This open source project uses OpenAI 4o API and Streamlit to analyze jewellery images, predicting the type and relevant details. Originally developed for a demo of the Kalyan Jewellers Jewellery Inventory Management System, this repository is now publicly available for community contributions.
- Image recognition for different jewellery types.
- Extensible model architecture for continuous improvement.
- Easy setup with Python and Streamlit.
- Create your Python environment.
- Activate the environment.
- Install dependencies:
pip install -r requirements.txt
streamlit run main.py
Any jewellery image can be uploaded and the model will predict the jewellery type and related details
- Run the Streamlit app:
streamlit run main.py
- Upload a jewellery image.
- View the predicted jewellery type and details.
We welcome contributions! Please follow these steps:
- Fork the repository.
- Create a new branch (
git checkout -b feature-branch). - Commit your changes (
git commit -am 'Add new feature'). - Push to the branch (
git push origin feature-branch). - Create a new Pull Request.
This project is licensed under the MIT License. See the LICENSE file for details.
For any questions or suggestions, feel free to open an issue or contact the project maintainers.
- OpenAI for the API.
- Streamlit for the web framework.
- Kalyan Jewellers for the initial development support.
- All contributors for their valuable input.
This project is for educational and demonstration purposes. The predictions made by the model should not be used for any commercial purposes without further validation.