{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# 1. Setup\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 1.1 Install Dependencies\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\n", "Usage: \n", " pip install [options] [package-index-options] ...\n", " pip install [options] -r [package-index-options] ...\n", " pip install [options] [-e] ...\n", " pip install [options] [-e] ...\n", " pip install [options] ...\n", "\n", "no such option: -u\n" ] } ], "source": [ "# Install Tensorflow version 2.4.1\n", "# Install the required drivers and packages: https://www.tensorflow.org/install\n", "# Here is a helpful guide that I used to set up the TF environment: https://towardsdatascience.com/install-tensorflow-with-cuda-cudnn-and-gpu-support-in-4-easy-steps-954f176daac3\n", "\n", "# !pip install tensorflow==2.4.1 tensorflow-gpu==2.4.1 opencv-python matplotlib --user\n", "!pip install tensorflow - -user opencv-python matplotlib numpy pandas seaborn protobuf == 3.20.* scikit-learn\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 1.2 Check the Available Devices\n", "\n", "##### (Optional. Helps troubleshoot if the GPU is being used)\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[name: \"/device:CPU:0\"\n", "device_type: \"CPU\"\n", "memory_limit: 268435456\n", "locality {\n", "}\n", "incarnation: 3110676867861078079\n", "xla_global_id: -1\n", "]\n" ] } ], "source": [ "# Check if the GPU is detected. If not, the model will take a very long time to train.\n", "from tensorflow.python.client import device_lib\n", "print(device_lib.list_local_devices())\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 1.3 Import Data Visualization Libraries and Image Processing Libraries\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import os\n", "import random\n", "import numpy as np\n", "import pandas as pd\n", "import seaborn as sns\n", "import datetime\n", "import matplotlib.pyplot as plt\n", "from matplotlib.pyplot import imshow\n", "import cv2\n", "from PIL import Image\n", "from sklearn.metrics import classification_report, confusion_matrix" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 1.4 Import TensorFlow and Keras libraries\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "import tensorflow as tf\n", "from tensorflow.keras.models import Sequential\n", "from tensorflow.keras.layers import Dense, Conv2D, Flatten, Dropout, MaxPooling2D\n", "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n", "from tensorflow.keras import regularizers\n", "from tensorflow.keras.optimizers import SGD\n", "from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, ReduceLROnPlateau" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# 2. Load and Preprocess the Data\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 2.1. Loading and Preprocessing Training Data\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\Sagar\\AppData\\Local\\Temp\\ipykernel_7344\\525592075.py:21: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n", " X_train = np.array(X_train)\n" ] } ], "source": [ "# \"./input/standard-ocr-dataset/data/training_data\"\n", "# import os\n", "# import numpy as np\n", "# from PIL import Image\n", "\n", "train_dir = './input/standard-ocr-dataset/data/training_data'\n", "classes = os.listdir(train_dir)\n", "\n", "X_train = []\n", "y_train = []\n", "\n", "for i, c in enumerate(classes):\n", " class_dir = os.path.join(train_dir, c)\n", " for img_name in os.listdir(class_dir):\n", " img_path = os.path.join(class_dir, img_name)\n", " img = Image.open(img_path)\n", " img = np.array(img)\n", " X_train.append(img)\n", " y_train.append(i)\n", "\n", "X_train = np.array(X_train)\n", "y_train = np.array(y_train)\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 2.2. Data Loading and Distribution Visualization\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 20628 images belonging to 36 classes.\n", "Found 1008 images belonging to 36 classes.\n" ] }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# import os\n", "# import numpy as np\n", "# import matplotlib.pyplot as plt\n", "# import seaborn as sns\n", "# from tensorflow.keras.preprocessing.image import ImageDataGenerator\n", "\n", "# Set up directories\n", "train_dir = './input/standard-ocr-dataset/data/training_data'\n", "test_dir = './input/standard-ocr-dataset/data/testing_data'\n", "\n", "# Create data generators\n", "train_datagen = ImageDataGenerator(rescale=1./255)\n", "test_datagen = ImageDataGenerator(rescale=1./255)\n", "\n", "train_data = train_datagen.flow_from_directory(\n", " train_dir,\n", " target_size=(32, 32),\n", " batch_size=32,\n", " color_mode='grayscale',\n", " class_mode='categorical')\n", "\n", "test_data = test_datagen.flow_from_directory(\n", " test_dir,\n", " target_size=(32, 32),\n", " batch_size=32,\n", " color_mode='grayscale',\n", " class_mode='categorical')\n", "\n", "# Concatenate training and testing data\n", "all_data = np.concatenate([train_data.labels, test_data.labels])\n", "\n", "# Create character list\n", "characters = [chr(i) for i in range(48, 58)] + [chr(i) for i in range(65, 91)]\n", "\n", "# Create countplot of character distribution\n", "plt.figure(figsize=(12, 6))\n", "sns.countplot(x=all_data, palette='coolwarm')\n", "plt.xlabel('Character')\n", "plt.ylabel('Count')\n", "plt.xticks(np.arange(36), characters)\n", "plt.title('Distribution of Characters in Dataset')\n", "plt.show()\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 2.3. Preview of the Dataset with Random Images\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# import os\n", "# import random\n", "# import matplotlib.pyplot as plt\n", "# from PIL import Image\n", "\n", "fig, axe = plt.subplots(7, 7, figsize=(10, 10))\n", "fig.suptitle('Preview of the Dataset')\n", "\n", "for i in range(7):\n", " for j in range(7):\n", " idx = i*7+j\n", " label_dir = os.path.join('./input/standard-ocr-dataset/data/training_data', str(\n", " random.choice(list(\"0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ\"))))\n", " img_path = os.path.join(\n", " label_dir, random.choice(os.listdir(label_dir)))\n", " img = Image.open(img_path)\n", " img = img.resize((32, 32), resample=Image.BOX)\n", " axe[i, j].imshow(img, cmap='gray')\n", " axe[i, j].set_title('letter: {} label: {}'.format(\n", " os.path.basename(label_dir), os.path.basename(img_path)[0]), fontsize=8)\n", " axe[i, j].axis('off')\n", "\n", "plt.show()\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 2.4. Defining ImageDataGenerator Objects for Data Augmentation and Normalization\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# Define an ImageDataGenerator object for data augmentation with the following settings:\n", "augmented_image_gen = ImageDataGenerator(\n", " rescale=1./255, # rescale pixel values to range [0, 1]\n", " rotation_range=15, # randomly rotate images up to 15 degrees\n", " width_shift_range=0.1, # randomly shift the width of the image by up to 10%\n", " height_shift_range=0.1, # randomly shift the height of the image by up to 10%\n", " shear_range=0.1, # randomly apply shear transformation up to 10%\n", " zoom_range=0.1, # randomly zoom into the image up to 10%\n", " horizontal_flip=False, # do not horizontally flip the image\n", " fill_mode='nearest', # use nearest pixel to fill gaps after transformations\n", " # randomly adjust brightness between 50% and 150%\n", " brightness_range=[0.5, 1.5],\n", " validation_split=0.2 # split the data into training and validation sets with 80/20 ratio\n", ")\n", "\n", "# Define an ImageDataGenerator object for normalizing the pixel values of test images\n", "normal_image_gen = ImageDataGenerator(\n", " rescale=1./255, # rescale pixel values to range [0, 1]\n", " validation_split=0.2 # split the data into training and validation sets with 80/20 ratio\n", ")\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 2.5. Setting up image data generators for training and validation sets\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 16524 images belonging to 36 classes.\n", "Found 180 images belonging to 36 classes.\n" ] } ], "source": [ "# Define constants and variables\n", "batch_size = 32\n", "epochs = 32\n", "image_height = 32\n", "image_width = 32\n", "seed = 12345\n", "data_dir = \"./input/standard-ocr-dataset/data/\"\n", "\n", "# Create image data generators\n", "train_data_gen = augmented_image_gen.flow_from_directory(\n", " batch_size=batch_size,\n", " directory=data_dir + \"training_data\",\n", " color_mode=\"grayscale\",\n", " shuffle=True,\n", " target_size=(image_height, image_width),\n", " class_mode=\"categorical\",\n", " seed=seed,\n", " subset='training'\n", ")\n", "\n", "val_data_gen = normal_image_gen.flow_from_directory(\n", " batch_size=batch_size,\n", " directory=data_dir + \"testing_data\",\n", " color_mode=\"grayscale\",\n", " shuffle=True,\n", " target_size=(image_height, image_width),\n", " class_mode=\"categorical\",\n", " seed=seed,\n", " subset='validation'\n", ")\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# 3. Creating the Deep Learning Model\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 3.1. Defining and compiling a Convolutional Neural Network (CNN) for image classification using Keras.\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# Import SGD optimizer from Keras library\n", "# from tensorflow.keras.optimizers import SGD\n", "\n", "# Define the architecture of a Convolutional Neural Network (CNN)\n", "\n", "\n", "def define_model():\n", " # Instantiate a sequential model\n", " model = Sequential()\n", "\n", " # Add a 2D convolutional layer with 32 filters, a 3x3 kernel, ReLU activation, and He uniform weight initialization\n", " model.add(Conv2D(32, (3, 3), activation='relu',\n", " kernel_initializer='he_uniform', input_shape=(32, 32, 1)))\n", "\n", " # Add a max pooling layer with a 2x2 pool size\n", " model.add(MaxPooling2D((2, 2)))\n", "\n", " # Add a flatten layer to convert the 2D feature maps to 1D feature vectors\n", " model.add(Flatten())\n", "\n", " # Add a fully connected layer with 100 neurons, ReLU activation, and He uniform weight initialization\n", " model.add(Dense(100, activation='relu', kernel_initializer='he_uniform'))\n", "\n", " # Add a final fully connected layer with 36 neurons (one for each class), softmax activation, and default weight initialization\n", " model.add(Dense(36, activation='softmax'))\n", "\n", " # Return the model\n", " return model\n", "\n", "\n", "# Instantiate the model\n", "model = define_model()\n", "\n", "# Define optimizer\n", "optimizer = SGD(learning_rate=0.01, momentum=0.9)\n", "\n", "# Compile the model with categorical cross-entropy loss and accuracy metric\n", "model.compile(optimizer=optimizer,\n", " loss='categorical_crossentropy', metrics=['accuracy'])\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 3.2. Testing an OCR model on a standard dataset and generating classification report and confusion matrix.