Application to monitor social distancing between people in public places using the video feed from Survillence or Security cameras. Many countries have mandated social distancing as a rule that people should follow while they are out in public places amidst the COVID-19 situation. So this application will help government agencies and private organizations to monitor how safe is their place at the current given time.
This application gets a live video feed from the camera or a recorded video file as an input and carry out the below steps,
- Detect people using SSD Mobilenet model trained on COCO dataset.
- Calculate the pixel distance between each person
- Highlight them if they cross the safe threshold distance
List of neccessary python packages to run this application
numpy==1.18.2
requests==2.18.4
tensorflow==1.15.4
opencv_python==4.1.2.30
Use this command to install all package at once
pip install requirements.txt
Download the SSD Mobilenet model from here and place it inside the saved_model folder. Your folder structure should look like this,
|_ input
|_ video.mp4
|_ saved_model
|_ get_model.py
|_ saved_model.pb
|_ README.md
|_ requirements.txt
|_ script.py
Execute this application using the following command,
python3 script.py --minThresh 40 --x 40 --y 10 --input input/video.mp4
This appllication requires few input data,
- minThresh - Minimum threshold score to detect person in the video
- model - Path to model
- input - File path to the input video or Camera ID
- x - Pixel difference in X axis
- y - Pixel difference in Y axis
