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Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. The absence of large datasets of ‘with_mask’ images has made this task cumbersome and challenging. Our face mask detector doesn't use any morphed masked images dataset and the model is accurate. Owing to the use of MobileNetV2 architecture, it is computationally efficient, thus making it easier to deploy the model to embedded systems (Raspberry Pi, Google Coral, etc.).
Features
- Our face mask detector doesn't use any morphed masked images dataset and the model is accurate
- This system can be used in real-time applications which require face-mask detection for safety purposes due to the outbreak of Covid-19
- This project can be integrated with embedded systems for application in airports, railway stations, offices, schools, and public places to ensure that public safety guidelines are followed
- It is computationally efficient, thus making it easier to deploy the model to embedded systems (Raspberry Pi, Google Coral, etc.)
- This dataset consists of 4095 images
- The images used were real images of faces wearing masks
- All the dependencies and required libraries are included in the file requirements.txt
Project Samples
Categories
Security, Healthcare, Machine Learning, Computer Vision Libraries, Deep Learning Frameworks, Raspberry PiLicense
MIT LicenseFollow Face Mask Detection
User Reviews
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Paranoic s***.
