--- title: FarmEyes emoji: 🌱 colorFrom: green colorTo: yellow sdk: docker app_port: 7860 pinned: false suggested_hardware: cpu-basic --- # 🌱 FarmEyes **AI-Powered Crop Disease Detection for African Farmers** [![Built for Awarri Challenge](https://img.shields.io/badge/Built%20for-Awarri%20Challenge%202025-green)](https://awarri.com) [![N-ATLaS Powered](https://img.shields.io/badge/Powered%20by-N--ATLaS-blue)](https://huggingface.co/NCAIR1/N-ATLaS) --- ## 🎯 What is FarmEyes? FarmEyes is an AI application that helps African farmers identify crop diseases and get treatment recommendations in their native languages. Simply upload a photo of your crop, and FarmEyes will: 1. **Detect** the disease using computer vision (YOLOv11) 2. **Diagnose** the condition with severity assessment 3. **Translate** all information to your preferred language 4. **Chat** with an AI assistant for follow-up questions --- ## 🌍 Supported Languages | Language | Native Name | |----------|-------------| | πŸ‡¬πŸ‡§ English | English | | πŸ‡³πŸ‡¬ Hausa | Yaren Hausa | | πŸ‡³πŸ‡¬ Yoruba | ÈdΓ¨ YorΓΉbΓ‘ | | πŸ‡³πŸ‡¬ Igbo | Asα»₯sα»₯ Igbo | --- ## 🦠 Detectable Diseases | Crop | Diseases | |------|----------| | 🌿 **Cassava** | Bacterial Blight, Mosaic Virus | | 🍫 **Cocoa** | Monilia Disease, Phytophthora Disease | | πŸ… **Tomato** | Gray Mold Disease, Wilt Disease | --- ## πŸš€ How to Use ### Step 1: Select Language Choose your preferred language from the welcome screen. ### Step 2: Upload Image Take a photo of the affected crop leaf and upload it. ### Step 3: View Results - Disease name and confidence score - Severity level (Low/Moderate/High/Critical) - Treatment recommendations - Cost estimates in Nigerian Naira (₦) ### Step 4: Ask Questions Use the chat feature to ask follow-up questions about the diagnosis. --- ## πŸ”§ Technology Stack | Component | Technology | |-----------|------------| | **Disease Detection** | YOLOv11 (trained on African crops) | | **Language Model** | N-ATLaS (Nigerian multilingual AI) | | **Speech-to-Text** | OpenAI Whisper | | **Backend** | FastAPI | | **Frontend** | Custom HTML/CSS/JS | --- ## πŸ“± Features - βœ… **Image Upload** - Drag & drop or click to upload - βœ… **Real-time Detection** - Results in seconds - βœ… **Multilingual Support** - 4 Nigerian languages - βœ… **Voice Input** - Speak your questions - βœ… **Text-to-Speech** - Listen to responses - βœ… **Treatment Advice** - Practical farming guidance - βœ… **Cost Estimates** - In Nigerian Naira --- ## ⚠️ First Startup Notice **Please be patient on first use!** The N-ATLaS language model (~4.92GB) is downloaded automatically on first startup. This may take **5-15 minutes** depending on connection speed. Subsequent uses will be much faster. --- ## πŸ† About FarmEyes was built for the **Awarri Developer Challenge 2025** to address the critical need for accessible agricultural AI in Africa. **The Problem:** - 20-80% crop losses annually due to diseases - Only 1 extension worker per 10,000 farmers (FAO recommends 1:1,000) - Agricultural knowledge locked in English **Our Solution:** - AI-powered disease detection accessible via smartphone - Native language support through N-ATLaS - Practical, localized treatment recommendations --- ## πŸ‘¨β€πŸ’» Developer **Fola-AI** - πŸ€— HuggingFace: [@Fola-AI](https://huggingface.co/Fola-AI) --- ## πŸ“„ License Apache 2.0 --- ## πŸ™ Acknowledgments - [NCAIR](https://ncair.nitda.gov.ng/) for N-ATLaS model - [Ultralytics](https://ultralytics.com/) for YOLOv11 - [HuggingFace](https://huggingface.co/) for hosting - [Awarri](https://awarri.com/) for the challenge opportunity --- *Built with ❀️ for African Farmers*