\n" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "32/32 [==============================] - 0s 5ms/step\n", " precision recall f1-score support\n", "\n", " 0 0.00 0.00 0.00 28\n", " 1 0.00 0.00 0.00 28\n", " 2 0.00 0.00 0.00 28\n", " 3 0.00 0.00 0.00 28\n", " 4 0.00 0.00 0.00 28\n", " 5 0.00 0.00 0.00 28\n", " 6 0.00 0.00 0.00 28\n", " 7 0.00 0.00 0.00 28\n", " 8 0.00 0.00 0.00 28\n", " 9 0.00 0.00 0.00 28\n", " A 0.00 0.00 0.00 28\n", " B 0.00 0.00 0.00 28\n", " C 0.01 0.04 0.01 28\n", " D 0.03 0.50 0.05 28\n", " E 0.00 0.00 0.00 28\n", " F 0.00 0.00 0.00 28\n", " G 0.00 0.00 0.00 28\n", " H 0.00 0.00 0.00 28\n", " I 0.00 0.00 0.00 28\n", " J 0.00 0.00 0.00 28\n", " K 0.00 0.00 0.00 28\n", " L 0.00 0.00 0.00 28\n", " M 0.00 0.00 0.00 28\n", " N 0.00 0.00 0.00 28\n", " O 0.00 0.00 0.00 28\n", " P 0.00 0.00 0.00 28\n", " Q 0.00 0.00 0.00 28\n", " R 0.00 0.00 0.00 28\n", " S 0.00 0.00 0.00 28\n", " T 0.00 0.00 0.00 28\n", " U 0.00 0.00 0.00 28\n", " V 0.00 0.00 0.00 28\n", " W 0.00 0.00 0.00 28\n", " X 0.00 0.00 0.00 28\n", " Y 0.00 0.00 0.00 28\n", " Z 0.00 0.00 0.00 28\n", "\n", " accuracy 0.01 1008\n", " macro avg 0.00 0.01 0.00 1008\n", "weighted avg 0.00 0.01 0.00 1008\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\Sagar\\AppData\\Roaming\\Python\\Python39\\site-packages\\sklearn\\metrics\\_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "C:\\Users\\Sagar\\AppData\\Roaming\\Python\\Python39\\site-packages\\sklearn\\metrics\\_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "C:\\Users\\Sagar\\AppData\\Roaming\\Python\\Python39\\site-packages\\sklearn\\metrics\\_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# import os\n", "# import numpy as np\n", "# import cv2\n", "# from sklearn.metrics import classification_report, confusion_matrix\n", "\n", "test_dir = './input/standard-ocr-dataset/data/testing_data'\n", "classes = os.listdir(test_dir)\n", "num_classes = len(classes)\n", "\n", "# Load images and labels for each subfolder\n", "X_test = []\n", "y_test = []\n", "for class_idx, class_name in enumerate(classes):\n", " class_dir = os.path.join(test_dir, class_name)\n", " for img_name in os.listdir(class_dir):\n", " img_path = os.path.join(class_dir, img_name)\n", " img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)\n", " # Resize image to match input size of your model\n", " img = cv2.resize(img, (32, 32))\n", " X_test.append(img)\n", " y_test.append(class_idx)\n", "\n", "# Convert lists to numpy arrays\n", "X_test = np.array(X_test)\n", "y_test = np.array(y_test)\n", "\n", "# Normalize pixel values\n", "X_test = X_test / 255.0\n", "\n", "# Make predictions\n", "y_pred = model.predict(X_test)\n", "\n", "# Get predicted class labels\n", "y_pred = np.argmax(y_pred, axis=1)\n", "\n", "# Print classification report\n", "print(classification_report(y_test, y_pred, target_names=classes))\n", "\n", "# Plot confusion matrix\n", "cm = confusion_matrix(y_test, y_pred)\n", "plt.imshow(cm, cmap=plt.cm.Blues)\n", "plt.colorbar()\n", "plt.xticks(np.arange(num_classes), classes, rotation=90)\n", "plt.yticks(np.arange(num_classes), classes)\n", "plt.xlabel('Predicted label')\n", "plt.ylabel('True label')\n", "plt.show()\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 3.3. Defining Callbacks and Training the Model\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/32\n", "516/516 [==============================] - ETA: 0s - loss: 2.1929 - categorical_accuracy: 0.3663" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 21s 39ms/step - loss: 2.1929 - categorical_accuracy: 0.3663 - val_loss: 0.3432 - val_categorical_accuracy: 0.9000\n", "Epoch 2/32\n", "516/516 [==============================] - ETA: 0s - loss: 0.9902 - categorical_accuracy: 0.7150" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 22s 43ms/step - loss: 0.9902 - categorical_accuracy: 0.7150 - val_loss: 0.1752 - val_categorical_accuracy: 0.9250\n", "Epoch 3/32\n", "516/516 [==============================] - 23s 44ms/step - loss: 0.6591 - categorical_accuracy: 0.8143 - val_loss: 0.2087 - val_categorical_accuracy: 0.9000\n", "Epoch 4/32\n", "516/516 [==============================] - ETA: 0s - loss: 0.5308 - categorical_accuracy: 0.8454" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 19s 38ms/step - loss: 0.5308 - categorical_accuracy: 0.8454 - val_loss: 0.1475 - val_categorical_accuracy: 0.9375\n", "Epoch 5/32\n", "515/516 [============================>.] - ETA: 0s - loss: 0.4799 - categorical_accuracy: 0.8641" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 23s 44ms/step - loss: 0.4795 - categorical_accuracy: 0.8641 - val_loss: 0.0840 - val_categorical_accuracy: 0.9563\n", "Epoch 6/32\n", "515/516 [============================>.] - ETA: 0s - loss: 0.4286 - categorical_accuracy: 0.8806" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 23s 44ms/step - loss: 0.4291 - categorical_accuracy: 0.8805 - val_loss: 0.0828 - val_categorical_accuracy: 0.9688\n", "Epoch 7/32\n", "516/516 [==============================] - ETA: 0s - loss: 0.3961 - categorical_accuracy: 0.8910" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 23s 44ms/step - loss: 0.3961 - categorical_accuracy: 0.8910 - val_loss: 0.0761 - val_categorical_accuracy: 0.9688\n", "Epoch 8/32\n", "516/516 [==============================] - 21s 41ms/step - loss: 0.3625 - categorical_accuracy: 0.8963 - val_loss: 0.1236 - val_categorical_accuracy: 0.9625\n", "Epoch 9/32\n", "515/516 [============================>.] - ETA: 0s - loss: 0.3593 - categorical_accuracy: 0.8987" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 20s 38ms/step - loss: 0.3596 - categorical_accuracy: 0.8988 - val_loss: 0.0716 - val_categorical_accuracy: 0.9625\n", "Epoch 10/32\n", "516/516 [==============================] - ETA: 0s - loss: 0.3317 - categorical_accuracy: 0.9049" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 22s 43ms/step - loss: 0.3317 - categorical_accuracy: 0.9049 - val_loss: 0.0550 - val_categorical_accuracy: 0.9750\n", "Epoch 11/32\n", "516/516 [==============================] - 21s 41ms/step - loss: 0.3241 - categorical_accuracy: 0.9101 - val_loss: 0.1017 - val_categorical_accuracy: 0.9500\n", "Epoch 12/32\n", "516/516 [==============================] - 19s 37ms/step - loss: 0.3132 - categorical_accuracy: 0.9087 - val_loss: 0.0717 - val_categorical_accuracy: 0.9563\n", "Epoch 13/32\n", "516/516 [==============================] - 19s 37ms/step - loss: 0.2985 - categorical_accuracy: 0.9127 - val_loss: 0.0556 - val_categorical_accuracy: 0.9625\n", "Epoch 14/32\n", "516/516 [==============================] - 19s 37ms/step - loss: 0.2895 - categorical_accuracy: 0.9137 - val_loss: 0.0717 - val_categorical_accuracy: 