An intelligent plant disease detection system using YOLOv8 and active learning.
Double-click start_dev.bat or run:
start_dev.batchmod +x start_dev.sh
./start_dev.shSee QUICKSTART.md for detailed instructions.
- Quick Start Guide - How to run the project
- Walkthrough - Development history and features
- Frontend: http://localhost:4200
- Backend API: http://localhost:8000
- API Docs: http://localhost:8000/docs
- Drag & drop ZIP upload for Label Studio exports
- Real-time training with GPU acceleration (CUDA)
- Live training logs streaming to UI
- Resizable layout with splitters
- System dashboard with run history
- Model rollback capability
- Fresh start / append mode for datasets
- Backend: FastAPI, PyTorch, YOLOv8, Ultralytics
- Frontend: Angular 17 (Standalone), TypeScript, SCSS
- ML: Active Learning, Object Detection
- Python 3.11
- Node.js 18+
- NVIDIA GPU with CUDA support (optional, falls back to CPU)