{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"gpu","dataSources":[{"sourceId":25563,"databundleVersionId":2094376,"sourceType":"competition"}],"dockerImageVersionId":30786,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\n# import os\n# for dirname, _, filenames in os.walk('/kaggle/input'):\n# for filename in filenames:\n# print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2024-11-03T16:53:53.370225Z","iopub.execute_input":"2024-11-03T16:53:53.370806Z","iopub.status.idle":"2024-11-03T16:53:53.377241Z","shell.execute_reply.started":"2024-11-03T16:53:53.370761Z","shell.execute_reply":"2024-11-03T16:53:53.375968Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"#IMPORT REQUIRED LIBRARIES:\n\nfrom tensorflow.keras.layers import Input, Lambda, Dense, Flatten\nfrom tensorflow.keras.models import Model\nfrom tensorflow.keras.applications.resnet50 import ResNet50\nfrom tensorflow.keras.applications.resnet50 import preprocess_input\nfrom tensorflow.keras.preprocessing import image\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator,load_img\nfrom tensorflow.keras.models import Sequential\nimport tensorflow as tf\nimport numpy as np\nfrom glob import glob\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\ngpus = tf.config.list_physical_devices('GPU')\nprint(\"GPUs:\", gpus)\n\n# Check if GPUs are available\nif gpus:\n print(\"GPU is available.\")\nelse:\n print(\"GPU is not available.\")","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:39:10.909378Z","iopub.execute_input":"2024-12-01T11:39:10.910005Z","iopub.status.idle":"2024-12-01T11:39:22.691003Z","shell.execute_reply.started":"2024-12-01T11:39:10.909962Z","shell.execute_reply":"2024-12-01T11:39:22.690131Z"},"trusted":true},"outputs":[{"name":"stdout","text":"GPUs: [PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]\nGPU is available.\n","output_type":"stream"}],"execution_count":1},{"cell_type":"code","source":"train_images_path = \"/kaggle/input/plant-pathology-2021-fgvc8/train_images\"\ntrain_images_labels_path = \"/kaggle/input/plant-pathology-2021-fgvc8/train.csv\"\ndf = pd.read_csv(train_images_labels_path)\n","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:40:54.742598Z","iopub.execute_input":"2024-12-01T11:40:54.74369Z","iopub.status.idle":"2024-12-01T11:40:54.781567Z","shell.execute_reply.started":"2024-12-01T11:40:54.743656Z","shell.execute_reply":"2024-12-01T11:40:54.78087Z"},"trusted":true},"outputs":[],"execution_count":2},{"cell_type":"code","source":"from sklearn.model_selection import train_test_split\n\ntrain_df, test_df = train_test_split(df, test_size=0.2, random_state=42, stratify=df['labels'])\n\n# Further split train_val_df into training and validation sets\n# train_df, val_df = train_test_split(train_val_df, test_size=0.115, random_state=42, stratify=train_val_df['labels'])\n# Summary of the split\nprint(f\"Default set: {len(df)} samples\")\nprint(f\"Training set: {len(train_df)} samples\")\n# print(f\"Validation set: {len(val_df)} samples\")\nprint(f\"Test set: {len(test_df)} samples\")","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:40:56.261963Z","iopub.execute_input":"2024-12-01T11:40:56.262285Z","iopub.status.idle":"2024-12-01T11:40:56.870539Z","shell.execute_reply.started":"2024-12-01T11:40:56.262258Z","shell.execute_reply":"2024-12-01T11:40:56.86959Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Default set: 18632 samples\nTraining set: 14905 samples\nTest set: 3727 samples\n","output_type":"stream"}],"execution_count":3},{"cell_type":"code","source":"labels = train_df.labels.value_counts().index\nlabels_count = list(train_df.labels.value_counts().values)\n\nprint(f\"Number of labels: {len(labels)}\")\nprint(labels_count)","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:40:58.150591Z","iopub.execute_input":"2024-12-01T11:40:58.151456Z","iopub.status.idle":"2024-12-01T11:40:58.162541Z","shell.execute_reply.started":"2024-12-01T11:40:58.151421Z","shell.execute_reply":"2024-12-01T11:40:58.16169Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Number of labels: 12\n[3861, 3699, 2545, 1488, 1281, 