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Real-time Hand Tracking with OpenCV and cvzone Project

This project demonstrates a simple hand tracking application using OpenCV and the cvzone library. The application captures video from the webcam, detects hands in real-time, and displays the annotated video feed.

Requirements

  • Python 3
  • OpenCV
  • Cvzone

Installation

To install the required libraries, please run:

pip install opencv-python cvzone

Usage

  1. Initialize the Webcam: The webcam is initialized using OpenCV's VideoCapture method.
  2. Initialize the Hand Tracker: The hand tracker is initialized using cvzone.HandDetector with a detection confidence of 0.8 and a maximum of 2 hands.
  3. Capture and Process Frames: The application continuously captures frames from the webcam, detects hands, and annotates the frames.
  4. Display the Annotated Frames: The annotated frames are displayed in a window titled "Hand Tracking - AI".
  5. Exit the Application: The application exits when any key is pressed.

Code Explanation

import cv2
from cvzone.HandTrackingModule import HandDetector

# Initialize the webcam
webcam = cv2.VideoCapture(0)

# Initialize the Hand Tracker
hand_detector = HandDetector(detectionCon=0.8, maxHands=2)

while True:
    # Capture the image from the webcam
    success, img = webcam.read()

    # Detect hands in the frame
    hands, img_hands = hand_detector.findHands(img)

    # Display the frame with annotations
    cv2.imshow("Hand Tracking - AI", img_hands)

    # Exit the application when any key is pressed
    if cv2.waitKey(1) != -1:
        break

# Release the webcam and close the windows
webcam.release()
cv2.destroyAllWindows()

How It Works

  1. Webcam Initialization: The webcam is accessed and initialized to capture video frames.
  2. Hand Detection: The HandDetector from cvzone is used to detect hands in each frame with a specified confidence level.
  3. Frame Annotation: Detected hands are annotated on the video frames.
  4. Display: The annotated frames are displayed in a window.
  5. Exit Condition: The application runs in a loop until any key is pressed, at which point it exits, releasing the webcam and closing all windows.

Conclusion

This project provides a basic implementation of hand tracking using OpenCV and cvzone. It can be extended and customized for various applications such as gesture recognition, virtual controls, and more.