«ZCls» is a classification model training/inferring framework
A more faster training framework is under building: ZCls2
Supported Recognizers:
Refer to roadmap for details
In the fields of object detection/object segmentation/action recognition, there have been many training frameworks with high integration and perfect process, such as facebookresearch/detectron2, open-mmlab/mmaction2 ...
Object classification is the most developed and theoretically basic field in deeplearning. Referring to the existing training framework, a training/inferring framework based on object classification model is implemented. I hope ZCls can bring you a better realization.
See INSTALL
How to train, see Get Started with ZCls
Use builtin datasets, see Use Builtin Datasets
Use custom datasets, see Use Custom Datasets
Use pretrained model, see Use Pretrained Model
- zhujian - Initial work - zjykzj
@misc{ding2021diverse,
title={Diverse Branch Block: Building a Convolution as an Inception-like Unit},
author={Xiaohan Ding and Xiangyu Zhang and Jungong Han and Guiguang Ding},
year={2021},
eprint={2103.13425},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{ding2021repvgg,
title={RepVGG: Making VGG-style ConvNets Great Again},
author={Xiaohan Ding and Xiangyu Zhang and Ningning Ma and Jungong Han and Guiguang Ding and Jian Sun},
year={2021},
eprint={2101.03697},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{fan2020pyslowfast,
author = {Haoqi Fan and Yanghao Li and Bo Xiong and Wan-Yen Lo and
Christoph Feichtenhofer},
title = {PySlowFast},
howpublished = {\url{https://github.com/facebookresearch/slowfast}},
year = {2020}
}
@misc{zhang2020resnest,
title={ResNeSt: Split-Attention Networks},
author={Hang Zhang and Chongruo Wu and Zhongyue Zhang and Yi Zhu and Haibin Lin and Zhi Zhang and Yue Sun and Tong He and Jonas Mueller and R. Manmatha and Mu Li and Alexander Smola},
year={2020},
eprint={2004.08955},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{han2020ghostnet,
title={GhostNet: More Features from Cheap Operations},
author={Kai Han and Yunhe Wang and Qi Tian and Jianyuan Guo and Chunjing Xu and Chang Xu},
year={2020},
eprint={1911.11907},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
For more thanks, check THANKS
Anyone's participation is welcome! Open an issue or submit PRs.
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Apache License 2.0 © 2020 zjykzj