DiscoGAN in Pytorch

Study Friendly Implementation of DiscoGAN in Pytorch

More Information: Original Paper

Implemenation based on Official Implementation, but Simplified.

• GAN: [Pytorch][Tensorflow]

• DCGAN: [Pytorch][Tensorflow]

• InfoGAN: [Pytorch][Tensorflow]

• Pix2Pix: [Pytorch][Tensorflow]

• DiscoGAN: [Pytorch][Tensorflow]

1. Environments

• Ubuntu 16.04

• Python 3.6 (Anaconda)

• Pytorch 0.2.0

• Torchvision 0.1.9

• PIL

• cv2 (OpenCV) (pip install python-opencv)

2. Code Description

• discogan.py: Main Code

• discogan_test.py: Test Code after Training

• network.py: Generator and Discriminator

• db/download.sh: DB Downloader (Edges/Shoes/Handbags)

• db/download.py: DB Downloader (Facescrub)

3. Networks and Parameters

3.1 Hyper-Parameters

• Image Size = 64x64

• Batch Size = 64

• Learning Rate = 0.0002

• Weight Decay = 0.00001

• Adam_beta1 = 0.5

• Loss Weights: See the code

• Scheduling: See the code

3.2 Generator Networks (network.py)

3.3 Discriminator Networks (network.py)

4. DB Download

4.1 Edges2Shoes / Edges2Handbags / Handbags2Shoes

./db/download.sh dataset_name

dataset_name can be one of [edges2shoes, edges2handbags]

You can do handbags2shoes using both datasets.

• edges2shoes : 600x500, 1096 for Train, 1098 for Val

• edges2handbags : 256x256, 138567 for Train, 200 for Val

4.2 Facescrubs

python ./db/download.py

This code downloads face image independently. So there are some problems.

After download images 10~20k,

You should remove some broken images MANUALLY. :<

• facescrub/actors/face : Various Size

• facescrub/actresses/face : Various Size

5. Train

5.1 edges2shoes (or handbags)

python discogan.py --task edges2shoes #(or handbags)

5.2 Handbags2Shoes

python discogan.py --task handbags2shoes --starting_rate 0.5

5.3 Facescrubs

python discogan.py --task facescrubs

6. Test

After finish training, saved models are in the ./models directory.

python discogan_test.py --task taskname --num_epochs N --batctSize M

• batchSize means test sample size.

• num_epochs is the parameter which model will be used for test.

Test results will be saved in ./test_result

7. Results

[Input A | A to B | A to B to A]

[Input B | B to A | B to A to B]

Edges to Shoes, Shoes to Edges (20 Epochs)

Handbags to Shoes, Shoes to Handbags (30 Epochs)

Face: Men to Women, Women to Men (150 Epochs)