Art and Design DCGAN in Tensorflow

Modified version of Taehoon Kim’s tensorflow implementation of DCGAN https://carpedm20.github.io/faces/ with a focus on generating paintings and soon graphic design.

It includes a script to scrape WikiArt, one to uniform images in a format that the Dcgan can work with and a Google Colab Notebook to train it on a free GPU.

Prerequisites

• Python 2.7 or Python 3.3+
• Tensorflow 0.12.1
• SciPy
• pillow

You can find a zip of my dataset in: https://drive.google.com/open?id=17Cm2352V9G1tR4kii5yHI_KUkevLC67_

Checkpoints here: https://drive.google.com/open?id=1yABe4LsWeDQz5p5IO2AYJPosGOgqtD2Z

Colab Notebook: https://colab.research.google.com/drive/18RglimpA1JH7bRbTXtxx9fAbDl60sFVQ#scrollTo=YLBwMdxMW3PR

You will have to convert the images to RGB and resize them with: uniform.py by changing path with your directory

Train your own dataset:

$ mkdir data/DATASET_NAME
... add images to data/DATASET_NAME ...
$ python main.py --dataset DATASET_NAME --train
$ python main.py --dataset DATASET_NAME
$ # example
$ python main.py --dataset=eyes --input_fname_pattern="*_cropped.png" --train

If your dataset is located in a different root directory:

$ python main.py --dataset DATASET_NAME --data_dir DATASET_ROOT_DIR --train
$ python main.py --dataset DATASET_NAME --data_dir DATASET_ROOT_DIR
$ # example
$ python main.py --dataset=eyes --data_dir ../datasets/ --input_fname_pattern="*_cropped.png" --train