val_range = json.loads(config['model-parameters']['val_range'])
train_data = train_data[int(data_len * val_range) + 1:]
val_data = train_data[:int(data_len * val_range)]
train_datagen = DataGenerator(train_data_dir,
train_data,
classes,
n_channels=n_channels,
dim=data_shape,
batch_size=batch_size,
rescale=255)
val_datagen = DataGenerator(train_data_dir,
val_data,
classes,
n_channels=n_channels,
dim=data_shape,
batch_size=batch_size,
rescale=255)
model.compile_model(optimizer=optimizer,
loss=loss,
metrics=metrics,
learning_rate=lr)
history = model.fit_model(train_gen=train_datagen,
val_gen=val_datagen,
steps_per_epoch=steps,
val_steps_per_epoch=steps,
epochs=epochs,
callbacks=callbacks)
