File size: 113,794 Bytes
1bf8195 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 | {
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4"
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ko1IVH1qHGKM",
"outputId": "fdea5781-d246-4818-dbaf-99fb119c843b"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Mounted at /content/drive\n"
]
}
],
"source": [
"# STEP 0: Mount Google Drive\n",
"# ============================\n",
"from google.colab import drive\n",
"drive.mount('/content/drive')"
]
},
{
"cell_type": "code",
"source": [
"# Set dataset path (change if your dataset folder name is different)\n",
"dataset_path = \"/content/drive/MyDrive/garbage_classification\""
],
"metadata": {
"id": "WgodfbMpNYYS"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# ============================\n",
"# 📌 STEP 2: Check Dataset Structure\n",
"# ============================\n",
"import os\n",
"\n",
"# Check if the dataset path exists\n",
"if not os.path.exists(dataset_path):\n",
" print(f\"Error: Dataset path not found at {dataset_path}\")\n",
" print(\"Please verify the path and ensure Google Drive is mounted correctly.\")\n",
"else:\n",
" classes = os.listdir(dataset_path)\n",
" print(\"Available Classes:\", classes)\n",
"\n",
" for cls in classes:\n",
" print(cls, \":\", len(os.listdir(os.path.join(dataset_path, cls))), \"images\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "hmBQpS_2PlGT",
"outputId": "87a1f57a-33b4-4025-d0cc-e36857f4cf10"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Available Classes: ['white-glass', 'trash', 'shoes', 'plastic', 'paper', 'metal', 'green-glass', 'brown-glass', 'cardboard', 'biological']\n",
"white-glass : 780 images\n",
"trash : 697 images\n",
"shoes : 1977 images\n",
"plastic : 865 images\n",
"paper : 1050 images\n",
"metal : 769 images\n",
"green-glass : 629 images\n",
"brown-glass : 607 images\n",
"cardboard : 891 images\n",
"biological : 985 images\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import os\n",
"import cv2\n",
"import numpy as np\n",
"from tensorflow.keras.preprocessing.image import img_to_array\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.preprocessing import LabelEncoder\n",
"from tensorflow.keras.utils import to_categorical\n",
"\n",
"IMG_SIZE = 128\n",
"DATASET_PATH = \"/content/drive/MyDrive/garbage_classification\" # Change to your path\n",
"\n",
"images = []\n",
"labels = []\n",
"\n",
"print(\"[INFO] Loading and processing TrashNet dataset...\")\n",
"\n",
"def enhance_image(img):\n",
" # Resize\n",
" img = cv2.resize(img, (IMG_SIZE, IMG_SIZE))\n",
"\n",
" # Convert to grayscale\n",
" gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
"\n",
" # Histogram equalization to improve contrast\n",
" equalized = cv2.equalizeHist(gray)\n",
"\n",
" # Apply Gaussian blur to reduce noise\n",
" blurred = cv2.GaussianBlur(equalized, (3, 3), 0)\n",
"\n",
" # Optional: Edge enhancement using Sobel filter\n",
" sobelx = cv2.Sobel(blurred, cv2.CV_64F, 1, 0, ksize=3)\n",
" sobely = cv2.Sobel(blurred, cv2.CV_64F, 0, 1, ksize=3)\n",
" sobel_combined = cv2.magnitude(sobelx, sobely)\n",
" sobel_combined = np.uint8(sobel_combined)\n",
"\n",
" # Normalize to [0,1]\n",
" final = sobel_combined / 255.0\n",
"\n",
" # Convert back to 3D (grayscale -> fake RGB) for CNN compatibility\n",
" final = cv2.merge([final, final, final])\n",
" return final\n",
"\n",
"# Loop through dataset\n",
"for label_folder in os.listdir(DATASET_PATH):\n",
" label_path = os.path.join(DATASET_PATH, label_folder)\n",
" if not os.path.isdir(label_path):\n",
" continue\n",
