import cv2
import numpy as np
from models import base_server
from configs import configs

# Read example image
test_img = cv2.imread(configs.test_img_fp)
test_img = cv2.resize(test_img, configs.face_describer_tensor_shape)

# Define input tensors feed to session graph
#dropout_rate = 0.5
input_data = np.array([np.expand_dims(test_img, axis=0)])
print(input_data.shape)
# Define a Base Server
srv = base_server.BaseServer(model_fp=configs.face_describer_model_fp,
                             input_tensor_names=configs.face_describer_input_tensor_names,
                             output_tensor_names=configs.face_describer_output_tensor_names,
                             device=configs.face_describer_device)
# Run prediction
prediction = srv.inference(data=input_data)

# Print results
print('512-D Features are \n{}'.format(prediction))
