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[Feature] Add Hourglass pose detection quantization evaluation result. (#1066)

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Detail results: https://github.com/Qingrenn/mmdeploy-summer-camp/blob/main/week4/result.md
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docs/en/03-benchmark/quantization.md
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@ -25,3 +25,11 @@ Note:
| [PANet](https://github.com/open-mmlab/mmocr/blob/main/configs/textdet/panet/panet_r18_fpem_ffm_600e_icdar2015.py) | ICDAR2015 | 0.795 | 0.792 @thr=0.9 |
Note: [mmocr](https://github.com/open-mmlab/mmocr) Uses 'shapely' to compute IoU, which results in a slight difference in accuracy
### Pose detection
| model | dataset | fp32 AP | int8 AP |
| :----------------------------------------------------------------------------------------------------------------------------------------------: | :------: | :-----: | :-----: |
| [Hourglass](https://github.com/open-mmlab/mmpose/blob/master/configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/hourglass52_coco_256x256.py) | COCO2017 | 0.726 | 0.713 |
Note: MMPose models are tested with `flip_test` explicitly set to `False` in model configs.

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docs/zh_cn/03-benchmark/quantization.md
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@ -25,3 +25,11 @@
| [PANet](https://github.com/open-mmlab/mmocr/blob/main/configs/textdet/panet/panet_r18_fpem_ffm_600e_icdar2015.py) | ICDAR2015 | 0.795 | 0.792 @thr=0.9 |
备注：[mmocr](https://github.com/open-mmlab/mmocr) 使用 `shapely` 计算 IoU，实现方法会导致轻微的精度差异
### 姿态检测任务
| model | dataset | fp32 AP | int8 AP |
| :----------------------------------------------------------------------------------------------------------------------------------------------: | :------: | :-----: | :-----: |
| [Hourglass](https://github.com/open-mmlab/mmpose/blob/master/configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/hourglass52_coco_256x256.py) | COCO2017 | 0.726 | 0.713 |
备注：测试转换后的模型精度时，对于 mmpose 模型，在模型配置文件中 `flip_test` 需设置为 `False`。