This is a proof-of-concept for our final project for CS 6476: Computer Vision - Spring '24 at Georgia Tech. It is a web application that uses object detection to detect vehicles in live traffic camera feeds from 511GA/Georgia Department of Transportation (GDOT). The application is built using Flask, YOLOv8, PyAv and PIL in the backend and Vanilla TypeScript and Mapbox GL JS in the frontend. For background work (fine-tuned models), check out this repository.
cover.mp4
cd server
python3 -m venv venv
source venv/bin/activate # for windows: venv\Scripts\activate
pip install -r requirements.txt
cd client
npm install
Create a .env
file in the server
directory with the following contents:
GDOT_API_KEY=<your-api-key>
and then run the following commands:
cd server
source venv/bin/activate # for windows: venv\Scripts\activate
flask run # --debug for auto-reload
Create a .env
file in the client
directory with the following contents:
VITE_MAPBOX_KEY=<your-mapbox-key>
and then run the following commands:
cd client
npm run dev