947, 549, 160, 132, 96, 77, 70]\n","output_type":"stream"}],"execution_count":4},{"cell_type":"code","source":"train_df.head()","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:41:00.364659Z","iopub.execute_input":"2024-12-01T11:41:00.365004Z","iopub.status.idle":"2024-12-01T11:41:00.377586Z","shell.execute_reply.started":"2024-12-01T11:41:00.364977Z","shell.execute_reply":"2024-12-01T11:41:00.37671Z"},"trusted":true},"outputs":[{"execution_count":5,"output_type":"execute_result","data":{"text/plain":" image labels\n16934 f5e90287ebb20179.jpg powdery_mildew\n13005 daf0fe310c0789f2.jpg rust\n2891 966555a24295b75b.jpg healthy\n16808 f58fc06940689eaf.jpg frog_eye_leaf_spot\n1598 8c94b4d7bb83194b.jpg scab frog_eye_leaf_spot","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
imagelabels
16934f5e90287ebb20179.jpgpowdery_mildew
13005daf0fe310c0789f2.jpgrust
2891966555a24295b75b.jpghealthy
16808f58fc06940689eaf.jpgfrog_eye_leaf_spot
15988c94b4d7bb83194b.jpgscab frog_eye_leaf_spot
\n
"},"metadata":{}}],"execution_count":5},{"cell_type":"code","source":"plt.figure(figsize=(35,15))\nplt.bar(labels, labels_count)\nplt.title(\"Number of instances per class\",fontweight=\"bold\",fontsize=40)\nplt.xlabel(\"Classes\",fontsize = 30)\nplt.xticks(rotation=20,fontsize = 20,fontweight = \"bold\")\nplt.yticks(fontsize = 20,fontweight = \"bold\")\nplt.ylabel(\"Count\",fontsize=30)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:41:02.432684Z","iopub.execute_input":"2024-12-01T11:41:02.433408Z","iopub.status.idle":"2024-12-01T11:41:03.111608Z","shell.execute_reply.started":"2024-12-01T11:41:02.433374Z","shell.execute_reply":"2024-12-01T11:41:03.110755Z"},"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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Augmentacja\nim_size = 224\nSEED = 42\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\nBATCH_SIZE = 32\ntrain_datagen = ImageDataGenerator(rescale = 1/255.,\n rotation_range=20,\n width_shift_range=0.2,\n height_shift_range=0.2,\n horizontal_flip=True,\n validation_split = 0.2,\n zoom_range = 0.2,\n shear_range = 0.2,\n vertical_flip = False)\n\ntrain_generator = train_datagen.flow_from_dataframe(\n train_df,\n directory = train_images_path,\n x_col = \"image\",\n y_col = \"labels\",\n target_size = (im_size,im_size),\n class_mode='categorical',\n batch_size = BATCH_SIZE,\n subset = \"training\",\n shuffle = True,\n seed = SEED,\n validate_filenames = False\n)","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:41:04.3031Z","iopub.execute_input":"2024-12-01T11:41:04.303425Z","iopub.status.idle":"2024-12-01T11:41:04.347745Z","shell.execute_reply.started":"2024-12-01T11:41:04.303395Z","shell.execute_reply":"2024-12-01T11:41:04.346877Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Found 11924 non-validated image filenames belonging to 12 classes.\n","output_type":"stream"}],"execution_count":7},{"cell_type":"code","source":"val_generator = train_datagen.flow_from_dataframe(\n train_df,\n directory = train_images_path,\n x_col = \"image\",\n y_col = \"labels\",\n target_size = (im_size,im_size),\n class_mode='categorical',\n batch_size = BATCH_SIZE,\n subset = \"validation\",\n shuffle = True,\n seed = SEED,\n validate_filenames = False\n)","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:41:05.932509Z","iopub.execute_input":"2024-12-01T11:41:05.932811Z","iopub.status.idle":"2024-12-01T11:41:05.959275Z","shell.execute_reply.started":"2024-12-01T11:41:05.932786Z","shell.execute_reply":"2024-12-01T11:41:05.958481Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Found 2981 non-validated image filenames belonging to 12 classes.\n","output_type":"stream"}],"execution_count":8},{"cell_type":"code","source":"test_datagen = ImageDataGenerator(\n preprocessing_function=tf.keras.applications.efficientnet.preprocess_input,\n rescale=1/255.0\n)\n\ntest_generator = test_datagen.flow_from_dataframe(\n dataframe=test_df,\n directory=train_images_path,\n x_col=\"image\",\n y_col=None,\n batch_size=BATCH_SIZE,\n seed=42,\n shuffle=False,\n class_mode=None,\n target_size=(im_size, im_size)\n)","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:41:07.521057Z","iopub.execute_input":"2024-12-01T11:41:07.521382Z","iopub.status.idle":"2024-12-01T11:41:21.524368Z","shell.execute_reply.started":"2024-12-01T11:41:07.521356Z","shell.execute_reply":"2024-12-01T11:41:21.523559Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Found 3727 validated image filenames.