Server Start Guide - person-in-hangang/HanRiver GitHub Wiki

Introduction

Server consists of official PyTorch implementation of [1] Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image (ICCV 2019) and [2] Pedestrain Attribute Recognition.

  • Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image (ICCV 2019) contains [3]RootNet part and [4]PoseNet part.

  • RootNet & PoseNet : These are used to estimate person's height & fallen detection

  • Pedestrain Attribute Recognition(PAR) : This is used to estimate person's three most probable features contains [2] Pedestrain Attribute Recognition.

Dependencies

Python 3.6 version with PyCharm is used for development

Start Guide For Socket Programming

  1. Install Python and Python development tool (ex. PyCharm) on your computer

  2. Download project

  3. Download pre-trained RootNet in here, and pre-trained PoseNet in here, then move them to demo folder

  4. Go to mysocket.py in demo folder

  5. Set your port number and path to save and load images

  6. Run mysocket.py

  7. Connect 119 App, Detection camera and Tracking camera then operate them

  8. You can see images received from connected Detection camera and Tracking camera

  9. Then Server will send calculated information to connected 119 App

More details

This project offer pre-trained RootNet and PoseNet model.

If you want to newly train model, Please refer RootNet part and PoseNet part.

Start Guide For pedestrian attribute recognition

  1. Download and prepare the dataset and pretrained model as follow:

PA100K Links

./dataset/pa100k/annotation.mat
./dataset/pa100k_ckpt_max.pth

Reference

[1] : Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image (ICCV 2019), https://arxiv.org/abs/1907.11346

[2] : Pedestrain Attribute Recognition, https://github.com/valencebond/Strong_Baseline_of_Pedestrian_Attribute_Recognition13

[3] : RootNet, https://github.com/mks0601/3DMPPE_ROOTNET_RELEASE

[4] : PoseNet, https://github.com/mks0601/3DMPPE_POSENET_RELEASE