Social Distancing Detection

Technologies | Computer Vision

Domain | Healthcare, Public Safety

Problem Statement:

Social distancing detection using deep learning to evaluate the distance between people to mitigate the impact of this coronavirus pandemic. The detection tool was developed to alert people to maintain a safe distance with each other by evaluating a video feed. The video frame from the camera was used as input, and the open-source object detection pre-trained model

Implementation

• YOLO trained on COCO dataset is used to detect people from camera frame as input
• After detecting people pairwise distance is calculated between all detected people
• Based on the computed distances, we determine whether social distancing rule is being violated or not.(here distince is used in pixels, minimum = 50 )

Installation

1. Clone the git reprository

$ git clone https://github.com/KalyaniAvhale/social-distance-detection.git
$ cd social-distance-detection

2. Install dependencies

$ pip install -r requirements.txt 

Before running the project make sure to add yolov3.weights to yolo-coco dir.

3. Run social_distance_detection.py file (input will be webcam by default to input local file use --input TestVideo.mp4)

$  python social_distance_detection.py --input TestVideo.mp4

Steps involved in Social Distance detection task

Screenshots

Input

Output

Video Demo

👋 THANKYOU!!