Plant Leaf Health Classifier 🌿

This project delivers a Streamlit web application for classifying plant leaf health. It uses traditional machine learning with handcrafted image features and integrates an AI assistant powered by Google's Gemini model.

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Live App : - https://plant-species-classification-csi.streamlit.app

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Technologies Used 💻

• Python: Core programming language.
• Streamlit: For building the interactive web application.
• OpenCV & Scikit-image: For image processing and feature extraction.
• Pandas & NumPy: Data handling.
• Scikit-learn: Machine learning models.
• Joblib: Model saving/loading.
• Plotly Express: Data visualization.
• Google Generative AI: Powers the AI assistant (gemini-1.5-flash).

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Methodology ⚙️

1. Feature Extraction

• Handcrafted features are extracted from leaf images:
  • Color Features (HSV): Mean and standard deviation of color channels.
  • Texture Features (GLCM): Measures like Contrast, Homogeneity, and Correlation to identify surface patterns.

2. Machine Learning Model

• Algorithm: A Random Forest Classifier is used to predict plant health status (healthy, multiple diseases, rust, scab).
• Training & Saving: The model is trained on extracted features and saved for use in the app.

3. Application Features

• Exploratory Data Analysis (EDA): Visualize dataset characteristics.
• Image Classification: Upload a leaf image to get an immediate health prediction with confidence.
• AI Assistant: Ask general questions about plant care and diseases.

How to run it on your own machine

1. Install the requirements

   $ pip install -r requirements.txt
   

2. Run the app

   $ streamlit run streamlit_app.py
   

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