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dcgan-svhn

Cycle GAN Winter-Summer transformation. The code is based on the miniproject of the chapter on GAN of the Udacity Deep Learning course.

Content

The notebook implements the following steps

  • Load in the data
  • Pre-process the data reducing the size of the images to 128x128x3
  • Define the Generator and Discriminator architectures
  • Define loss function and optimizer
  • Train the networks, save after training and generate new images

Features

If available, PyTorch trains on GPU.

References

Udacity github

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