Found 27 repositories(showing 27)
kishan-vk
The new Coronavirus disease (COVID-19) has seriously affected the world. By the end of November 2020, the global number of new coronavirus cases had already exceeded 60 million and the number of deaths 1,410,378 according to information from the World Health Organization (WHO). To limit the spread of the disease, mandatory face-mask rules are now becoming common in public settings around the world. Additionally, many public service providers require customers to wear face-masks in accordance with predefined rules (e.g., covering both mouth and nose) when using public services. These developments inspired research into automatic (computer-vision-based) techniques for face-mask detection that can help monitor public behavior and contribute towards constraining the COVID-19 pandemic. Although existing research in this area resulted in efficient techniques for face-mask detection, these usually operate under the assumption that modern face detectors provide perfect detection performance (even for masked faces) and that the main goal of the techniques is to detect the presence of face-masks only. In this study, we revisit these common assumptions and explore the following research questions: (i) How well do existing face detectors perform with masked-face images? (ii) Is it possible to detect a proper (regulation-compliant) placement of facial masks? and iii) How useful are existing face-mask detection techniques for monitoring applications during the COVID-19 pandemic? To answer these and related questions we conduct a comprehensive experimental evaluation of several recent face detectors for their performance with masked-face images. Furthermore, we investigate the usefulness of multiple off-the-shelf deep-learning models for recognizing correct face-mask placement. Finally, we design a complete pipeline for recognizing whether face-masks are worn correctly or not and compare the performance of the pipeline with standard face-mask detection models from the literature. To facilitate the study, we compile a large dataset of facial images from the publicly available MAFA and Wider Face datasets and annotate it with compliant and non-compliant labels. The annotation dataset, called Face-Mask-Label Dataset (FMLD), is made publicly available to the research community.
sayantann11
No description available
Sanaya04
Face Mask Detection Project
Eason0227
Realtime face mask dectection by using YOLO v8
No description available
MuhammadTalha-crypto
Face Mask Detection in Webcam live stream, Video and Images Using Custom YOLOv4 Model
Ali-bakhash
face mask detection using CNN
long0901
No description available
Purvika18
No description available
SaiTeja0501
No description available
Vickineshwaran
No description available
nish-bit
No description available
AkashYadav-02
No description available
Anilkumar052000
No description available
rnishitha1
No description available
tbang188
No description available
Sakshamchakradhar
No description available
surya-gunti
No description available
anujachereddy
No description available
SAIREDDY07
No description available
LakhanGitHub
No description available
jahidhrk
Real-time Face Mask Detector implemented in Python. Uses OpenCV for face detection and a deep learning model (TensorFlow/Keras) to classify mask vs. no-mask. Ideal for safety monitoring, health compliance, and AI learning projects.
li812
Simple face mask detection using python
Sammytechi
this is is s python code written to create a system to create a system to detect if an individual is putting on a face_mask or note
shbmpandey
No description available
Creating A real time mask +gender +smile detection using opencv , Deep learning(CNN tensorflow) ,Mobilenet ssd python Tkinter and Streamlit WebApp version.
majedn01
Dectection algorithm that tracks users face, providing a warning of whether or not the user is wearing a mask.
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