A solution to detect persons violating the Social Distancing Protocols
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- Table of Contents
- About The Project
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- Getting Started
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YOLO Object Detection, Objection Tracking and Object Measuring to detect persons violating the Social Distancing Protocols
To get a local copy up and running follow these simple example steps.
You will need:
- A webcam
- Visual Studio installed in your PC
- Desktop development with C++ in Visual Studio
- Python
- Scipy
- Yolo Weights
- Yolo Config Files
- Coco Class Names
- OpenCV
- Make sure you have python3 setup on your system
- Clone the repo
git clone https://github.com/ctrl-gaurav/Social-Distancing-Alert.git- Install requirements
pip install -r requirements.txt- Download Yolo Weights
- Move Yolo Weights to yolo weights and coco classes folder
- If u don't have gpu enabled pc set USE_GPU = False in config.py
- Run main.py for realtime detections
python main.py- If You want to process a particular video not realtime
- Then move that video in current directory and rename it as test.mp4
- Run main.py
python main.py --input test.mp4- If you want to save your results in a video :
- Run main.py
python main.py --input test.mp4 --output output.mp4- Your video will be saved in current directory after processing
See the open issues for a list of proposed features (and known issues).
To add your contributions to this project follow these steps :
- Fork the Project
- Create your improvements Branch (
git checkout -b improvements/myimprovements) - Commit your Changes (
git commit -m 'Done some Improvements') - Push to the Branch (
git push origin improvements/myimprovements) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
- Gaurav
- Project Link: https://github.com/ctrl-gaurav/Social-Distancing-Alert