This is a Tensorflow implementation for "Accurate Image Super-Resolution Using Very Deep Convolutional Networks", CVPR 16'.
- The author's project page
- To download the required data for training/testing, please refer to the README.md at data directory.
- VDSR.py : main training file.
- MODEL.py : model definition.
- MODEL_FACTORIZED.py : model definition for Factorized CNN. (not recommended to use. for record purpose only)
- PSNR.py : define how to calculate PSNR in python
- TEST.py : test all the saved checkpoints
- PLOT.py : plot the test result from TEST.py
# if start from scratch
python VDSR.py
# if start with a checkpoint
python VDSR.py --model_path ./checkpoints/CHECKPOINT_NAME.ckpt
# this will test all the checkpoint in ./checkpoint directory.
# and save the results in ./psnr directory
python TEST.py
# plot the psnr result stored in ./psnr directory
python PLOT.py
- The training is further accelerated with asynchronous data fetch.
- Tried to accelerate the network with the idea from Factorized CNN. It is possible to implement with
tf.nn.depthwise_conv2d
and 1x1 convolution, but not so effective.