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Social Distancing Analyser Covid 19

A Python computer-vision application that analyzes surveillance video to estimate social-distancing risk and count people in an area.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Social Distancing Analyser Covid 19 — OpenViST project profile in AI Data & Analytics.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when examining surveillance footage for area-level distancing indicators and a video record for review, with the camera-angle setting considered for version 2.0.

Who it is for

  • People working with CCTV or drone footage who need area-level counts and distancing-risk estimates.
  • Developers or learners interested in a repository-based Python video-analysis project.

Documented uses

  • Estimate how many people appear in a monitored area.
  • Identify people classified as high risk and estimate individual distancing risk.
  • Save analyzed video output for later review.
Before you choose

Requirements & limits

  • The README requires the YOLOv3 configuration and weights files alongside the code, plus installed dependencies.
  • Version 2.0 requires a camera-angle factor between 0 and 1, adjusted to the camera view.
  • The repository describes the project as educational and notes processing speed as an area for improvement.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the analyzer with YOLOv3 model files

Prepare the repository and model files before running an analyzer script.

Before you start

  • A forked and downloaded copy of the repository.
  • The YOLOv3 configuration and weights files.
  • Dependencies installed.

Steps

  1. Fork the repository and download the code.

  2. Download yolov3.cfg and yolov3.weights, then place both files in the same directory as the code.

  3. Install the dependencies.

  4. For slower CPUs, use yolov3-tiny as suggested in the code comments.

Expected outcome

The repository and model files are prepared for the documented analyzer-script stage.

Guide limitations

  • The source does not specify dependency installation commands or enumerate dependencies.
  • The angle factor for v2.0 must be set between 0 and 1 according to the camera angle.
  • The project notes that processing speed needs improvement.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
Ank-Cha/Social-Distancing-Analyser-COVID-19 · Official homepage title · retained in its source language
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