🌙 LunarSight AI

A versatile and user-friendly visual analysis interface powered by Moondream VLM, built with Python and Streamlit.

🌟 Features

• 📝 Intelligent Image Captioning
• 🎯 Precise Object Detection with Bounding Boxes
• 📍 Object Pointing Capabilities
• 🔍 Natural Language Visual Querying
• 🎨 Clean, Tab-based User Interface
• 💾 Download Options for Analyzed Images
• 🔐 Secure API Key Management

🖼️ Demo

🔧 Prerequisites

• Python 3.11 or higher
• Web Browser
• Moondream API key from Moondream Console or download the model file from here

📥 Installation

1. Clone the repository:

git clone https://github.com/smaranjitghose/lunarsightai.git
cd lunarsightai

2. Create and activate virtual environment:

# Windows
python -m venv env
.\env\Scripts\activate

# Linux/Mac
python3 -m venv env
source env/bin/activate

3. Install required packages:

pip install -r requirements.txt

🚀 Usage

1. Start the application:

streamlit run app.py

2. Open your browser and navigate to:

http://localhost:8501

🎯 Example Use Cases

📝 Image Captioning

• Get detailed descriptions of any image
• Perfect for accessibility features
• Useful for content indexing

🎯 Object Detection

• "Detect all people in the image"
• "Find books on the shelf"
• "Locate electronic devices"

📍 Object Pointing

• "Point to the main subject"
• "Identify the location of logos"
• "Mark all faces in the image"

🔍 Visual Querying

• "What colors are dominant in this image?"
• "How many people are wearing glasses?"
• "Describe the environment in the image"

🛠️ Troubleshooting

Common Issues:

1. API Key Error

   • Verify API key is entered correctly
   • Check if API key has necessary permissions
   • Ensure API key is active

2. Image Upload Issues

   • Check if image format is supported (JPG, JPEG, PNG)
   • Ensure image size is reasonable
   • Verify image is not corrupted

3. Analysis Failures

   • Check internet connection
   • Verify API quota hasn't been exceeded
   • Ensure prompts are clear and specific

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the project
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Made with ❤️ by Smaranjit Ghose