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lllyasviel
2024-01-28 07:05:32 -08:00
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@@ -447,7 +447,8 @@ class ControlNetExampleForge(scripts.Script):
unet = p.sd_model.forge_objects.unet 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. # Below is an example for stronger control in middle block.
# This is helpful for some high-res fix passes. (p.is_hr_pass) # This is helpful for some high-res fix passes. (p.is_hr_pass)
positive_advanced_weighting = { 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 advanced_frame_weighting is a weight applied to each image in a batch.
# The length of this list must be same with batch size # 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] # 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)] 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 # But in this simple example we do not use them