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
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