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add lite-hrnet_256x192 to keypoint model_zoo (#3907)

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README_cn.md
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...@@ -237,6 +237,7 @@ PaddleDetection模块化地实现了多种主流目标检测算法，提供了 ...@@ -237,6 +237,7 @@ PaddleDetection模块化地实现了多种主流目标检测算法，提供了
- [关键点检测](configs/keypoint) - [关键点检测](configs/keypoint)
- HigherHRNet - HigherHRNet
- HRNet - HRNet
- LiteHRNet
- [多目标跟踪](configs/mot/README_cn.md) - [多目标跟踪](configs/mot/README_cn.md)
- [DeepSORT](configs/mot/deepsort/README_cn.md) - [DeepSORT](configs/mot/deepsort/README_cn.md)
- [JDE](configs/mot/jde/README_cn.md) - [JDE](configs/mot/jde/README_cn.md)
......
README_en.md
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...@@ -251,6 +251,7 @@ The relationship between COCO mAP and FPS on Tesla V100 of representative models ...@@ -251,6 +251,7 @@ The relationship between COCO mAP and FPS on Tesla V100 of representative models
- [Keypoint detection](configs/keypoint) - [Keypoint detection](configs/keypoint)
- HigherHRNet - HigherHRNet
- HRNet - HRNet
- LiteHRNet
- [Multi-Object Tracking](configs/mot/README.md) - [Multi-Object Tracking](configs/mot/README.md)
- [DeepSORT](configs/mot/deepsort/README.md) - [DeepSORT](configs/mot/deepsort/README.md)
- [JDE](configs/mot/jde/README.md) - [JDE](configs/mot/jde/README.md)
......
configs/keypoint/README.md
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...@@ -14,21 +14,25 @@ ...@@ -14,21 +14,25 @@
#### Model Zoo #### Model Zoo
COCO数据集 COCO数据集
| 模型 | 输入尺寸 | 通道数 | AP(coco val) | 模型下载 | 配置文件 | | 模型 | 输入尺寸 | AP(coco val) | 模型下载 | 配置文件 |
| :---------------- | -------- | ------ | :----------: | :----------------------------------------------------------: | ----------------------------------------------------------- | | :---------------- | -------- | :----------: | :----------------------------------------------------------: | ----------------------------------------------------------- |
| HigherHRNet | 512 | 32 | 67.1 | [higherhrnet_hrnet_w32_512.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/higherhrnet_hrnet_w32_512.pdparams) | [config](./higherhrnet/higherhrnet_hrnet_w32_512.yml) | | HigherHRNet-w32 | 512 | 67.1 | [higherhrnet_hrnet_w32_512.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/higherhrnet_hrnet_w32_512.pdparams) | [config](./higherhrnet/higherhrnet_hrnet_w32_512.yml) |
| HigherHRNet | 640 | 32 | 68.3 | [higherhrnet_hrnet_w32_640.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/higherhrnet_hrnet_w32_640.pdparams) | [config](./higherhrnet/higherhrnet_hrnet_w32_640.yml) | | HigherHRNet-w32 | 640 | 68.3 | [higherhrnet_hrnet_w32_640.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/higherhrnet_hrnet_w32_640.pdparams) | [config](./higherhrnet/higherhrnet_hrnet_w32_640.yml) |
| HigherHRNet+SWAHR | 512 | 32 | 68.9 | [higherhrnet_hrnet_w32_512_swahr.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/higherhrnet_hrnet_w32_512_swahr.pdparams) | [config](./higherhrnet/higherhrnet_hrnet_w32_512_swahr.yml) | | HigherHRNet-w32+SWAHR | 512 | 68.9 | [higherhrnet_hrnet_w32_512_swahr.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/higherhrnet_hrnet_w32_512_swahr.pdparams) | [config](./higherhrnet/higherhrnet_hrnet_w32_512_swahr.yml) |
