MoLa RGB CovSurv
This repository presents one of the datasets described in the article "AI based monitoring of different risk levels in Covid19 context", published in the Multidisciplinary Digital Publishing Institute special issue "Human Activity Recognition Based on Image Sensors and Deep Learning". The repository includes the complete dataset used for the training, validation and testing tasks, in order to detect the presence or absence of mask by people in public areas. There are two different folders: images and labels, each divided in three different subdatasets (train, valid, test). For each image, there is a text document with the exactly same name, where is present the information about each object (in this case, people's faces). This labels information uses the class associated to the object (0: With_Mask and 1: Without_Mask), and the correspondent normalized values of the bounding box of the face (x_center, y_center, width, height).