如何理解Imagenet预处理的TensorFlow源代码

import tensorflow as tf
import tensorflow.contrib.slim as slim
from tensorflow.contrib.slim import preprocessing

input_image = tf.placeholder(tf.uint8, shape=(None, None, 3))

image = tf.image.convert_image_dtype(input_image, dtype=tf.float32)

image = preprocessing.resize_image(image, desired_size)

image = tf.subtract(image, 0.5)
image = tf.multiply(image, 2.0)

image = preprocessing.random_flip_left_right(image)
image = preprocessing.random_crop(image, crop_size)

image = preprocessing.apply_with_random_selector(
    image,
    lambda x, method: preprocessing.distort_color(x, method),
    num_cases=4)

image = tf.expand_dims(image, 0)
image = tf.image.resize_bilinear(image, [input_height, input_width], align_corners=False)
image = tf.squeeze(image, [0])