0.9688\n", "Epoch 15/32\n", "516/516 [==============================] - 19s 37ms/step - loss: 0.2876 - categorical_accuracy: 0.9171 - val_loss: 0.0649 - val_categorical_accuracy: 0.9750\n", "Epoch 16/32\n", "516/516 [==============================] - 19s 37ms/step - loss: 0.2867 - categorical_accuracy: 0.9172 - val_loss: 0.1133 - val_categorical_accuracy: 0.9438\n", "Epoch 17/32\n", "516/516 [==============================] - 19s 37ms/step - loss: 0.2602 - categorical_accuracy: 0.9232 - val_loss: 0.1510 - val_categorical_accuracy: 0.9312\n", "Epoch 18/32\n", "516/516 [==============================] - 19s 38ms/step - loss: 0.2582 - categorical_accuracy: 0.9235 - val_loss: 0.0601 - val_categorical_accuracy: 0.9625\n", "Epoch 19/32\n", "516/516 [==============================] - 19s 36ms/step - loss: 0.2604 - categorical_accuracy: 0.9236 - val_loss: 0.0613 - val_categorical_accuracy: 0.9625\n", "Epoch 20/32\n", "515/516 [============================>.] - ETA: 0s - loss: 0.2598 - categorical_accuracy: 0.9259" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 20s 38ms/step - loss: 0.2598 - categorical_accuracy: 0.9259 - val_loss: 0.0487 - val_categorical_accuracy: 0.9750\n", "Epoch 21/32\n", "515/516 [============================>.] - ETA: 0s - loss: 0.2372 - categorical_accuracy: 0.9301" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 22s 43ms/step - loss: 0.2373 - categorical_accuracy: 0.9300 - val_loss: 0.0343 - val_categorical_accuracy: 0.9812\n", "Epoch 22/32\n", "516/516 [==============================] - 22s 42ms/step - loss: 0.2345 - categorical_accuracy: 0.9291 - val_loss: 0.0437 - val_categorical_accuracy: 0.9750\n", "Epoch 23/32\n", "516/516 [==============================] - 19s 36ms/step - loss: 0.2258 - categorical_accuracy: 0.9323 - val_loss: 0.0608 - val_categorical_accuracy: 0.9688\n", "Epoch 24/32\n", "516/516 [==============================] - 19s 37ms/step - loss: 0.2274 - categorical_accuracy: 0.9332 - val_loss: 0.0667 - val_categorical_accuracy: 0.9750\n", "Epoch 25/32\n", "516/516 [==============================] - 19s 36ms/step - loss: 0.2166 - categorical_accuracy: 0.9336 - val_loss: 0.0572 - val_categorical_accuracy: 0.9688\n", "Epoch 26/32\n", "516/516 [==============================] - 21s 41ms/step - loss: 0.2232 - categorical_accuracy: 0.9312 - val_loss: 0.0354 - val_categorical_accuracy: 0.9812\n", "Epoch 27/32\n", "516/516 [==============================] - 20s 39ms/step - loss: 0.2112 - categorical_accuracy: 0.9358 - val_loss: 0.0557 - val_categorical_accuracy: 0.9750\n", "Epoch 28/32\n", "516/516 [==============================] - 19s 38ms/step - loss: 0.2133 - categorical_accuracy: 0.9350 - val_loss: 0.0598 - val_categorical_accuracy: 0.9688\n", "Epoch 29/32\n", "516/516 [==============================] - 21s 41ms/step - loss: 0.2033 - categorical_accuracy: 0.9363 - val_loss: 0.0555 - val_categorical_accuracy: 0.9688\n", "Epoch 30/32\n", "516/516 [==============================] - 21s 40ms/step - loss: 0.2149 - categorical_accuracy: 0.9340 - val_loss: 0.0387 - val_categorical_accuracy: 0.9812\n", "Epoch 31/32\n", "516/516 [==============================] - 21s 40ms/step - loss: 0.2039 - categorical_accuracy: 0.9363 - val_loss: 0.0557 - val_categorical_accuracy: 0.9625\n", "Epoch 32/32\n", "516/516 [==============================] - 21s 40ms/step - loss: 0.2013 - categorical_accuracy: 0.9398 - val_loss: 0.0477 - val_categorical_accuracy: 0.9750\n" ] } ], "source": [ "# import tensorflow\n", "# from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, ReduceLROnPlateau\n", "\n", "# Prepare callbacks\n", "EarlyStop_callback = EarlyStopping(\n", " monitor='val_loss', patience=20, restore_best_weights=True)\n", "checkpoint = ModelCheckpoint('./checkpoint',\n", " monitor='val_loss', mode='min', save_best_only=True)\n", "lr = ReduceLROnPlateau(monitor='val_loss', factor=0.5,\n", " patience=3, min_lr=0.00001)\n", "my_callback = [EarlyStop_callback, checkpoint]\n", "\n", "# Training our model\n", "model.compile(optimizer=tf.keras.optimizers.SGD(learning_rate=0.01, momentum=0.9),\n", " loss=tf.keras.losses.CategoricalCrossentropy(), metrics=['categorical_accuracy'])\n", "\n", "# set logging level to INFO to avoid warning messages\n", "tf.get_logger().setLevel('INFO')\n", "history = model.fit(\n", " train_data_gen,\n", " steps_per_epoch=train_data_gen.samples // batch_size,\n", " epochs=32,\n", " validation_data=val_data_gen,\n", " validation_steps=val_data_gen.samples // batch_size,\n", " callbacks=my_callback)\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# 4. Testing and Evaluating the Model\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 4.1. Testing the Trained Model on New Data and Generating Classification Metrics\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "32/32 [==============================] - 0s 4ms/step\n", " precision recall f1-score support\n", "\n", " 0 0.57 0.93 0.70 28\n", " 1 1.00 1.00 1.00 28\n", " 2 1.00 1.00 1.00 28\n", " 3 1.00 1.00 1.00 28\n", " 4 1.00 1.00 1.00 28\n", " 5 1.00 1.00 1.00 28\n", " 6 1.00 1.00 1.00 28\n", " 7 1.00 1.00 1.00 28\n", " 8 1.00 1.00 1.00 28\n", " 9 1.00 1.00 1.00 28\n", " A 1.00 1.00 1.00 28\n", " B 0.97 1.00 0.98 28\n", " C 0.90 0.96 0.93 28\n", " D 1.00 1.00 1.00 28\n", " E 0.96 0.96 0.96 28\n", " F 1.00 0.96 0.98 28\n", " G 1.00 0.86 0.92 28\n", " H 1.00 1.00 1.00 28\n", " I 0.93 1.00 0.97 28\n", " J 1.00 1.00 1.00 28\n", " K 1.00 1.00 1.00 28\n", " L 1.00 1.00 1.00 28\n", " M 1.00 1.00 1.00 28\n", " N 1.00 1.00 1.00 28\n", " O 0.80 0.29 0.42 28\n", " P 1.00 1.00 1.00 28\n", " Q 1.00 1.00 1.00 28\n", " R 1.00 1.00 1.00 28\n", " S 1.00 1.00 1.00 28\n", " T 1.00 1.00 1.00 28\n", " U 1.00 1.00 1.00 28\n", " V 1.00 1.00 1.00 28\n", " W 1.00 1.00 1.00 28\n", " X 1.00 1.00 1.00 28\n", " Y 1.00 1.00 1.00 28\n", " Z 1.00 1.00 1.00 28\n", "\n", " accuracy 0.97 