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Clarified Soft/Custom ControlNet SD1.5/T2I Adapter Weights nodes, deprecated old versions

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Jedrzej Kosinski
2024-08-30 05:59:05 -05:00
parent ce72ce674f
commit 9c00ec00ea
4 changed files with 229 additions and 71 deletions
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adv_control/nodes.py
+20 -11
View File
@@ -7,15 +7,16 @@ from comfy.model_patcher import ModelPatcher
from .control import load_controlnet, convert_to_advanced, is_advanced_controlnet, is_sd3_advanced_controlnet
from .utils import ControlWeights, LatentKeyframeGroup, TimestepKeyframeGroup, AbstractPreprocWrapper, BIGMAX
from .nodes_weight import (DefaultWeights, ScaledSoftMaskedUniversalWeights, ScaledSoftUniversalWeightsDeprecated, SoftControlNetWeightsDeprecated, CustomControlNetWeightsDeprecated,
SoftT2IAdapterWeightsDeprecated, CustomT2IAdapterWeightsDeprecated)
from .nodes_weight import (DefaultWeights, ScaledSoftMaskedUniversalWeights, ScaledSoftUniversalWeightsDeprecated,
SoftControlNetWeightsSD15, CustomControlNetWeightsSD15, SoftT2IAdapterWeights, CustomT2IAdapterWeights)
from .nodes_keyframes import (LatentKeyframeGroupNode, LatentKeyframeInterpolationNode, LatentKeyframeBatchedGroupNode, LatentKeyframeNode,
TimestepKeyframeNode, TimestepKeyframeInterpolationNode, TimestepKeyframeFromStrengthListNode)
from .nodes_sparsectrl import SparseCtrlMergedLoaderAdvanced, SparseCtrlLoaderAdvanced, SparseIndexMethodNode, SparseSpreadMethodNode, RgbSparseCtrlPreprocessor, SparseWeightExtras
from .nodes_reference import ReferenceControlNetNode, ReferenceControlFinetune, ReferencePreprocessorNode
from .nodes_plusplus import PlusPlusLoaderAdvanced, PlusPlusLoaderSingle, PlusPlusInputNode
from .nodes_loosecontrol import ControlNetLoaderWithLoraAdvanced
from .nodes_deprecated import LoadImagesFromDirectory
from .nodes_deprecated import (LoadImagesFromDirectory, SoftControlNetWeightsDeprecated, CustomControlNetWeightsDeprecated,
SoftT2IAdapterWeightsDeprecated, CustomT2IAdapterWeightsDeprecated)
from .logger import logger
from .sampling import acn_sample_factory
@@ -245,10 +246,10 @@ NODE_CLASS_MAPPINGS = {
# Weights
"ScaledSoftControlNetWeights": ScaledSoftUniversalWeightsDeprecated,
"ScaledSoftMaskedUniversalWeights": ScaledSoftMaskedUniversalWeights,
"SoftControlNetWeights": SoftControlNetWeightsDeprecated,
"CustomControlNetWeights": CustomControlNetWeightsDeprecated,
"SoftT2IAdapterWeights": SoftT2IAdapterWeightsDeprecated,
"CustomT2IAdapterWeights": CustomT2IAdapterWeightsDeprecated,
