Utilities.py

import matplotlib.pyplot as plt
import seaborn as sns


def plot_training_history(history):
    """Plot training and validation loss and accuracy"""
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))
    
    # Loss plot
    ax1.plot(history['train_loss'], label='Training Loss')
    ax1.plot(history['val_loss'], label='Validation Loss')
    ax1.set_title('Training and Validation Loss')
    ax1.set_xlabel('Epoch')
    ax1.set_ylabel('Loss')
    ax1.legend()
    ax1.grid(True)
    
    # Accuracy plot
    ax2.plot(history['train_acc'], label='Training Accuracy')
    ax2.plot(history['val_acc'], label='Validation Accuracy')
    ax2.set_title('Training and Validation Accuracy')
    ax2.set_xlabel('Epoch')
    ax2.set_ylabel('Accuracy (%)')
    ax2.legend()
    ax2.grid(True)
    
    plt.tight_layout()
    plt.show()

def plot_confusion_matrix(cm, classes):
    """Plot confusion matrix"""
    plt.figure(figsize=(12, 10))
    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues',
                xticklabels=classes, yticklabels=classes)
    plt.title('Confusion Matrix')
    plt.ylabel('True Label')
    plt.xlabel('Predicted Label')
    plt.xticks(rotation=45)
    plt.yticks(rotation=0)
    plt.tight_layout()
    plt.show()