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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 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:

Bicubic interpolated image:

Super-resolved image:

References
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