"ACN_SoftControlNetWeightsSD15": SoftControlNetWeightsSD15,
"ACN_CustomControlNetWeightsSD15": CustomControlNetWeightsSD15,
"ACN_SoftT2IAdapterWeights": SoftT2IAdapterWeights,
"ACN_CustomT2IAdapterWeights": CustomT2IAdapterWeights,
"ACN_DefaultUniversalWeights": DefaultWeights,
# SparseCtrl
"ACN_SparseCtrlRGBPreprocessor": RgbSparseCtrlPreprocessor,
@@ -269,6 +270,10 @@ NODE_CLASS_MAPPINGS = {
#"ACN_ControlNetLoaderWithLoraAdvanced": ControlNetLoaderWithLoraAdvanced,
# Deprecated
"LoadImagesFromDirectory": LoadImagesFromDirectory,
"SoftControlNetWeights": SoftControlNetWeightsDeprecated,
"CustomControlNetWeights": CustomControlNetWeightsDeprecated,
"SoftT2IAdapterWeights": SoftT2IAdapterWeightsDeprecated,
"CustomT2IAdapterWeights": CustomT2IAdapterWeightsDeprecated,
}
NODE_DISPLAY_NAME_MAPPINGS = {
@@ -289,10 +294,10 @@ NODE_DISPLAY_NAME_MAPPINGS = {
# Weights
"ScaledSoftControlNetWeights": "Scaled Soft Weights 🛂🅐🅒🅝",
"ScaledSoftMaskedUniversalWeights": "Scaled Soft Masked Weights 🛂🅐🅒🅝",
"SoftControlNetWeights": "ControlNet Soft Weights 🛂🅐🅒🅝",
"CustomControlNetWeights": "ControlNet Custom Weights 🛂🅐🅒🅝",
"SoftT2IAdapterWeights": "T2IAdapter Soft Weights 🛂🅐🅒🅝",
"CustomT2IAdapterWeights": "T2IAdapter Custom Weights 🛂🅐🅒🅝",
"ACN_SoftControlNetWeightsSD15": "ControlNet Soft Weights [SD1.5] 🛂🅐🅒🅝",
"ACN_CustomControlNetWeightsSD15": "ControlNet Custom Weights [SD1.5] 🛂🅐🅒🅝",
"ACN_SoftT2IAdapterWeights": "T2IAdapter Soft Weights 🛂🅐🅒🅝",
"ACN_CustomT2IAdapterWeights": "T2IAdapter Custom Weights 🛂🅐🅒🅝",
"ACN_DefaultUniversalWeights": "Default Weights 🛂🅐🅒🅝",
# SparseCtrl
"ACN_SparseCtrlRGBPreprocessor": "RGB SparseCtrl 🛂🅐🅒🅝",
@@ -313,4 +318,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
#"ACN_ControlNetLoaderWithLoraAdvanced": "Load Adv. ControlNet Model w/ LoRA 🛂🅐🅒🅝",
# Deprecated
"LoadImagesFromDirectory": "🚫Load Images [DEPRECATED] 🛂🅐🅒🅝",
"SoftControlNetWeights": "ControlNet Soft Weights 🛂🅐🅒🅝",
"CustomControlNetWeights": "ControlNet Custom Weights 🛂🅐🅒🅝",
"SoftT2IAdapterWeights": "T2IAdapter Soft Weights 🛂🅐🅒🅝",
"CustomT2IAdapterWeights": "T2IAdapter Custom Weights 🛂🅐🅒🅝",
}
adv_control/nodes_deprecated.py
+156 -1
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@@ -4,7 +4,7 @@ import torch
import numpy as np
from PIL import Image, ImageOps
from .utils import BIGMAX
from .utils import BIGMAX, ControlWeights, TimestepKeyframeGroup, TimestepKeyframe, get_properly_arranged_t2i_weights
from .logger import logger
@@ -69,3 +69,158 @@ class LoadImagesFromDirectory:
raise FileNotFoundError(f"No images could be loaded from directory '{directory}'.")
