bonjour-npy/UndergraduateDissertation
Undergraduate Dissertation of Guilin University of Electronic Technology
This project helps graphic designers and digital artists adapt existing image generation models to new styles with minimal effort. You provide a source image generator (like StyleGAN) and specify a target style using text prompts (e.g., "a Disney character"). The system then outputs a modified generator capable of creating images in that new style, making it easier to explore different artistic directions.
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Use this if you need to quickly modify an existing generative image model to produce images in a new, distinct visual style guided by text descriptions.
Not ideal if you're looking to generate images from scratch without adapting a pre-existing generative model, or if your primary goal is fine-tuning a model for specific object recognition tasks.
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Language
Python
License
MIT
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Last pushed
May 24, 2024
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