The project aims to detect people wearing masks/glasses in live video streams using deep learning techniques. It utilizes the YOLOv5 object detection framework combined with Cython for improved performance. The system can identify individuals wearing masks or glasses in real-time and can be used for various applications such as surveillance, safety monitoring, or public health management.
Follow these steps to set up the project:
- Create a Python 3.7 environment using your preferred method (e.g., virtualenv, conda).
- Clone the repository:
git clone https://github.com/BlackChesire/FaceMask_Glasses_Detector.git - Navigate to the project directory:
cd FaceMask_Glasses_Detector - Install the required packages by running the following command:
pip install -r requirements.txt
- Run the
Detection_on_Video.pyscript to start the detection on a live video stream. - Adjust the settings or parameters in the script as needed.
- The output will be displayed on the screen, showing detections of people wearing masks or glasses.
- Our model uses yolov5
This project is licensed under the MIT License - see the LICENSE file for details. Feel free to customize the template according to your project's needs. Good luck with your deep learning project! 🎉