{ "cells": [ { "cell_type": "code", "execution_count": 23, "id": "dd7d4f2a-3fd1-4ae3-a9b8-bf69c3ed2a36", "metadata": {}, "outputs": [], "source": [ "# Download image dataset from kaggle\n", "# https://www.kaggle.com/datasets/dhamur/cotton-plant-disease" ] }, { "cell_type": "code", "execution_count": 4, "id": "d2c07237-c371-46d1-80f7-f4c3329e6ded", "metadata": {}, "outputs": [], "source": [ "import splitfolders\n", "\n", "input_folder = r\"C:\\Users\\STCs\\Desktop\\Project-1\"\n", "\n", "output_folder = \"data_split\"\n", "\n", "splitfolders.ratio(input_folder, output=output_folder, seed=42, ratio=(.7, .15, .15))\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "5c7a2752-774e-4af0-9ed0-981d6aafb030", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 3351 images belonging to 8 classes.\n", "Found 718 images belonging to 8 classes.\n", "Found 719 images belonging to 8 classes.\n" ] } ], "source": [ "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n", "\n", "\n", "train_datagen = ImageDataGenerator(\n", " rescale=1./255,\n", " rotation_range=25,\n", " width_shift_range=0.2,\n", " height_shift_range=0.2,\n", " shear_range=0.15,\n", " zoom_range=0.2,\n", " horizontal_flip=True,\n", " fill_mode='nearest'\n", ")\n", "\n", "\n", "val_test_datagen = ImageDataGenerator(rescale=1./255)\n", "\n", "\n", "train_dir = \"data_split/train\"\n", "val_dir = \"data_split/val\"\n", "test_dir = \"data_split/test\"\n", "\n", "\n", "train_generator = train_datagen.flow_from_directory(\n", " train_dir,\n", " target_size=(224, 224),\n", " batch_size=32,\n", " class_mode='categorical'\n", ")\n", "\n", "\n", "val_generator = val_test_datagen.flow_from_directory(\n", " val_dir,\n", " target_size=(224, 224),\n", " batch_size=32,\n", " class_mode='categorical'\n", ")\n", "\n", "\n", "test_generator = val_test_datagen.flow_from_directory(\n", " test_dir,\n", " target_size=(224, 224),\n", " batch_size=32,\n", " class_mode='categorical',\n", " shuffle=False\n", ")\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "55f6bc25-b8e5-447a-9a31-39d4847edcb4", "metadata": {}, "outputs": [], "source": [ "from tensorflow.keras.applications import MobileNetV2\n", "from tensorflow.keras.models import Sequential\n", "from tensorflow.keras.layers import GlobalAveragePooling2D, Dense, Dropout\n", "from tensorflow.keras.optimizers import Adam\n", "\n", "def build_transfer_model(input_shape, num_classes):\n", " base_model = MobileNetV2(weights='imagenet', include_top=False, input_shape=input_shape)\n", " base_model.trainable = False \n", "\n", " model = Sequential([\n", " base_model,\n", " GlobalAveragePooling2D(),\n", " Dropout(0.5),\n", " Dense(num_classes, activation='softmax')\n", " ])\n", "\n", " model.compile(optimizer=Adam(learning_rate=1e-4),\n", " loss='categorical_crossentropy',\n", " metrics=['accuracy'])\n", " return model\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "01e1a20d-da31-495c-b01e-9b4ca348639c", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Model: \"sequential_1\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ mobilenetv2_1.00_224            │ (None, 7, 7, 1280)     │     2,257,984 │\n",
       "│ (Functional)                    │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ global_average_pooling2d_1      │ (None, 1280)           │             0 │\n",
       "│ (GlobalAveragePooling2D)        │                        │               │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout_1 (Dropout)             │ (None, 1280)           │             0 │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_1 (Dense)                 │ (None, 8)              │        10,248 │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "
\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", "│ mobilenetv2_1.00_224 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m1280\u001b[0m) │ \u001b[38;5;34m2,257,984\u001b[0m │\n", "│ (\u001b[38;5;33mFunctional\u001b[0m) │ │ │\n", "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", "│ global_average_pooling2d_1 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1280\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", "│ (\u001b[38;5;33mGlobalAveragePooling2D\u001b[0m) │ │ │\n", "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", "│ dropout_1 (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1280\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;34m8\u001b[0m) │ \u001b[38;5;34m10,248\u001b[0m │\n", "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 Total params: 2,268,232 (8.65 MB)\n",
