hotspot-game.py - MOTION TRACKING GAME

A Windows, Unix or Raspberry Pi opencv, python, Motion Tracking Game

using a USB Web Camera or pi-camera Module (RPI Only)

Reference Information

• hotspot-game YouTube video here https://youtu.be/xFl3lmbEO9Y
• RPI Forum post here https://www.raspberrypi.org/forums/viewtopic.php?p=1026124#p1026124
• motion-track YouTube video here using RPI B2 https://youtu.be/09JS7twPBsQ
• github repo here https://github.com/pageauc/hotspot-game

Quick Install

For easy hotspot-game install onto a Debian or Raspberry Pi computer.

curl -L https://raw.github.com/pageauc/hotspot-game/master/hotspot-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 hotspot-install.sh script for hotspot-game

Manual install

cd ~
wget https://raw.github.com/pageauc/hotspot-game/master/hotspot-install.sh
chmod +x hotspot-install.sh
./hotspot-install.sh

This will install required files into a folder called ~/hotspot-game.

• IMPORTANT - hotspot-install.sh will perform a raspbian update and upgrade that could take a while. Reboot if there are significant changes.

Windows or Non RPI Unix Installs

For Windows or Unix computer platforms (non RPI or Debian) ensure you have the most up-to-date python version. For Downloads visit https://www.python.org/downloads

The latest python versions include numpy and recent opencv that is required to run this code. You will also need a USB web cam installed and working. To install this program access the GitHub project page at
https://raw.github.com/pageauc/hotspot-game
and select the green Clone or download zip option. The files will be cloned or zipped to a cam-track folder. You can run the code from console, gui desktop or from python IDLE application.

See How to Run Program section below for details on running hotspot-game.py

Program Description

This is a Windows, Unix or Raspberry pi computer opencv (computer vision) motion tracking game. It is written in python and uses opencv and a camera video stream running in a threaded to detect and track motion. Motion is tracked and activates menu's and game play using body motion. Can be played by one or two players and high score is saved.

The game play involves using 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.

Hardware Requirements

• USB Web Camera or pi-camera module connected and working.
• Computer monitor or HD Television needs to be connected via an HDMI cable (composite video not tested) or a VGA adapter.

The program is run from the computers GUI desktop in an opencv window. The default 640x480 window can be resized using the WINDOW_BIGGER resize multiplier variable. Use a text editor to change config.py settings.

How to Run Program

To launch program make sure camera and video display are connected. You must be in a RPI desktop GUI session. Open a desktop terminal session, File Manger. or Menu Programming, Python2 (IDLE). Navigate to the hotspot-game folder and execute

cd ~/hotspot-game
./hotspot-game.py

or

cd ~/hotspot-game
python ./hotspot-game.py

Settings

Variable values are stored in the config.py file. Use the nano editor to modify these settings per the comments. Most settings should be OK and will not need to be changed. You may need to flip the camera image to suit your camera module orientation. Others like game settings may need to be fine tuned.
Most openCV settings will not need changing unless you are familiar with them. Make a backup of the config.py file if you want to experiment. This will allow you to return to previous known good settings or you can just download default config.py again using the hotspot-install.sh script

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

Have Fun

Claude Pageau

YouTube Channel https://www.youtube.com/user/pageaucp
GitHub https://github.com/pageauc