jeromeyoon / tensorflow-vdsr

A tensorflow implementation of "Accurate Image Super-Resolution Using Very Deep Convolutional Networks", CVPR 16'

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tensorflow-vdsr

Overview

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.

Files

  • 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

How To Use

Training

# if start from scratch
python VDSR.py
# if start with a checkpoint
python VDSR.py --model_path ./checkpoints/CHECKPOINT_NAME.ckpt

Testing

# this will test all the checkpoint in ./checkpoint directory.
# and save the results in ./psnr directory
python TEST.py

Plot Result

# plot the psnr result stored in ./psnr directory
python PLOT.py

Result

Remarks

  • 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.

About

A tensorflow implementation of "Accurate Image Super-Resolution Using Very Deep Convolutional Networks", CVPR 16'


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