Introduction
SRZoo is a collection of toolkits and models for deep learning-based image super-resolution. It provides various pre-trained state-of-the-art super-resolution models that are ready for use.
Here are the key features of SRZoo:
SRZoo provides official pre-trained models of various super-resolution methods.
With SRZoo, you can easily obtain the super-resolved images from the supported super-resolution methods.
It is possible to employ the super-resolution models in various environments such as GPUs supporting CUDA and web browsers via TensorFlow.js.
It is possible to compare the performance of the super-resolution methods with the same evaluation metrics and the same environment.
You can find our motivation and some detailed description of SRZoo such as performance comparison in the following paper.
J.-H. Choi, J.-H. Kim, J.-S. Lee. SRZoo: an integrated repository for super-resolution using deep learning. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2020 [Paper] [arXiv]
github地址：https://github.com/idearibosome/srzoo?u=1402400261&m=4512148967116203&cu=1968044071