Tensorflow implementation of the paper "Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution"
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README.md

Tensorflow implementation of the paper "Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution" (CVPR 2017)

This is a Tensorflow implementation using TensorLayer. Original paper and implementation using MatConNet can be found on their project webpage.

Environment

The implementation is tested using python 3.6 and cuda 8.0.

Download repository:

$ git clone https://github.com/zjuela/LapSRN-tensorflow.git

Train model

Specify dataset path in config.py file and run:

$ python main.py

The pre-trained model is trained using NTIRE 2017 challenge dataset.

Test

Run with your test image:

$ python main.py -m test -f TESTIMAGE

Results can be find in folder ./samples/