Smart Vision
Final project for the computer engineering course: car detection system using artificial intelligence.
Final Project - šµ Smart Vision
Video analysis with artificial intelligence for vehicle model and license plate detection
- Investigation management / detection processing
- Next.js (Web Application)
- Firebase (Authentication, Cloud Firestore, Storage)
- Flask API (AI detection)
- JSON Server (Car database)
š Use Cases, System Flow, Architecture
System Flow
General System Architecture
š¦ How to use the project (instructions)
How to run (Open 3 terminals for better viewing)
1. Next.js
./smart-vision/nextjs >
npm run dev
2. Flask API
./smart-vision/car-detector-api >
python3 api.py
3. JSON Server
./smart-vision/nextjs >
npx json-server --watch db.json -p 3333
After starting the frontend and backend applications, simply access 'localhost' on port 3000 to be directed to the Next.js application and perform the necessary tests.
Development Order
- Obtain images to train the model - Roboflow
- Train Detection Model - YOLOv8 + OpenCV
- Web Application with Firebase Services - Next.js + Firebase
- Flask API - Python
- Obtain vehicle data - JSON Server
Academic advisor
š Links
š Roboflow - Car Models
š License Plate Detection using YOLOv8
š JSON Server
