PyTorch implementation for Semantic Segmentation, include FCN, U-Net, SegNet, GCN, PSPNet, Deeplabv3, Deeplabv3+, Mask R-CNN, DUC, GoogleNet, and more dataset
This repository contains some models for semantic segmentation and the pipeline of training and testing models, implemented in PyTorch
*models*
directory and set the path of pretrained models in *config.py*
*datasets*
directory and do following the README
I'm going to implement The Image Segmentation Paper Top10 Net in PyTorch firstly.
Use this bibtex to cite this repository:
@misc{PyTorch for Semantic Segmentation in Action,
title={Some Implementation of Semantic Segmentation in PyTorch},
author={Charmve},
year={2020.10},
publisher={Github},
journal={GitHub repository},
howpublished={\url{https://github.com/Charmve/Semantic-Segmentation-PyTorch}},
}