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The-Bricklayer7/
cropguard-system

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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

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.
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.

The-Bricklayer7/cropguard-system

CropGuard GH 🌿

Two ways to run it

Quick start (backend)

The-Bricklayer7/
cropguard-system