Generating cartoon faces using a Deep Convolutional Generative Adversarial Network (DCGAN).

Dataset

The dataset is taken from here. processed using a face detector based on the repo https://github.com/nagadomi/lbpcascade_animeface. The dataset contains images of size 64 by 64 pixels.

Objective

• The objective of the project is to generate images of Cartoon faces using a Deep Convolutional GAN.
• The DCGAN has two networks, the 'generator' and the 'discriminator'.
• The generator takes in a random vector which then uses transposed convolutions to generate an image out of it.
• The discriminator is a Convolutional network which then classifies whether an image is real or fake. It takes in samples of images from the dataset and also images generated by the generator.
• Both networks try to improve each other's performance through backpropagation.