return (torch.cat(images, dim=0), torch.stack(masks, dim=0), image_count)
class SoftControlNetWeightsDeprecated:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 0.09941396206337118, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 0.12050177219802567, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 0.14606275417942507, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 0.17704576264172736, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_04": ("FLOAT", {"default": 0.214600924414215, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_05": ("FLOAT", {"default": 0.26012233262329093, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_06": ("FLOAT", {"default": 0.3152997971191405, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_07": ("FLOAT", {"default": 0.3821815722656249, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_08": ("FLOAT", {"default": 0.4632503906249999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_09": ("FLOAT", {"default": 0.561515625, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_10": ("FLOAT", {"default": 0.6806249999999999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_11": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_12": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
},
"optional": {
"uncond_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}, ),
"cn_extras": ("CN_WEIGHTS_EXTRAS",),
"autosize": ("ACNAUTOSIZE", {"padding": 0}),
}
}
DEPRECATED = True
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = ("CN_WEIGHTS", "TK_SHORTCUT")
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/ControlNet"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11, weight_12, flip_weights,
uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
weights_output = [weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11]
weights_middle = [weight_12]
weights = ControlWeights.controlnet(weights_output=weights_output, weights_middle=weights_middle, uncond_multiplier=uncond_multiplier, extras=cn_extras)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class CustomControlNetWeightsDeprecated:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_04": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_05": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_06": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_07": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_08": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_09": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_10": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_11": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_12": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
},
"optional": {
"uncond_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}, ),
"cn_extras": ("CN_WEIGHTS_EXTRAS",),
"autosize": ("ACNAUTOSIZE", {"padding": 0}),
}
}
DEPRECATED = True
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = ("CN_WEIGHTS", "TK_SHORTCUT")
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/ControlNet"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11, weight_12, flip_weights,
uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
weights_output = [weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11]
weights_middle = [weight_12]
weights = ControlWeights.controlnet(weights_output=weights_output, weights_middle=weights_middle, uncond_multiplier=uncond_multiplier, extras=cn_extras)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class SoftT2IAdapterWeightsDeprecated:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 0.25, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 0.62, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
},
"optional": {
"uncond_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}, ),
"cn_extras": ("CN_WEIGHTS_EXTRAS",),
"autosize": ("ACNAUTOSIZE", {"padding": 0}),
}
}
DEPRECATED = True
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = ("CN_WEIGHTS", "TK_SHORTCUT")
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, flip_weights,
uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
weights = [weight_00, weight_01, weight_02, weight_03]
weights = get_properly_arranged_t2i_weights(weights)
weights = ControlWeights.t2iadapter(weights_input=weights, uncond_multiplier=uncond_multiplier, extras=cn_extras)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class CustomT2IAdapterWeightsDeprecated:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
},
"optional": {
"uncond_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}, ),
"cn_extras": ("CN_WEIGHTS_EXTRAS",),
"autosize": ("ACNAUTOSIZE", {"padding": 0}),
}
}
DEPRECATED = True
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = ("CN_WEIGHTS", "TK_SHORTCUT")
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, flip_weights,
uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
weights = [weight_00, weight_01, weight_02, weight_03]
weights = get_properly_arranged_t2i_weights(weights)
weights = ControlWeights.t2iadapter(weights_input=weights, uncond_multiplier=uncond_multiplier, extras=cn_extras)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
adv_control/nodes_weight.py
+52 -58
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@@ -92,25 +92,24 @@ class ScaledSoftUniversalWeightsDeprecated:
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class SoftControlNetWeightsDeprecated:
class SoftControlNetWeightsSD15:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 0.09941396206337118, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 0.12050177219802567, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 0.14606275417942507, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 0.17704576264172736, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_04": ("FLOAT", {"default": 0.214600924414215, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_05": ("FLOAT", {"default": 0.26012233262329093, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_06": ("FLOAT", {"default": 0.3152997971191405, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_07": ("FLOAT", {"default": 0.3821815722656249, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_08": ("FLOAT", {"default": 0.4632503906249999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_09": ("FLOAT", {"default": 0.561515625, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_10": ("FLOAT", {"default": 0.6806249999999999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_11": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_12": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
