parameters

README.md

@@ -16,6 +16,7 @@ imgs_transition = lb.run_transition()
 ```
 ## Gradio UI
 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
 ![](example1.jpg)
@@ -46,7 +47,7 @@ lb.set_width(1024)
 lb.set_guidance_scale(5.0)
 ```
 ### 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

latent_blending.py

@@ -252,7 +252,7 @@ class LatentBlending():
                 Deeper injections will cause (unwanted) formation of new structures,
                 more shallow values will go into alpha-blendy land.
             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 
                 at the end of the inference.
             nmb_mindist (int): The minimum number of diffusion steps 

parameters.md

@@ -0,0 +1,21 @@
+# 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.
+
+