pix2pix_transform.py

def transform(image, scale):
        r = image
        if a.flip:
            r = tf.image.random_flip_left_right(r, seed=seed)

        # area produces a nice downscaling, but does nearest neighbor for upscaling
        # assume we're going to be doing downscaling here
        
        r = tf.image.resize_images(r, [scale[0], scale[0]], method=tf.image.ResizeMethod.AREA)

        offset = tf.cast(tf.floor(tf.random_uniform([2], 0, tf.cast(scale[0], dtype=tf.float32) - CROP_SIZE + 1, seed=seed)), dtype=tf.int32)
        if a.scale_size > CROP_SIZE:
            r = tf.image.crop_to_bounding_box(r, offset[0], offset[1], CROP_SIZE, CROP_SIZE)
        elif a.scale_size < CROP_SIZE:
            raise Exception("scale size cannot be less than crop size")
        return r
    
    scale = tf.random_uniform([1], minval=286, maxval=300, dtype=tf.int32)
    with tf.name_scope("input_images"):
        input_images = transform(inputs, scale)

    with tf.name_scope("target_images"):
        target_images = transform(targets, scale)