SRCNN-Tensorflow

# SRCNN-Tensorflow Tensorflow implementation of Convolutional Neural Networks for super-resolution. The original Matlab and Caffe from official website can be found [here](http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html). ## Prerequisites * Tensorflow * Scipy version > 0.18 ('mode' option from scipy.misc.imread function) * h5py * matplotlib This code requires Tensorflow. Also scipy is used instead of Matlab or OpenCV. Especially, installing OpenCV at Linux is sort of complicated. So, with reproducing this paper, I used scipy instead. For more imformation about scipy, click [here](https://www.scipy.org/). ## Usage For training, `python main.py` <br> For testing, `python main.py --is_train False --stride 21` ## Result After training 15,000 epochs, I got similar super-resolved image to reference paper. Training time takes 12 hours 16 minutes and 1.41 seconds. My desktop performance is Intel I7-6700 CPU, GTX970, and 16GB RAM. Result images are shown below.<br><br> Original butterfly image: <br> Bicubic interpolated image: <br> Super-resolved image:  ## References * [liliumao/Tensorflow-srcnn](https://github.com/liliumao/Tensorflow-srcnn) * - I referred to this repository which is same implementation using Matlab code and Caffe model. <br> * [carpedm20/DCGAN-tensorflow](https://github.com/carpedm20/DCGAN-tensorflow) * - I have followed and learned training process and structure of this repository.