Crax Rat -

train_generator = train_datagen.flow_from_directory(train_dir, target_size=(224, 224), batch_size=32, class_mode='categorical')

# Fine-tune. Make all layers trainable. for layer in model.layers: layer.trainable = True crax rat

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy']) train_generator = train_datagen

# Assuming you've collected and preprocessed your data train_dir = 'path/to/train' validation_dir = 'path/to/validation' crax rat