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Drake Levy
2017-03-01 17:25:03 -08:00
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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](http://mmlab.ie.cuhk.edu.hk/projects/FSRCNN.html).
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](http://mmlab.ie.cuhk.edu.hk/projects/FSRCNN.html).
## Prerequisites
* Python 2.7
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## Usage
For training: `python main.py`
<br>
Can specify epochs, learning rate, data directory, etc: `python main.py --epochs 10 --learning_rate 0.0001 --data_dir Train`
Can specify epochs, learning rate, data directory, etc:
<br>
`python main.py --epochs 10 --learning_rate 0.0001 --data_dir Train`
<br>
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`
Includes script `expand_data.py` which scales and rotates all the images in your training set to expand it:
<br>
`python expand_data.py Train`
## Result