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 Trainable params: 10,248 (40.03 KB)\n",
       "
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 Non-trainable params: 2,257,984 (8.61 MB)\n",
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\n" ], "text/plain": [ "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m2,257,984\u001b[0m (8.61 MB)\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "input_shape = (224, 224, 3)\n", "num_classes = 8\n", "model = build_transfer_model(input_shape, num_classes)\n", "model.summary()\n" ] }, { "cell_type": "code", "execution_count": 18, "id": "f49eef01-29a9-41bc-ae7b-a1ce6437f333", "metadata": {}, "outputs": [], "source": [ "from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint\n", "\n", "early_stop = EarlyStopping(\n", " monitor='val_loss', \n", " patience=5, \n", " restore_best_weights=True \n", ")\n" ] }, { "cell_type": "code", "execution_count": 19, "id": "f3cce5cc-22d9-4af7-b7bd-934a51fb17fb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m528s\u001b[0m 5s/step - accuracy: 0.6960 - loss: 0.8562 - val_accuracy: 0.8036 - val_loss: 0.5707\n", "Epoch 2/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m287s\u001b[0m 3s/step - accuracy: 0.6878 - loss: 0.8269 - val_accuracy: 0.8036 - val_loss: 0.5555\n", "Epoch 3/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m246s\u001b[0m 2s/step - accuracy: 0.6883 - loss: 0.8495 - val_accuracy: 0.8078 - val_loss: 0.5386\n", "Epoch 4/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m219s\u001b[0m 2s/step - accuracy: 0.7227 - loss: 0.7708 - val_accuracy: 0.8203 - val_loss: 0.5003\n", "Epoch 5/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m178s\u001b[0m 2s/step - accuracy: 0.7137 - loss: 0.7650 - val_accuracy: 0.8273 - val_loss: 0.4882\n", "Epoch 6/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m170s\u001b[0m 2s/step - accuracy: 0.7372 - loss: 0.7340 - val_accuracy: 0.8217 - val_loss: 0.4802\n", "Epoch 7/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m167s\u001b[0m 2s/step - accuracy: 0.7526 - loss: 0.6911 - val_accuracy: 0.8217 - val_loss: 0.4713\n", "Epoch 8/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m172s\u001b[0m 2s/step - accuracy: 0.7513 - loss: 0.6769 - val_accuracy: 0.8426 - val_loss: 0.4435\n", "Epoch 9/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m167s\u001b[0m 2s/step - accuracy: 0.7665 - loss: 0.6426 - val_accuracy: 0.8482 - val_loss: 0.4337\n", "Epoch 10/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m166s\u001b[0m 2s/step - accuracy: 0.7671 - loss: 0.6639 - val_accuracy: 0.8440 - val_loss: 0.4326\n", "Epoch 11/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m166s\u001b[0m 2s/step - accuracy: 0.7854 - loss: 0.6037 - val_accuracy: 0.8538 - val_loss: 0.4145\n", "Epoch 12/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m167s\u001b[0m 2s/step - accuracy: 0.7956 - loss: 0.5714 - val_accuracy: 0.8538 - val_loss: 0.4095\n", "Epoch 13/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m168s\u001b[0m 2s/step - accuracy: 0.7839 - loss: 0.6191 - val_accuracy: 0.8524 - val_loss: 0.4054\n", "Epoch 14/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m167s\u001b[0m 2s/step - accuracy: 0.8008 - loss: 0.5564 - val_accuracy: 0.8565 - val_loss: 0.3997\n", "Epoch 15/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m168s\u001b[0m 2s/step - accuracy: 0.7984 - loss: 0.5785 - val_accuracy: 0.8705 - val_loss: 0.3765\n", "Epoch 16/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m172s\u001b[0m 2s/step - accuracy: 0.7893 - loss: 0.5909 - val_accuracy: 0.8649 - val_loss: 0.3778\n", "Epoch 17/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m167s\u001b[0m 2s/step - accuracy: 0.8002 - loss: 0.5505 - val_accuracy: 0.8663 - val_loss: 0.3819\n", "Epoch 18/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m171s\u001b[0m 2s/step - accuracy: 0.8025 - loss: 0.5504 - val_accuracy: 0.8621 - val_loss: 0.3721\n", "Epoch 19/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m171s\u001b[0m 2s/step - accuracy: 0.8111 - loss: 0.5417 - val_accuracy: 0.8733 - val_loss: 0.3613\n", "Epoch 20/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m166s\u001b[0m 2s/step - accuracy: 0.7998 - loss: 0.5439 - val_accuracy: 0.8802 - val_loss: 0.3469\n", "Epoch 21/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m206s\u001b[0m 2s/step - accuracy: 0.8116 - loss: 0.5652 - val_accuracy: 0.8858 - val_loss: 0.3337\n", "Epoch 22/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m169s\u001b[0m 2s/step - accuracy: 0.8105 - loss: 0.5362 - val_accuracy: 0.8816 - val_loss: 0.3467\n", "Epoch 23/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m167s\u001b[0m 2s/step - accuracy: 0.8149 - loss: 0.5089 - val_accuracy: 0.8886 - val_loss: 0.3340\n", "Epoch 24/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m169s\u001b[0m 2s/step - accuracy: 0.8274 - loss: 0.4936 - val_accuracy: 0.8802 - val_loss: 0.3410\n", "Epoch 25/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m168s\u001b[0m 2s/step - accuracy: 0.8286 - loss: 0.5067 - val_accuracy: 0.8830 - val_loss: 0.3346\n", "Epoch 26/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m169s\u001b[0m 2s/step - accuracy: 0.8253 - loss: 0.5065 - val_accuracy: 0.8969 - val_loss: 0.3179\n", "Epoch 27/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m166s\u001b[0m 2s/step - accuracy: 0.8295 - loss: 0.4700 - val_accuracy: 0.8914 - val_loss: 0.3223\n", "Epoch 28/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m167s\u001b[0m 2s/step - accuracy: 0.8238 - loss: 0.4747 - val_accuracy: 0.8844 - val_loss: 0.3242\n", "Epoch 29/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m168s\u001b[0m 2s/step - accuracy: 0.8387 - loss: 0.4573 - val_accuracy: 0.8928 - val_loss: 0.3171\n", "Epoch 30/30\n", "\u001b[1m105/105\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m168s\u001b[0m 2s/step - accuracy: 0.8284 - loss: 0.4875 - val_accuracy: 0.9039 - val_loss: 0.3017\n" ] } ], "source": [ "\n", "history = model.fit(\n", " train_generator,\n", " epochs=30,\n", " validation_data=val_generator,\n", " callbacks=[early_stop, checkpoint]\n", ")\n" ] }, { "cell_type": "code", "execution_count": 20, "id": "5579588b-3dca-4c32-9df5-72db5d56e9a4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m25s\u001b[0m 1s/step - accuracy: 0.8606 - loss: 0.4014\n", "Test accuracy: 88.46%\n" ] } ], "source": [ "test_loss, test_acc = model.evaluate(test_generator)\n", "print(f\"Test accuracy: {test_acc*100:.2f}%\")\n" ] }, { "cell_type": "code", "execution_count": 21, "id": "7003e7cc-a74c-46cc-b8b8-f132001706a4", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "acc = history.history['accuracy']\n", "val_acc = history.history['val_accuracy']\n", "loss = history.history['loss']\n", "val_loss = history.history['val_loss']\n", "epochs_range = range(len(acc))\n", "\n", "plt.figure(figsize=(12, 6))\n", "plt.subplot(1, 2, 1)\n", "plt.plot(epochs_range, acc, label='Training Accuracy')\n", "plt.plot(epochs_range, val_acc, label='Validation Accuracy')\n", "plt.legend(loc='lower right')\n", "plt.title('Training and Validation Accuracy')\n", "\n", "plt.subplot(1, 2, 2)\n", "plt.plot(epochs_range, loss, label='Training Loss')\n", "plt.plot(epochs_range, val_loss, label='Validation Loss')\n", "plt.legend(loc='upper right')\n", "plt.title('Training and Validation Loss')\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 22, "id": "06fe2aeb-47f3-4cac-874a-35017fabfade", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "epochs_range = range(len(history.history['accuracy']))\n", "\n", "plt.figure(figsize=(10,5))\n", "plt.plot(epochs_range, history.history['accuracy'], label='Training Accuracy', marker='o')\n", "plt.plot(epochs_range, history.history['val_accuracy'], label='Validation Accuracy', marker='o')\n", "plt.plot(epochs_range, history.history['loss'], label='Training Loss', linestyle='--')\n", "plt.plot(epochs_range, history.history['val_loss'], label='Validation Loss', linestyle='--')\n", "plt.title('Model Accuracy and Loss')\n", "plt.xlabel('Epoch')\n", "plt.ylabel('Value')\n", "plt.legend()\n", "plt.grid(True)\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "id": "6e415852-da3c-405f-8377-642219fb3bf7", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "0a9d85ab-ae72-423e-ae65-c3d455996015", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.11" } }, "nbformat": 4, "nbformat_minor": 5 }