This repository is for my graduation project.
Face-mask Detection in Real-time is a software that helps users automatically identify whether someone or a group of people are wearing a face mask or not or in the wrong way in a real-time fashion.
This is software for Custom Object Detection, a paradigm that appeared in the Computer Vision Applications field of research relating to Deep Learning.
Table of Contents:
| Description | |
|---|---|
| Overview | The idea itself and how it lead to the creation of the project. |
| Phase 1 | Detection using static images for one mask only. |
| Phase 2 | Detection using static images as well as in real-time video streams for more than one mask (groups). |
In our project, we try to enforce the culture of wearing masks to further prevent the spread of the virus by monitoring vital facilities.
- It can be used to encourage and help people to wear masks in important areas.
- It can be used to prevent people from entering some other areas without it as well.
Masks are a simple barrier to help prevent your respiratory droplets from reaching others. Studies show that masks reduce the spray of droplets when worn over the nose and mouth. You should wear a mask, even if you do not feel sick.
Used Dataset: Face Mask Detection ~12K Images Dataset This dataset consists of images belonging to two classes (With Mask / Without Mask) divided into:
- Train Data: 5000 Without Mask Images / 5000 With Mask Images
- Test Data : 509 Without Mask Images / 483 With Mask Images
- Validation Data: 400 Without Mask Images / 400 With Mask Images
Complete Project (Notebook): face-mask-detection.ipynb
Feel free to use the raw python scripts to train or inference:
1- Train: train.py
2- Inference: predict.py
Note: For more info about this phase of the project feel free to read the SRS Document. Link.
Used Dataset: Face Mask Detection [3 Classes] This dataset consists of 853 images belonging to three classes (With Mask / Without Mask / Wearing Wrong)
Complete Project (Notebook): YOLOv3_Face_mask_Detection.ipynb
Feel free to use our simple python OpenCV Application to infer images, videos, and real-time streaming through a camera:
1- Inference Images (multi objects detection): Images.py
2- Inference Videos (multi objects detection): Videos.py
3- Online camera: Camera.py
Note: For more info about this phase of the project feel free to read the project Documentation. Link.