Returns a Keras layer to do subpixel convolution.
NOTE: Tensorflow backend only. Uses tf.depth_to_space
- Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network. (Shi et Al.) [https://arxiv.org/abs/1609.05158]
(Please see requirements.txt for latest update)
Keras==2.0.2
tensorflow==1.1.0
# Subpixel Conv will upsample from (h, w, c) to (h/r, w/r, c/r^2)
scale = 4
inputs = Input(shape=input_shape)
x = Convolution2D(channels * scale ** 2, (3, 3),
activation='relu',
name='conv3x3')(inputs)
out = SubpixelConv2D(input_shape, scale=scale)(x)
model = Model(inputs=inputs, outputs=out)
MIT