/face-mask-detection

Face mask detection is a system that detects whether a person is wearing a face mask or not. The system uses a self-trained neural network model for detection. It can be used in various places such as hospitals and public places to check whether the people coming to these places are wearing a mask or not.

Primary LanguageJupyter Notebook

Face-mask-detection

Aim: To detect whether the person is wearing face mask or not

Face Mask Detection system is built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts to detect face masks in real-time video streams.

Dataset Source

Required Frameworks

  • Tensorflow
  • Keras

Required Libraries:

  • Numpy
  • Sklearn
  • mtcnn
  • OpenCV
  • Pandas
  • Matplotlib
  • Seaborn

Installation guide:

  • Download the zip file of this repo or clone the repo
  • (optional) make a new environment
  • pip install -r requirements.txt
  • If model is not available Download the h5 file from here and move it to the working directory

Working guide:

  • Open terminal and change the directory to the downloaded unzipped folder
  • Run the below command
python face_detection_and_classification.py
  • Face Mask Detection will be done in real-time

Retrain the Model

  • Upload face_mask_detection.ipynb file on google colab
  • Download the api key from kaggle
  • Run all the cells

👏 Credits