Omni-Zero-Couples
O
Omni Zero Couples
Overview :
Omni-Zero-Couples is a zero-shot stylized couple portrait model utilizing the diffusers pipeline. It leverages deep learning technology to generate couple portraits in a specific artistic style without the need for predefined style samples. This technology has broad application prospects in the fields of artistic creation, personalized gift-making, and digital entertainment.
Target Users :
The target audience includes artists, designers, photographers, couples, and anyone interested in personalized portrait creation. This technology is especially suited for users who need to quickly generate portraits in a particular style without spending excessive time on manual adjustments.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 59.6K
Use Cases
Artists use Omni-Zero-Couples to create personalized artistic works.
Designers utilize the model to customize couple portraits for clients in specific styles.
Photographers offer this as a value-added service to clients post-shoot, enhancing customer satisfaction.
Features
Zero-shot creation: Generate stylized portraits without predefined style samples.
Support for multiple identities and styles: Capable of handling portraits with various identities and artistic styles.
HuggingFace Spaces integration: Users can directly use the model on HuggingFace Spaces.
Replicate platform support: The model can be run on the Replicate platform.
Open-source code: All source code is publicly available on GitHub, facilitating community contributions and improvements.
Flexible input: Supports flexible data input via scripts such as app.py and predict.py.
Continuous updates: The project is regularly updated to adapt to the latest technologies and user needs.
How to Use
1. Visit the GitHub project page to clone or download the source code.
2. Ensure that Python and the necessary dependencies are installed on your system.
3. Follow the guidelines in the README.md document to install the required Python packages.
4. Prepare the input images of couples for the portraits.
5. Use the app.py or predict.py scripts to input images as directed in the documentation.
6. Run the script, and the model will generate stylized couple portraits.
7. Review the generated portraits and proceed with any required post-processing or sharing.
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