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Check out the documentation for more information.
CropGuard GH πΏ
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
Instant / no install β open
cropguard.htmlon 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.Full production system β the real Chapter 3 stack:
backend/train.pyβ train the MobileNetV2 modelbackend/app.pyβ FastAPI inference serverbackend/recommendations.jsonβ treatment knowledge basefrontend/src/CropGuard.jsxβ 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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