angeluriot/Generative_adversarial_network
A deep learning model that can create high quality images by training on a dataset.
Implements a style-based architecture combining equalized learning rates, wavelet transforms, and adaptive discriminator augmentation across both generator and discriminator networks. Built on PyTorch with training stability features including path length regularization, gradient penalty, and Fréchet Inception Distance (FID) evaluation. Supports multi-dataset training with checkpoint resumption and includes latent space projection, style mixing, and interpolation capabilities for advanced image synthesis control.
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Python
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MIT
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Jan 14, 2025
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