AI Crop Disease Detector

The AI-Powered Crop Disease Detector is a tool that helps farmers quickly identify diseases on their crops just by taking a picture. Once a farmer uploads a photo, the system analyzes it and gives a clear diagnosis, shows how serious the disease is, and suggests practical solutions they can use. It also helps farmers find nearby agro-dealers or experts and keeps a record of all previous scans. The goal is to make it easier for farmers to protect their crops, reduce losses, and improve their harvests using easy, accessible technology.

Demo Video

Watch here: https://www.youtube.com/watch?v=pu_mLWLz-ZQ

Project Structure

 crop-disease-detector/
├──  backend/
│   ├── api/ (models, views, serializers)
│   ├── cropdetector/ (settings, urls, ai_model.py)
│   ├── media/
│   └── manage.py
│
└──  frontend/
    ├── src/
    │   ├── api/axios.js
    │   ├── components/ (Navbar, Footer, etc.)
    │   ├── pages/ (Dashboard, Upload, Admin)
    │   ├── App.jsx / main.jsx
    └── package.json

Setup Instructions

1️1 Clone the Repository

git clone https://github.com/justineneema/crop-disease-detector.git
cd crop-disease-detector
cd frontend
cd backend

2️2 Install Dependencies

# Frontend
cd frontend
npm install

# Backend
cd backend
pip install -r requirements.txt

3️3 Run the Application

# Frontend
cd frontend
npm install
npm run dev

# Backend
cd backend
python3 -m venv venv
source venv/bin/activate
for window
venv\script\activate
pip manage.py migrate
python manage.py runserver

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Overview

• The AI Crop Disease Detector uses advanced machine learning to diagnose plant diseases through image uploads.
• It provides instant results, treatment guidance, appointment booking, and expert validation — all in one easy-to-use web app.

Key Features

AI Disease Detection — Upload crop photos and get real-time diagnosis.
Role-Based Access — Farmers, Experts, Agro-dealers, and Admins.
Smart Treatment Advice — Step-by-step recovery instructions.
Admin Dashboard — Manage users, monitor reports, and update models.
phone call — Connect with agro-dealers or field experts.
Expert Validation — Professionals can verify or adjust AI predictions.

Tech Stack

Frontend

• React 18 — UI framework
• Vite — Fast bundler & dev server
• Tailwind CSS — Modern responsive design
• Axios — API communication
• Framer Motion — Beautiful animations

Backend

• Django 5.2 + Django REST Framework - API logic
• TensorFlow - AI model integration
• Pillow - Image processing
• JWT Auth - Secure login system
• PostgreSQL - Database layer

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4 Requirements

Functional

• Image upload and AI detection
• Treatment recommendation
• Role-based access control
• Appointment scheduling on call
• Historical records & reporting
• admin management

Non-Functional

• JWT-based security
• Fast AI processing (<10s perimage)
• Mobile-friendly, bilingual UI
• Scalable architecture 95% uptime - reliability

Done by Justine Neema

License

This project is licensed under the MIT License.