Comments (4)
@mynameisfiber oh ok! the datasets used can be found in the reference section below. as for the training, image size was set at 256x256 with the rest of the settings unchanged, trained for about 3 days on one RTX 2080 Ti
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Hi! If you are referring to the officially released models, you can find all the details for how they were trained at https://github.com/NVlabs/stylegan2 and in the paper itself
from stylegan2-pytorch.
I was referring to the training parameters in order to re-create the images in the README. Were they generated using this repo?
from stylegan2-pytorch.
I was referring to the images in the README. I assume they were generated with the code from this repo?
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Related Issues (20)
- What do the G, D, GP, and SS numbers mean? HOT 1
- I get a "DefaultCPUAllocation error: not enough memory" error
- Parameters for generating faces HOT 1
- Performance on MNIST
- Out of memory after exactly 5024 iterations? HOT 1
- Web application for generating content while reloading.
- Tesla V100 GPU - 2600 Image - Too Slow Training HOT 1
- Uneven GPU utilization.
- Trainning on images with one (single) channel HOT 1
- Bug: random_hflip function HOT 1
- where can i download train data?
- Bug: gradient_accumulate_contexts function HOT 1
- Generate full resolution images 1024x1024 HOT 1
- generate all seeds of latent space
- ability to calculate Perpectual Path Length (PPL)? HOT 1
- Save Interval Flag
- /torch_utils/custom_ops.py - _find_compiler_bindir: incorrect Visual Studio Path
- Inconsistent evaluation of self.av HOT 2
- How to Train on a Single Image
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