def save_model_to_json(modeljsonfname):
layers = get_feature_layers(backbone_name, 4)
if backbone_type == 'FPN':
model = FPN(input_shape=(None, None, num_channels),
classes=num_mask_channels,
encoder_weights=encoder_weights,
backbone_name=backbone_name,
activation=act_fcn,
encoder_features=layers)
elif backbone_type == 'Unet':
model = Unet(input_shape=(None, None, num_channels),
classes=num_mask_channels,
encoder_weights=encoder_weights,
backbone_name=backbone_name,
activation=act_fcn,
encoder_features=layers)
#model.summary()
# serialize model to JSON
model_json = model.to_json()
with open(modeljsonfname, "w") as json_file:
json_file.write(model_json)
save_name = 'weights/' + args.backbone + '.h5'
callbacks_list = [
ModelCheckpoint(save_name,
monitor='loss',
verbose=1,
save_best_only=True,
mode='min',
save_weights_only=True),
ReduceLROnPlateau(monitor='loss', factor=0.2, patience=2, min_lr=1e-5)
]
model.compile(optimizer=Adam(1e-4),
loss=custom_loss,
metrics=[dice_coef, jaccard_coef, mean_iou])
history = model.fit_generator(generator,
steps_per_epoch=3000,
epochs=10,
verbose=1,
callbacks=callbacks_list)
model_json = model.to_json()
json_file = open('models/' + args.backbone + '.json', 'w')
json_file.write(model_json)
json_file.close()
print('Model saved!')
K.clear_session()
print('Cache cleared')