🌱 PlantCare AI

An AI-powered Plant Disease Detection System built using Deep Learning and the PlantVillage Dataset.

The system detects plant diseases from uploaded leaf images and provides:

• Disease Prediction
• Confidence Score
• Symptoms
• Treatment Suggestions
• Prevention Methods

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Features

✅ 38 Plant Disease Classes
✅ MobileNetV2 Deep Learning Model
✅ Flask Backend API
✅ Interactive Frontend (HTML, CSS, JavaScript)
✅ Disease Confidence Visualization
✅ Dark Mode UI
✅ Drag & Drop Image Upload
✅ Real-time Disease Prediction

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Technologies Used

• Python
• TensorFlow / Keras
• MobileNetV2
• Flask
• HTML
• CSS
• JavaScript

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Dataset

PlantVillage Dataset

Contains 38 plant disease classes across multiple crops including:

• Apple
• Tomato
• Potato
• Corn
• Grape
• Strawberry
• Peach
• Pepper
• Squash
• Soybean

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Model Architecture

Transfer Learning using:

MobileNetV2

Architecture:

model = Sequential([
    base_model,
    GlobalAveragePooling2D(),
    Dropout(0.3),
    Dense(128, activation='relu'),
    Dropout(0.3),
    Dense(15, activation='softmax')
])

Project Screenshots

Home Page

Disease Detection

Prediction Results

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Installation

Clone repository:

git clone https://github.com/yourusername/PlantCare-AI.git

Install dependencies:

pip install -r requirements.txt

Run Flask server:

python app.py

Open browser:

http://localhost:5000

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Sample Images

Example plant leaf images are included in the project for testing.

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Future Improvements

• Live camera detection
• Multi-language support
• Disease severity estimation
• Deployment on cloud
• Mobile app integration

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