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gan-cgan

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    GAN & cGAN tutorial.

    Filipe PENNA CERAVOLO SOARES

    Part1: DC-GAN

    • In this part, generative adversarial network (GAN) has been trained to generate new handwritten digits, after feeding it with pictures from the MNIST database
    • To do so, the DCGAN tutorial of pytorch has been followed. This tutorial generate new celebrities after showing it pictures of many real celebrities.
    • To adapt this tutorial to the MNIST database, the most relevant change in its implematation reflects the change of number of channels in the training images (from 3 [RGB] to 1 [Black and White]).

    Part2: Conditional GAN (cGAN)