https://github.com/josualimbu/hand-landmark

Hand Landmark is a system for recognizing and tracking key points on the hand using MediaPipe technology, a machine learning and computer vision framework from Google.
https://github.com/josualimbu/hand-landmark

hand-landmarks-detection machine-learning mediapipe mediapipe-hands opencv pipeline

Last synced: 2 months ago
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Hand Landmark is a system for recognizing and tracking key points on the hand using MediaPipe technology, a machine learning and computer vision framework from Google.

• Host: GitHub
• URL: https://github.com/josualimbu/hand-landmark
• Owner: JosuaLimbu
• Created: 2024-05-21T03:35:33.000Z (about 2 years ago)
• Default Branch: master
• Last Pushed: 2024-07-15T11:00:50.000Z (almost 2 years ago)
• Last Synced: 2025-04-02T20:29:17.056Z (about 1 year ago)
• Topics: hand-landmarks-detection, machine-learning, mediapipe, mediapipe-hands, opencv, pipeline
• Language: Python
• Homepage:
• Size: 3.91 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
Hand landmark is a technology used to detect and track specific points on the human hand in images or videos, often used in hand gesture recognition, human-computer interaction, and augmented reality (AR). This technology utilizes Machine Learning (ML) and Computer Vision (CV) to identify and track the positions of the fingers and other hand parts. A popular framework for this is MediaPipe by Google, which offers real-time solutions for hand tracking, landmark detection, and gesture recognition using pre-trained deep learning models. MediaPipe can detect up to 21 key points on each hand, enabling applications like device control through gestures, intuitive human-computer interaction, and realistic hand integration in AR environments.