How to improve image fidelity?
soon-yau opened this issue · comments
(Left:generated. Right: from dataset)
I have trained on mannequin dataset and the results look quite good. However, the generated images are a bit blurry and fine details are lost. Therefore, I wonder what changes do I need to do make them look crispier.
I currently use VQGAN pretrained on imagenet. I have also tried to train a VAE from scratch (using default train_vae.py) but it is blurry. I tried increasing the number of layers, number of tokens etc but didn't see improvement and made it a bit more unstable. Any advise on what VAE parameters to change?
You could try to use vqgan 16k or even the f=8 ( see the details on their
page)
…On Thu, Nov 25, 2021, 01:21 Soon-Yau Cheong ***@***.***> wrote:
[image: brown]
<https://user-images.githubusercontent.com/19167278/143328331-6fb1f1a7-1094-478d-a0c5-615192a9b3e9.png>
I have trained on mannequin dataset and the results look quite good.
However, the generated images are a bit blurry and fine details are loss.
Therefore, I wonder what changes do I need to do make them look better.
I currently use VQGAN pretrained on imagenet. I have also tried to train a
VAE from scratch (using default train_vae.py) but it is blurry. I tried
increasing the number of layers, number of tokens etc but didn't see
improvement and made it a bit more unstable. Any advise on what VAE
parameters to change?
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Managed to train a mannequin-only model with vqgan_gumbel_f8_8192 that produces quality matching OpenAI.
