def imageSummary(opt, image, tag, H, W):
blockSize = opt.visBlockSize
imageOne = tf.batch_to_space(image[:blockSize**2],
crops=[[0, 0], [0, 0]],
block_size=blockSize)
imagePermute = tf.reshape(imageOne, [H, blockSize, W, blockSize, -1])
imageTransp = tf.transpose(imagePermute, [1, 0, 3, 2, 4])
imageBlocks = tf.reshape(imageTransp,
[1, H * blockSize, W * blockSize, -1])
summary = tf.summary.image(tag, imageBlocks)
return summary
def upscale(images, scale):
"""Box upscaling (also called nearest neighbors) of images.
Args:
images: A 4D `Tensor` in NHWC format.
scale: A positive integer scale.
Returns:
A 4D `Tensor` of `images` up scaled by a factor `scale`.
Raises:
ValueError: If `scale` is not a positive integer.
"""
scale = _get_validated_scale(scale)
if scale == 1:
return images
return tf.batch_to_space(tf.tile(images, [scale**2, 1, 1, 1]),
crops=[[0, 0], [0, 0]],
block_size=scale)