An awesome and easy to use detector with training samples
This COVID-19 pandemic has raised many concerns regarding health and our environment and to stop them from spreading is wearing mask in public places. Therefore, this issue to be addressed efficiently cannot be possible by humans single handedly.
Here's why:
- Even if a team of people are gathered it would be difficult to keep a note of all people not wearing masks
- Manual labor can be reduced and thus reducing the price of expenditure on hiring more people for a job which can be accomplished by machine
- This can not only be used for mask detection but can be tweaked a bit and then used for attendance manager in workplaces or schools, etc.
Of course, no machine can be perfected completely but this detector has accuracy of over 90% and can learn from the usage too.
A list of commonly used resources that I find helpful are listed in the acknowledgements.
Here is list of MAJOR dependencies for this project (for running this you will need a few more too; and how to install them is shown further below)
To get a local copy up and running follow these simple example steps.
List of things you need to use the software and how to install them.
- Python
- Tensorflow
- CV2
- Tensorflow
pip install tensorflow --user- Matplotlib
pip install matplotlib --user- NumPy
pip install numpy --user- CV2
pip install cv2 --user-
If user wants to see the how the model is created, then open the Mask_detection.ipynb file or just run it directly to create model.
-
Run the mask.py in ./Detect for the input and output
No further features are planned to be added, if planned it will be shown here
Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch
- Commit your Changes
- Push to the Branch
- Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Shree Ratn
Project Link: Github