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A Deep learning flask based application used to predict whether Person is having mask to his face or not

Face-Mask-Detection

Logo

📌 Introduction

This Deep Learning Web Application utilizes a Convolutional Neural Network to process the person Images and predict if their Mask is ON/OFF accuracy of nearly 98%. Here this model is made by a pretrained model VGG16.

🎯 Purpose of the Project

As Social Distancing is only tool to prevent COVID-19 wearing face masks is compulsory. To monitor the mass no of people whether they wear a mask or not I came up with a solution using deep learning Here I can used Convulutional Nueral Networks(CNN) to predict whether the person is wearing the mask or not . I took the person images with and with_out masks through web scraping and started working on it. the dataset consists of nearly 2000.

Our Model performs fairly well with an accuracy of 98% and an F1 Score of 97%. This provides a handy tool to utilize the power of Machine Learning and Artificial Intelligence in Binary Classification Problems where time and accuracy is the paramount objective of classification.

🏁 Technology Stack

🏃‍♂️ Local Installation

  1. Drop a ⭐ on the Github Repository.
  2. Clone the Repo by going to your local Git Client and pushing in the command:
https://github.com/ksdkamesh99/Face-Mask-Detection.git
  1. Install the Packages:
pip install -r requirements.txt
  1. At last, push in the command:
python app.py
  1. Go to http://127.0.0.1:5000/ and enjoy the application.

  2. Examples are provided in the directory You can try using them.

  3. Some screenshots of the application are mentioned Below.

📜 Screenshots

  1. Home Page.
    home

  2. About Page.
    about

  3. Predictions Page/Result Page.

    i. Narendra Modi With Mask.
    narendra ii. Donald Trump without Mask.
    trump

Future Work to do:-

1 . To convert the application to asyncronous way by using ajax call.
2 . To deploy the application in AWS/GCP Platform for beter reach.

Contact:-

For any kind of suggesstions/ help in model code Please mail me at [email protected].

📜 LICENSE

MIT