A semantic segmentation toolbox based on PyTorch
vedaseg
vedaseg is an open source semantic segmentation toolbox based on PyTorch.
Features
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Modular Design
We decompose the semantic segmentation framework into different components. The flexible and extensible design make it easy to implement a customized semantic segmentation project by combining different modules like building Lego.
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Support of several popular frameworks
The toolbox supports several popular semantic segmentation frameworks out of the box, e.g. DeepLabv3+, DeepLabv3, U-Net, PSPNet, FPN, etc.
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High efficiency
Multi-GPU data parallelism & distributed training.
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Multi-Class/Multi-Label segmentation
We implement multi-class and multi-label segmentation(where a pixel can belong to multiple classes).
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Acceleration and deployment
Models can be accelerated and deployed with TensorRT.
License
This project is released under the