SRCNN-Tensorflow

Why we included this project

SRCNN is the paper that showed deep convolutional networks could beat bicubic interpolation for image super-resolution, and this repository is a readable TensorFlow port of it. The code runs a low-resolution image through a small convolutional network and outputs a sharper, higher-resolution version. Because it depends only on TensorFlow, SciPy, and h5py, it runs on a plain Linux box without the Matlab or OpenCV setup the original reference implementation needs. The training and testing entry points are simple command-line calls, and the whole thing is compact enough to read end to end, which makes it a good study reference for students or engineers new to computer vision. Treat it as a learning tool and a baseline: it is a research reproduction, not a maintained production library.