In this Python programming video, we'll learn how to create a Face Mask Detector with Keras, Tensorflow, MobileNet, and OpenCV. We'll also look at how to do this using a live video camera. With future advancements, these models may be connected with CCTV cameras to detect and identify persons who are not wearing masks. There was no morphing masked picture dataset used by the face mask detector. The model is accurate, and because it is based on the MobileNetV2 architecture, it is also computationally efficient, making it simpler to apply the model to embedded devices (Raspberry Pi, Google Coral, etc.).
As a result of the Covid-19 outbreak, this technology can be utilised in real-time applications that need face-mask detection for safety considerations. This project may be connected with embedded systems and used to guarantee that public safety rules are followed at airports, train stations, offices, schools, and public areas. Feel free to experiment with the code, modify the settings, and come up with a better solution. Please notify me of any modifications in the comments area. Code: https://github.com/sohaibcs1/Face-mask-detection-using-OpenCV-Python-code #facemaskdetection #objectdetection
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