Comments (2)
In what sense are you trying to change the size of the output? If you have a pre-trained model with another output size, you can use the --size argument to tell the model to expect this alternative size. If you're asking whether a pre-trained 1024x1024 model can be used to produce images of other resolutions - the answer is no. You'll have to resize the output yourself. For decreasing resolution you can probably just work with PIL's resize. If you want to increase resolution, I'd have a look at super resolution models like ESRGAN.
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I really appreciate your help here!
I looked through the closed issues and found some tips about the quality of images, increasing iterations, and decreasing learning_rate. Also, tried to use the ESRGAN model, and the resolution is increased but the quality and blur effect remained the same.
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Related Issues (20)
- Gradio related inquiry HOT 1
- Question about specifying the style HOT 4
- About the bug when running Demo HOT 7
- Style transfer of "White Walker" HOT 1
- How to use style mapper HOT 1
- A specific domain changes in global direction HOT 1
- Sample Code for retraining OASIS HOT 2
- Control eye position HOT 2
- Question about gradient of transforms HOT 2
- Unexpexted output when providing randomly sampled latents HOT 1
- clip_model_weights and auto_layer_k HOT 3
- Nvidia error when running docker-compose up HOT 1
- Cross-domain image interpolation HOT 3
- When choose other than 'ffhq' for source model type
- i want to add eyeglasses boundary from stylegan ffhq . HOT 1
- unauthorized: authentication required on docker compose up
- Ajout de nouvelle couche dans le modèle de stylegan_nada(transfert learning)
- image2image
- Migration with a specific content image HOT 5
- Performance Metric Missing HOT 2
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