" for img_file in os.listdir(label_path):\n",
" try:\n",
" img_path = os.path.join(label_path, img_file)\n",
" img = cv2.imread(img_path)\n",
" if img is None:\n",
" continue\n",
" enhanced_img = enhance_image(img)\n",
" images.append(enhanced_img)\n",
" labels.append(label_folder)\n",
" except Exception as e:\n",
" print(f\"[WARN] Skipped corrupt image: {img_path} - {e}\")\n",
"\n",
"# Convert to NumPy arrays\n",
"X = np.array(images, dtype=\"float32\")\n",
"y = np.array(labels)\n",
"\n",
"# Encode labels\n",
"le = LabelEncoder()\n",
"y_encoded = le.fit_transform(y)\n",
"y_categorical = to_categorical(y_encoded)\n",
"\n",
"# Train-test split\n",
"X_train, X_test, y_train, y_test = train_test_split(X, y_categorical, test_size=0.2, random_state=42)\n",
"\n",
"print(f\"[INFO] Dataset ready: {len(X_train)} training samples, {len(X_test)} test samples\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "e26KKHWWeskK",
"outputId": "fa54d048-eaf4-40ab-cda7-6c53ad832531"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[INFO] Loading and processing TrashNet dataset...\n",
"[INFO] Dataset ready: 7400 training samples, 1850 test samples\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"# Show a sample image from the training set\n",
"index = 2000 # Change this to see other images\n",
"sample_image = X_train[index]\n",
"\n",
"plt.figure(figsize=(4, 4))\n",
"plt.imshow(sample_image)\n",
"plt.title(f\"Label: {le.inverse_transform([np.argmax(y_train[index])])[0]}\")\n",
"plt.axis(\"off\")\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 367
},
"id": "uKQtB4L4ffIx",
"outputId": "641ee76b-82aa-4b0e-fa94-72fd2bdebe3b"
},
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"import pandas as pd\n",
"pd.Series(le.inverse_transform(np.argmax(y_train, axis=1))).value_counts().plot(kind='bar')\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 516
},
"id": "teknkOx5gFwK",
"outputId": "903403a0-c716-4f58-b088-b7a53e85f5b5"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<Axes: >"
]
},
"metadata": {},
"execution_count": 5
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"import tensorflow as tf\n",
"from tensorflow.keras.layers import GlobalAveragePooling2D, Dense, Dropout\n",
"from tensorflow.keras.models import Model\n",
"\n",
"base_model = tf.keras.applications.DenseNet121(input_shape=(IMG_SIZE , IMG_SIZE , 3) ,include_top=False,weights='imagenet')\n",
"base_model.trainable = True\n",
"\n",
"x = base_model.output\n",
"\n",
"x = GlobalAveragePooling2D()(x)\n",
"x = Dropout(0.3)(x)\n",
"predictions = Dense(10, activation='softmax')(x)\n",
"model_DenseNet121 = Model(inputs=base_model.input, outputs=predictions)"
],
"metadata": {
"id": "hoz7E6_-hE3-"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from tensorflow.keras.optimizers import AdamW\n",
"\n",
"optimizer = AdamW(learning_rate=1e-4)\n",
"\n",
"model_DenseNet121.compile(loss ='categorical_crossentropy',optimizer=optimizer,metrics=['accuracy'])"
],
"metadata": {
"id": "m7OxCoIEkarl"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from tensorflow.keras.callbacks import EarlyStopping\n",
"\n",
"earlystop = EarlyStopping(patience=5, restore_best_weights=True , monitor='val_accuracy')\n",
"epchos = 20\n",
"\n",
"history = model_DenseNet121.fit(\n",
" X_train,\n",
" validation_data=(X_test, y_test), # Corrected validation data\n",
" epochs=epchos,\n",
" callbacks=[earlystop]\n",
")"
],
"metadata": {
"id": "WWFaSYvLklyp"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "kIw9Q5N-k9Eq"
},
"execution_count": null,
"outputs": []
}
]
} |