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FGVCLib is an open-source and well documented library for Fine-grained Visual Classification.
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PRIS-CV/Fine-grained-Visual-Analysis-Library
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FGVCLib is an open-source and well documented library for Fine-grained Visual Classification. It is based on Pytorch with performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.The branch works withtorch 1.12.1,torchvision 0.13.1.
For more details and the tutorials about the FGVCLib, seeFGVCLib
Major features
Modular Design
We decompose the detection framework into different components and one can easily construct a customized object detection framework by combining different modules.
State of the artWe implement state-of-the-art methods by the FGVCLib,PMG,PMG_V2,MCL,API-Net,CAL,TransFG,PIM.
Please refer toInstallation for installation instructions.
Please seeget_started.md for the basic usage of FGVCLib. We provide the tutorials for:
| Fine-grained Visual Classification | Other |
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| Backbones | Encoders | Heads | Necks | Sotas |
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Thanks for your attention! If you have any suggestion or question, you can leave a message here or contact us directly:
Based on the fgvclib, we have developed an FGVC WeChat applet for fine-grained visual classification in practice, which can be accessed by searching "细粒度图像分类" in WeChat, and there is a demo:https://reurl.cc/rRZE7O.
If you find this library useful in your research, please consider citing:
@misc{Chang2023, author = {Dongliang, Chang and Ruoyi, Du and Xinran, Wang and Yuqi, Yang and Yi-Zhe, Song and Zhanyu, Ma}, title = {Fine-grained Visual Analysis Library}, year = {2023}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/PRIS-CV/Fine-grained-Visual-Analysis-Library}}}About
FGVCLib is an open-source and well documented library for Fine-grained Visual Classification.
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