evanhu1/pytorch-CelebA-faCeGAN
Deep convolutional conditional GAN implementation with CelebA dataset that allows for generation of custom faces according to textual input.
This project helps graphic designers, content creators, or game developers generate unique human faces based on text descriptions. You provide words describing facial features (like 'blond hair', 'smiling', 'sunglasses'), and it produces corresponding face images. It's ideal for anyone needing to quickly create diverse, customized facial imagery without manual drawing or photography.
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Use this if you need to generate diverse synthetic human faces programmatically using simple text prompts.
Not ideal if you need to generate faces of specific, recognizable individuals or require highly realistic images indistinguishable from real photos for commercial use.
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Language
Python
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Last pushed
Jun 15, 2021
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