Class Distribution

from collections import Counter

# Check class distribution in training data
train_labels = train_data_gen.classes  # Get labels for training data
train_class_counts = Counter(train_labels)  # Count occurrences of each class
print("Training Class Distribution:", train_class_counts)

# Check class distribution in validation data
val_labels = val_data_gen.classes  # Get labels for validation data
val_class_counts = Counter(val_labels)  # Count occurrences of each class
print("Validation Class Distribution:", val_class_counts)

# Plotting class distribution
def plot_class_distribution(class_counts, title):
    classes = list(class_counts.keys())
    counts = list(class_counts.values())
    plt.bar(classes, counts, tick_label=[train_data_gen.class_indices[i] for i in classes])
    plt.xlabel("Classes")
    plt.ylabel("Number of Samples")
    plt.title(title)
    plt.show()

# Plot for training data
plot_class_distribution(train_class_counts, "Training Data Class Distribution")

# Plot for validation data
plot_class_distribution(val_class_counts, "Validation Data Class Distribution")