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A Tensorflow implementation of a Conditional GAN for generating human faces from a text description.

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Sketch-Artist

Overview

A Tensorflow implementation of a Conditional GAN (Generative Adversarial Network) for generating human faces from a text description. This project was created for my CSC 340 (Artificial Intelligence) final project.

TO-DO

  • Does not produce samples accurate to condition yet

Label Vector

The label is a vector with 5 indices each corresponding to a different facial feature

The values for each feature can either be 1 or -1

  • Black hair
  • Blonde hair
  • Brown hair
  • Male
  • Beard

Generator

Generator

Discriminator

Discriminator

Installation

Git clone the repository and cd into the directory

git clone https://github.com/greerviau/Sketch-Artist.git && cd Sketch-Artist

Download the CelebA dataset here and extract

In CGAN.py add data directory to CelebA object

  • Make sure that directory contains list_attr_celeba.csv and img_align_celeba
celebA = CelebA(output_size, channel, sample_size, batch_size, crop, data_dir=<path-to-data>)

Usage

python CGAN.py train
python CGAN.py test

Results

After 100 epochs

epoch_100_batch_310

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A Tensorflow implementation of a Conditional GAN for generating human faces from a text description.

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