Mask-Detection

Detects if the person in front of the camera is wearing a mask or not.
Outlines the face of the person's face making it easy for the person monitoring to discover.
The create dataset ability can be used to create or increase the size of the dataset which will result in a better accuracy when trained later.

Detection:

Creating Dataset:

Built with:

Python
OpenCV
Mediapipe
Tensorflow
Tkinter
asyncio

Prerequisites:

For Linux: sudo apt-get install python3.9 pip
For Windows: Follow these links to install python and pip
- https://www.python.org/downloads/
- https://phoenixnap.com/kb/install-pip-windows

Installation:

Clone the repository: git clone https://github.com/PrathamBhatTech/Mask-Detection.git
Change current directory to the repo: cd Mask-Detection
Install requirements: pip install -r requirements.txt

Usage:

To run the mask detection: python3.9 Run.py
To run the dataset creator: python3.9 CreateDataset.py
To train a model using the dataset you created:
- Upload the dataset after zipping(.zip) to your drive. NOTE: Name of folder data.
- open the train.ipynb file using google collab. Login to the account you uploaded the dataset.
- Modify the path of the dataset in the code.
- Start training.
- Download the trained model.

Project Link: https://github.com/PrathamBhatTech/Mask-Detection