Implementation BEGAN(Boundary Equilibrium Generative Adversarial Networks) by Keras.

Developed by these software versions.

• Mac OS Sierra: 10.12.4
• Python: 3.5.3
• Keras: 2.0.3
• Theano: 0.9.0
• Pillow: 4.1.0

pip install -r requirements.txt

You can use any square images. For example,

images in http://vis-www.cs.umass.edu/lfw/

[new] All images aligned with deep funneling 
(111MB, md5sum 68331da3eb755a505a502b5aacb3c201)

For convert command, install imagemagick.

brew install imagemagick

• ORIGINAL_IMAGE_DIR: dir of original JPG images
• TARGET_DIR: dir of after converted images

ORIGINAL_IMAGE_DIR=PATH/TO/ORIGINAL/IMAGE_DIR
CONVERTED_DIR=PATH/TO/CONVERTED/IMAGE_DIR

mkdir -p "$CONVERTED_DIR"
for f in $(find "$ORIGINAL_IMAGE_DIR" -name '*.jpg')
do
  echo "$f"
  convert "$f" -resize 64x64 ${CONVERTED_DIR}/$(basename $f)
done

PYTHONPATH=src python src/began/create_dataset.py "$CONVERTED_DIR"

PYTHONPATH=src python src/began/training.py

Images are generated in each epoch into generated/epXXX/ directory.

About 680 sec/epoch

• Linux

• Dataset: All images aligned with deep funneling (13194 samples)

• Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz

• GeForce GTX 1080

• Environment Variables

  KERAS_BACKEND=theano
  THEANO_FLAGS=device=gpu,floatX=float32,lib.cnmem=1.0

PYTHONPATH=src python src/began/generate_image.py

Generated images are outputted in generated/main/ directory.

Epoch 1
Epoch 25
Epoch 50
Epoch 75
Epoch 100
Epoch 125
Epoch 150
Epoch 175
Epoch 200
Epoch 215

more filters or layers?

Theano 0.9.0 CPU mode on Linux seems to have memory leak problem. See: keras-team/keras#5935