cifar_input.py 文件源码

def cifar_tf_preprocess(random_crop=True, random_flip=True, whiten=True):
  image_size = 32
  inp = tf.placeholder(tf.float32, [image_size, image_size, 3])
  image = inp
  # image = tf.cast(inp, tf.float32)
  if random_crop:
    log.info("Apply random cropping")
    image = tf.image.resize_image_with_crop_or_pad(inp, image_size + 4,
                                                   image_size + 4)
    image = tf.random_crop(image, [image_size, image_size, 3])
  if random_flip:
    log.info("Apply random flipping")
    image = tf.image.random_flip_left_right(image)
  # Brightness/saturation/constrast provides small gains .2%~.5% on cifar.
  # image = tf.image.random_brightness(image, max_delta=63. / 255.)
  # image = tf.image.random_saturation(image, lower=0.5, upper=1.5)
  # image = tf.image.random_contrast(image, lower=0.2, upper=1.8)
  if whiten:
    log.info("Apply whitening")
    image = tf.image.per_image_whitening(image)
  return inp, image