ContextLab: A Toolbox for Context Feature Augmentation developed with PyTorch
The master branch works with PyTorch 1.1 or higher
ContextLab is an open source context feature augmentation toolbox based on PyTorch. It is a part of the Open-PLUS project developed by ShanghaiTech PLUS Lab
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Modular Design
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High Efficiency
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State-of-the-art Performance
We have implemented several context augmentation algorithms in PyTorch with comparable performance.
This project is released under the MIT License
V0.2.0 (27/09/2019)
- Support for CCNet, TreeFilter and EMANet
v0.1.0 (26/07/2019)
- Start the project
| Method | Block-wise | Stage-wise | Paper |
|---|---|---|---|
| Non-local Network | ✗ | ✓ | CVPR 18 |
| Dual-attention | ✗ | ✓ | CVPR 19 |
| GCNet | ✗ | ✓ | Arxiv |
| CCNet | ✓ | ✓ | ICCV 19 |
| LatentGNN | ✗ | ✓ | ICML 19 |
| TreeFilter | ✗ | ✓ | NIPS 19 |
| EMANet | ✗ | ✓ | ICCV 19 |
git clone https://github.com/SHTUPLUS/contextlab.git
cd contextlab/
python setup.py build develop
# GCNet
from contextlab.layers import GlobalContextBlock2d
# Dual-Attention
from contextlab.layers import SelfAttention
# LatentGNN
from contextlab.layers import LatentGNN
# TreeFilter
from contextlab.layers import MinimumSpanningTree, TreeFilter2D
# CCNet
from contextlab.layers import CrissCrossAttention
# EMAttetnion
from contextlab.layers import EMAttentionUnit- Experiments on Segmentation and Detection
- Performance Comparison
We appreciate all contributions to improve ContextLab. Please refer to CONTRIBUTING.md for the contributing guideline.
ContextLab 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.
@misc{contextlab,
title = {{ContextLab}: A Toolbox for Context Feature Augmentation},
author = {Songyang Zhang},
year={2019}
}
email: sy.zhangbuaa@gmail.com