning_rate: 1.0000e-05\n",
      "Epoch 28/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 92ms/step - accuracy: 0.2812 - loss: 3.3733 - val_accuracy: 0.1562 - val_loss: 2.9060 - learning_rate: 1.0000e-05\n",
      "Epoch 29/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 2s/step - accuracy: 0.2179 - loss: 3.7921 - val_accuracy: 0.2188 - val_loss: 2.8935 - learning_rate: 1.0000e-05\n",
      "Epoch 30/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 88ms/step - accuracy: 0.2500 - loss: 4.1179 - val_accuracy: 0.1875 - val_loss: 2.8995 - learning_rate: 2.0000e-06\n",
      "Epoch 31/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 2s/step - accuracy: 0.1971 - loss: 3.6033 - val_accuracy: 0.2188 - val_loss: 2.8831 - learning_rate: 2.0000e-06\n",
      "Epoch 32/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 89ms/step - accuracy: 0.1875 - loss: 3.6035 - val_accuracy: 0.1875 - val_loss: 2.9204 - learning_rate: 2.0000e-06\n",
      "Epoch 33/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 2s/step - accuracy: 0.2064 - loss: 3.7735 - val_accuracy: 0.2188 - val_loss: 2.8850 - learning_rate: 2.0000e-06\n",
      "Epoch 34/50\n",
      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 84ms/step - accuracy: 0.1304 - loss: 4.1112 - val_accuracy: 0.2500 - val_loss: 2.8983 - learning_rate: 2.0000e-06\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "File not found: filepath=best_model.keras. Please ensure the file is an accessible `.keras` zip file.",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[8], line 114\u001b[0m\n\u001b[0;32m    102\u001b[0m history \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mfit(\n\u001b[0;32m    103\u001b[0m     train_generator,\n\u001b[0;32m    104\u001b[0m     steps_per_epoch\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mlen\u001b[39m(X_train) \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m32\u001b[39m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    110\u001b[0m     verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[0;32m    111\u001b[0m )\n\u001b[0;32m    113\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtensorflow\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodels\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m load_model\n\u001b[1;32m--> 114\u001b[0m best_model \u001b[38;5;241m=\u001b[39m \u001b[43mload_model\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mbest_model.keras\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m    115\u001b[0m test_loss, test_acc \u001b[38;5;241m=\u001b[39m best_model\u001b[38;5;241m.\u001b[39mevaluate(test_generator, verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n\u001b[0;32m    116\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mЛучшая точность на тестовых данных: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtest_acc\u001b[38;5;132;01m:\u001b[39;00m\u001b[38;5;124m.4f\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
      "File \u001b[1;32mc:\\Users\\Admin\\StudioProjects\\AIM-PIbd-31-Alekseev-I-S\\aimenv\\Lib\\site-packages\\keras\\src\\saving\\saving_api.py:200\u001b[0m, in \u001b[0;36mload_model\u001b[1;34m(filepath, custom_objects, compile, safe_mode)\u001b[0m\n\u001b[0;32m    196\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m legacy_h5_format\u001b[38;5;241m.\u001b[39mload_model_from_hdf5(\n\u001b[0;32m    197\u001b[0m         filepath, custom_objects\u001b[38;5;241m=\u001b[39mcustom_objects, \u001b[38;5;28mcompile\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mcompile\u001b[39m\n\u001b[0;32m    198\u001b[0m     )\n\u001b[0;32m    199\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mstr\u001b[39m(filepath)\u001b[38;5;241m.\u001b[39mendswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.keras\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m--> 200\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m    201\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFile not found: filepath=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfilepath\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    202\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPlease ensure the file is an accessible `.keras` \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    203\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mzip file.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    204\u001b[0m     )\n\u001b[0;32m    205\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    206\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m    207\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFile format not supported: filepath=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfilepath\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    208\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mKeras 3 only supports V3 `.keras` files and \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    217\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmight have a different name).\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    218\u001b[0m     )\n",
      "\u001b[1;31mValueError\u001b[0m: File not found: filepath=best_model.keras. Please ensure the file is an accessible `.keras` zip file."
