https://github.com/pageauc/track-inout
Windows, Unix, Raspberry Pi program uses opencv and python to track moving objects that enter and leave camera view and cross a vert or horz trigger center line. Can be configured to take an image and log data to a csv file. Includes a standalone web server for viewing image files. At this point it is a demo since it would need more work but the basic operation is functional.
https://github.com/pageauc/track-inout
csv-files curl-install demo enter images leave monitor motion-tracking opencv pi-camera python raspberry-pi tracking unix web-camera webserver windows
Last synced: about 2 months ago
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Windows, Unix, Raspberry Pi program uses opencv and python to track moving objects that enter and leave camera view and cross a vert or horz trigger center line. Can be configured to take an image and log data to a csv file. Includes a standalone web server for viewing image files. At this point it is a demo since it would need more work but the basic operation is functional.
- Host: GitHub
- URL: https://github.com/pageauc/track-inout
- Owner: pageauc
- Created: 2017-08-18T11:57:27.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2020-08-11T22:13:51.000Z (about 5 years ago)
- Last Synced: 2025-04-08T17:12:08.701Z (6 months ago)
- Topics: csv-files, curl-install, demo, enter, images, leave, monitor, motion-tracking, opencv, pi-camera, python, raspberry-pi, tracking, unix, web-camera, webserver, windows
- Language: Python
- Homepage:
- Size: 51.8 KB
- Stars: 11
- Watchers: 2
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
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README
# 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.
* Motion Track Demo YouTube Video http://youtu.be/09JS7twPBsQ
* GitHub Repo https://github.com/pageauc/motion-track
* RPI forum post https://www.raspberrypi.org/forums/viewtopic.php?p=790082#p790082
## 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.
* GitHub Repo https://github.com/pageauc/speed-camera
* YouTube Speed Camera Video https://youtu.be/eRi50BbJUro
* RPI forum post https://www.raspberrypi.org/forums/viewtopic.php?p=1004150#p1004150
## 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.
* GitHub Repo https://github.com/pageauc/rpi-cam-track
* YouTube Cam-Track Video https://www.youtube.com/edit?video_id=yjA3UtwbD80
* Code Walkthrough YouTube Video https://youtu.be/lkh3YbbNdYg
* RPI Forum Post https://www.raspberrypi.org/forums/viewtopic.php?p=1027463#p1027463
## 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.
* GitHub hotspot-game Repo https://github.com/pageauc/hotspot-game
* YouTube Hotspot Gam Video https://youtu.be/xFl3lmbEO9Y
* RPI Forum Post https://www.raspberrypi.org/forums/viewtopic.php?p=1026124#p1026124
## ----------------------------------------------------------------------------
Have Fun
Claude Pageau
YouTube Channel https://www.youtube.com/user/pageaucp
GitHub Repo https://github.com/pageauc