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README.md

English | 简体中文

PP-PicoDet + PP-TinyPose Co-deployment (Pipeline)

Model Description

Now FastDeploy supports the deployment of the following models

Prepare PP-TinyPose Deployment Model

Export the PP-TinyPose and PP-PicoDet models. Please refer to Model Export

Attention: The exported inference model contains three files, including model.pdmodel、model.pdiparams and infer_cfg.yml. FastDeploy will get the pre-processing information for inference from yaml files.

Download Pre-trained Model

For developers' testing, part of the PP-PicoDet + PP-TinyPose（Pipeline）exported models are provided below. Developers can download and use them directly.

Application Scenario Model Parameter File Size AP(Service Data set) AP(COCO Val Single/Multi-person) Single/Multi-person Inference Time (FP32) Single/Multi-person Inference Time（FP16)
Single-person Model Configuration PicoDet-S-Lcnet-Pedestrian-192x192 + PP-TinyPose-128x96 4.6MB + 5.3MB 86.2% 52.8% 12.90ms 9.61ms
Multi-person Model Configuration PicoDet-S-Lcnet-Pedestrian-320x320 + PP-TinyPose-256x192 4.6M + 5.3MB 85.7% 49.9% 47.63ms 34.62ms

Note

  • The accuracy of the keypoint detection model is based on the detection frame obtained by the pedestrian detection model.
  • The flip operation is removed from the accuracy test with the detection confidence threshold of 0.5.
  • The speed test environment is qualcomm snapdragon 865 with 4-thread inference under arm8.
  • The Pipeline speed covers the preprocessing, inference, and post-processing of the model.
  • In the accuracy test, images with more than 6 people (excluding 6 people) were removed from the multi-person data for fair comparison.

For more information: refer to PP-TinyPose official document

Detailed Deployment Tutorials