Social Distancing Detector Using YOLOv3

The Social Distancing Detector project is an application that utilizes computer vision techniques to monitor and enforce social distancing guidelines in public spaces. It aims to help prevent the spread of contagious diseases by detecting and alerting individuals who are not maintaining a safe distance from others.

Here's a high-level overview of the Social Distancing Detector project:

To implement this project, you will need knowledge of computer vision, object detection algorithms, distance measurement techniques, and programming skills in languages such as Python. Popular computer vision libraries like OpenCV and deep learning frameworks like TensorFlow or PyTorch can be utilized for various components of the project.

YOLO (You Only Look Once) is a popular real-time object detection algorithm that can identify and localize multiple objects in an image or video. YOLOv3 is the third iteration of the YOLO algorithm and comes with improvements in accuracy and speed compared to its predecessors.

Installation Steps

Install ANACONDA latest version and open the Anaconda Prompt. Use the command Conda create -n tf python=3.7. 

1. Install Anaconda Latest Version

2. Open anaconda Prompt

3. Conda create -n tf python=3.7

4. Conda activate tf

5. Install require softwares

scikit-image==0.17.2,scikit-learn==0.23.2,pandas==1.1.1,matplotlib==3.3.1,Pillow==7.2.0,plotly==4.10.0,

opencv-python==4.4.0.42,spacy==2.3.2,lightgbm==3.0.0,mahotas==1.4.11, nltk==3.5, xgboost==1.2.0


To execute the file open anaconda prompt and goto the file directory and run Python run.py –i mylib/videos/test.mp4