qbxlvnf11/conditional-GAN
Pytorch implementation of Conditional-GAN (CGAN)
This project helps machine learning practitioners generate images with specific characteristics, rather than just random ones. You provide it with existing images and labels (like 't-shirt' or 'trouser'), and it learns to produce new, distinct images that match those given labels. This is ideal for researchers or developers working on synthetic data generation for image-based tasks.
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Use this if you need to create new, labeled images that are visually similar to a dataset you already possess.
Not ideal if you need to generate highly photorealistic images or if you don't have labeled data to train the model.
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Jupyter Notebook
License
MIT
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Last pushed
Jul 27, 2022
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