computer vision and machine learning library
Project description
metaidigitcv
🚀 Hand Tracking & Gesture Recognition with metaidigitcv
metaidigitcv is an advanced computer vision and machine learning library designed to detect, track, and analyze hand keypoints using MediaPipe and OpenCV. Whether you're building interactive applications, gesture-based controls, or AI-powered hand recognition systems, metaidigitcv simplifies the process with efficient hand tracking and keypoint extraction.
🔥 Features
✅ Hand Detection – Accurately detects multiple hands in real-time.
✅ Landmark Tracking – Tracks 21 keypoints per hand.
✅ Finger Recognition – Identifies raised fingers for gesture recognition.
✅ Distance Measurement – Computes distance between two keypoints.
✅ Optimized Performance – Uses MediaPipe for fast processing.
📦 Installation
pip install metaidigitcv
Ensure you have OpenCV and MediaPipe installed:
pip install opencv-python mediapipe numpy
🎯 Quick Start
import cv2
from metaidigitcv.main import Handtracker
# Initialize the tracker
detector = Handtracker()
# Capture video
cap = cv2.VideoCapture(0)
while True:
success, img = cap.read()
if not success:
break
hands, img = detector.identifyHands(img)
if hands:
lmList = hands[0]["lmList"] # List of hand landmarks
print("Thumb Tip Position:", lmList[4])
cv2.imshow("Hand Tracking", img)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
✨ Key Functions
🖐 Hand Detection
hands, img = detector.identifyHands(img, draw=True)
- Detects hands in an image/video frame.
- Draws hand landmarks if
draw=True.
🏷️ Landmark Extraction
lmList, bbox = detector.trackPosition(img)
- Returns a list of hand landmark positions.
- Provides the bounding box of the detected hand.
✋ Finger State Detection
fingers = detector.trackRaisedFingers(hands[0])
- Returns a list
[1, 0, 1, 1, 0]where1means the finger is up.
📏 Distance Calculation
length, img, points = detector.trackDistance(4, 8, img)
- Measures the Euclidean distance between two keypoints (e.g., thumb and index finger).
🎯 Applications
🔹 Gesture-based UI controls 🎮
🔹 Sign language recognition 🤟
🔹 Virtual painting & drawing 🎨
🔹 Touchless interaction systems 🤖
🔹 AI-powered hand gesture games 🎭
📜 License
This project is licensed under the MIT License – see the LICENSE file for details.
🤝 Contributing
We welcome contributions! Feel free to fork the repository and submit a pull request.
📧 Contact
👤 Author: Suhal Samad
✉️ Email: samadsuhal@gmail.com
If you like metaidigitcvcv, don't forget to ⭐ the repository!
🚀 Let's build amazing hand-tracking applications together! 🚀
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