File size: 12,328 Bytes
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from torch import Tensor
import folder_paths
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, ScaledSoftUniversalWeights, SoftControlNetWeights, CustomControlNetWeights,
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_loosecontrol import ControlNetLoaderWithLoraAdvanced
from .nodes_deprecated import LoadImagesFromDirectory
from .logger import logger
class ControlNetLoaderAdvanced:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"control_net_name": (folder_paths.get_filename_list("controlnet"), ),
},
"optional": {
"timestep_keyframe": ("TIMESTEP_KEYFRAME", ),
}
}
RETURN_TYPES = ("CONTROL_NET", )
FUNCTION = "load_controlnet"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝"
def load_controlnet(self, control_net_name,
timestep_keyframe: TimestepKeyframeGroup=None
):
controlnet_path = folder_paths.get_full_path("controlnet", control_net_name)
controlnet = load_controlnet(controlnet_path, timestep_keyframe)
return (controlnet,)
class DiffControlNetLoaderAdvanced:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": ("MODEL",),
"control_net_name": (folder_paths.get_filename_list("controlnet"), )
},
"optional": {
"timestep_keyframe": ("TIMESTEP_KEYFRAME", ),
}
}
RETURN_TYPES = ("CONTROL_NET", )
FUNCTION = "load_controlnet"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝"
def load_controlnet(self, control_net_name, model,
timestep_keyframe: TimestepKeyframeGroup=None
):
controlnet_path = folder_paths.get_full_path("controlnet", control_net_name)
controlnet = load_controlnet(controlnet_path, timestep_keyframe, model)
if is_advanced_controlnet(controlnet):
controlnet.verify_all_weights()
return (controlnet,)
class AdvancedControlNetApply:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"positive": ("CONDITIONING", ),
"negative": ("CONDITIONING", ),
"control_net": ("CONTROL_NET", ),
"image": ("IMAGE", ),
"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
"end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001})
},
"optional": {
"mask_optional": ("MASK", ),
"timestep_kf": ("TIMESTEP_KEYFRAME", ),
"latent_kf_override": ("LATENT_KEYFRAME", ),
"weights_override": ("CONTROL_NET_WEIGHTS", ),
"model_optional": ("MODEL",),
"vae_optional": ("VAE",),
}
}
RETURN_TYPES = ("CONDITIONING","CONDITIONING","MODEL",)
RETURN_NAMES = ("positive", "negative", "model_opt")
FUNCTION = "apply_controlnet"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝"
def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent,
mask_optional: Tensor=None, model_optional: ModelPatcher=None, vae_optional=None,
timestep_kf: TimestepKeyframeGroup=None, latent_kf_override: LatentKeyframeGroup=None,
weights_override: ControlWeights=None):
if strength == 0:
return (positive, negative, model_optional)
if model_optional:
model_optional = model_optional.clone()
control_hint = image.movedim(-1,1)
cnets = {}
out = []
for conditioning in [positive, negative]:
c = []
for t in conditioning:
d = t[1].copy()
prev_cnet = d.get('control', None)
if prev_cnet in cnets:
c_net = cnets[prev_cnet]
else:
# copy, convert to advanced if needed, and set cond
c_net = convert_to_advanced(control_net.copy()).set_cond_hint(control_hint, strength, (start_percent, end_percent), vae_optional)
if is_advanced_controlnet(c_net):
# disarm node check
c_net.disarm()
# if model required, verify model is passed in, and if so patch it
if c_net.require_model:
if not model_optional:
raise Exception(f"Type '{type(c_net).__name__}' requires model_optional input, but got None.")
c_net.patch_model(model=model_optional)
# if vae required, verify vae is passed in
if c_net.require_vae:
# if controlnet can accept preprocced condhint latents and is the case, ignore vae requirement
if c_net.allow_condhint_latents and isinstance(control_hint, AbstractPreprocWrapper):
pass
elif not vae_optional:
# make sure SD3 ControlNet will get a special message instead of generic type mention
if is_sd3_advanced_controlnet:
raise Exception(f"SD3 ControlNet requires vae_optional input, but got None.")
else:
raise Exception(f"Type '{type(c_net).__name__}' requires vae_optional input, but got None.")
