TY - GEN
T1 - Desarrollo de un sistema de detección de rostro con o sin mascarilla mediante el uso de software Development of a face detection system with or without a mask using software
AU - León León, Ryan Abraham
AU - Arroyo Anticona, Danner Enrique
AU - Carranza Albites, Rebecca
AU - Lozano Castañeda, Roger
AU - Terrones Pinedo, Claudia
N1 - Publisher Copyright:
© 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
PY - 2022
Y1 - 2022
N2 - This article presents a software with artificial vision using the Python language in Visual Studio Code which is capable of detecting if a person is wearing a mask or not, this project was made in order to be able to identify people who are without masks or misplaced either at work or at the entrance of a premises, for example this would be applied in companies that work with toxic waste, gases, dust and any agent that is transmitted by air, thanks to this it will be possible to identify certain people and give them a feedback on the correct use of the mask. For the development of this software, the main modules such as opencv-contrib-python, numpy and mediapipe were used, in addition to having their dependencies which are installed automatically, as well as a camera with which to capture the images; The first step was to search for a data set and resize it, followed by training it using opencv and finally using mediapipe for face detection and implementing the model in programming. Finally, after the tests carried out, a result of 83.13% validation was obtained, however, its percentage would increase or decrease depending on the quality of the camera, since the errors would decrease if you have a camera with a good quality implemented.
AB - This article presents a software with artificial vision using the Python language in Visual Studio Code which is capable of detecting if a person is wearing a mask or not, this project was made in order to be able to identify people who are without masks or misplaced either at work or at the entrance of a premises, for example this would be applied in companies that work with toxic waste, gases, dust and any agent that is transmitted by air, thanks to this it will be possible to identify certain people and give them a feedback on the correct use of the mask. For the development of this software, the main modules such as opencv-contrib-python, numpy and mediapipe were used, in addition to having their dependencies which are installed automatically, as well as a camera with which to capture the images; The first step was to search for a data set and resize it, followed by training it using opencv and finally using mediapipe for face detection and implementing the model in programming. Finally, after the tests carried out, a result of 83.13% validation was obtained, however, its percentage would increase or decrease depending on the quality of the camera, since the errors would decrease if you have a camera with a good quality implemented.
KW - Python
KW - Software
KW - Visual Studio Code
KW - computer vision
KW - modules
UR - http://www.scopus.com/inward/record.url?scp=85140017260&partnerID=8YFLogxK
U2 - 10.18687/LACCEI2022.1.1.753
DO - 10.18687/LACCEI2022.1.1.753
M3 - Contribución a la conferencia
AN - SCOPUS:85140017260
T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
BT - 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
A2 - Larrondo Petrie, Maria M.
A2 - Texier, Jose
A2 - Pena, Andrea
A2 - Viloria, Jose Angel Sanchez
T2 - 20th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2022
Y2 - 18 July 2022 through 22 July 2022
ER -