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403f212 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | # 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`**.
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