face-detection-lib 0.2

A library for face detection using YOLOv8

Face 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_detection_lib

Usage

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

Basic Usage

from face_detection_lib.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_detection_lib.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

Build and Upload to PyPI

To publish your library to PyPI, follow these steps:

1. Install Twine

   Make sure twine is installed:

   pip install twine
   

2. Build the Package

   Navigate to the root directory of your project and build the package:

   python setup.py sdist bdist_wheel
   

3. Upload to PyPI

   Use twine to upload your package to PyPI:

   twine upload dist/*
   

   Replace dist/* with the actual path to your distribution files if necessary.

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.

Contact

For any questions or support, please reach out to [e-mail].

---

Thank you for using face_detection_lib!