frankashax1-dotcom/petcheck

AI-powered veterinary care for Uganda pet owners # 🐾 PetCheck — AI-Powered Veterinary Web App **UICT Group 46 | Final Year Project | Diploma in Computer Science** --- ## Project Structure ``` petcheck/ ├── app.py ← Main Flask application ├── schema.sql ← MySQL database setup ├── requirements.txt ← Python dependencies ├── .env ← Environment variables (edit this!) ├── model/ │ ├── predict.py ← AI prediction logic │ ├── train.py ← Model training script │ └── petcheck_model.pth ← Trained model (generated after training) ├── templates/ │ ├── base.html ← Base layout │ ├── index.html ← Home page │ ├── upload.html ← Upload & diagnose page │ ├── results.html ← Diagnosis results page │ └── vets.html ← Vet finder page ├── static/ │ ├── css/style.css ← All styles │ └── js/main.js ← Frontend JavaScript └── uploads/ ← Uploaded pet images (auto-created) ``` --- ## ⚙️ Setup Instructions ### Step 1 — Create & activate virtual environment ```bash python -m venv venv venv\Scripts\Activate.ps1 # Windows PowerShell # OR source venv/bin/activate # Mac/Linux ``` ### Step 2 — Install dependencies ```bash pip install -r requirements.txt ``` ### Step 3 — Set up MySQL database 1. Open MySQL Workbench or phpMyAdmin 2. Run the contents of `schema.sql` 3. Edit `.env` with your MySQL password ### Step 4 — Run the app ```bash python app.py ``` Open your browser at: **http://127.0.0.1:5000** --- ## 🤖 Training the AI Model ### Step 1 — Collect images Create this folder structure and add pet images: ``` dataset/ train/ Healthy/ ← at least 50 images per class Skin Infection/ Eye Infection/ Ear Infection/ Ringworm/ Wounds/ Obesity/ Dental Disease/ val/ Healthy/ ← about 20% of your total images Skin Infection/ ... ``` ### Step 2 — Train the model ```bash python model/train.py ``` This will train for 20 epochs and save the best mod …