In this project I’m going to show how hand tracking could be used to control Raspberry PI. We'll use the simplest Computer Vision algorithms, so anyone can implement and run this on his own device.
1 Laptop, 1 Raspberry PI 2, 1 Web-camera
1. Install conda (downloads)
2. Get code from repository
git clone https://github.com/jackersson/hand_mouse_control.git cd hand_mouse_control
3. Create conda environment (prepared environment in repository folder environment.yml)
conda env create -f environment.yml source activate tutor # environment name - ‘tutor’
Required libraries: python3, OpenCV, numpy, pyautogui
Additional: Learn how to manage conda environments.
4. Install Visual Studio Code for code editing.
1. Start program
python main.py -c 0 # where ‘-c 0’ defines camera index (if only one camera plugged to Raspberry PI use 0)
Note: to list connected cameras use
ls -ltrh /dev/video*
After you launched application, you are going to see two windows - ‘Hand mouse control’ with live video from webcamera and ‘Colored mask’ - with extracted skin segments from camera stream.
Hope this project will inspire you to modify this code and make more advanced system. This could be also extremely useful in Augmented Reality applications. So looking forward to your suggestions and possible collaboration.
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