AI-Based Cattle Disease Detection System for Ghanaian Farmers and Traders Final Year Project — University of Ghana, Department of Computer Science (2025/2026)
# 🐄 CattleCare AI
**AI-Based Cattle Disease Detection System for Ghanaian Farmers and Traders**
Final Year Project — University of Ghana, Department of Computer Science (2025/2026)
CattleCare AI helps smallholder farmers and cattle traders get an early, AI-assisted read on three common conditions — **Foot-and-Mouth Disease (FMD)**, **Lumpy Skin Disease (LSD)**, and **Healthy** — from a photo, a description of observed symptoms, or both. It is built around a Gemma 3 vision-language model fine-tuned specifically on Ghanaian cattle disease presentations, served through a Streamlit interface.
> ⚠️ **Disclaimer:** This is a decision-support tool, not a replacement for veterinary diagnosis. Always consult a qualified veterinarian for confirmation and treatment.
---
## Features
- **Three ways to get a diagnosis:**
- 📷 Upload a photo of the animal
- 📝 Describe symptoms (checkboxes + free text)
- 🔗 Both together, for the most accurate result
- **Input validation before diagnosis** — a lightweight classification layer checks that an uploaded photo actually shows cattle and that a symptom description is real and observable, rather than letting the model guess at chitchat, junk input, or irrelevant images.
- **Transparent source attribution** — the UI shows exactly which inputs (image / symptom description) were actually used for a given diagnosis.
- **Symmetric fallback logic** — a bad photo will not derail a real symptom description, and vice versa; the app automatically falls back to whichever input is actually usable.
- **Model comparison mode** — base model vs. fine-tuned model, side by side, on the same input.
- **Disease reference guide** — a built-in tab covering symptoms, spread, and recommended actions for each condition.
- **Emergency contacts** — direct numbers for the Ghana Veterinary Service and Animal Research Institute surfaced alongside every diagnosis.
---
## How It Works
```
┌─────────────────────┐
Photo + Symptoms │ Input Validation │ gpt-4o …