The YOLOv5 framework yields extremely fast inference times with high accuracy.
This project has been integrated into a web application found here (no longer active).
- You have installed a 64-bit release of Python 3.7 or above
- All Python modules required are installed (see "Installing SDM" below)
-
Clone this repository.
-
Navigate to the root of the project folder via the CLI. Use the package manager pip to install the necessary dependencies. e.g.,
pip install -r requirements.txt
Option 1: Navigate to the root of the project folder via the CLI. e.g.,
python sdm.py [source]
- Image or video: [source] is the path to that file (relative to the root folder)
- Webcam: Do not enter [source]
- HTTP/RTSP stream: [source] is the URL
Ensure that the default interpreter for the python
command is version 3.7 or above (or use python3
)
Option 2: Upload images/videos to the web application.
This project was created by:
- Zeyad Mansour (@zeyad-mansour)
- Manav Malik (@0xmmalik)
It was created for the 2021 High School I/O hackathon and received 1st place.
- Use computer vision to implement social distancing approximation
- Improve the style of the web application
This project uses the following license: GNU GPL v3