RediSafe - An AI Tool for PPE safety checks during COVID-19

During the COVID-19 pandemic, Redisafe is developed to be a secured AI platform with the purpose of detecting PPE on medical staff for safety protocol to prevent the spread of virus. This project combines several Redis data structures and Redis Modules to process a stream of images and classify them with the Tensorflow detection model.

It uses:

Redis Streams to capture the input video stream: camera:0
RedisAI to classify the images with TensorFlow mask detection model.
Express.js to serve the client side.

It forwards the classifies images to a stream: results

Architecture

Runtime

Python 3.6

Requirements

OpenCV
Redis - python client
RedisAI - python client
Numpy

Running the Demo

To run the demo:

$ git clone https://github.com/sagban/redisPPEScan.git
$ cd redisPPEScan
$ pip install -r requirements.txt # Now install the python dependencies

RedisAi Detection Model

Start the redisAI detction model:

$ cd app/mask_detection
$ python detection.py

Camera Feed

Open a second terminal for the video capturing:

$ python camera/read_camera.py

UI

Open a third terminal for the express.js client application:

$ cd client
$ npm install
$ node server.js

http://localhost:3000 shows all the classified frames.

Limitations

This demo is designed to be easy to setup, so it relies heavily on docker. You can get better performance and a higher FPS by runninng this demo outside docker.

Contributer

Sagar Bansal VI LY

sagban / redisPPEScan