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.
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.
**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!
**Recent update**
**Recent update**
- 2020.10.12 Add Paddle-Lite demo。
- 2020.10.12 Add Paddle-Lite demo。
- 2020.10.10 Add cpp inference demo and improve FAQ tutorial.
- 2020.10.10 Add cpp inference demo and improve FAQ tutorial.
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-[Inception series](#Inception_series)
-[Inception series](#Inception_series)
-[EfficientNet and ResNeXt101_wsl series](#EfficientNet_and_ResNeXt101_wsl_series)
-[EfficientNet and ResNeXt101_wsl series](#EfficientNet_and_ResNeXt101_wsl_series)
-[ResNeSt and RegNet series](#ResNeSt_and_RegNet_series)
-[ResNeSt and RegNet series](#ResNeSt_and_RegNet_series)
- HS-ResNet: arxiv link: [https://arxiv.org/pdf/2010.07621.pdf](https://arxiv.org/pdf/2010.07621.pdf). Code and models are coming soon!