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parameters

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Johannes Stelzer 2023-01-09 13:42:02 +01:00
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README.md
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@ -16,6 +16,7 @@ imgs_transition = lb.run_transition()
``` ```
## Gradio UI ## Gradio UI
To run the UI on your local machine, run `gradio_ui.py` To run the UI on your local machine, run `gradio_ui.py`
You can find the [most relevant parameters here](parameters.md)
## Example 1: Simple transition ## Example 1: Simple transition
![](example1.jpg) ![](example1.jpg)
@ -46,7 +47,7 @@ lb.set_width(1024)
lb.set_guidance_scale(5.0) lb.set_guidance_scale(5.0)
``` ```
### depth_strength / list_injection_strength ### depth_strength / list_injection_strength
The strength dictates how early the blending process starts. The closer its value is to zero, the more inventive the results will be; whereas, a value closer to one indicates a more simple alpha blending. The strength of the diffusion iterations determines when the blending process will begin. A value close to zero results in more creative and intricate outcomes, while a value closer to one indicates a simpler alpha blending. However, low values may also bring about the introduction of additional objects and motion.
## Set up the branching structure ## Set up the branching structure

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latent_blending.py
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@ -252,7 +252,7 @@ class LatentBlending():
Deeper injections will cause (unwanted) formation of new structures, Deeper injections will cause (unwanted) formation of new structures,
more shallow values will go into alpha-blendy land. more shallow values will go into alpha-blendy land.
num_inference_steps: int num_inference_steps: int
Number of diffusion steps. Larger values will take more compute time. Number of diffusion steps. Higher values will take more compute time.
nmb_branches_final (int): The number of diffusion-generated images nmb_branches_final (int): The number of diffusion-generated images
at the end of the inference. at the end of the inference.
nmb_mindist (int): The minimum number of diffusion steps nmb_mindist (int): The minimum number of diffusion steps

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parameters.md Normal file
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# Gradio parameters
## depth_strength
determines when the blending process will begin in terms of diffusion steps. A value close to zero results in more creative and intricate outcomes, while a value closer to one indicates a simpler alpha blending. However, low values may also bring about the introduction of additional objects and motion.
## guidance_scale
higher guidance scale encourages the creation of images that are closely aligned with the text. However, the best results for latent blending are achieved with lower values.
## guidance_scale_mid_damper
decreases the guidance scale in the middle of a transition. A value of 1 would maintain a constant guidance scale, while a value of 0 would decrease the guidance scale to 1 at the midpoint of the transition
## mid_compression_scaler
stretches the spacing towards the center, with a linear spacing at mid_compression_scaler=1 and a higher sampling density in the middle at mid_compression_scaler=2
## num_inference_steps
determines the quality of the results. While an increase in this value may improve the outcome, it will also require more computation time.
## nmb_trans_images
final number of images computed in the last branch of the tree. Higher values will give better results but require more computation time.