From 5b8ca63b61a518344fd5fd3895d4dcf9a77054f2 Mon Sep 17 00:00:00 2001 From: lllyasviel Date: Sun, 28 Jan 2024 07:05:32 -0800 Subject: [PATCH] Update README.md --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b614201a..9b3dc887 100644 --- a/README.md +++ b/README.md @@ -447,7 +447,8 @@ class ControlNetExampleForge(scripts.Script): unet = p.sd_model.forge_objects.unet - # Unet has input, middle, output blocks, and we can give different weights to each layers in all blocks. + # Unet has input, middle, output blocks, and we can give different + # weights to each layers in all blocks. # Below is an example for stronger control in middle block. # This is helpful for some high-res fix passes. (p.is_hr_pass) positive_advanced_weighting = { @@ -464,7 +465,8 @@ class ControlNetExampleForge(scripts.Script): # The advanced_frame_weighting is a weight applied to each image in a batch. # The length of this list must be same with batch size # For example, if batch size is 5, the below list is [0, 0.25, 0.5, 0.75, 1.0] - # If you view the 5 images as 5 frames in a video, this will lead to progressively stronger control over time. + # If you view the 5 images as 5 frames in a video, this will lead to + # progressively stronger control over time. advanced_frame_weighting = [float(i) / float(batch_size - 1) for i in range(batch_size)] # But in this simple example we do not use them