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A plant disease detector which detects the disease of the crops. It was my first time training a model and even using a flask backend.

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🌿 Plant Disease Detection

Overview

The Plant Disease Detection project is a web application aimed at helping farmers and agricultural experts diagnose plant diseases through images of plant leaves. Leveraging a deep learning model trained on a dataset of plant leaf images, the tool quickly and accurately identifies diseases, providing timely insights to prevent disease spread and enhance crop health.

✨ Features

  • Image Upload: Users can upload images of plant leaves via a user-friendly interface.
  • Disease Prediction: The app processes uploaded images to predict the type of disease affecting the plant.
  • Class Labels: Identifies 38 different plant diseases, including healthy plants.
  • Backend Processing: Flask-powered backend handles image processing and model inference.

🛠️ Technical Details

  • Frontend: Built with React, enabling users to upload images and view predictions.
  • Backend: Flask backend manages HTTP requests, image processing, and model interactions.
  • Model:Trained with Kaggle datasets using tensorflow and mobilenet pretrained model.
  • CORS: Flask-CORS enabled for seamless frontend-backend communication.

🔧 Setup

To get started with this project:

  1. Clone the repository:

    git clone  https://github.com/ESR-style/Crop-Disease-ml.git
  2. Backend Setup:

        cd backend
        python app.py
  3. Frontend Setup:

        npm install
        npm run dev

🚀 Usage

  • Open the web application in your browser.
  • upload an image of a plant leaf.
  • Click the "Upload" button to submit the image.
  • View the predicted disease and take appropriate action.

📋 Class Labels

The model can identify the following plant diseases:

  • Apple: Apple scab, Black rot, Cedar apple rust, Healthy
  • Blueberry: Healthy
  • Cherry: Powdery mildew, Healthy
  • Corn: Cercospora leaf spot, Common rust, Northern Leaf - Blight, Healthy
  • Grape: Black rot, Esca (Black Measles), Leaf blight, Healthy
  • Orange: Haunglongbing (Citrus greening)
  • Peach: Bacterial spot, Healthy
  • Pepper: Bacterial spot, Healthy
  • Potato: Early blight, Late blight, Healthy
  • Raspberry: Healthy
  • Soybean: Healthy
  • Strawberry: Leaf scorch, Healthy
  • Tomato: Bacterial spot, Early blight, Late blight, Leaf Mold, Septoria leaf spot, Spider mites, Target Spot, Tomato Yellow Leaf Curl Virus, Tomato mosaic virus, Healthy

Training Process

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A plant disease detector which detects the disease of the crops. It was my first time training a model and even using a flask backend.

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