Read-Time-Face-Mask-Detecting-System

Read Time Face Mask Detecting System using OpenCV, Keras/TensorFlow, and Deep Learning.

Easily detects whether you are wearing a Face Mask or not. Binary Classification was performed using a CNN Model giving highly accurate results .The Deep Learning model was built using the Pre-Trained Xception model (All Layers Freezed during training) who's output was given to Fully Connected Dense layers trained using Dataset for Binary Classification between Masked and Un-masked Human Faces.

Real-time detection of Masked/Un-masked faces is done using OpenCV and Python. The detected area having a confidence value above 50% was given to the Fully Connected CNN for Classification. Need some more fine-tuning in Masked Face Detection as the artificially generated data was less.

Getting Started

Dependencies

• Jupyter Notebook required

• Python Libraries

  • Imutils
  • Tensorflow
  • Keras
  • Numpy
  • Pickle
  • cv2
  • os
  • Scikit-Learn
  • Matplotlib

Installing

• Download Jupyter Notebook

• No further installation

Executing program

There are 3 phases of this program, run each of them.

• Train a Deep Convolutional Neural Network to distinguish between Masked and Non-Masked faces

• Recognize faces with OpenCV in Video Streams

• Classify the faces using the trained model

Help

Installing the libraries beforehand will solve most issues

Authors

Contributors names and contact info ex. @priyanshkedia04

Version History

• 0.1
  • Initial Release

License

GNU General Public License v3.0