| HRNet | 256x192 | 32 | 76.9 | [hrnet_w32_256x192.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_256x192.pdparams) | [config](./hrnet/hrnet_w32_256x192.yml) | | HRNet-w32 | 256x192 | 76.9 | [hrnet_w32_256x192.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_256x192.pdparams) | [config](./hrnet/hrnet_w32_256x192.yml) |
| HRNet | 384x288 | 32 | 77.8 | [hrnet_w32_384x288.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_384x288.pdparams) | [config](./hrnet/hrnet_w32_384x288.yml) | | HRNet-w32 | 384x288 | 77.8 | [hrnet_w32_384x288.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_384x288.pdparams) | [config](./hrnet/hrnet_w32_384x288.yml) |
| HRNet+DarkPose | 256x192 | 32 | 78.0 | [dark_hrnet_w32_256x192.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/dark_hrnet_w32_256x192.pdparams) | [config](./hrnet/dark_hrnet_w32_256x192.yml) | | HRNet-w32+DarkPose | 256x192 | 78.0 | [dark_hrnet_w32_256x192.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/dark_hrnet_w32_256x192.pdparams) | [config](./hrnet/dark_hrnet_w32_256x192.yml) |
| HRNet+DarkPose | 384x288 | 32 | 78.3 | [dark_hrnet_w32_384x288.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/dark_hrnet_w32_384x288.pdparams) | [config](./hrnet/dark_hrnet_w32_384x288.yml) | | HRNet-w32+DarkPose | 384x288 | 78.3 | [dark_hrnet_w32_384x288.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/dark_hrnet_w32_384x288.pdparams) | [config](./hrnet/dark_hrnet_w32_384x288.yml) |
| LiteHRNet-18 | 256x192 | 66.5 | [lite_hrnet_18_256x192_coco.pdparams](https://bj.bcebos.com/v1/paddledet/models/keypoint/lite_hrnet_18_256x192_coco.pdparams) | [config](./lite_hrnet/lite_hrnet_18_256x192_coco.yml) |
| LiteHRNet-30 | 256x192 | 69.4 | [lite_hrnet_30_256x192_coco.pdparams](https://bj.bcebos.com/v1/paddledet/models/keypoint/lite_hrnet_30_256x192_coco.pdparams) | [config](./lite_hrnet/lite_hrnet_30_256x192_coco.yml) |
备注： Top-Down模型测试AP结果基于GroundTruth标注框 备注： Top-Down模型测试AP结果基于GroundTruth标注框
MPII数据集 MPII数据集
| 模型 | 输入尺寸 | 通道数 | PCKh(Mean) | PCKh(Mean@0.1) | 模型下载 | 配置文件 | | 模型 | 输入尺寸 | PCKh(Mean) | PCKh(Mean@0.1) | 模型下载 | 配置文件 |
| :---- | -------- | ------ | :--------: | :------------: | :----------------------------------------------------------: | -------------------------------------------- | | :---- | -------- | :--------: | :------------: | :----------------------------------------------------------: | -------------------------------------------- |
| HRNet | 256x256 | 32 | 90.6 | 38.5 | [hrnet_w32_256x256_mpii.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_256x256_mpii.pdparams) | [config](./hrnet/hrnet_w32_256x256_mpii.yml) | | HRNet-w32 | 256x256 | 90.6 | 38.5 | [hrnet_w32_256x256_mpii.pdparams](https://paddledet.bj.bcebos.com/models/keypoint/hrnet_w32_256x256_mpii.pdparams) | [config](./hrnet/hrnet_w32_256x256_mpii.yml) |
## 快速开始 ## 快速开始
...@@ -146,4 +150,11 @@ python deploy/python/mot_keypoint_unite_infer.py --mot_model_dir=output_inferenc ...@@ -146,4 +150,11 @@ python deploy/python/mot_keypoint_unite_infer.py --mot_model_dir=output_inferenc
month = {June}, month = {June},
year = {2020} year = {2020}
} }
@inproceedings{Yulitehrnet21,
title={Lite-HRNet: A Lightweight High-Resolution Network},
author={Yu, Changqian and Xiao, Bin and Gao, Changxin and Yuan, Lu and Zhang, Lei and Sang, Nong and Wang, Jingdong},
booktitle={CVPR},
year={2021}
}
``` ```
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