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hand-gesture-recogination

Overview This Python-based computer vision project focuses on the recognition of hand gestures, offering a versatile solution for diverse applications, from virtual interfaces to gesture-based control systems. By utilizing various Python libraries, the project delivers accurate and real-time hand gesture recognition.

https://github.com/cprakash64/hand-gesture-recogination

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
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    Scientific vocabulary similarity
    Low similarity (10.1%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Overview This Python-based computer vision project focuses on the recognition of hand gestures, offering a versatile solution for diverse applications, from virtual interfaces to gesture-based control systems. By utilizing various Python libraries, the project delivers accurate and real-time hand gesture recognition.

Basic Info
  • Host: GitHub
  • Owner: cprakash64
  • License: apache-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 1.29 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

Hand-Gesture-Recogination

This Python-based computer vision project focuses on the recognition of hand gestures, offering a versatile solution for diverse applications, from virtual interfaces to gesture-based control systems. By utilizing various Python libraries, the project delivers accurate and real-time hand gesture recognition.

Features

Multi-library Integration: Harnessing the capabilities of popular Python libraries such as OpenCV, MediaPipe, and others, this project ensures robust and efficient hand gesture recognition.

Real-time Recognition: The system provides real-time detection and recognition of hand gestures, making it suitable for applications requiring instantaneous response.

Flexibility: With support for a wide range of gestures, the project offers flexibility for customization. Whether you're interested in simple gestures for control or complex sign language recognition, the system can be adapted to suit different needs.

User-friendly Interface: The application comes with a user-friendly interface, making it accessible for developers and end-users alike. The system is designed to be easily integrated into larger projects or used as a standalone application.

Contributions

Contributions are welcome! Whether you're interested in fixing bugs, implementing new features, or improving documentation, your contributions will be highly appreciated.

License

This project is licensed under the MIT License.

Acknowledgments

Special thanks to the open-source community for the fantastic libraries and resources that make this project possible. Feel free to reach out if you have questions or suggestions. Let's advance hand gesture recognition together!

Owner

  • Name: Chandra prakash Pandey
  • Login: cprakash64
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
title: "hand-gesture-recognition-using-mediapipe"
authors:
- family-names: "Pandey"
  given-names: "Chandra prakash"
  orcid: "https://orcid.org/0000-0002-1343-9181"
date-released: 09-11-2003
message: "If you use 'hand-gesture-recognition-using-mediapipe' in your research, please cite it using these metadata."
url: "https://github.com/cprakash64"
license: Apache-2.0 license

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Dependencies

Dockerfile docker
  • ubuntu 20.04 build
requirements.txt pypi
  • matplotlib ==3.5.1
  • mediapipe ==0.8.4
  • opencv-python ==4.6.0.66
  • protobuf <3.20,>=3.9.2
  • scikit-learn ==1.0.2
  • tensorflow ==2.9.0