DGCN: Deep Graph Convolutional Network for image denoising.

This repository contains a PyTorch implementation of the paper Deep Graph Convoluitonal Image Denoising.

File Descriptions:

• analyze.py: contains functions for obtaining training curves, test-set performance, etc. given an argument file (i.e. $ python3 analyze.py path/to/args.json)
• args.json: sample arguments file used to interface with model configurations and checkpoints.
• data.py: defines datasets and data-loading functions.
• knn.py: defines functions for peforming K-nearest neighbors with local-masks.
• net.py: defines GCDN network and submodules.
• train.py: used like analyze.py, initializes and fits a model to training data given an arguments file.
• utils.py: defines functions for data pre/post processing, indexing, etc.
• visual.py: visualization tools written with matplotlib package, such as an interactive receptive field viewer.

Further Improvements:

• Faster nearest neighbors computations, perhaps with packages such as FAISS.