Face Detection System for Security Checkpoints

This repository contains a face detection system designed for security checkpoints. The system utilizes a deep learning model to detect faces in images or video streams, aiding in the security screening process.

Installation

To install the necessary dependencies for running the face detection system, use the provided requirements.txt file:

pip install -r requirements.txt

Model Weights

The best.onnx file contains the pre-trained weights of our neural network model for face detection. These weights are essential for running the detection algorithm.

Integration

The bot_integration.py file contains the core class Yolov8Detector() responsible for face detection. This class provides methods for loading the model, performing inference on images, and drawing bounding boxes around detected faces.

Usage Example

For a demonstration of how to use our face detection system, refer to the example.ipynb notebook. This notebook provides a step-by-step guide on how to load the model, process images, and visualize the detection results.

Here some outputs of our model

License

This project is licensed under the MIT License, allowing for both personal and commercial use with proper attribution.

Syrenny/face_detection