ObjectSight AI 👁️

A powerful and intuitive image analysis interface powered by Google's Gemini Flash 2, built with Python and Streamlit.

🌟 Features

• 🎯 Real-time object detection and localization
• 📦 Clear bounding box visualization with enhanced labels
• 🔄 Support for common image formats (JPG, JPEG, PNG)
• 🎨 Clean and minimalist user interface
• 💾 Download capability for analyzed images
• 🔑 Secure API key management

🖼️ Snapshot

🔧 Prerequisites

• Python 3.10 or higher
• A web Browser
• Google API key from Google AI Studio

📥 Installation

1. Clone the repository:

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

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 ObjectSight AI:

streamlit run app.py

2. Open your browser and navigate to:

http://localhost:8501

💡 Quick Start Guide

1. Enter your Google API key in the sidebar
2. Upload an image using the file uploader
3. Write a descriptive prompt about what to analyze
4. Click "Run!" to start the analysis
5. View results and download the analyzed image if desired

🎯 Example Prompts

"Identify and locate all objects in this image"
"Find and label all people and furniture"
"Detect all electronic devices"
"Locate and identify different types of vehicles"

🛠️ 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
   • Ensure image size is under limit
   • Verify image is not corrupted

3. Analysis Failures

   • Check internet connection
   • Verify API quota hasn't been exceeded
   • Ensure prompt is 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.

---

Made with ❤️ by Smaranjit Ghose