1008\n", " macro avg 0.98 0.97 0.97 1008\n", "weighted avg 0.98 0.97 0.97 1008\n", "\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# import os\n", "# import numpy as np\n", "# import cv2\n", "# from sklearn.metrics import classification_report, confusion_matrix\n", "\n", "test_dir = './input/standard-ocr-dataset/data/testing_data'\n", "classes = os.listdir(test_dir)\n", "num_classes = len(classes)\n", "\n", "# Load images and labels for each subfolder\n", "X_test = []\n", "y_test = []\n", "for class_idx, class_name in enumerate(classes):\n", " class_dir = os.path.join(test_dir, class_name)\n", " for img_name in os.listdir(class_dir):\n", " img_path = os.path.join(class_dir, img_name)\n", " img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)\n", " img = cv2.resize(img, (32, 32)) # Resize image to match input size of your model\n", " X_test.append(img)\n", " y_test.append(class_idx)\n", "\n", "# Convert lists to numpy arrays\n", "X_test = np.array(X_test)\n", "y_test = np.array(y_test)\n", "\n", "# Normalize pixel values\n", "X_test = X_test / 255.0\n", "\n", "# Make predictions\n", "y_pred = model.predict(X_test)\n", "\n", "# Get predicted class labels\n", "y_pred = np.argmax(y_pred, axis=1)\n", "\n", "# Print classification report\n", "print(classification_report(y_test, y_pred, target_names=classes))\n", "\n", "# Plot confusion matrix\n", "cm = confusion_matrix(y_test, y_pred)\n", "plt.imshow(cm, cmap=plt.cm.Blues)\n", "plt.colorbar()\n", "plt.xticks(np.arange(num_classes), classes, rotation=90)\n", "plt.yticks(np.arange(num_classes), classes)\n", "plt.xlabel('Predicted label')\n", "plt.ylabel('True label')\n", "plt.show()\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 4.2. Plotting Training and Validation Accuracy/Loss over Epochs\n" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "acc = history.history['categorical_accuracy']\n", "val_acc = history.history['val_categorical_accuracy']\n", "loss = history.history['loss']\n", "val_loss = history.history['val_loss']\n", "epochs_range = range(1, 33, 1)\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.xlabel('Epochs')\n", "plt.ylabel('Accuracy')\n", "plt.legend(loc='lower right')\n", "plt.title('Training and Validation Accuracy')\n", "plt.grid(linestyle='--')\n", "\n", "highest_val_acc = max(val_acc)\n", "highest_val_acc_idx = val_acc.index(highest_val_acc) + 1\n", "highest_train_acc = acc[highest_val_acc_idx-1]\n", "\n", "plt.annotate(f'Highest Validation Accuracy: {highest_val_acc:.4f}', xy=(highest_val_acc_idx, highest_val_acc),\n", " xytext=(highest_val_acc_idx, highest_val_acc-0.1), arrowprops=dict(facecolor='black', arrowstyle='->'))\n", "\n", "plt.annotate(f'Training Accuracy at Highest Validation: {highest_train_acc:.4f}', xy=(highest_val_acc_idx, highest_train_acc),\n", " xytext=(highest_val_acc_idx-2, highest_train_acc-0.2), arrowprops=dict(facecolor='black', arrowstyle='->'))\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.xlabel('Epochs')\n", "plt.ylabel('Loss')\n", "plt.legend(loc='upper right')\n", "plt.title('Training and Validation Loss')\n", "plt.grid(linestyle='--')\n", "\n", "plt.show()\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 4.3. Generating Test Data for Image Classification using ImageDataGenerator\n" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 1008 images belonging to 36 classes.\n" ] } ], "source": [ "# Import required libraries\n", "# from tensorflow.keras.preprocessing.image import ImageDataGenerator\n", "\n", "# Set image height and width\n", "image_height = 32\n", "image_width = 32\n", "\n", "# Create ImageDataGenerator object for normalizing test images\n", "normal_image_gen = ImageDataGenerator(\n", " samplewise_center=True, # set each sample mean to 0\n", " samplewise_std_normalization=True # divide each input by its std\n", ")\n", "\n", "# Generate test data from directory using ImageDataGenerator\n", "test_data_gen = normal_image_gen.flow_from_directory(\n", " # path to testing images directory\n", " directory=\"./input/standard-ocr-dataset/data/testing_data\",\n", " target_size=(image_height, image_width), # resize images to this size\n", " color_mode=\"grayscale\", # convert images to grayscale\n", " class_mode=\"categorical\", # return 2D one-hot encoded labels\n", " shuffle=True, # shuffle order of the images\n", " batch_size=1008 # number of images to be yielded per batch\n", ")\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 4.4. Extracting predictions and labels for test data using a trained TensorFlow model.\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "32/32 [==============================] - 0s 5ms/step\n" ] } ], "source": [ "# Import required libraries\n", "# import tensorflow as tf\n", "# from PIL import Image\n", "\n", "# Generate test data and labels\n", "test_images, test_labels = next(test_data_gen)\n", "\n", "# Get filenames for test data\n", "filenames = test_data_gen.filenames\n", "\n", "# Make predictions on test data\n", "test_pred = model.predict(test_images)\n", "\n", "# Import necessary libraries\n", "\n", "# Get true labels by finding the index of the maximum value in each row of test_labels\n", "true_labels = tf.argmax(test_labels, 1)\n", "\n", "# Get predicted labels by finding the index of the maximum value in each row of test_pred\n", "predicted_labels = tf.argmax(test_pred, 1)\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 4.5. Testing the model's performance on sample images.