@@ -9,7 +9,7 @@ PaddleClas is an image recognition toolset for industry and academia, helping us
**Recent updates**
- 2021.06.29 Add Swin-transformer series model,Highest top1 acc on ImageNet1k dataset reaches 87.2%, training, evaluation and inference are all supported. Pretrained models can be downloaded [here](docs/en/models/models_intro_en.md).
- 2021.06.16 PaddleClas release/2.2. Add metric learning and vector search modules. Add product recognition, animation character recognition, vehicle recognition and logo recognition. Added 24 pretrained models of LeViT, TNT, DLA, HarDNet, and RedNet, and the accuracy is roughly the same as that of the paper.
- 2021.06.16 PaddleClas release/2.2. Add metric learning and vector search modules. Add product recognition, animation character recognition, vehicle recognition and logo recognition. Added 30 pretrained models of LeViT, Twins, TNT, DLA, HarDNet, and RedNet, and the accuracy is roughly the same as that of the paper.
-[more](./docs/en/update_history_en.md)
## Features
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- 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 150 ImageNet pre-trained models in 33 series, among which 6 selected series of models support fast structural modification.
- 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.
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@@ -51,7 +51,7 @@ Quick experience of image recognition:[Link](./docs/en/tutorials/quick_start_r
-[Introduction to Image Recognition Systems](#Introduction_to_Image_Recognition_Systems)
-[Demo images](#Demo_images)
- Algorithms Introduction
-[Backbone Network and Pre-trained Model Library](./docs/en/ImageNet_models.md)
-[Backbone Network and Pre-trained Model Library](./docs/en/ImageNet_models_en.md)