def save(self, file_path=FILE_PATH):
file_dir = os.path.dirname(file_path)
if not os.path.exists(file_dir):
os.makedirs(file_dir)
self.model.save(file_path)
print('Model Saved.')
def load(self, file_path=FILE_PATH):
self.model = load_model(file_path)
print('Model Loaded.')
def predict(self, predict_image):
image = resize_with_pad(predict_image)
image = image.astype('float32')
image /= 255
result = self.model.predict(np.array([image]))[0]
whois = 0 if (result[0] > result[1]) else 1
return whois
if __name__ == '__main__':
model = Model()
model.build_model()
model.train(nb_epoch=model.TrainEpoch)
model.save()
