Skip to content

VedantKhairnar/Wingardium-Leviosa

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Wingardium Leviosa

J.K. Rowling — 'It's leviOsa, not levioSA!'

Stars Forks GitHub contributors Language GitHub Say Thanks! HitCount Issues PRsWelcome

Dedicated to my soulmate...a PotterHead

Computer System Control using gestures

Ever thought, how awesome it will be if you could control ur computer system just by ur hand gestures? This project provides you the provision to do so.

Control your system by your fist. Now you can say, your computer is in your fist...

Using the ability that the whole system can be controlled using Keyboard.

y coordinate increase : fist up : Tab View 
y coordinate decrease : fist down : minimize all windows 
x coordinate decrese : fist left : open task manager
x coordinate decrease : fist right : change window 

Libraries Used :

pynput (for keyboard control)
cv2    (for hand gesture recognition)

Installation :

pip install opencv-python pynput

Logic:

Fist Detection using HaarCascade
Instruct System as per the gesture detected

Theory :

Haar Cascade is a machine learning object detection algorithm used to identify objects in an image or video It is a machine learning based approach where a cascade function is trained from a lot of positive and negative images. It is then used to detect objects in other images.

The algorithm has four stages:

1) Haar Feature Selection
2) Creating  Integral Images
3) Adaboost Training
4) Cascading Classifiers

It is well known for being able to detect faces and body parts in an image, but can be trained to identify almost any object.

For pynput reference, click here

For various Virtual-Key Codes, click here

Future Prospects :

Addition of multiple gestures (now limited to fist)
Improve the Efficieny using Deep Learning (specifically trained )

For Any Queries, connect me :

Vedant Khairnar