https://github.com/juliasouz/real-time-hand-tracking

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.
https://github.com/juliasouz/real-time-hand-tracking

cvzone opencv python3

Last synced: 8 days ago
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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.

• Host: GitHub
• URL: https://github.com/juliasouz/real-time-hand-tracking
• Owner: juliasouz
• Created: 2024-08-11T22:18:13.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-08-11T23:07:38.000Z (3 months ago)
• Last Synced: 2024-08-12T23:50:26.459Z (3 months ago)
• Topics: cvzone, opencv, python3
• Language: Jupyter Notebook
• Homepage:
• Size: 3.91 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 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:

```bash

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

```python

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.