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FSRCNN-TensorFlow

TensorFlow implementation of the Fast Super-Resolution Convolutional Neural Network (FSRCNN). This implements two models: FSRCNN which is more accurate but slower and FSRCNN-s which is faster but less accurate. Based on this project.

Prerequisites

  • Python 2.7
  • TensorFlow
  • Scipy version > 0.18
  • h5py
  • PIL

Usage

For training: python main.py
For testing: python main.py --train False

To use FSCRNN-s instead of FSCRNN: python main.py --fast True

Can specify epochs, learning rate, data directory, etc:
python main.py --epochs 10 --learning_rate 0.0001 --data_dir Train
Check main.py for all the possible flags

Also includes script expand_data.py which scales and rotates all the images in the specified training set to expand it

Result


Original butterfly image:
![orig](https://github.com/drakelevy/FSRCNN-Tensorflow/blob/master/result/original.png?raw=true)
Bicubic interpolated image:
![bicubic](https://github.com/drakelevy/FSRCNN-Tensorflow/blob/master/result/bicubic.png?raw=true)
Super-resolved image:
![srcnn](https://github.com/drakelevy/FSRCNN-Tensorflow/blob/master/result/fsrcnn.png?raw=true)

References

S
Description
An implementation of the Fast Super-Resolution Convolutional Neural Network in TensorFlow
Readme GPL-3.0
48 MiB
Languages
Python 100%