# CropGuard GH 🌿

Image-Based Crop Disease Detection System for Smallholder Farmers in Ghana.
Final Year Project — Oppong David, BTech Computer Technology, Kumasi Technical University.

## Two ways to run it

1. **Instant / no install** — open `cropguard.html` on any phone or browser.
   Covers all 14 Ghanaian crops via the model; works offline as an estimate (English + Twi). Can also connect
   to the trained model — see Settings / docs.

2. **Full production system** — the real Chapter 3 stack:
   - `backend/train.py` — train the MobileNetV2 model
   - `backend/app.py` — FastAPI inference server
   - `backend/recommendations.json` — treatment knowledge base
   - `frontend/src/CropGuard.jsx` — React frontend

## Quick start (backend)

```bash
cd backend
pip install -r requirements.txt
python train.py --data ./data          # train (needs a dataset)
uvicorn app:app --port 8000            # serve
```

Full details, API reference and report mapping: **`docs/DOCUMENTATION.md`**.