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout, BatchNormalization\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau, ModelCheckpoint\n",
    "from tensorflow.keras.regularizers import l2\n",
    "\n",
    "# Улучшенная архитектура модели\n",
    "def create_improved_model(input_shape, num_classes):\n",
    "    model = Sequential([\n",
    "        # Увеличение количества фильтров и добавление L2 регуляризации\n",
    "        Conv2D(64, (3, 3), activation='relu', padding='same', \n",
    "               input_shape=input_shape, kernel_regularizer=l2(0.001)),\n",
    "        BatchNormalization(),\n",
    "        Conv2D(64, (3, 3), activation='relu', padding='same'),\n",
    "        BatchNormalization(),\n",
    "        MaxPooling2D((2, 2)),\n",
    "        Dropout(0.3),\n",
    "        \n",
    "        Conv2D(128, (3, 3), activation='relu', padding='same', kernel_regularizer=l2(0.001)),\n",
    "        BatchNormalization(),\n",
    "        Conv2D(128, (3, 3), activation='relu', padding='same'),\n",
    "        BatchNormalization(),\n",
    "        MaxPooling2D((2, 2)),\n",
    "        Dropout(0.4),\n",
    "        \n",
    "        Conv2D(256, (3, 3), activation='relu', padding='same', kernel_regularizer=l2(0.001)),\n",
    "        BatchNormalization(),\n",
    "        Conv2D(256, (3, 3), activation='relu', padding='same'),\n",
    "        BatchNormalization(),\n",
    "        MaxPooling2D((2, 2)),\n",
    "        Dropout(0.5),\n",
    "        \n",
    "        Flatten(),\n",
    "        Dense(512, activation='relu', kernel_regularizer=l2(0.001)),\n",
    "        BatchNormalization(),\n",
    "        Dropout(0.6),\n",
    "        Dense(num_classes, activation='softmax')\n",
    "    ])\n",
    "    \n",
    "    # Измененный оптимизатор с более низким learning rate\n",
    "    optimizer = Adam(learning_rate=0.00001)\n",
    "    \n",
    "    model.compile(optimizer=optimizer,\n",
    "                 loss='categorical_crossentropy',\n",
    "                 metrics=['accuracy'])\n",
    "    \n",
    "    return model\n",
    "\n",
    "# Улучшенная аугментация данных\n",
    "def create_datagen():\n",
    "    return ImageDataGenerator(\n",
    "        rotation_range=30,\n",
    "        width_shift_range=0.3,\n",
    "        height_shift_range=0.3,\n",
    "        shear_range=0.3,\n",
    "        zoom_range=0.3,\n",
    "        horizontal_flip=True,\n",
    "        vertical_flip=True,\n",
    "        brightness_range=[0.7, 1.3],\n",
    "        fill_mode='nearest'\n",
    "    )\n",
    "\n",
    "# Улучшенные callback-функции\n",
    "def create_callbacks():\n",
    "    return [\n",
    "        EarlyStopping(monitor='val_loss', patience=15, restore_best_weights=True),\n",
    "        ReduceLROnPlateau(monitor='val_loss', factor=0.2, patience=10, min_lr=1e-7),\n",
    "        ModelCheckpoint('best_model.h5', save_best_only=True, monitor='val_accuracy')\n",
    "    ]\n",
    "\n",
    "# Проверка баланса классов\n",
    "def check_class_balance(y):\n",
    "    class_counts = np.sum(y, axis=0)\n",
    "    plt.figure(figsize=(10, 5))\n",
    "    plt.bar(range(len(class_counts)), class_counts)\n",
    "    plt.title('Распределение классов')\n",
    "    plt.xlabel('Класс')\n",
    "    plt.ylabel('Количество образцов')\n",
    "    plt.show()\n",
    "    return class_counts\n",
    "\n",
    "# Проверяем баланс классов\n",
    "class_counts = check_class_balance(y_train)\n",
    "print(\"Количество образцов в классах:\", class_counts)\n",
    "\n",
    "# Если классы несбалансированы, добавляем взвешивание классов\n",
    "class_weights = {i: 1./class_counts[i] for i in range(num_classes)}\n",
    "\n",
    "# Создаем и обучаем модель\n",
    "model = create_improved_model(input_shape, num_classes)\n",
    "model.summary()\n",
    "\n",
    "train_datagen = create_datagen()\n",
    "test_datagen = ImageDataGenerator()\n",
    "\n",
    "train_generator = train_datagen.flow(X_train, y_train, batch_size=32)\n",
    "test_generator = test_datagen.flow(X_test, y_test, batch_size=32)\n",
    "\n",
    "history = model.fit(\n",
    "    train_generator,\n",
    "    steps_per_epoch=len(X_train) // 32,\n",
    "    epochs=50,\n",
    "    validation_data=test_generator,\n",
    "    validation_steps=len(X_test) // 32,\n",
    "    callbacks=create_callbacks(),\n",
    "    class_weight=class_weights if min(class_counts) < max(class_counts) * 0.7 else None,\n",
    "    verbose=1\n",
    ")\n",
    "\n",
    "from tensorflow.keras.models import load_model\n",
    "best_model = load_model('best_model.keras')\n",
    "test_loss, test_acc = best_model.evaluate(test_generator, verbose=0)\n",
    "print(f\"\\nЛучшая точность на тестовых данных: {test_acc:.4f}\")\n",
    "print(f\"Лучшие потери на тестовых данных: {test_loss:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d928753",
   "metadata": {},
   "source": [
    "### Оценим проделанную работу"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4b6e2a18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Финальная точность на обучении: 0.1304\n",
      "Финальная точность на валидации: 0.2500\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Визуализация результатов обучения\n",
    "plt.figure(figsize=(14, 5))\n",
    "\n",
    "# График точности\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.plot(history.history['accuracy'], label='Точность на обучении')\n",
    "plt.plot(history.history['val_accuracy'], label='Точность на валидации')\n",
    "plt.title('График точности модели')\n",
    "plt.ylabel('Точность')\n",
    "plt.xlabel('Эпоха')\n",
    "plt.ylim([0, 1])  # Ограничиваем ось Y от 0 до 1 для точности\n",
    "plt.legend(loc='lower right')\n",
    "\n",
    "# График потерь\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.plot(history.history['loss'], label='Потери на обучении')\n",
    "plt.plot(history.history['val_loss'], label='Потери на валидации')\n",
    "plt.title('График потерь модели')\n",
    "plt.ylabel('Потери')\n",
    "plt.xlabel('Эпоха')\n",
    "plt.legend(loc='upper right')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Дополнительная информация\n",
    "final_train_acc = history.history['accuracy'][-1]\n",
    "final_val_acc = history.history['val_accuracy'][-1]\n",
    "print(f\"\\nФинальная точность на обучении: {final_train_acc:.4f}\")\n",
    "print(f\"Финальная точность на валидации: {final_val_acc:.4f}\")\n",
    "\n",
    "# Сохранение графиков\n",
    "plt.savefig('training_metrics.png', dpi=300, bbox_inches='tight')"
   ]
  },
  {
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   "id": "da219227",
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    "Модель эффективнее распознает персонажей, но всё еще не с самой высокой точностью. В качестве причин таких результатов можно указать одну из описанных ранее(1-ю причину в блоке описания причин полученных результатов у прошлой модели) и достаточно агрессивную регуляризацию"
   ]
  }
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