\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1/1 [==============================] - 0s 73ms/step\n", "H\n", "1/1 [==============================] - 0s 22ms/step\n", "E\n", "1/1 [==============================] - 0s 26ms/step\n", "L\n", "1/1 [==============================] - 0s 23ms/step\n", "L\n", "1/1 [==============================] - 0s 22ms/step\n", "O\n" ] } ], "source": [ "# Demonstrate that the model works\n", "\n", "mapping = {\n", " 0: '0', 1: '1', 2: '2', 3: '3', 4: '4', 5: '5', 6: '6', 7: '7', 8: '8', 9: '9',\n", " 10: 'A', 11: 'B', 12: 'C', 13: 'D', 14: 'E', 15: 'F', 16: 'G', 17: 'H', 18: 'I',\n", " 19: 'J', 20: 'K', 21: 'L', 22: 'M', 23: 'N', 24: 'O', 25: 'P', 26: 'Q', 27: 'R',\n", " 28: 'S', 29: 'T', 30: 'U', 31: 'V', 32: 'W', 33: 'X', 34: 'Y', 35: 'Z'\n", "}\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/H/28399.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/E/29008.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/L/28727.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/L/29159.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/O/28406.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1/1 [==============================] - 0s 25ms/step\n", "1.png H\n", "1/1 [==============================] - 0s 23ms/step\n", "2.png R\n", "1/1 [==============================] - 0s 23ms/step\n", "3.png L\n", "1/1 [==============================] - 0s 26ms/step\n", "4.png L\n", "1/1 [==============================] - 0s 23ms/step\n", "5.png Q\n" ] } ], "source": [ "# Define the path to the \"word1\" folder\n", "\n", "# Loop over every image in the folder\n", "for filename in os.listdir(\"./input/standard-ocr-dataset/word1\"):\n", " # Load the image and preprocess it\n", " img = cv2.imread(os.path.join(\n", " \"./input/standard-ocr-dataset/word1\", filename), 0)\n", " img = img / 255\n", " img = cv2.resize(img, (32, 32))\n", " img = img.reshape((1, 32, 32, 1))\n", "\n", " # Predict the character and print it\n", " output = tf.argmax(model.predict(img), 1)\n", " predicted_char = mapping[output.numpy()[0]]\n", " print(filename, predicted_char)\n" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1/1 [==============================] - 0s 26ms/step\n", "1.png A\n", "1/1 [==============================] - 0s 24ms/step\n", "2.png E\n", "1/1 [==============================] - 0s 24ms/step\n", "3.png C\n", "1/1 [==============================] - 0s 24ms/step\n", "4.png A\n", "1/1 [==============================] - 0s 31ms/step\n", "5.png R\n" ] } ], "source": [ "# Define the path to the \"word2\" folder\n", "\n", "# Loop over every image in the folder\n", "for filename in os.listdir(\"./input/standard-ocr-dataset/word2\"):\n", " # Load the image and preprocess it\n", " img = cv2.imread(os.path.join(\n", " \"./input/standard-ocr-dataset/word2\", filename), 0)\n", " img = img / 255\n", " img = cv2.resize(img, (32, 32))\n", " img = img.reshape((1, 32, 32, 1))\n", "\n", " # Predict the character and print it\n", " output = tf.argmax(model.predict(img), 1)\n", " predicted_char = mapping[output.numpy()[0]]\n", " print(filename, predicted_char)\n" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1/1 [==============================] - 0s 22ms/step\n", "1.png 0\n", "1/1 [==============================] - 0s 23ms/step\n", "2.png 0\n", "1/1 [==============================] - 0s 22ms/step\n", "3.png M\n", "1/1 [==============================] - 0s 26ms/step\n", "4.png U\n", "1/1 [==============================] - 0s 23ms/step\n", "5.png O\n", "1/1 [==============================] - 0s 24ms/step\n", "6.png 0\n" ] } ], "source": [ "# Define the path to the \"word3\" folder\n", "\n", "# Loop over every image in the folder\n", "for filename in os.listdir(\"./input/standard-ocr-dataset/word3\"):\n", " # Load the image and preprocess it\n", " img = cv2.imread(os.path.join(\n", " \"./input/standard-ocr-dataset/word3\", filename), 0)\n", " img = img / 255\n", " img = cv2.resize(img, (32, 32))\n", " img = img.reshape((1, 32, 32, 1))\n", "\n", " # Predict the character and print it\n", " output = tf.argmax(model.predict(img), 1)\n", " predicted_char = mapping[output.numpy()[0]]\n", " print(filename, predicted_char)\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# 5. Retraining the Model at 5 Epochs\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 5.1. Defining and compiling a Convolutional Neural Network (CNN) model for classification using Keras library.\n" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "# Import SGD optimizer from Keras library\n", "# from tensorflow.keras.optimizers import SGD\n", "\n", "# Define the architecture of a Convolutional Neural Network (CNN)\n", "\n", "\n", "def define_model():\n", " # Instantiate a sequential model\n", " model = Sequential()\n", "\n", " # Add a 2D convolutional layer with 32 filters, a 3x3 kernel, ReLU activation, and He uniform weight initialization\n", " model.add(Conv2D(5, (3, 3), activation='relu',\n", " kernel_initializer='he_uniform', input_shape=(32, 32, 1)))\n", "\n", " # Add a max pooling layer with a 2x2 pool size\n", " model.add(MaxPooling2D((2, 2)))\n", "\n", " # Add a flatten layer to convert the 2D feature maps to 1D feature vectors\n", " model.add(Flatten())\n", "\n", " # Add a fully connected layer with 100 neurons, ReLU activation, and He uniform weight initialization\n", " model.add(Dense(100, activation='relu', kernel_initializer='he_uniform'))\n", "\n", " # Add a final fully connected layer with 36 neurons (one for each class), softmax activation, and default weight initialization\n", " model.add(Dense(36, activation='softmax'))\n", "\n", " # Return the model\n", " return model\n", "\n", "\n", "# Instantiate the model\n", "model = define_model()\n", "\n", "# Define optimizer\n", "optimizer = SGD(learning_rate=0.01, momentum=0.9)\n", "\n", "# Compile the model with categorical cross-entropy loss and accuracy metric\n", "model.compile(optimizer=optimizer,\n", " loss='categorical_crossentropy', metrics=['accuracy'])\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 5.2. Modifying and Training the Model with Callbacks.