Face-Mask-Detection

Adapted from https://github.com/TanyaChutani/Face-Mask-Detection-Tf2.x

This project has been transformed from a Jupyter notebook to a couple of Python scripts to make it easier to train and deploy. Plus, all dependencies have been packed in a Docker image.

Instructions

1. Run docker-compose build to create the Docker image.
2. (Optional) Run scripts/train.py to train the network from scratch. You will need:
   • The training data (in data/train)
   • Optionally, the testing data (in data/test)
3. Run scripts/run.py <image.jpg> to annotate one image. You will need:
   • The training weights (in data/mask_classification_model.h5)
4. The output image will be in data/output.jpg.

If you want to use it as a module, the run.py file exposes a method annotate_image(path) that does all the heavy work.

Data

All necessary data is shared in a release.