2017-03-01 17:16:44 -08:00
2017-03-01 17:16:44 -08:00
2017-03-01 17:16:44 -08:00
2017-03-01 17:16:44 -08:00
2017-03-01 17:16:44 -08:00

FSRCNN-TensorFlow

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

Prerequisites

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

Usage

For training: python main.py
Can specify epochs, learning rate, data directory, etc: python main.py --epochs 10 --learning_rate 0.0001 --data_dir Train
For testing: python main.py --is_train False

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

Includes script expand_data.py which scales and rotates all the images in your training set to expand it: python expand_data.py Train

Result



Original butterfly image: orig
Bicubic interpolated image: bicubic
Super-resolved image: srcnn

References

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