MaskedFace-Net is a dataset of human faces with a correctly and incorrectly worn mask based on the dataset Flickr-Faces-HQ (FFHQ).

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This repository is designed to solve different issues which may occur in developing a face mask detector (Creating and modifying manual annotations, training Yolo v5, testing Yolo v5). The considered datasets for face mask detection are: COCO dataset, Real and Fake Face Detection by Kaggle, MaskedFace-Net, FMLD.

Various methods used for face detection on masked and unmasked images.

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Finding individuals who are wearing facial masks. Datasets were used from MaskedFace-Net

Utilizing the Caffe Deep Learning Model to detect face masks. The training data is part of the MaskedFace-Net dataset.

A CNN architecture that employs multi-task learning to detect the presence of a face mask and its coverage of the nose, mouth, and chin on human faces. Conducted training on MaskedFace-Net 138k synthetic images.