提交 2c609edd 编写于 作者: C cuicheng01

Update LCNet docs

上级 d2adc3cd
......@@ -8,7 +8,7 @@ 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)
- 2021.09.08 Add LCNet series model developed by PaddleClas, these models show strong competitiveness on Intel CPUs. The metrics and pretrained model are available [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.
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......@@ -66,14 +66,14 @@ Accuracy and inference time metrics of LCNet series models are shown as follows.
| Model | Top-1 Acc | Top-5 Acc | Intel-Xeon-Gold-6148 time(ms)<br>bs=1 | FLOPs(M) | Params(M) | Download Address |
|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
| LCNet_x0_25 |0.5186 | 0.7565 | 1.74 | 18 | 1.5 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x0_25_pretrained.pdparams) |
| LCNet_x0_35 |0.5809 | 0.8083 | 1.92 | 29 | 1.6 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x0_35_pretrained.pdparams) |
| LCNet_x0_5 |0.6314 | 0.8466 | 2.05 | 47 | 1.9 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x0_5_pretrained.pdparams) |
| LCNet_x0_75 |0.6818 | 0.8830 | 2.29 | 99 | 2.4 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x0_75_pretrained.pdparams) |
| LCNet_x1_0 |0.7132 | 0.9003 | 2.46 | 161 | 3.0 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x1_0_pretrained.pdparams) |
| LCNet_x1_5 |0.7371 | 0.9153 | 3.19 | 342 | 4.5 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x1_5_pretrained.pdparams) |
| LCNet_x2_0 |0.7518 | 0.9227 | 4.27 | 590 | 6.5 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x2_0_pretrained.pdparams) |
| LCNet_x2_5 |0.7660 | 0.9300 | 5.39 | 906 | 9.0 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x2_5_pretrained.pdparams) |
| LCNet_x0_25 |0.5186 | 0.7565 | 1.74 | 18 | 1.5 | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x0_25_pretrained.pdparams) |
| LCNet_x0_35 |0.5809 | 0.8083 | 1.92 | 29 | 1.6 | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x0_35_pretrained.pdparams) |
| LCNet_x0_5 |0.6314 | 0.8466 | 2.05 | 47 | 1.9 | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x0_5_pretrained.pdparams) |
| LCNet_x0_75 |0.6818 | 0.8830 | 2.29 | 99 | 2.4 | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x0_75_pretrained.pdparams) |
| LCNet_x1_0 |0.7132 | 0.9003 | 2.46 | 161 | 3.0 | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x1_0_pretrained.pdparams) |
| LCNet_x1_5 |0.7371 | 0.9153 | 3.19 | 342 | 4.5 | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x1_5_pretrained.pdparams) |
| LCNet_x2_0 |0.7518 | 0.9227 | 4.27 | 590 | 6.5 | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x2_0_pretrained.pdparams) |
| LCNet_x2_5 |0.7660 | 0.9300 | 5.39 | 906 | 9.0 | [Download link](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/LCNet_x2_5_pretrained.pdparams) |
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