Compare commits
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1c488eec11 | ||
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c3eed0936f | ||
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44adbbe282 |
@@ -228,11 +228,14 @@ This custom node helps to conveniently enhance images through Detector, Detailer
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### Batch/List Util
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* `Image batch To Image List` - Convert Image batch to Image List
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* `Image Batch to Image List` - Convert Image batch to Image List
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- You can use images generated in a multi batch to handle them
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* `Image List to Image Batch` - Convert Image List to Image Batch
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* `Make Image List` - Convert multiple images into a single image list
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* `Make Image Batch` - Convert multiple images into a single image batch
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- The input of images can be scaled up as needed
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* `Masks to Mask List`, `Mask List to Masks`, `Make Mask List`, `Make Mask Batch` - It has the same functionality as the nodes above, but uses mask as input instead of image.
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* `Flatten Mask Batch` - Flattens a Mask Batch into a single Mask. Normal operation is not guaranteed for non-binary masks.
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### Logics (experimental)
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+11
-3
@@ -161,6 +161,7 @@ NODE_CLASS_MAPPINGS = {
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"ImpactSegsAndMask": SegsBitwiseAndMask,
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"ImpactSegsAndMaskForEach": SegsBitwiseAndMaskForEach,
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"EmptySegs": EmptySEGS,
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"ImpactFlattenMask": FlattenMask,
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"MediaPipeFaceMeshToSEGS": MediaPipeFaceMeshToSEGS,
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"MaskToSEGS": MaskToSEGS,
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@@ -249,6 +250,8 @@ NODE_CLASS_MAPPINGS = {
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"ImpactImageBatchToImageList": ImageBatchToImageList,
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"ImpactMakeImageList": MakeImageList,
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"ImpactMakeImageBatch": MakeImageBatch,
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"ImpactMakeMaskList": MakeMaskList,
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"ImpactMakeMaskBatch": MakeMaskBatch,
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"RegionalSampler": RegionalSampler,
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"RegionalSamplerAdvanced": RegionalSamplerAdvanced,
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@@ -332,6 +335,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"BitwiseAndMask": "Pixelwise(MASK & MASK)",
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"SubtractMask": "Pixelwise(MASK - MASK)",
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"AddMask": "Pixelwise(MASK + MASK)",
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"ImpactFlattenMask": "Flatten Mask Batch",
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"DetailerForEach": "Detailer (SEGS)",
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"DetailerForEachPipe": "Detailer (SEGS/pipe)",
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"DetailerForEachDebug": "DetailerDebug (SEGS)",
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@@ -400,12 +404,16 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"ImpactInversedSwitch": "Inversed Switch (Any)",
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"ImpactExecutionOrderController": "Execution Order Controller",
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"MasksToMaskList": "Masks to Mask List",
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"MaskListToMaskBatch": "Mask List to Masks",
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"ImpactImageBatchToImageList": "Image batch to Image List",
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"MasksToMaskList": "Mask Batch to Mask List",
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"MaskListToMaskBatch": "Mask List to Mask Batch",
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"ImpactImageBatchToImageList": "Image Batch to Image List",
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"ImageListToImageBatch": "Image List to Image Batch",
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"ImpactMakeImageList": "Make Image List",
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"ImpactMakeImageBatch": "Make Image Batch",
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"ImpactMakeMaskList": "Make Mask List",
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"ImpactMakeMaskBatch": "Make Mask Batch",
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"ImpactStringSelector": "String Selector",
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"StringListToString": "String List to String",
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"WildcardPromptFromString": "Wildcard Prompt from String",
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@@ -393,6 +393,7 @@ app.registerExtension({
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}
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if (nodeData.name === 'ImpactMakeImageList' || nodeData.name === 'ImpactMakeImageBatch' ||
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nodeData.name === 'ImpactMakeMaskList' || nodeData.name === 'ImpactMakeMaskBatch' ||
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nodeData.name === 'CombineRegionalPrompts' ||
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nodeData.name === 'ImpactCombineConditionings' || nodeData.name === 'ImpactConcatConditionings' ||
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nodeData.name === 'ImpactSEGSConcat' ||
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@@ -405,6 +406,11 @@ app.registerExtension({
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input_name = "image";
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break;
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case 'ImpactMakeMaskList':
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case 'ImpactMakeMaskBatch':
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input_name = "mask";
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break;
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case 'ImpactSEGSConcat':
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input_name = "segs";
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break;
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@@ -5,6 +5,13 @@ from impact.core import SEG
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from impact.segs_nodes import SEGSPaste
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try:
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from comfy_extras import nodes_differential_diffusion
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except Exception:
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print(f"\n#############################################\n[Impact Pack] ComfyUI is an outdated version.\n#############################################\n")
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raise Exception("[Impact Pack] ComfyUI is an outdated version.")
