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Face-Mask-Detection (92% Accuracy)

Note: For a nicer rendering of the notebook, click on this link to NBViewer.

In this project, I used a Convolutional neural-network architecture using the PyTorch framework on image data to create a model that can detect whether or not an image has: a fully covered mask, a partially covered mask a non covered face or not a face at all

Below is a sample of the images used in this project, two samples from each category.

Fully covered Partially Covered Not covered Not Face
\"Fully \"Partially \"Not \"Not
\"Fully \"Partially \"Not \"Not

Concepts used in this project:

Deep Learning

  • Convolutional Neural Networks

Data Visualization:

  • Matplotlib

Potential Improvements to this project

  • Setting a learning rate decay
  • decreasing the learning rate

HAPPY CODING!!!

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