Merge PR #130 from Kosinkadink/develop - ControlNet++ support

ControlNet++ support

adv_control/control.py

@@ -519,6 +519,11 @@ def copy(self):
 
 def load_controlnet(ckpt_path, timestep_keyframe: TimestepKeyframeGroup=None, model=None):
     controlnet_data = comfy.utils.load_torch_file(ckpt_path, safe_load=True)
+    # from pathlib import Path
+    # log_name = ckpt_path.split('\\')[-1]
+    # with open(Path(__file__).parent.parent.parent / rf"keys_{log_name}.txt", "w") as afile:
+    #     for key, value in controlnet_data.items():
+    #         afile.write(f"{key}:\t{value.shape}\n")
     control = None
     # check if a non-vanilla ControlNet
     controlnet_type = ControlWeightType.DEFAULT
@@ -538,6 +543,10 @@ def load_controlnet(ckpt_path, timestep_keyframe: TimestepKeyframeGroup=None, mo
         # SVD-ControlNet check
         elif "temporal_res_block" in key:
             has_temporal_res_block_key = True
+        # ControlNet++ check
+        elif "task_embedding" in key:
+            raise Exception("ControlNet++ model detected; must be loaded using the Load ControlNet++ Model nodes.")
+
     if has_controlnet_key and has_motion_modules_key:
         controlnet_type = ControlWeightType.SPARSECTRL
     elif has_controlnet_key and has_temporal_res_block_key:

adv_control/nodes.py

@@ -12,6 +12,7 @@
                               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 .logger import logger
@@ -199,6 +200,10 @@ def apply_controlnet(self, positive, negative, control_net, image, strength, sta
     "ACN_SparseCtrlIndexMethodNode": SparseIndexMethodNode,
     "ACN_SparseCtrlSpreadMethodNode": SparseSpreadMethodNode,
     "ACN_SparseCtrlWeightExtras": SparseWeightExtras,
+    # ControlNet++
+    "ACN_ControlNet++LoaderSingle": PlusPlusLoaderSingle,
+    "ACN_ControlNet++LoaderAdvanced": PlusPlusLoaderAdvanced,
+    "ACN_ControlNet++InputNode": PlusPlusInputNode,
     # Reference
     "ACN_ReferencePreprocessor": ReferencePreprocessorNode,
     "ACN_ReferenceControlNet": ReferenceControlNetNode,
@@ -238,6 +243,10 @@ def apply_controlnet(self, positive, negative, control_net, image, strength, sta
     "ACN_SparseCtrlIndexMethodNode": "SparseCtrl Index Method 🛂🅐🅒🅝",
     "ACN_SparseCtrlSpreadMethodNode": "SparseCtrl Spread Method 🛂🅐🅒🅝",
     "ACN_SparseCtrlWeightExtras": "SparseCtrl Weight Extras 🛂🅐🅒🅝",
+    # ControlNet++
+    "ACN_ControlNet++LoaderSingle": "Load ControlNet++ Model (Single) 🛂🅐🅒🅝",
+    "ACN_ControlNet++LoaderAdvanced": "Load ControlNet++ Model (Multi) 🛂🅐🅒🅝",
+    "ACN_ControlNet++InputNode": "ControlNet++ Input 🛂🅐🅒🅝",
     # Reference
     "ACN_ReferencePreprocessor": "Reference Preproccessor 🛂🅐🅒🅝",
     "ACN_ReferenceControlNet": "Reference ControlNet 🛂🅐🅒🅝",

adv_control/nodes_plusplus.py

@@ -0,0 +1,84 @@
+from torch import Tensor
+import math
+
+import folder_paths
+
+from .control_plusplus import load_controlnetplusplus, PlusPlusType, PlusPlusInput, PlusPlusInputGroup, PlusPlusImageWrapper
+from .utils import BIGMAX
+
+
+class PlusPlusLoaderAdvanced:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "plus_input": ("PLUS_INPUT", ),
+                "name": (folder_paths.get_filename_list("controlnet"), ),
+            }
+        }
+
+    RETURN_TYPES = ("CONTROL_NET", "IMAGE",)
+    FUNCTION = "load_controlnet_plusplus"
+
+    CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/ControlNet++"
+
+    def load_controlnet_plusplus(self, plus_input: PlusPlusInputGroup, name: str):
+        controlnet_path = folder_paths.get_full_path("controlnet", name)
+        controlnet = load_controlnetplusplus(controlnet_path)
+        controlnet.verify_control_type(name, plus_input)
+        return (controlnet, PlusPlusImageWrapper(plus_input),)
+
+
+class PlusPlusLoaderSingle:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "name": (folder_paths.get_filename_list("controlnet"), ),
+                "control_type": (PlusPlusType._LIST_WITH_NONE, {"default": PlusPlusType.NONE}, ),
+            }
+        }
+
+    RETURN_TYPES = ("CONTROL_NET",)
+    FUNCTION = "load_controlnet_plusplus"
+
+    CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/ControlNet++"
+
+    def load_controlnet_plusplus(self, name: str, control_type: str):
+        controlnet_path = folder_paths.get_full_path("controlnet", name)
+        controlnet = load_controlnetplusplus(controlnet_path)
+        controlnet.single_control_type = control_type
+        controlnet.verify_control_type(name)
+        return (controlnet,)
+
+
+class PlusPlusInputNode:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "control_type": (PlusPlusType._LIST,),
+            },
+            "optional": {
+                "prev_plus_input": ("PLUS_INPUT",),
+                #"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": BIGMAX, "step": 0.01}),
+            }
+        }
+
+    RETURN_TYPES = ("PLUS_INPUT", )
+    FUNCTION = "wrap_images"
+
+    CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/ControlNet++"
+
+    def wrap_images(self, image: Tensor, control_type: str, strength=1.0, prev_plus_input: PlusPlusInputGroup=None):
+        if prev_plus_input is None:
+            prev_plus_input = PlusPlusInputGroup()
+        prev_plus_input = prev_plus_input.clone()
+
+        if math.isclose(strength, 0.0):
+            strength = 0.0000001
+        pp_input = PlusPlusInput(image, control_type, strength)
+        prev_plus_input.add(pp_input)
+
+        return (prev_plus_input,)

adv_control/utils.py

@@ -145,6 +145,7 @@ class ControlWeightType:
     UNIVERSAL = "universal"
     T2IADAPTER = "t2iadapter"
     CONTROLNET = "controlnet"
+    CONTROLNETPLUSPLUS = "controlnet++"
     CONTROLLORA = "controllora"
     CONTROLLLLITE = "controllllite"
     SVD_CONTROLNET = "svd_controlnet"
@@ -380,7 +381,7 @@ def default(cls, keyframe: TimestepKeyframe) -> 'TimestepKeyframeGroup':
 
 class AbstractPreprocWrapper:
     error_msg = "Invalid use of [InsertHere] output. The output of [InsertHere] preprocessor is NOT a usual image, but a latent pretending to be an image - you must connect the output directly to an Apply ControlNet node (advanced or otherwise). It cannot be used for anything else that accepts IMAGE input."
-    def __init__(self, condhint: Tensor):
+    def __init__(self, condhint):
         self.condhint = condhint
 
     def movedim(self, *args, **kwargs):

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-advanced-controlnet"
 description = "Nodes for scheduling ControlNet strength across timesteps and batched latents, as well as applying custom weights and attention masks."
-version = "1.1.0"
+version = "1.1.1"
 license = "LICENSE"
 dependencies = []