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Check out the documentation for more information.

CropGuard GH 🌿

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

Two ways to run it

  1. Instant / no install β€” 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 β€” see Settings / docs.

  2. Full production system β€” the real Chapter 3 stack:

    • backend/train.py β€” train the MobileNetV2 model
    • backend/app.py β€” FastAPI inference server
    • backend/recommendations.json β€” treatment knowledge base
    • frontend/src/CropGuard.jsx β€” React frontend

Quick start (backend)

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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