Logo Lanfrica

PAMify001/BotanIQ

Domaine:

agriculture

Type de record:

software
Créateur:
PAM
Hôte:
AI-powered crop disease detection app with TTS feature for local African farmers # BotanIQ - Tomato Plant Disease Detection AI An AI-powered mobile-friendly web application for identifying tomato plant diseases using computer vision and machine learning. Perfect for farmers, gardeners, and agricultural professionals. ## 🌟 Features - **Disease Detection**: Identifies 5 tomato diseases with high accuracy - **Mobile Optimized**: Works on phones, tablets, and desktops - **Offline Capable**: Runs completely offline after initial setup - **Voice Feedback**: Audio descriptions of diagnoses - **Real-time Analysis**: Instant results from leaf photos - **User-friendly Interface**: Simple upload and analyze workflow ## 📱 Mobile Usage ### ✅ **Works on Mobile Phones** BotanIQ is designed to work seamlessly on mobile devices: - **Camera Integration**: Take photos directly from your phone's camera - **Touch Optimized**: Large buttons and mobile-friendly interface - **Responsive Design**: Adapts to any screen size - **Fast Loading**: Optimized for mobile networks and data usage ### 🔄 **Offline Mobile Usage** **Yes, BotanIQ works completely offline on mobile devices!** #### What Works Offline: - ✅ Disease detection and analysis - ✅ Voice feedback (on supported mobile browsers) - ✅ All core functionality - ✅ Saved model predictions #### What Requires Internet (One-time): - ⏳ Initial app loading and model download - ⏳ Streamlit server connection (if running remotely) ### 📲 **Mobile Deployment Options** #### Option 1: Local Network Access (Recommended) ```bash # Run on your computer streamlit run scripts/app.py # Access from phone via local network: # your_computer_ip ``` #### Option 2: Cloud Deployment Deploy to services like: - **Streamlit Cloud** (free tier available) - **Heroku** - **AWS/GCP/Azure** - **Railway** or **Render** **Recommended cloud build/start commands** ```bash pip install --upgrade pip pip install -r requirements.txt streamlit run scripts/app.py --server.port $PORT --server.headless true --server.address 0.0.0.0 ``` …