Comments (2)
Thank you!
- The code does not support multiple GPUs currently.
- For this you will need to add a loop to the training function for each of your images.
- G(z_opt) is the reconstruction of the real image. Please see explanation in section 2 in our paper: http://openaccess.thecvf.com/content_ICCV_2019/papers/Shaham_SinGAN_Learning_a_Generative_Model_From_a_Single_Natural_Image_ICCV_2019_paper.pdf
from singan.
Thank you!
- The code does not support multiple GPUs currently.
- For this you will need to add a loop to the training function for each of your images.
- G(z_opt) is the reconstruction of the real image. Please see explanation in section 2 in our paper: http://openaccess.thecvf.com/content_ICCV_2019/papers/Shaham_SinGAN_Learning_a_Generative_Model_From_a_Single_Natural_Image_ICCV_2019_paper.pdf
Thank you for your reply. I'd like to ask you another question.
As mentioned in the supplementary materials submitted by you, when generating 256 * 256 images, on a single 1080ti GPU, the training time will take about 30 minutes, and the actual generated images will be less than one second each. But when I run main.train.py, when I train to generate 224 * 224 images, the actual training time is nearly two hours. Why? My image size for training is 224 * 224. My device is 2080ti, cuda9.0, pytorch1.1.0, python3.6. I've also tested it on 1080ti, and it takes longer to train.
Looking forward to your reply again.
from singan.
Related Issues (20)
- Is there someone know how many variants of SinGAN since 2019? Could you please send me some variants for me, thanks!
- Does everyone know how to fix this runtime error? HOT 3
- Error: Providing a bool or integral fill value without setting the optional `dtype` or `out` arguments is currently unsupported
- ValueError: the input array must have size 3 along `channel_axis`, got (197, 250) HOT 2
- Why the training always stop at scale 8 ?
- Black Image for fake_sample.png at scale 8 and 9 HOT 2
- How to use SinGAN to perform image translation just as CycleGAN.
- Lack of package versions in requirements.txt file.
- Lack of imsave in random_samples.py
- process of inject scale for image manip (supplemental material figure 3)
- Getting black images as output of harmonization HOT 2
- Can I train model from multiple images?
- mask result image
- version another pytorch intead of 1.4.0
- About Pretrained Model (Harmonize and Super Resolution)
- ValueRrror of SIFID
- No such file or directory: 'TrainedModels/balloons/scale_factor=0.793701,alpha=100/Gs.pth' HOT 2
- SIFID: nan
- draw_concat
- How to input image name
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