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.
- Python
- OpenCV
- Mediapipe
- Tensorflow
- Tkinter
- asyncio
- For Linux:
sudo apt-get install python3.9 pip
- For Windows: Follow these links to install python and pip
-
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
- 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.
- Upload the dataset after zipping(.zip) to your drive. NOTE: Name of folder
Project Link: https://github.com/PrathamBhatTech/Mask-Detection