\n" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/5\n", "515/516 [============================>.] - ETA: 0s - loss: 2.0082 - categorical_accuracy: 0.4358" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 20s 38ms/step - loss: 2.0061 - categorical_accuracy: 0.4363 - val_loss: 0.3000 - val_categorical_accuracy: 0.8938\n", "Epoch 2/5\n", "515/516 [============================>.] - ETA: 0s - loss: 1.1537 - categorical_accuracy: 0.6735" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 22s 42ms/step - loss: 1.1537 - categorical_accuracy: 0.6736 - val_loss: 0.1785 - val_categorical_accuracy: 0.9500\n", "Epoch 3/5\n", "515/516 [============================>.] - ETA: 0s - loss: 0.9361 - categorical_accuracy: 0.7323" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 22s 42ms/step - loss: 0.9358 - categorical_accuracy: 0.7324 - val_loss: 0.1279 - val_categorical_accuracy: 0.9563\n", "Epoch 4/5\n", "515/516 [============================>.] - ETA: 0s - loss: 0.7931 - categorical_accuracy: 0.7817" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:tensorflow:Assets written to: .\\checkpoint\\assets\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "516/516 [==============================] - 22s 42ms/step - loss: 0.7927 - categorical_accuracy: 0.7817 - val_loss: 0.1087 - val_categorical_accuracy: 0.9563\n", "Epoch 5/5\n", "516/516 [==============================] - 21s 41ms/step - loss: 0.7107 - categorical_accuracy: 0.8054 - val_loss: 0.1162 - val_categorical_accuracy: 0.9375\n" ] } ], "source": [ "# Changing number of epochs to 5\n", "# import tensorflow\n", "# from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, ReduceLROnPlateau\n", "\n", "# Prepare callbacks\n", "EarlyStop_callback = EarlyStopping(\n", " monitor='val_loss', patience=20, restore_best_weights=True)\n", "checkpoint = ModelCheckpoint('./checkpoint',\n", " monitor='val_loss', mode='min', save_best_only=True)\n", "lr = ReduceLROnPlateau(monitor='val_loss', factor=0.5,\n", " patience=3, min_lr=0.00001)\n", "my_callback = [EarlyStop_callback, checkpoint]\n", "\n", "# Training our model\n", "model.compile(optimizer=tf.keras.optimizers.SGD(learning_rate=0.01, momentum=0.9),\n", " loss=tf.keras.losses.CategoricalCrossentropy(), metrics=['categorical_accuracy'])\n", "\n", "# set logging level to INFO to avoid warning messages\n", "tf.get_logger().setLevel('INFO')\n", "history = model.fit(\n", " train_data_gen,\n", " steps_per_epoch=train_data_gen.samples // batch_size,\n", " epochs=5,\n", " validation_data=val_data_gen,\n", " validation_steps=val_data_gen.samples // batch_size,\n", " callbacks=my_callback)\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 5.3. Testing and evaluating the performance of a trained image classification model on a standard OCR dataset.\n" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "32/32 [==============================] - 0s 3ms/step\n", " precision recall f1-score support\n", "\n", " 0 0.45 0.75 0.56 28\n", " 1 0.96 0.82 0.88 28\n", " 2 1.00 1.00 1.00 28\n", " 3 0.84 0.93 0.88 28\n", " 4 1.00 1.00 1.00 28\n", " 5 1.00 1.00 1.00 28\n", " 6 1.00 0.93 0.96 28\n", " 7 1.00 1.00 1.00 28\n", " 8 0.78 1.00 0.88 28\n", " 9 1.00 0.79 0.88 28\n", " A 1.00 1.00 1.00 28\n", " B 0.97 1.00 0.98 28\n", " C 1.00 0.57 0.73 28\n", " D 0.97 1.00 0.98 28\n", " E 1.00 1.00 1.00 28\n", " F 1.00 1.00 1.00 28\n", " G 0.68 1.00 0.81 28\n", " H 1.00 1.00 1.00 28\n", " I 0.93 1.00 0.97 28\n", " J 1.00 0.86 0.92 28\n", " K 1.00 1.00 1.00 28\n", " L 1.00 1.00 1.00 28\n", " M 1.00 1.00 1.00 28\n", " N 1.00 1.00 1.00 28\n", " O 0.22 0.07 0.11 28\n", " P 1.00 1.00 1.00 28\n", " Q 1.00 1.00 1.00 28\n", " R 1.00 1.00 1.00 28\n", " S 1.00 1.00 1.00 28\n", " T 1.00 1.00 1.00 28\n", " U 1.00 1.00 1.00 28\n", " V 1.00 1.00 1.00 28\n", " W 1.00 1.00 1.00 28\n", " X 1.00 1.00 1.00 28\n", " Y 1.00 1.00 1.00 28\n", " Z 1.00 1.00 1.00 28\n", "\n", " accuracy 0.94 1008\n", " macro avg 0.94 0.94 0.93 1008\n", "weighted avg 0.94 0.94 0.93 1008\n", "\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# import os\n", "# import numpy as np\n", "# import cv2\n", "# from sklearn.metrics import classification_report, confusion_matrix\n", "\n", "test_dir = './input/standard-ocr-dataset/data/testing_data'\n", "classes = os.listdir(test_dir)\n", "num_classes = len(classes)\n", "\n", "# Load images and labels for each subfolder\n", "X_test = []\n", "y_test = []\n", "for class_idx, class_name in enumerate(classes):\n", " class_dir = os.path.join(test_dir, class_name)\n", " for img_name in os.listdir(class_dir):\n", " img_path = os.path.join(class_dir, img_name)\n", " img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)\n", " # Resize image to match input size of your model\n", " img = cv2.resize(img, (32, 32))\n", " X_test.append(img)\n", " y_test.append(class_idx)\n", "\n", "# Convert lists to numpy arrays\n", "X_test = np.array(X_test)\n", "y_test = np.array(y_test)\n", "\n", "# Normalize pixel values\n", "X_test = X_test / 255.0\n", "\n", "# Make predictions\n", "y_pred = model.predict(X_test)\n", "\n", "# Get predicted class labels\n", "y_pred = np.argmax(y_pred, axis=1)\n", "\n", "# Print classification report\n", "print(classification_report(y_test, y_pred, target_names=classes))\n", "\n", "# Plot confusion matrix\n", "cm = confusion_matrix(y_test, y_pred)\n", "plt.imshow(cm, cmap=plt.cm.Blues)\n", "plt.colorbar()\n", "plt.xticks(np.arange(num_classes), classes, rotation=90)\n", "plt.yticks(np.arange(num_classes), classes)\n", "plt.xlabel('Predicted label')\n", "plt.ylabel('True label')\n", "plt.show()\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 5.4. Plotting Training and Validation Accuracy/Loss over Epochs with Annotations\n" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "acc = history.history['categorical_accuracy']\n", "val_acc = history.history['val_categorical_accuracy']\n", "loss = history.history['loss']\n", "val_loss = history.history['val_loss']\n", "epochs_range = range(1, 6, 