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PaddleClas is a toolset for image classification tasks prepared for the industry and academia. It helps users train better computer vision models and apply them in real scenarios.
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**Note**: Baidu proposed a new image classification network structure **`HS-ResNet`**, which reaches 81.3% on ImageNet-1k dataset, while its `params` is almost same as `ResNet50`.The arxiv link is here: [HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network](https://arxiv.org/pdf/2010.07621.pdf). The model structure and the pretrained weights are coming soon!
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**Recent update**
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- 2020.09.17 Add `Res2Net50_vd_26w_4s_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 83.1%. Add `Res2Net101_vd_26w_4s_ssld` pretrained model, whose Top-1 Acc on ImageNet-1k dataset reaches 83.9%.
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- 2020.10.12 Add Paddle-Lite demo。
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- [Inception series](#Inception_series)
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- [EfficientNet and ResNeXt101_wsl series](#EfficientNet_and_ResNeXt101_wsl_series)
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- [ResNeSt and RegNet series](#ResNeSt_and_RegNet_series)
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- HS-ResNet: arxiv link: [https://arxiv.org/pdf/2010.07621.pdf](https://arxiv.org/pdf/2010.07621.pdf). Code and models are coming soon!
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- Model training/evaluation
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- [Data preparation](./docs/en/tutorials/data_en.md)
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- [Model training and finetuning](./docs/en/tutorials/getting_started_en.md)
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- [Inception系列](#Inception系列)
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- [EfficientNet与ResNeXt101_wsl系列](#EfficientNet与ResNeXt101_wsl系列)
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- [ResNeSt与RegNet系列](#ResNeSt与RegNet系列)
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- HS-ResNet: arxiv文章链接: [https://arxiv.org/pdf/2010.07621.pdf](https://arxiv.org/pdf/2010.07621.pdf)。 代码和预训练模型即将开源,敬请期待。
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- 模型训练/评估
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- [数据准备](./docs/zh_CN/tutorials/data.md)
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- [模型训练与微调](./docs/zh_CN/tutorials/getting_started.md)
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