🌾 Rice Type Classifier using CNN

A Deep Learning–based application that classifies different types of rice grains from uploaded images.
Built with Python, TensorFlow/Keras, and Streamlit for an interactive web interface.

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🔗 Live Demo

👉 Visit Rice Grain Classifier Web App

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✨ Key Features

• 📤 Upload & Predict – Upload a rice grain image and get instant predictions
• 🔎 Top-K Results – Displays most probable varieties with confidence scores
• 🌾 Supported Varieties:
  • Arborio
  • Basmati
  • Ipsala
  • Jasmine
  • Karacadag
• 💻 Clean Web UI – Simple and interactive Streamlit interface
• ⚡ Real-Time Predictions – Powered by a custom-trained CNN

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📊 Dataset

• Custom-labeled dataset of different rice varieties (Arborio, Basmati, Ipsala, Jasmine, Karacadag)
• Preprocessing: resize, normalize, data augmentation
• Model trained on balanced rice image dataset

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🛠️ Tech Stack

Technology	Purpose
Python 3.8+	Core Programming
TensorFlow / Keras	Deep Learning (CNN Model)
Streamlit	Web App Interface
FastAPI (optional)	REST API Backend
OpenCV & PIL	Image Preprocessing
NumPy / Pandas	Data Handling
Matplotlib / Seaborn	Training Visualizations

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🔮 How It Works

1️⃣ Upload a rice grain image (JPG/PNG)
2️⃣ Image is preprocessed (resize → normalize)
3️⃣ CNN model predicts probabilities of each variety
4️⃣ App shows Top-K predictions with confidence scores

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🖼️ Web Interface Screenshots

🌾 Home Page (Uploading Image)

🔍 Resizing the uploaded image

📊 Prediction with Confidence Score

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🚀 Future Enhancements

• ➕ Add more rice varieties and expand dataset
• 📱 Mobile-friendly responsive UI
• ☁️ Deploy on Hugging Face Spaces, AWS, or GCP
• 🧩 Enable batch prediction for multiple grains

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🤝 Contributing

Contributions are welcome!

1. 🍴 Fork the repository
2. 🌱 Create a feature branch
3. 🚀 Submit a pull request

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👨‍💻 Author

Lomada Siva Gangi Reddy

• 🎓 B.Tech CSE (Data Science), RGMCET (2021–2025)
• 💡 Interests: Python | Machine Learning | Deep Learning | Data Science
• 📍 Open to Internships & Job Offers

📬 Contact Me:

• 📞 9346493592
• 💼 LinkedIn 🌐 GitHub

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📌 Project Workflow

flowchart LR
    A[Importing Libraries] --> B[Loading Image Dataset]
    B --> C[Preprocessing: Augmentation, Normalization]
    C --> D[Model Building: CNN]
    D --> E[Prediction Result]
    E --> F[Project Deployment: Streamlit / FastAPI]

    %% Styles
    style A fill:#FFD54F,stroke:#F57F17,stroke-width:2px,color:#000;
    style B fill:#4FC3F7,stroke:#0277BD,stroke-width:2px,color:#fff;
    style C fill:#AED581,stroke:#33691E,stroke-width:2px,color:#000;
    style D fill:#BA68C8,stroke:#4A148C,stroke-width:2px,color:#fff;
    style E fill:#FF8A65,stroke:#BF360C,stroke-width:2px,color:#fff;
    style F fill:#90CAF9,stroke:#0D47A1,stroke-width:2px,color:#000;

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