GitHub - Nithinkumar-29/Real-Time-Hand-Sign-Recognition: This project combines two powerful technologies – MediaPipe and Neural Networks – to recognize hand signs and gestures in real time. The aim is to enable computers to accurately interpret hand movements, opening doors for various applications across different domains.

Name		Name	Last commit message	Last commit date
.ipynb_checkpoints		.ipynb_checkpoints
data		data
.gitattributes		.gitattributes
1.jpeg		1.jpeg
2.jpeg		2.jpeg
3-1.jpeg		3-1.jpeg
3.jpeg		3.jpeg
4.jpeg		4.jpeg
5.jpeg		5.jpeg
Dataset creation.ipynb		Dataset creation.ipynb
ak1.jpg		ak1.jpg
ak2.jpg		ak2.jpg
dataset-1.csv		dataset-1.csv
dataset.csv		dataset.csv
dataset1.csv		dataset1.csv
hand tracking.ipynb		hand tracking.ipynb
hand_sign_landmarks.csv		hand_sign_landmarks.csv
handgesture-akshat.hdf5		handgesture-akshat.hdf5
handgesture.hdf5		handgesture.hdf5
handgesture2.hdf5		handgesture2.hdf5
hands.h5		hands.h5
image.jpeg		image.jpeg
index finger tracking - border box.ipynb		index finger tracking - border box.ipynb
re_model.hdf5		re_model.hdf5
rnn_model.hdf5		rnn_model.hdf5

About

This project combines two powerful technologies – MediaPipe and Neural Networks – to recognize hand signs and gestures in real time. The aim is to enable computers to accurately interpret hand movements, opening doors for various applications across different domains.

Activity

0 stars

1 watching

0 forks

Report repository

Navigation Menu

About

Releases

Packages

Contributors

Languages

Latest commit

History

Folders and files

About

Stars

Watchers

Forks

Releases

Packages

Contributors

Languages