1)\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.xlabel('Epochs')\n", "plt.ylabel('Accuracy')\n", "plt.legend(loc='lower right')\n", "plt.title('Training and Validation Accuracy')\n", "plt.grid(linestyle='--')\n", "\n", "highest_val_acc = max(val_acc)\n", "highest_val_acc_idx = val_acc.index(highest_val_acc) + 1\n", "highest_train_acc = acc[highest_val_acc_idx-1]\n", "\n", "plt.annotate(f'Highest Validation Accuracy: {highest_val_acc:.4f}', xy=(highest_val_acc_idx, highest_val_acc),\n", " xytext=(highest_val_acc_idx, highest_val_acc-0.1), arrowprops=dict(facecolor='black', arrowstyle='->'))\n", "\n", "plt.annotate(f'Training Accuracy at Highest Validation: {highest_train_acc:.4f}', xy=(highest_val_acc_idx, highest_train_acc),\n", " xytext=(highest_val_acc_idx-2, highest_train_acc-0.2), arrowprops=dict(facecolor='black', arrowstyle='->'))\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.xlabel('Epochs')\n", "plt.ylabel('Loss')\n", "plt.legend(loc='upper right')\n", "plt.title('Training and Validation Loss')\n", "plt.grid(linestyle='--')\n", "\n", "plt.subplots_adjust(wspace=0.9)\n", "plt.show()\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## 5.5. Testing the model's performance on sample images.\n" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1/1 [==============================] - 0s 79ms/step\n", "H\n", "1/1 [==============================] - 0s 20ms/step\n", "E\n", "1/1 [==============================] - 0s 24ms/step\n", "L\n", "1/1 [==============================] - 0s 22ms/step\n", "L\n", "1/1 [==============================] - 0s 22ms/step\n", "0\n" ] } ], "source": [ "# Demonstrate that the model works\n", "\n", "mapping = {\n", " 0: '0', 1: '1', 2: '2', 3: '3', 4: '4', 5: '5', 6: '6', 7: '7', 8: '8', 9: '9',\n", " 10: 'A', 11: 'B', 12: 'C', 13: 'D', 14: 'E', 15: 'F', 16: 'G', 17: 'H', 18: 'I',\n", " 19: 'J', 20: 'K', 21: 'L', 22: 'M', 23: 'N', 24: 'O', 25: 'P', 26: 'Q', 27: 'R',\n", " 28: 'S', 29: 'T', 30: 'U', 31: 'V', 32: 'W', 33: 'X', 34: 'Y', 35: 'Z'\n", "}\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/H/28399.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/E/29008.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/L/28727.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/L/29159.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n", "\n", "img = cv2.imread(\n", " './input/standard-ocr-dataset/data/testing_data/O/28406.png', 0)\n", "img = cv2.resize(img, (32, 32))\n", "img = img.reshape((1, 32, 32, 1))\n", "\n", "output = tf.argmax(model.predict(img), 1)\n", "predicted_char = mapping[output.numpy()[0]]\n", "print(predicted_char)\n" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1/1 [==============================] - 0s 71ms/step\n", "1.png R\n", "1/1 [==============================] - 0s 22ms/step\n", "2.png R\n", "1/1 [==============================] - 0s 21ms/step\n", "3.png L\n", "1/1 [==============================] - 0s 25ms/step\n", "4.png L\n", "1/1 [==============================] - 0s 21ms/step\n", "5.png Q\n" ] } ], "source": [ "# Define the path to the \"word1\" folder\n", "\n", "# Loop over every image in the folder\n", "for filename in os.listdir(\"./input/standard-ocr-dataset/word1\"):\n", " # Load the image and preprocess it\n", " img = cv2.imread(os.path.join(\n", " \"./input/standard-ocr-dataset/word1\", filename), 0)\n", " img = img / 255\n", " img = cv2.resize(img, (32, 32))\n", " img = img.reshape((1, 32, 32, 1))\n", "\n", " # Predict the character and print it\n", " output = tf.argmax(model.predict(img), 1)\n", " predicted_char = mapping[output.numpy()[0]]\n", " print(filename, predicted_char)\n" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1/1 [==============================] - 0s 25ms/step\n", "1.png 4\n", "1/1 [==============================] - 0s 22ms/step\n", "2.png 8\n", "1/1 [==============================] - 0s 21ms/step\n", "3.png L\n", "1/1 [==============================] - 0s 23ms/step\n", "4.png 5\n", "1/1 [==============================] - 0s 23ms/step\n", "5.png R\n" ] } ], "source": [ "# Define the path to the \"word2\" folder\n", "\n", "# Loop over every image in the folder\n", "for filename in os.listdir(\"./input/standard-ocr-dataset/word2\"):\n", " # Load the image and preprocess it\n", " img = cv2.imread(os.path.join(\n", " \"./input/standard-ocr-dataset/word2\", filename), 0)\n", " img = img / 255\n", " img = cv2.resize(img, (32, 32))\n", " img = img.reshape((1, 32, 32, 1))\n", "\n", " # Predict the character and print it\n", " output = tf.argmax(model.predict(img), 1)\n", " predicted_char = mapping[output.numpy()[0]]\n", " print(filename, predicted_char)\n" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1/1 [==============================] - 0s 26ms/step\n", "1.png 0\n", "1/1 [==============================] - 0s 24ms/step\n", "2.png 4\n", "1/1 [==============================] - 0s 23ms/step\n", "3.png 4\n", "1/1 [==============================] - 0s 23ms/step\n", "4.png G\n", "1/1 [==============================] - 0s 26ms/step\n", "5.png O\n", "1/1 [==============================] - 0s 23ms/step\n", "6.png Q\n" ] } ], "source": [ "# Define the path to the \"word3\" folder\n", "\n", "# Loop over every image in the folder\n", "for filename in os.listdir(\"./input/standard-ocr-dataset/word3\"):\n", " # Load the image and preprocess it\n", " img = cv2.imread(os.path.join(\n", " \"./input/standard-ocr-dataset/word3\", filename), 0)\n", " img = img / 255\n", " img = cv2.resize(img, (32, 32))\n", " img = img.reshape((1, 32, 32, 1))\n", "\n", " # Predict the character and print it\n", " output = tf.argmax(model.predict(img), 1)\n", " predicted_char = mapping[output.numpy()[0]]\n", " print(filename, predicted_char)\n" ] } ], "metadata": { "kernelspec": { "display_name": "tf", "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": "3.9.16" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }