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简体中文 | English
PaddleClas is an image recognition toolset for industry and academia, helping users train better computer vision models and apply them in real scenarios.
Recent updates
A practical image recognition system consist of detection, feature learning and retrieval modules, widely applicable to all types of image recognition tasks.
Four sample solutions are provided, including product recognition, vehicle recognition, logo recognition and animation character recognition.
Rich library of pre-trained models: Provide a total of 164 ImageNet pre-trained models in 35 series, among which 6 selected series of models support fast structural modification.
Comprehensive and easy-to-use feature learning components: 12 metric learning methods are integrated and can be combined and switched at will through configuration files.
SSLD knowledge distillation: The 14 classification pre-training models generally improved their accuracy by more than 3%; among them, the ResNet50_vd model achieved a Top-1 accuracy of 84.0% on the Image-Net-1k dataset and the Res2Net200_vd pre-training model achieved a Top-1 accuracy of 85.1%.
Data augmentation: Provide 8 data augmentation algorithms such as AutoAugment, Cutout, Cutmix, etc. with detailed introduction, code replication and evaluation of effectiveness in a unified experimental environment.
Quick experience of image recognition:Link
Image recognition can be divided into three steps:
For a new unknown category, there is no need to retrain the model, just prepare images of new category, extract features and update retrieval database and the category can be recognised.
PaddleClas is released under the Apache 2.0 license Apache 2.0 license
Contributions are highly welcomed and we would really appreciate your feedback!!
A treasure chest for visual classification and recognition powered by PaddlePaddle
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Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》