@@ -8,6 +8,8 @@ PaddleClas is an image recognition toolset for industry and academia, helping us
**Recent updates**
- 2021.09.08 Add LCNet series model developed by PaddleClas, these models show strong competitiveness on Intel CPUs. The metrics and pretrained model can be downloaded [here](docs/en/ImageNet_models_en.md)
- 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 30 pretrained models of LeViT, Twins, TNT, DLA, HarDNet, and RedNet, and the accuracy is roughly the same as that of the paper.
* Note: `Reference Top-1 Acc` means accuracy of pretrained models which are trained on ImageNet1k dataset.
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### LCNet_series
Accuracy and inference time metrics of LCNet series models are shown as follows. More detailed information can be refered to [LCNet series tutorial](../en/models/LCNet_en.md).
The LCNet series is a network that has excellent performance on Intel-CPU proposed by the Baidu PaddleCV team. The author summarizes some methods that can improve the accuracy of the model on Intel-CPU but hardly increase the inference time. The author combines these methods into a new network, namely LCNet. Compared with other lightweight networks, LCNet can achieve higher accuracy with the same inference time. LCNet has shown strong competitiveness in image classification, object detection, and semantic segmentation.
