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TRACK-INOUT written by Claude Pageau

Tracks Enter, Leave Activity that cross a vert or horiz center line. Runs on Windows or Unix using Web Cam or Raspberry Pi using Web Cam or pi camera module. Uses python, opencv to track motion in real time

YouTube Video https://youtu.be/9et7QpbT5cc

Introduction

This project came about when I decided to update my motion tracking demo and thought it would be a good idea to include something useful. I decided to track entering a leaving Activity when they cross a vertical or horizontal centerline At first it was a simple counter but now it also allows for options to take an image and update a csv file. You can add more features if you are familiar with python programming. See my speed camera project for some ideas https://github.com/pageauc/speed-camera

Prerequisites

Requires Windows, Unix computer with a Web Camera or a Raspberry Pi computer with a Web Camera or RPI Camera Module and an up-to-date Raspbian distro. If you wish to use a web camera that is plugged into a usb port. Set WEBCAM = True in config.py otherwise, WEBCAM = False will use a connected raspberry pi camera module video stream. If running under Windows or a Non RPI unix distro then Web camera will automatically be selected WEBCAM = True

The dependencies and code files can be installed per the inout-install.sh script if you are using Debian or Raspbian, Otherwise select the Github download zip or clone green button on top right of GitHub repo web page here https://github.com/pageauc/track-inout See Quick or Manual install instructions below for further details

Note The device control demo option is designed for a Raspberry Pi computer Only. I wrote this to help a student and decided to leave this code in. I have not fully tested this with servo and LED's. If you try this feature let me know.

Quick Install

Easy Install of track-inout onto Debian or Raspberry Pi Computer.

curl -L https://raw.githubusercontent.com/pageauc/track-inout/master/inout-install.sh | bash

From a computer logged into the RPI via ssh(Putty) session use mouse to highlight command above, right click, copy. Then select ssh(Putty) window, mouse right click, paste. The command should download and execute the github inout-install.sh script and install the files into the track-inout folder. This install can also be done directly on from a console or desktop terminal session and web browser. Note A raspbian/debian apt-get update and upgrade will be performed as part of install so it may take some time if these are not up-to-date

Manual Install

From logged in RPI SSH session or console terminal perform the following.

wget https://raw.githubusercontent.com/pageauc/track-inout/master/inout-install.sh
chmod +x inout-install.sh
./inout-install.sh

How to Run

Default is console only display. Use Nano or text editor to Edit config.py variable WINDOW_ON = True to display the opencv tracking window on GUI desktop. See other variables and descriptions for additional variable customization settings. From SSH session, console or GUI desktop terminal session execute the following commands

cd ~/track-inout
./inout.py

On Windows make sure you have the latest python installed from https://www.python.org/downloads/ To install track-inout, clone or download zip from project github web page https://github.com/pageauc/track-inout use 7zip to unzip file if required. A track-inout folder will be created for the files (extract here).
Run inout.py from IDLE or if python file association exists it can also be run from cmd prompt by double clicking on inout.py. Use a text editor to modify settings in the config.py file per settings comments. To view opencv window(s) on GUI desktop, edit config.py variable WINDOW_ON=True.

Trouble Shooting

Edit the config.py file

cd ~/track-inout
nano config.py

Set variable WINDOW_ON = True so the opencv status windows can display camera motion images and a circle marking x,y coordinates and optionally the opencv threshold window. The circle diameter can be change using CIRCLE_SIZE variable. You can set WINDOW_ON = False if you need to run from SSH terminal session only. If VERBOSE = True (default), then logging information will be displayed without a GUI desktop session.

Credits

Some of this code is based on a YouTube tutorial by Kyle Hounslow using C here https://www.youtube.com/watch?v=X6rPdRZzgjg

Thanks to Adrian Rosebrock jrosebr1 at http://www.pyimagesearch.com for the PiVideoStream Class code available on github at https://github.com/jrosebr1/imutils/blob/master/imutils/video/pivideostream.py

Other motion Tracking Projects

motion-track.py - Motion Track Demo - Basic concept of tracking moving objects

This Demo program detects motion in the field of view and uses opencv to calculate the largest contour above a minimum size and return its x,y coordinate.

speed-camera.py - Object (vehicle) speed camera based on motion tracking

Tracks vehicle speeds or other moving objects in real time and records image and logs data. Now improved using threading for video stream and clipping of area of interest for greater performance.

cam-track.py - Tracks camera x y movements

Uses a clipped search image rectangle to search subsequent video stream images and returns the location. Can be used for tracking camera x y movements for stabilization, robotics, Etc.

hotspot-game.py - A simple motion tracking game

The game play involves using streaming video of body motion to get as many hits as possible inside shrinking boxes that randomly move around the screen. Position the camera so you can see body motions either close or standing. Pretty simple but I think kids would have fun with it and they just might take a look at the code to see how it works, change variables or game logic.

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Have Fun Claude Pageau YouTube Channel https://www.youtube.com/user/pageaucp GitHub Repo https://github.com/pageauc