Templete_utils.py

import tensorflow as tf
import random

class ImageData:

    def __init__(self, batch_size, load_size, channels, augment_flag):
        self.batch_size = batch_size
        self.load_size = load_size
        self.channels = channels
        self.augment_flag = augment_flag

    def image_processing(self, filename):
        x = tf.read_file(filename)
        x_decode = tf.image.decode_jpeg(x, channels=self.channels)
        img = tf.image.resize_images(x_decode, [self.load_size, self.load_size])
        img = tf.cast(img, tf.float32) / 127.5 - 1

        if self.augment_flag :
            augment_size = self.load_size + (30 if self.load_size == 256 else 15)
            p = random.random()
            if p > 0.5:
                img = augmentation(img, augment_size)

        return img


def augmentation(image, augment_size):
    seed = random.randint(0, 2 ** 31 - 1)
    ori_image_shape = tf.shape(image)
    image = tf.image.random_flip_left_right(image, seed=seed)
    image = tf.image.resize_images(image, [augment_size, augment_size])
    image = tf.random_crop(image, ori_image_shape, seed=seed)
    return image