"output_0": ("FLOAT", {"default": 0.09941396206337118, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_1": ("FLOAT", {"default": 0.12050177219802567, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_2": ("FLOAT", {"default": 0.14606275417942507, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_3": ("FLOAT", {"default": 0.17704576264172736, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_4": ("FLOAT", {"default": 0.214600924414215, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_5": ("FLOAT", {"default": 0.26012233262329093, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_6": ("FLOAT", {"default": 0.3152997971191405, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_7": ("FLOAT", {"default": 0.3821815722656249, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_8": ("FLOAT", {"default": 0.4632503906249999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_9": ("FLOAT", {"default": 0.561515625, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_10": ("FLOAT", {"default": 0.6806249999999999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_11": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"middle_0": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
},
"optional": {
"uncond_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}, ),
@@ -125,35 +124,34 @@ class SoftControlNetWeightsDeprecated:
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/ControlNet"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11, weight_12, flip_weights,
def load_weights(self, output_0, output_1, output_2, output_3, output_4, output_5, output_6,
output_7, output_8, output_9, output_10, output_11, middle_0,
uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
weights_output = [weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11]
weights_middle = [weight_12]
weights_output = [output_0, output_1, output_2, output_3, output_4, output_5, output_6,
output_7, output_8, output_9, output_10, output_11]
weights_middle = [middle_0]
weights = ControlWeights.controlnet(weights_output=weights_output, weights_middle=weights_middle, uncond_multiplier=uncond_multiplier, extras=cn_extras)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class CustomControlNetWeightsDeprecated:
class CustomControlNetWeightsSD15:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_04": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_05": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_06": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_07": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_08": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_09": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_10": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_11": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_12": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
"output_0": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_1": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_2": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_3": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_4": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_5": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_6": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_7": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_8": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_9": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_10": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"output_11": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"middle_0": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
},
"optional": {
"uncond_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}, ),
@@ -168,26 +166,25 @@ class CustomControlNetWeightsDeprecated:
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/ControlNet"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11, weight_12, flip_weights,
def load_weights(self, output_0, output_1, output_2, output_3, output_4, output_5, output_6,
output_7, output_8, output_9, output_10, output_11, middle_0,
uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
weights_output = [weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11]
weights_middle = [weight_12]
weights_output = [output_0, output_1, output_2, output_3, output_4, output_5, output_6,
output_7, output_8, output_9, output_10, output_11]
weights_middle = [middle_0]
weights = ControlWeights.controlnet(weights_output=weights_output, weights_middle=weights_middle, uncond_multiplier=uncond_multiplier, extras=cn_extras)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class SoftT2IAdapterWeightsDeprecated:
class SoftT2IAdapterWeights:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 0.25, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 0.62, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
"input_0": ("FLOAT", {"default": 0.25, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"input_1": ("FLOAT", {"default": 0.62, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"input_2": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"input_3": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
},
"optional": {
"uncond_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}, ),
@@ -202,25 +199,23 @@ class SoftT2IAdapterWeightsDeprecated:
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, flip_weights,
def load_weights(self, input_0, input_1, input_2, input_3,
uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
weights = [weight_00, weight_01, weight_02, weight_03]
weights = [input_0, input_1, input_2, input_3]
weights = get_properly_arranged_t2i_weights(weights)
weights.reverse() # to account for recent ComfyUI changes
weights = ControlWeights.t2iadapter(weights_input=weights, uncond_multiplier=uncond_multiplier, extras=cn_extras)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class CustomT2IAdapterWeightsDeprecated:
class CustomT2IAdapterWeights:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
"input_0": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"input_1": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"input_2": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"input_3": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
},
"optional": {
"uncond_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}, ),
@@ -235,10 +230,9 @@ class CustomT2IAdapterWeightsDeprecated:
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, flip_weights,
def load_weights(self, input_0, input_1, input_2, input_3,
uncond_multiplier: float=1.0, cn_extras: dict[str]={}):
weights = [weight_00, weight_01, weight_02, weight_03]
weights = [input_0, input_1, input_2, input_3]
weights = get_properly_arranged_t2i_weights(weights)
weights.reverse() # to account for recent ComfyUI changes
weights = ControlWeights.t2iadapter(weights_input=weights, uncond_multiplier=uncond_multiplier, extras=cn_extras)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
adv_control/utils.py
+1 -1
View File
@@ -184,7 +184,7 @@ class ControlWeights:
if key == "middle":
relevant_weights = self.weights_middle
elif key == "input":
relevant_weights = self.weights_input
relevant_weights = list(reversed(self.weights_input))
else:
relevant_weights = self.weights_output
if relevant_weights is None: