Real time face-mask detection using Deep Learning and OpenCV

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https://www.hackster.io/Altaga/facemask-detector-f0c10f

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Building a simple facemask detector using Deep Learning(Keras) and OpenCV

This Detects if you are wearing a face mask or not.

Android application which detects human faces and classifies them under wearing a face mask or not

Building face mask detector with Convolutional Neural Network.

Demo de detector de tapabocas usando una ESP32-cam y la API de Proyecto Horus

Checks if person on the video is wearing a medical mask (Hi, COVID-19)

A deep learning project for detecting face mask status (with mask, without mask, incorrect mask) using YOLOv8m.

To develop a “Face mask detection” software using Python Programming Language & DataScience, to facilitate easy mask detection from real time video stream as well as from image. About Module: The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection methods is wearing a face mask in public areas according to the World Health Organization (WHO). The COVID-19 pandemic forced governments across the world to impose lockdowns to prevent virus transmissions. Reports indicate that wearing facemasks while at work clearly reduces the risk of transmission. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. A hybrid model using deep and classical machine learning for face mask detection will be presented. A face mask detection dataset consists of with mask and without mask images, we are going to use OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to build a COVID-19 face mask detector with computer vision using Python, OpenCV, and Tensor Flow and Keras. Our goal is to identify whether the person on image/video stream is wearing a face mask or not with the help of computer vision, data science and deep learning.

This project integrates Meraki MV Cameras with Amazon Rekognition through their APIs to perform deeper image analysis, to detect whether a person is wearing a facemask or not. The results will be posted into a Webex Teams space.

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CNN which detects the presence of face mask.

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Deteccion de Barbijos con OpenCV, Keras y Tensorflow

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Android application to detect face mask from image and live camera feed.

A voice assisted facemask detector using the facenet and mobilenet networks along with google text to speech API

The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection methods is wearing a face mask in public areas according to the World Health Organization (WHO). The COVID-19 pandemic forced governments acrossthe world to impose lockdownsto prevent virustransmissions. Reportsindicate that wearing facemasks while at work clearly reduces the risk of transmission. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. A hybrid model using deep and classical machine learning for face mask detection will be presented. A face mask detection dataset consists of with mask and without mask images , we are going to use OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to build a COVID-19 face mask detector with computer vision using Python, OpenCV, and Tensor Flow and Keras. Our goal isto identifywhether the person on image/video stream is wearing a face mask or not with the help of computer vision and deep learning.

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Face Mask Detection in PyTorch

Coursework for Project III of OpenCV - Applications 😷

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Face Mask Detector is used to automate the detection of face mask using images captured from a thermal camera. The problem is posed as a binary classification problem, wherein the input face image needs to be classified as with mask or without mask. Transfer learning is used for classification, wherein deep CNN model, MobileNetV2, is trained on a dataset of thermal face images with mask and without mask. The steps for building model are collecting the data, pre-processing, split the data, training the model, testing the model, and implement the model. The dataset is prepared using lepton FLIR camera interfaced to a Raspberry pi board. The built model can now detect people who are wearing a face mask and not wearing with an accuracy of 97 percent.

Real time face-mask detection using OpenCV

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A simple face-mask detector