jfzhang95/pytorch-deeplab-xception
A PyTorch implementation of DeepLab v3+ semantic segmentation supporting ResNet, MobileNet, Xception and DRN backbones.
Not currently ranked — collecting fresh signals.
star history
This repository provides a PyTorch implementation of the DeepLab v3+ architecture for semantic image segmentation. It supports multiple backbone networks including Modified Aligned Xception, ResNet, MobileNet, and DRN. The model can be trained and evaluated on standard computer vision datasets such as Pascal VOC 2012, SBD, Cityscapes, and COCO. Multi-GPU training is supported.
Frequently asked
- What is jfzhang95/pytorch-deeplab-xception?
- A PyTorch implementation of DeepLab v3+ semantic segmentation supporting ResNet, MobileNet, Xception and DRN backbones.
- Is pytorch-deeplab-xception open source?
- Yes — jfzhang95/pytorch-deeplab-xception is open source, released under the MIT license.
- What language is pytorch-deeplab-xception written in?
- jfzhang95/pytorch-deeplab-xception is primarily written in Python.
- How popular is pytorch-deeplab-xception?
- jfzhang95/pytorch-deeplab-xception has 3k stars on GitHub.
- Where can I find pytorch-deeplab-xception?
- jfzhang95/pytorch-deeplab-xception is on GitHub at https://github.com/jfzhang95/pytorch-deeplab-xception.