PyTorch Implementation of ECCV 2020 Spotlight TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images

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Deep Learning TuiGAN-PyTorch
Overview

TuiGAN-PyTorch

Official PyTorch Implementation of "TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images" (ECCV 2020 Spotlight)

TuiGAN's applications

TuiGAN can be use for various computer vision tasks ranging from image style transfer to object transformation and appearance transformation:

Usage

Install dependencies

python -m pip install -r requirements.txt

Our code was tested with python 3.6 and PyToch 1.0.0 or 1.2.0

Train

To train TuiGAN model on two unpaired images, put the first training image under datas/task_name/trainA and the second training image under datas/task_name/trainB, and run

python train.py --input_name 
   
     --root

For example,

python train.py --input_name apple --root datas/apple

Comparison Results

General Unsupervised Image-to-Image Translation

Image Style Transfer

Animal Face Translation

Painting-to-Image Translation

More Results

Art Style Transfer

Photorealistic Style Transfer

Animal Face Translation

Comments
  • PatchSize

    PatchSize

    Hello, I read that the patchsize of the paper is 11×11, but the image patch obtained by the discriminator in the code is a whole picture. Can you explain it to me? Thank you

    opened by YQX1996 0
  • RuntimeError: The size of tensor a (314) must match the size of tensor b (107) at non-singleton dimension 3

    RuntimeError: The size of tensor a (314) must match the size of tensor b (107) at non-singleton dimension 3

    when I train on my imgs , I encount the following issue: Traceback (most recent call last): File "train.py", line 30, in train(opt, Gs, Zs, reals, NoiseAmp, Gs2, Zs2, reals2, NoiseAmp2) File "/data/TuiGAN-PyTorch-master/models/TuiGAN.py", line 72, in train z_curr,in_s,G_curr, z_curr2,in_s2,G_curr2 = train_single_scale(D_curr,G_curr, reals,Gs,Zs,in_s,NoiseAmp, D_curr2,G_curr2, reals2,Gs2,Zs2,in_s2,NoiseAmp2, opt,scale_num) File "/data/TuiGAN-PyTorch-master/models/TuiGAN.py", line 192, in train_single_scale noise2 = opt.noise_amp2 * noise_2 + m_image(real2) envirinment is: pytorch1.0, cuda9.0

    opened by stillstream 0
  • Unable to generate similar images in the paper

    Unable to generate similar images in the paper

    Hello, author! The image generated according to the code is a little fuzzy, and the effect is quite different from the original paper. What parameters do I need to modify to achieve the same result?

    opened by kgstutwh 1
  • Cannot reproduce the results of cross-domain translation

    Cannot reproduce the results of cross-domain translation

    Could you please release the pre-trained weights and source images of the task animal face translation? I have tried you model for several input pairs from AFHQ dataset. It seems that there is a gap between my results and your official results. If you do not have a plan to release your checkpoints, could you please upload all source images you used in you paper? In that case, I can reproduce your amazing results. Thank you so much.

    opened by crownk1997 1
  • trainA&trainB.size

    trainA&trainB.size

    When i have put two different style images in datas/trainA&trainB randomly, run code ,but got a error ,''The size of tensor a (150) must match the size of tensor b (35) at non-singleton dimension 3'',shoud i resize the source images what it was needed.Novice consult.Thanks.

    opened by Allex-shell 1
Owner
Ph.D. Candidate of University of Science and Technology of China
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