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[Fix] Fix MMHuman3D description and BiSeNetV2 FP16 hyperlink (#1111) 

* fix mmhuman3d readme

* fix mmhuman3d readme
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MengzhangLI 2021-12-07 15:51:18 +08:00 committed by GitHub
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README.md
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@ -169,4 +169,4 @@ and develop their own new semantic segmentation methods.
- [MIM](https://github.com/open-mmlab/mim): MIM Installs OpenMMLab Packages.
- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.
- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab few shot learning toolbox and benchmark.
- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab Human Pose and Shape Estimation Toolbox and Benchmark.
- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark.

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docs/model_zoo.md
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@ -129,7 +129,7 @@ Please refer to [CGNet](https://github.com/open-mmlab/mmsegmentation/blob/master
### Mixed Precision (FP16) Training
Please refer [Mixed Precision (FP16) Training] on BiSeNetV2 (https://github.com/open-mmlab/mmsegmentation/blob/master/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py) for details.
Please refer [Mixed Precision (FP16) Training on BiSeNetV2](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py) for details.
### U-Net

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docs_zh-CN/model_zoo.md
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@ -119,7 +119,7 @@
### Mixed Precision (FP16) Training
请参考 [Mixed Precision (FP16) Training] 在 BiSeNetV2 训练的样例 (https://github.com/open-mmlab/mmsegmentation/blob/master/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py) for details.
请参考 [Mixed Precision (FP16) Training 在 BiSeNetV2 训练的样例](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py) for details.
## 速度标定