# apply optional parameters and overrides, if provided
if timestep_kf is not None:
c_net.set_timestep_keyframes(timestep_kf)
if latent_kf_override is not None:
c_net.latent_keyframe_override = latent_kf_override
if weights_override is not None:
c_net.weights_override = weights_override
# verify weights are compatible
c_net.verify_all_weights()
# set cond hint mask
if mask_optional is not None:
mask_optional = mask_optional.clone()
# if not in the form of a batch, make it so
if len(mask_optional.shape) < 3:
mask_optional = mask_optional.unsqueeze(0)
c_net.set_cond_hint_mask(mask_optional)
c_net.set_previous_controlnet(prev_cnet)
cnets[prev_cnet] = c_net
d['control'] = c_net
d['control_apply_to_uncond'] = False
n = [t[0], d]
c.append(n)
out.append(c)
return (out[0], out[1], model_optional)
# NODE MAPPING
NODE_CLASS_MAPPINGS = {
# Keyframes
"TimestepKeyframe": TimestepKeyframeNode,
"ACN_TimestepKeyframeInterpolation": TimestepKeyframeInterpolationNode,
"ACN_TimestepKeyframeFromStrengthList": TimestepKeyframeFromStrengthListNode,
"LatentKeyframe": LatentKeyframeNode,
"LatentKeyframeTiming": LatentKeyframeInterpolationNode,
"LatentKeyframeBatchedGroup": LatentKeyframeBatchedGroupNode,
"LatentKeyframeGroup": LatentKeyframeGroupNode,
# Conditioning
"ACN_AdvancedControlNetApply": AdvancedControlNetApply,
# Loaders
"ControlNetLoaderAdvanced": ControlNetLoaderAdvanced,
"DiffControlNetLoaderAdvanced": DiffControlNetLoaderAdvanced,
# Weights
"ScaledSoftControlNetWeights": ScaledSoftUniversalWeights,
"ScaledSoftMaskedUniversalWeights": ScaledSoftMaskedUniversalWeights,
"SoftControlNetWeights": SoftControlNetWeights,
"CustomControlNetWeights": CustomControlNetWeights,
"SoftT2IAdapterWeights": SoftT2IAdapterWeights,
"CustomT2IAdapterWeights": CustomT2IAdapterWeights,
"ACN_DefaultUniversalWeights": DefaultWeights,
# SparseCtrl
"ACN_SparseCtrlRGBPreprocessor": RgbSparseCtrlPreprocessor,
"ACN_SparseCtrlLoaderAdvanced": SparseCtrlLoaderAdvanced,
"ACN_SparseCtrlMergedLoaderAdvanced": SparseCtrlMergedLoaderAdvanced,
"ACN_SparseCtrlIndexMethodNode": SparseIndexMethodNode,
"ACN_SparseCtrlSpreadMethodNode": SparseSpreadMethodNode,
"ACN_SparseCtrlWeightExtras": SparseWeightExtras,
# Reference
"ACN_ReferencePreprocessor": ReferencePreprocessorNode,
"ACN_ReferenceControlNet": ReferenceControlNetNode,
"ACN_ReferenceControlNetFinetune": ReferenceControlFinetune,
# LOOSEControl
#"ACN_ControlNetLoaderWithLoraAdvanced": ControlNetLoaderWithLoraAdvanced,
# Deprecated
"LoadImagesFromDirectory": LoadImagesFromDirectory,
}
NODE_DISPLAY_NAME_MAPPINGS = {
# Keyframes
"TimestepKeyframe": "Timestep Keyframe 🛂🅐🅒🅝",
"ACN_TimestepKeyframeInterpolation": "Timestep Keyframe Interpolation 🛂🅐🅒🅝",
"ACN_TimestepKeyframeFromStrengthList": "Timestep Keyframe From List 🛂🅐🅒🅝",
"LatentKeyframe": "Latent Keyframe 🛂🅐🅒🅝",
"LatentKeyframeTiming": "Latent Keyframe Interpolation 🛂🅐🅒🅝",
"LatentKeyframeBatchedGroup": "Latent Keyframe From List 🛂🅐🅒🅝",
"LatentKeyframeGroup": "Latent Keyframe Group 🛂🅐🅒🅝",
# Conditioning
"ACN_AdvancedControlNetApply": "Apply Advanced ControlNet 🛂🅐🅒🅝",
# Loaders
"ControlNetLoaderAdvanced": "Load Advanced ControlNet Model 🛂🅐🅒🅝",
"DiffControlNetLoaderAdvanced": "Load Advanced ControlNet Model (diff) 🛂🅐🅒🅝",
# 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_DefaultUniversalWeights": "Default Weights 🛂🅐🅒🅝",
# SparseCtrl
"ACN_SparseCtrlRGBPreprocessor": "RGB SparseCtrl 🛂🅐🅒🅝",
"ACN_SparseCtrlLoaderAdvanced": "Load SparseCtrl Model 🛂🅐🅒🅝",
"ACN_SparseCtrlMergedLoaderAdvanced": "🧪Load Merged SparseCtrl Model 🛂🅐🅒🅝",
"ACN_SparseCtrlIndexMethodNode": "SparseCtrl Index Method 🛂🅐🅒🅝",
"ACN_SparseCtrlSpreadMethodNode": "SparseCtrl Spread Method 🛂🅐🅒🅝",
"ACN_SparseCtrlWeightExtras": "SparseCtrl Weight Extras 🛂🅐🅒🅝",
# Reference
"ACN_ReferencePreprocessor": "Reference Preproccessor 🛂🅐🅒🅝",
"ACN_ReferenceControlNet": "Reference ControlNet 🛂🅐🅒🅝",
"ACN_ReferenceControlNetFinetune": "Reference ControlNet (Finetune) 🛂🅐🅒🅝",
# LOOSEControl
#"ACN_ControlNetLoaderWithLoraAdvanced": "Load Adv. ControlNet Model w/ LoRA 🛂🅐🅒🅝",
# Deprecated
"LoadImagesFromDirectory": "🚫Load Images [DEPRECATED] 🛂🅐🅒🅝",
}
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