People tracking and counting with Raspberry pi 4 and Intel neural compute stick

People tracking and counting with Raspberry pi 4 and Intel neural compute stick

or Pedestrian Tracker

Hardware

▪ Raspberry pi 4B ( 1GB )
▪ Intel Neural Compute Stick 2
▪ 32GB SD card

Software

▪ Raspbien 10 ( buster )

▪ OpenVINO toolkit 2019 R1

▪ OpenCV 4.0.0

▪ Code C/C++

▪ Model : Person-detection-retail-0013

▪ Model : Person-reidentification-0031

▪ Video MP4 768 x 432 12 fps

 

What is Intel Neural Compute Stick and OpenVINO?

https://raspberrypi4u.blogspot.com/2019/04/raspberry-pi-openvino-intel-movidius.html

Pedestrian Tracker C++ Demo

This demo showcases Pedestrian Tracking scenario: it reads frames from an input video sequence, detects pedestrians in the frames, and builds trajectories of movement of the pedestrians in a frame-by-frame manner. You can use a set of the following pre-trained models with the demo:

• person-detection-retail-0013, which is the primary detection network for finding pedestrians
• person-reidentification-retail-0031, which is the network that is executed on top of the results from inference of the first network and makes reidentification of the pedestrians

Source Code

https://docs.openvinotoolkit.org/latest/_demos_pedestrian_tracker_demo_README.html

Reference

Install the Intel® Distribution of OpenVINO™ Toolkit for Raspbian* OS

https://software.intel.com/en-us/articles/OpenVINO-Install-RaspberryPI

Pretrained Models

https://software.intel.com/en-us/openvino-toolkit/documentation/pretrained-models

Inference Engine Samples 

http://docs.openvinotoolkit.org/latest/_docs_IE_DG_Samples_Overview.html

OpenVINO, OpenCV, and Movidius NCS on the Raspberry Pi

https://www.pyimagesearch.com/2019/04/08/openvino-opencv-and-movidius-ncs-on-the-raspberry-pi/