Mask detection is a task in where it is wanted to detect whether a person is wearing a mask or not. It seems like a simple problem, but some facets, such as the fact that people wear such masks and respirators in a multitude of ways, are often ignored and trivialized to the worn/not worn case.
The database is ready-to-be-used and, due to its size, it was divided into three files:
- WWMR-DB - part 1.zip and WWMR-DB - part 2.zip files contain the database images;
- WWMR-DB - Labels.zip file contains the labels in PascalVOC and the YOLO format for each database image.
Due to the limitations imposed by the coronavirus, the database was created by asking volunteers for selfies through Google Forms. For this reason:
- number of images per class
- image quality
- intra-class differences
- rotation of the face
could also have great variations.
Google Forms are still open: if you want to contribute to the database, you can easily submit your images through the following links:
- Front photos (at 0 degrees): https://forms.gle/qLBjfCVhGoaJhnSo9
- Side photos (at 45 degrees): https://forms.gle/D3BuUQgjBLd6dqPj6
- Profile photos (at 90 degrees): https://forms.gle/yHgCAgcGJrfC7X4YA
Recently, the coronavirus pandemic has made the use of facial masks and respirators common, the former to reduce the likelihood of spreading saliva droplets and the latter as Personal Protective Equipment (PPE). As a result, this caused problems for the existing face detection algorithms. For this reason, and for the implementation of other more sophisticated systems, able to recognize the type of facial mask or respirator and to react given this information, we created the Facial Masks and Respirators Database (FMR-DB).
For reasons related to the copyright of the images, we cannot publish the entire database here. If you are a student, a professor, or a researcher and you want to use it for research purposes, send an email to email@example.com attaching the license, duly completed, which you can find here on IEEE DataPort.