Face Mask Detection using Python, Keras, OpenCV and MobileNet | Detect masks real-time video streams

Face Mask Detection using Python, Keras, OpenCV and MobileNet | Detect masks real-time video streams



In this Python programming video, we will learn building a Face Mask Detector using Keras, Tensorflow, MobileNet and OpenCV. We will also see how to apply this on a Live Video Camera. With further improvements these types of models could be integrated with CCTV cameras to detect and identify people without masks.

The face mask detector didn’t use any morphed masked images dataset. The model is accurate, and since the MobileNetV2 architecture is used, it’s also computationally efficient and thus making it easier to deploy the model to embedded systems (Raspberry Pi, Google Coral, etc.).

This system can therefore 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.

Feel free to play around with the code, change the parameters and come ip with better accuracy. Let me know the changes in the comment section.

GitHub:
Numpy:
Matplotlib:
Learn more about ImageDataGenerator:
LinkedIn: LinkedIn:

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#python #FaceMaskDetection #keras #tensorflow #opencv

Introduction and Demo: (0:00)
Install Dependancies: (1:18)
Dataset: (2:10)
Data Preprocessing: (2:58)
Training: (9:03)
Run and View Accuracy: (17:09)
Use model in real time Camera: (18:20)
Final Result: (25:30)

How to Make Face Masks

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