\n","output_type":"stream"}],"execution_count":9},{"cell_type":"code","source":"from tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Conv2D, MaxPooling2D, GlobalAveragePooling2D, Dense, Dropout, BatchNormalization\n\nmodel = Sequential([\n Conv2D(32, (3, 3), activation='relu', padding='same', input_shape=(224, 224, 3)),\n BatchNormalization(),\n MaxPooling2D(pool_size=(2, 2)),\n \n Conv2D(64, (3, 3), activation='relu', padding='same'),\n BatchNormalization(),\n MaxPooling2D(pool_size=(2, 2)),\n \n Conv2D(128, (3, 3), activation='relu', padding='same'),\n BatchNormalization(),\n MaxPooling2D(pool_size=(2, 2)),\n \n Conv2D(256, (3, 3), activation='relu', padding='same'),\n BatchNormalization(),\n MaxPooling2D(pool_size=(2, 2)),\n \n # Use GlobalAveragePooling2D instead of Flatten to reduce parameters\n GlobalAveragePooling2D(),\n \n Dense(256, activation='relu'),\n Dropout(0.5),\n \n Dense(12, activation='softmax') # Adjust the output for your number of classes\n])\n\nmodel.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])\nmodel.summary()\n","metadata":{"execution":{"iopub.status.busy":"2024-12-01T11:41:22.171885Z","iopub.execute_input":"2024-12-01T11:41:22.17215Z","iopub.status.idle":"2024-12-01T11:41:22.270433Z","shell.execute_reply.started":"2024-12-01T11:41:22.172124Z","shell.execute_reply":"2024-12-01T11:41:22.269691Z"},"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"\u001b[1mModel: \"sequential_1\"\u001b[0m\n","text/html":"
Model: \"sequential_1\"\n
\n"},"metadata":{}},{"output_type":"display_data","data":{"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_4 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m224\u001b[0m, \u001b[38;5;34m224\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m896\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ batch_normalization_4 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m224\u001b[0m, \u001b[38;5;34m224\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_4 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_5 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m18,496\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ batch_normalization_5 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m112\u001b[0m, \u001b[38;5;34m112\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_5 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_6 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m73,856\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ batch_normalization_6 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m56\u001b[0m, \u001b[38;5;34m56\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_6 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_7 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m256\u001b[0m) │ \u001b[38;5;34m295,168\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ batch_normalization_7 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m28\u001b[0m, \u001b[38;5;34m28\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_7 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m256\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ global_average_pooling2d_1 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n│ (\u001b[38;5;33mGlobalAveragePooling2D\u001b[0m) │ │ │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dense_2 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m) │ \u001b[38;5;34m65,792\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dropout_1 (\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_3 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m12\u001b[0m) │ \u001b[38;5;34m3,084\u001b[0m │\n└─────────────────────────────────┴────────────────────────┴───────────────┘\n","text/html":"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n│ conv2d_4 (Conv2D)               │ (None, 224, 224, 32)   │           896 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ batch_normalization_4           │ (None, 224, 224, 32)   │           128 │\n│ (BatchNormalization)            │                        │               │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_4 (MaxPooling2D)  │ (None, 112, 112, 32)   │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_5 (Conv2D)               │ (None, 112, 112, 64)   │        18,496 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ batch_normalization_5           │ (None, 112, 112, 64)   │           256 │\n│ (BatchNormalization)            │                        │               │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_5 (MaxPooling2D)  │ (None, 56, 56, 64)     │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_6 (Conv2D)               │ (None, 56, 56, 128)    │        73,856 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ batch_normalization_6           │ (None, 56, 56, 128)    │           512 │\n│ (BatchNormalization)            │                        │               │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_6 (MaxPooling2D)  │ (None, 28, 28, 128)    │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_7 (Conv2D)               │ (None, 28, 28, 256)    │       295,168 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ batch_normalization_7           │ (None, 28, 28, 256)    │         1,024 │\n│ (BatchNormalization)            │                        │               │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_7 (MaxPooling2D)  │ (None, 14, 14, 256)    │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ global_average_pooling2d_1      │ (None, 256)            │             0 │\n│ (GlobalAveragePooling2D)        │                        │               │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dense_2 (Dense)                 │ (None, 256)            │        65,792 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dropout_1 (Dropout)             │ (None, 256)            │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dense_3 (Dense)                 │ (None, 12)             │         3,084 │\n└─────────────────────────────────┴────────────────────────┴───────────────┘\n
\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m459,212\u001b[0m (1.75 MB)\n","text/html":"
 Total params: 459,212 (1.75 MB)\n
\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m458,252\u001b[0m (1.75 MB)\n","text/html":"
 Trainable params: 458,252 (1.75 MB)\n
\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m960\u001b[0m (3.75 KB)\n","text/html":"
 Non-trainable params: 960 (3.75 KB)\n
\n"},"metadata":{}}],"execution_count":11},{"cell_type":"code","source":"# # Calculate train and validation steps\n# train_steps = (len(train_df) + BATCH_SIZE - 1) // BATCH_SIZE # Round up division\n# val_steps = (len(val_df) + BATCH_SIZE - 1) // BATCH_SIZE # Round up division ","metadata":{"execution":{"iopub.status.busy":"2024-11-03T18:48:25.555519Z","iopub.execute_input":"2024-11-03T18:48:25.556222Z","iopub.status.idle":"2024-11-03T18:48:25.560525Z","shell.execute_reply.started":"2024-11-03T18:48:25.556183Z","shell.execute_reply":"2024-11-03T18:48:25.559773Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Train the model\nhistory = model.fit(\n train_generator,\n epochs=5,\n validation_data=val_generator,\n)","metadata":{"execution":{"iopub.status.busy":"2024-12-01T14:54:01.434349Z","iopub.execute_input":"2024-12-01T14:54:01.435163Z","iopub.status.idle":"2024-12-01T16:05:08.347069Z","shell.execute_reply.started":"2024-12-01T14:54:01.435128Z","shell.execute_reply":"2024-12-01T16:05:08.346163Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Epoch 1/5\n\u001b[1m373/373\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m847s\u001b[0m 2s/step - accuracy: 0.8399 - loss: 0.5005 - val_accuracy: 0.5790 - val_loss: 1.3948\nEpoch 2/5\n\u001b[1m373/373\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m869s\u001b[0m 2s/step - accuracy: 0.8450 - loss: 0.4847 - val_accuracy: 0.6293 - val_loss: 1.4860\nEpoch 3/5\n\u001b[1m373/373\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m861s\u001b[0m 2s/step - accuracy: 0.8470 - loss: 0.4792 - val_accuracy: 0.8319 - val_loss: 0.5451\nEpoch 4/5\n\u001b[1m373/373\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m843s\u001b[0m 2s/step - accuracy: 0.8417 - loss: 0.4865 - val_accuracy: 0.3784 - val_loss: 4.6943\nEpoch 5/5\n\u001b[1m373/373\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m843s\u001b[0m 2s/step - accuracy: 0.8500 - loss: 0.4690 - val_accuracy: 0.8004 - val_loss: 0.6385\n","output_type":"stream"}],"execution_count":16},{"cell_type":"code","source":"from sklearn.metrics import accuracy_score\n\n# Generate predictions on the test set\npredictions = model.predict(test_generator)\npredicted_classes = predictions.argmax(axis=-1) # Get the class with the highest probability\n\n# Map indices back to class labels\nclass_indices = train_generator.class_indices # Assuming same class indices as train generator\nlabels = {v: k for k, v in class_indices.items()}\npredicted_labels = [labels[idx] for idx in predicted_classes]\n\n# Extract the true labels from test_df\ntrue_labels = test_df[\"labels\"].tolist()\n\n# Calculate accuracy\naccuracy = accuracy_score(true_labels, predicted_labels)\n\nprint(f\"Test Accuracy: {accuracy * 100:.2f}%\")","metadata":{"execution":{"iopub.status.busy":"2024-11-03T21:54:35.199804Z","iopub.execute_input":"2024-11-03T21:54:35.200791Z","iopub.status.idle":"2024-11-03T21:57:41.073007Z","shell.execute_reply.started":"2024-11-03T21:54:35.200749Z","shell.execute_reply":"2024-11-03T21:57:41.072023Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plt.figure(figsize=(12, 4))\nplt.subplot(1, 2, 1)\nplt.plot(history.history['accuracy'], label='Train Accuracy')\nplt.plot(history.history['val_accuracy'], label='Validation Accuracy')\nplt.title('Model Accuracy')\nplt.xlabel('Epoch')\nplt.ylabel('Accuracy')\nplt.legend()\n\n# Plot training & validation loss\nplt.subplot(1, 2, 2)\nplt.plot(history.history['loss'], label='Train Loss')\nplt.plot(history.history['val_loss'], label='Validation Loss')\nplt.title('Model Loss')\nplt.xlabel('Epoch')\nplt.ylabel('Loss')\nplt.legend()\n\nplt.tight_layout()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-01T16:13:06.556671Z","iopub.execute_input":"2024-12-01T16:13:06.55703Z","iopub.status.idle":"2024-12-01T16:13:07.065782Z","shell.execute_reply.started":"2024-12-01T16:13:06.556998Z","shell.execute_reply":"2024-12-01T16:13:07.064797Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}],"execution_count":17},{"cell_type":"code","source":"from sklearn.metrics import accuracy_score, confusion_matrix\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n\ncm = confusion_matrix(true_labels, predicted_labels)\n\n# Plot the confusion matrix using seaborn heatmap\nplt.figure(figsize=(8, 6))\nsns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", xticklabels=labels.values(), yticklabels=labels.values())\nplt.title(\"Confusion Matrix\")\nplt.xlabel(\"Predicted Label\")\nplt.ylabel(\"True Label\")\nplt.show()","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model.save(\"first_cnn.h5\")","metadata":{"execution":{"iopub.status.busy":"2024-11-03T19:05:23.10098Z","iopub.execute_input":"2024-11-03T19:05:23.101801Z","iopub.status.idle":"2024-11-03T19:05:23.175454Z","shell.execute_reply.started":"2024-11-03T19:05:23.101759Z","shell.execute_reply":"2024-11-03T19:05:23.17467Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Check a single batch of training data\nx_train, y_train = next(train_generator)\nprint(x_train.shape, y_train.shape)\n\n# Check a single batch of validation data\nx_val, y_val = next(val_generator)\nprint(x_val.shape, y_val.shape)\n","metadata":{"execution":{"iopub.status.busy":"2024-11-03T17:40:03.976481Z","iopub.execute_input":"2024-11-03T17:40:03.977296Z","iopub.status.idle":"2024-11-03T17:40:07.608047Z","shell.execute_reply.started":"2024-11-03T17:40:03.977252Z","shell.execute_reply":"2024-11-03T17:40:07.606958Z"},"trusted":true},"outputs":[],"execution_count":null}]}