Introduction
The master branch works with PyTorch 1.1 or higher
plusseg is an open source image semantic segmentation toolbox based on PyTorch. It is a part of the plus project developed by ShanghaiTech PLUS Lab
Major Features
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Modular Design
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Multiple Frameworks
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High Efficiency
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State-of-the-art Performance
We have implemented several semantic segmentation algorithms in PyTorch with comparable performance Code will be updated in Oct.
License
This project is released under the MIT License
Updates
v0.1.0 (26/07/2019)
- Start the project
Benchmark and Model Zoo
Supported methods and backbones are shown in the below table Results and models are available in the Model Zoo
| ResNet | ResNeXt | DenseNet | HRNet | |
|---|---|---|---|---|
| FCN | ✓ | ✓ | ☐ | ✓ |
| PSPNet | ✓ | ✓ | ☐ | ✓ |
| DeepLab-V1 | ✓ | ✓ | ☐ | ✓ |
| DeepLab-V2 | ✓ | ✓ | ☐ | ✓ |
| DeepLab-V3 | ✓ | ✓ | ☐ | ✓ |
| DeepLab-V3++ | ✓ | ✓ | ☐ | ✓ |
| PSANet | ✗ | ✗ | ✗ | ✗ |
| EncNet | ✓ | ✓ | ☐ | ✓ |
| DenseASPP | ✓ | ✓ | ☐ | ✓ |
| UNet | ✓ | ✓ | ☐ | ✓ |
| Dilation Net | ✓ | ✓ | ☐ | ✓ |
Installation
Please refer to Install.md for installation and dataset preparation.
Get Started
Please see GETTING_STARTED.md for the basic usage of PLUSSeg.
Contributing
We appreciate all contributions to improve MMDetection. Please refer to CONTRIBUTING.md for the contributing guideline.
Acknowledgement
PLUSSeg is an open source project that is contributed by researchers and engineers from various colledges and companies. We appreciate all the contributors who implement their methods or add new features.
We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new segmentation methods.