test.py 文件源码

def preprocessing(input_img_path,input_height,input_width):

  input_image = cv2.imread(input_img_path)

  # Resize the image and convert to array of float32
  resized_image = cv2.resize(input_image,(input_height, input_width), interpolation = cv2.INTER_CUBIC)
  image_data = np.array(resized_image, dtype='f')

  # Normalization [0,255] -> [0,1]
  image_data /= 255.

  # BGR -> RGB? The results do not change much
  # copied_image = image_data
  #image_data[:,:,2] = copied_image[:,:,0]
  #image_data[:,:,0] = copied_image[:,:,2]

  # Add the dimension relative to the batch size needed for the input placeholder "x"
  image_array = np.expand_dims(image_data, 0)  # Add batch dimension

  return image_array