AI Crop Doctor for African Farmers
# 🌾 AI Crop Doctor
AI-powered crop disease detection web application for Nigerian farmers. Detect diseases in Maize, Cassava, and Tomatoes with instant results and treatment recommendations in multiple local languages.
## ✨ Features
- 🔍 **AI-Powered Detection**: Advanced machine learning models for accurate disease identification
- 📸 **Image Upload & Camera**: Upload images or take photos directly from your device
- 🌍 **Multi-Language Support**: Available in English, Hausa, Yoruba, Igbo, and Pidgin English
- 💊 **Treatment Recommendations**: Get expert treatment and prevention advice
- 📊 **Detection History**: Track your past detections
- 🎨 **Beautiful UI**: Modern, responsive design with smooth animations
- 📱 **Mobile-First**: Optimized for mobile devices
## 🚀 Quick Start
### Prerequisites
- Python 3.8+
- Node.js 18+
- npm or yarn
### Backend Setup
1. Navigate to the backend directory:
```bash
cd backend
```
2. Create a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Create necessary directories:
```bash
mkdir -p models data
```
5. Run the backend server:
```bash
python main.py
```
The API will be available at `
localhost`
### Frontend Setup
1. Navigate to the frontend directory:
```bash
cd frontend
```
2. Install dependencies:
```bash
npm install
```
3. Start the development server:
```bash
npm run dev
```
The frontend will be available at `
localhost`
## 📁 Project Structure
```
AI-Crop-Doctor/
├── backend/
│ ├── api/
│ │ └── routes/ # API endpoints
│ ├── models/ # ML model wrappers
│ ├── services/ # Business logic
│ ├── schemas/ # Pydantic models
│ ├── utils/ # Utilities
│ └── main.py # FastAPI app
├── frontend/
│ ├── src/
│ │ ├── pages/ # React pages
│ │ ├── components/ # Re …