# 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, but may also introduce additional objects and motion. - A value closer to one indicates a simpler alpha blending. ## branch1_crossfeed_power - Controls the level of cross-feeding between the first and last image branch. This allows to preserve structures from the first image. - A value of 0.0 disables crossfeeding. - A value of 1.0 fully copies the latents from the first branch to the last. ## branch1_crossfeed_range - Sets the duration of active crossfeed during development. High values enforce strong structural similarity. - The value x ranges from [0,1], and the crossfeeding is deactivated after x*num_inference_steps steps ## branch1_crossfeed_decay - Sets decay for branch1_crossfeed_power. Lower values make the decay stronger across the range - The value x ranges from [0,1], and the branch1_crossfeed_power is decreased until the end of the branch1_crossfeed_range to a value of x*branch1_crossfeed_power ## parental_crossfeed_power Similar to branch1_crossfeed_power, however applied for the images withinin the transition. ## parental_crossfeed_range Similar to branch1_crossfeed_range, however applied for the images withinin the transition. ## parental_crossfeed_power_decay Similar to branch1_crossfeed_decay, however applied for the images withinin the transition. ## guidance_scale - Higher guidance scale encourages the creation of images that are closely aligned with the text. - Lower values are recommended for the best results in latent blending. ## guidance_scale_mid_damper - Decreases the guidance scale in the middle of a transition. - A value of 1 maintains a constant guidance scale. - A value of 0 decreases the guidance scale to 1 at the midpoint of the transition. ## num_inference_steps - Determines the quality of the results. - Higher values improve the outcome, but also require more computation time. ## nmb_trans_images - Final number of images computed in the last branch of the tree. - Higher values give better results but require more computation time.