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class SEGSDetailerForAnimateDiff:
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@classmethod
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def INPUT_TYPES(cls):
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@@ -53,6 +60,9 @@ class SEGSDetailerForAnimateDiff:
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new_segs = []
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cnet_image_list = []
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if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
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model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
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for seg in segs[1]:
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cropped_image_frames = None
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@@ -1,7 +1,7 @@
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import configparser
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import os
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version_code = [7, 4, 5]
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version_code = [7, 5, 1]
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version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
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dependency_version = 22
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@@ -29,6 +29,14 @@ import impact.wildcards as wildcards
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from . import hooks
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from . import utils
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try:
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from comfy_extras import nodes_differential_diffusion
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except Exception:
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print(f"\n#############################################\n[Impact Pack] ComfyUI is an outdated version.\n#############################################\n")
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raise Exception("[Impact Pack] ComfyUI is an outdated version.")
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warnings.filterwarnings('ignore', category=UserWarning, message='TypedStorage is deprecated')
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model_path = folder_paths.models_dir
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@@ -257,6 +265,9 @@ class DetailerForEach:
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else:
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ordered_segs = segs[1]
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if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
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model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
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for i, seg in enumerate(ordered_segs):
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cropped_image = crop_ndarray4(image.cpu().numpy(), seg.crop_region) # Never use seg.cropped_image to handle overlapping area
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cropped_image = to_tensor(cropped_image)
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@@ -1696,6 +1707,25 @@ class ToBinaryMask:
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return (mask,)
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class FlattenMask:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"masks": ("MASK",),
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}
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}
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RETURN_TYPES = ("MASK",)
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FUNCTION = "doit"
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CATEGORY = "ImpactPack/Operation"
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def doit(self, masks):
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masks = utils.make_3d_mask(masks)
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masks = utils.flatten_mask(masks)
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return (masks,)
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class BitwiseAndMask:
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@classmethod
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def INPUT_TYPES(s):
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@@ -14,6 +14,13 @@ from comfy.cli_args import args
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import math
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try:
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from comfy_extras import nodes_differential_diffusion
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except Exception:
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print(f"\n#############################################\n[Impact Pack] ComfyUI is an outdated version.\n#############################################\n")
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raise Exception("[Impact Pack] ComfyUI is an outdated version.")
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class SEGSDetailer:
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@classmethod
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def INPUT_TYPES(s):
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@@ -69,6 +76,9 @@ class SEGSDetailer:
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new_segs = []
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cnet_pil_list = []
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if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
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model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
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for i in range(batch_size):
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seed += 1
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for seg in segs[1]:
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@@ -392,6 +392,26 @@ class ImageBatchToImageList:
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return (images, )
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class MakeMaskList:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"mask1": ("MASK",), }}
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RETURN_TYPES = ("MASK",)
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OUTPUT_IS_LIST = (True,)
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FUNCTION = "doit"
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CATEGORY = "ImpactPack/Util"
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def doit(self, **kwargs):
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masks = []
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for k, v in kwargs.items():
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masks.append(v)
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return (masks, )
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class MakeImageList:
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@classmethod
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def INPUT_TYPES(s):
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@@ -437,6 +457,31 @@ class MakeImageBatch:
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return (image1,)
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class MakeMaskBatch:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"mask1": ("MASK",), }}
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RETURN_TYPES = ("MASK",)
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FUNCTION = "doit"
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CATEGORY = "ImpactPack/Util"
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def doit(self, **kwargs):
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mask1 = kwargs['mask1']
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del kwargs['mask1']
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masks = [utils.make_3d_mask(value) for value in kwargs.values()]
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if len(masks) == 0:
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return (mask1,)
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else:
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for mask2 in masks:
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if mask1.shape[1:] != mask2.shape[1:]:
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mask2 = comfy.utils.common_upscale(mask2.movedim(-1, 1), mask1.shape[2], mask1.shape[1], "lanczos", "center").movedim(1, -1)
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mask1 = torch.cat((mask1, mask2), dim=0)
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return (mask1,)
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class ReencodeLatent:
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@classmethod
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def INPUT_TYPES(s):
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@@ -5,8 +5,7 @@ import numpy as np
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import folder_paths
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import nodes
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from . import config
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from PIL import Image, ImageFilter
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from scipy.ndimage import zoom
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from PIL import Image
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import comfy
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@@ -579,6 +578,14 @@ def apply_mask_alpha_to_pil(decoded_pil, mask):
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return decoded_rgba
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def flatten_mask(all_masks):
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merged_mask = (all_masks[0] * 255).to(torch.uint8)
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for mask in all_masks[1:]:
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merged_mask |= (mask * 255).to(torch.uint8)
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return merged_mask
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def try_install_custom_node(custom_node_url, msg):
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try:
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import cm_global
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+1
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@@ -1,7 +1,7 @@
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[project]
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name = "comfyui-impact-pack"
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description = "This extension offers various detector nodes and detailer nodes that allow you to configure a workflow that automatically enhances facial details. And provide iterative upscaler."
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version = "7.4.5"
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version = "7.5.1"
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license = { file = "LICENSE.txt" }
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dependencies = ["segment-anything", "scikit-image", "piexif", "transformers", "opencv-python-headless", "GitPython", "scipy>=1.11.4"]
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@@ -6,3 +6,4 @@ opencv-python-headless
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GitPython
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scipy>=1.11.4
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numpy<2
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dill
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Reference in New Issue
Block a user