FaceMe

Identify if a person is wearing a face mask or whether the person is wearing it properly using Computer vision and deep learning.

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The Dataset

Masks play a crucial role in protecting the health of individuals against respiratory diseases, as is one of the few precautions available for COVID-19 in the absence of immunization. With this dataset, it is possible to create a model to detect people wearing masks, not wearing them, or wearing masks improperly.
This dataset contains 853 images belonging to the 3 classes, as well as their bounding boxes in the PASCAL VOC format.
The classes are:

• With mask
• Without mask
• Mask worn incorrectly

Directory structure

        Face Mask Detection
        ├───data/
        │    ├───annotations/
        │    └───images/
        ├───notebooks/
        │    ├───Data-exploration-and-preprocessing.ipynb
        │    ├───FaceMe-MTCNN-face-detection.ipynb
        │    ├───FaceMe-ultra-light-face-detection.ipynb
        │    └───Traning-model.ipynb
        ├───modeljs/
        │    ├───model.json
        ...

Workflow

• Base model: InceptionV3 with imagenet weights.
• Face detector: MTCNN
• AVG FPS: 2.4
• Model accuracy: 97%