Face-Access Detection Library

A Python library for face detection using YOLOv8. This library enables real-time face detection via webcam, leveraging the YOLOv8 model for high-performance object detection.

Features

• Real-time face detection with YOLOv8
• Easy integration with webcam
• Customizable detection thresholds and labels

Installation

You can install the library via pip. Run the following command in your terminal:

pip install face-access-detection

Usage

To use the face-access-detection library for face detection, follow these steps:

Basic Usage

from face_access_detection.detector import FaceDetector

# Initialize the FaceDetector
detector = FaceDetector()

# Start the webcam and run face detection
detector.run_webcam()

Custom Configuration

You can customize the face detection by passing parameters to the FaceDetector class. For example, you can set a custom model path, labels, or confidence threshold:

from face_access_detection.detector import FaceDetector

# Define custom parameters
custom_model_path = 'path/to/your/custom/model.pt'
custom_labels = {0: 'Person A', 1: 'Person B'}
custom_confidence_threshold = 0.7

# Initialize the FaceDetector with custom parameters
detector = FaceDetector(
    model_path=custom_model_path,
    labels=custom_labels,
    confidence_threshold=custom_confidence_threshold
)

# Start the webcam with custom settings
detector.run_webcam()

Testing

Ensure that your library functions as expected by writing tests in the tests/test_detector.py file. Here's a basic example of how you might start testing:

def test_face_detection():
    # Initialize the FaceDetector
    detector = FaceDetector()
    
    # Add tests to verify the functionality
    assert detector is not None
    # Further tests can be added here

Running Tests

To run your tests, execute:

pytest

Contributing

Contributions are welcome! If you have suggestions or improvements, please submit a pull request or open an issue.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Thank you for using face-access-detection!