About The Project

LeafLens

a web app that helps you detect whether the plant is healthy or infected. If an infection is detected, the app identifies the specific disease and provides a description along with recommended cures with a user-friendly interface.

Technologies Used

• Backend: Django, Django REST Framework
• Ai Model: MobileNet
• Frontend: React
• Database: Mysql

Setup

Backend (Django)

1. Clone the repository to your local machine:

   git clone https://github.com/BodaTech/PLANTS_DISEASE_DETECTION_WEBAPP.git

2. Navigate to the backend directory:

   cd Backend

3. Virtual environment

   • create a virtual environment py -m venv venv
   • activate it venv/Scripts/activate ( source venv/bin/activate in macOS/Linux)

4. Install dependencies:

   pip install -r requirements.txt

5. Apply migrations:

   config your database in core/settings.py

   py manage.py migrate

6. Seed the database located in plant\data\

   py manage.py loaddata plant\data\plants.json

   py manage.py loaddata plant\data\diseases.json

   py manage.py loaddata plant\data\cures.json

   py manage.py loaddata plant\data\cures_diseases.json

7. Run the Django development server:

   py manage.py migrate

Frontend (React)

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install

3. Start the development server:

   npm run dev

Warning

The model can make false prediction in some cases and can detect only these disease categories:

• Apple
  • Apple scab
  • Black rot
  • Cedar apple rust
  • Healthy
• Corn (maize)
  • Cercospora leaf spot (Gray leaf spot)
  • Common rust
  • Northern Leaf Blight
  • Healthy
• Grape
  • Black rot
  • Esca (Black Measles)
  • Leaf blight (Isariopsis Leaf Spot)
  • Healthy
• Potato
  • Early blight
  • Late blight
  • Healthy
• Tomato
  • Bacterial spot
  • Early blight
  • Late blight
  • Leaf Mold
  • Septoria leaf spot
  • Spider mites (Two-spotted spider mite)
  • Target Spot
  • Tomato Yellow Leaf Curl Virus
  • Tomato mosaic virus
  • Healthy