| HRNet-w32 + DarkPose | Top-Down|256x192 | AP: 87.1 (on internal dataset)| 2.9ms per person |[Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.pdparams) |[Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip) | Especially optimized for fall scenarios, the model is applied to [PP-Human](../../deploy/pphuman/README_en.md) |
We also release [PP-TinyPose](./tiny_pose/README_en.md), a real-time keypoint detection model optimized for mobile devices. Welcome to experience.
To make users have access to models of different scenarios, PP-Human provides pre-trained models of object detection, attribute recognition， behavior recognition, and ReID.
| Task | Scenario | Precision | Inference Speed（FPS） | Model Inference and Deployment |
Action Recognition is widely used in the intelligent community/smart city, and security monitoring. PP-Human provides the module of skeleton-based action recognition.
...
...
@@ -12,11 +14,11 @@ used for academic research here. </center>
There are multiple available pretrained models including pedestrian detection/tracking, keypoint detection, and fall detection models. Users can download and use them directly.
Pedestrian detection and tracking is widely used in the intelligent community, industrial inspection, transportation monitoring and so on. PP-Human has the detection and tracking module, which is fundamental to keypoint detection, attribute action recognition, etc. Users enjoy easy access to pretrained models here.
# Multi-Target Multi-Camera Tracking Module of PP-Human
Multi-target multi-camera tracking, or MTMCT, matches the identity of a person in different cameras based on the single-camera tracking. MTMCT is usually applied to the security system and the smart retailing.
