提交 64f98d64 编写于 作者: Z zhiboniu 提交者: zhiboniu

pphuman doc add reid data; test=document_fix

上级 e366e929
...@@ -44,7 +44,7 @@ PP-Human提供了目标检测、属性识别、行为识别、ReID预训练模 ...@@ -44,7 +44,7 @@ PP-Human提供了目标检测、属性识别、行为识别、ReID预训练模
| 属性识别 | 图片/视频输入 属性识别 | mA: 94.86 | 单人2ms | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/strongbaseline_r50_30e_pa100k.zip) | | 属性识别 | 图片/视频输入 属性识别 | mA: 94.86 | 单人2ms | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/strongbaseline_r50_30e_pa100k.zip) |
| 关键点检测 | 视频输入 行为识别 | AP: 87.1 | 单人2.9ms | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip) | 关键点检测 | 视频输入 行为识别 | AP: 87.1 | 单人2.9ms | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip)
| 行为识别 | 视频输入 行为识别 | 准确率: 96.43 | 单人2.7ms | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/STGCN.zip) | | 行为识别 | 视频输入 行为识别 | 准确率: 96.43 | 单人2.7ms | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/STGCN.zip) |
| ReID | 视频输入 跨镜跟踪 | mAP: 99.7 | - | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip) | | ReID | 视频输入 跨镜跟踪 | mAP: 98.8 | 单人1.5ms | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip) |
下载模型后,解压至`./output_inference`文件夹 下载模型后,解压至`./output_inference`文件夹
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...@@ -42,7 +42,7 @@ To make users have access to models of different scenarios, PP-Human provides pr ...@@ -42,7 +42,7 @@ To make users have access to models of different scenarios, PP-Human provides pr
| Attribute Recognition | Image/Video Input Attribute Recognition | MOTA: 72.0 | 33.1ms | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/strongbaseline_r50_30e_pa100k.zip) | | Attribute Recognition | Image/Video Input Attribute Recognition | MOTA: 72.0 | 33.1ms | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/strongbaseline_r50_30e_pa100k.zip) |
| Keypoint Detection | Video Input Action Recognition | mA: 94.86 | 2ms per person | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip) | Keypoint Detection | Video Input Action Recognition | mA: 94.86 | 2ms per person | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip)
| Behavior Recognition | Video Input Bheavior Recognition | Precision 96.43 | 2.7ms per person | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/STGCN.zip) | | Behavior Recognition | Video Input Bheavior Recognition | Precision 96.43 | 2.7ms per person | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/STGCN.zip) |
| ReID | Multi-Target Multi-Camera Tracking | mAP: 99.7 | - | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip) | | ReID | Multi-Target Multi-Camera Tracking | mAP: 98.8 | 1.5ms per person | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip) |
Then, unzip the downloaded model to the folder `./output_inference`. Then, unzip the downloaded model to the folder `./output_inference`.
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