A COVID-19 nose mask detector built with OpenCV, Keras/TensorFlow, and Deep Learning.
Trained by fine-tuning the MobileNet V2 architecture, a highly efficient architecture that can be applied to embedded devices with limited computational capacity (eg. Raspberry Pi, NVIDIA Jetson Nano, Google Coral ...).
- Clone the repository
$ git clone https://github.com/FredDoe/nose-mask-checker.git
$ cd nose-mask-checker
- Create virtual environment and install dependencies
python -m venv venv
source venv/Scripts/activate
pip install -r requirements.txt
- To build the mask detector model, open up a shell and issue the following command:
python mask_detector_trainer.py --dataset dataset
- Implementing the COVID-19 nose mask checker for images with OpenCV
python detect_mask_image.py --image test_images/test_01.jpeg
- Implementing the COVID-19 nose mask checker for video stream with OpenCV
python detect_mask_video.py
- COVID-19 noee mask checker training accuracy/loss curves demonstrate high accuracy and little signs of overfitting the data:sweat_smile:.
- Mask detection using the COVID-19 nose mask checker:mask:
MIT © Godfred Doe