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.
- Does not produce samples accurate to condition yet
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
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.csvandimg_align_celeba
celebA = CelebA(output_size, channel, sample_size, batch_size, crop, data_dir=<path-to-data>)
python CGAN.py train
python CGAN.py test
