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5 changed files with 145 additions and 70 deletions

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@ -543,7 +543,7 @@ class AudioConcat(IO.ComfyNode):
return IO.Schema(
node_id="AudioConcat",
search_aliases=["join audio", "combine audio", "append audio"],
display_name="Audio Concat",
display_name="Concatenate Audio",
description="Concatenates the audio1 to audio2 in the specified direction.",
category="audio",
inputs=[
@ -597,7 +597,7 @@ class AudioMerge(IO.ComfyNode):
return IO.Schema(
node_id="AudioMerge",
search_aliases=["mix audio", "overlay audio", "layer audio"],
display_name="Audio Merge",
display_name="Merge Audio",
description="Combine two audio tracks by overlaying their waveforms.",
category="audio",
inputs=[
@ -667,8 +667,9 @@ class AudioAdjustVolume(IO.ComfyNode):
return IO.Schema(
node_id="AudioAdjustVolume",
search_aliases=["audio gain", "loudness", "audio level"],
display_name="Audio Adjust Volume",
display_name="Adjust Audio Volume",
category="audio",
description="Adjust the volume of the audio by a specified amount in decibels (dB).",
inputs=[
IO.Audio.Input("audio"),
IO.Int.Input(

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@ -47,8 +47,10 @@ class LoadImageDataSetFromFolderNode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="LoadImageDataSetFromFolder",
display_name="Load Image Dataset from Folder",
category="dataset",
search_aliases=["load folder", "load from folder", "load dataset", "load images", "import dataset"],
display_name="Load Image (from Folder)",
category="image",
description="Load a dataset of images from a specified folder and return a list of images. Supported formats: PNG, JPG, JPEG, WEBP.",
is_experimental=True,
inputs=[
io.Combo.Input(
@ -84,14 +86,16 @@ class LoadImageTextDataSetFromFolderNode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="LoadImageTextDataSetFromFolder",
display_name="Load Image and Text Dataset from Folder",
category="dataset",
search_aliases=["load folder", "load from folder", "load dataset", "load images", "import dataset"],
display_name="Load Image-Text (from Folder)",
category="image",
description="Load a dataset of pairs of images and text captions from a specified folder and return them as a list. Supported formats: PNG, JPG, JPEG, WEBP.",
is_experimental=True,
inputs=[
io.Combo.Input(
"folder",
options=folder_paths.get_input_subfolders(),
tooltip="The folder to load images from.",
tooltip="The folder to load images and text captions from.",
)
],
outputs=[
@ -206,8 +210,10 @@ class SaveImageDataSetToFolderNode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SaveImageDataSetToFolder",
display_name="Save Image Dataset to Folder",
category="dataset",
search_aliases=["save folder", "save to folder", "save dataset", "save images", "export dataset"],
display_name="Save Image (to Folder) (DEPRECATED)",
category="image",
description="Save a dataset of images to a specified folder. Supported formats: PNG.",
is_experimental=True,
is_output_node=True,
is_input_list=True, # Receive images as list
@ -226,6 +232,7 @@ class SaveImageDataSetToFolderNode(io.ComfyNode):
),
],
outputs=[],
is_deprecated=True, # This node is redundant and superseded by existing Save Image nodes where the target folder can be specified in the filename_prefix
)
@classmethod
@ -246,14 +253,20 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SaveImageTextDataSetToFolder",
display_name="Save Image and Text Dataset to Folder",
category="dataset",
search_aliases=["save folder", "save to folder", "save dataset", "save images", "save text", "export dataset"],
display_name="Save Image-Text (to Folder)",
category="image",
description="Save a dataset of pairs of images and text captions to a specified folder. Images are saved as PNG files and captions are saved as TXT files with the same filename_prefix.",
is_experimental=True,
is_output_node=True,
is_input_list=True, # Receive both images and texts as lists
inputs=[
io.Image.Input("images", tooltip="List of images to save."),
io.String.Input("texts", tooltip="List of text captions to save."),
io.String.Input("texts",
optional=True,
force_input=True,
tooltip="List of text captions to save."
),
io.String.Input(
"folder_name",
default="dataset",
@ -270,7 +283,7 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
)
@classmethod
def execute(cls, images, texts, folder_name, filename_prefix):
def execute(cls, images, folder_name, filename_prefix, texts=None):
# Extract scalar values
folder_name = folder_name[0]
filename_prefix = filename_prefix[0]
@ -279,11 +292,12 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
saved_files = save_images_to_folder(images, output_dir, filename_prefix)
# Save captions
for idx, (filename, caption) in enumerate(zip(saved_files, texts)):
caption_filename = filename.replace(".png", ".txt")
caption_path = os.path.join(output_dir, caption_filename)
with open(caption_path, "w", encoding="utf-8") as f:
f.write(caption)
if texts:
for idx, (filename, caption) in enumerate(zip(saved_files, texts)):
caption_filename = filename.replace(".png", ".txt")
caption_path = os.path.join(output_dir, caption_filename)
with open(caption_path, "w", encoding="utf-8") as f:
f.write(caption)
logging.info(f"Saved {len(saved_files)} images and captions to {output_dir}.")
return io.NodeOutput()
@ -314,11 +328,13 @@ class ImageProcessingNode(io.ComfyNode):
Child classes should set:
node_id: Unique node identifier (required)
search_aliases: List of search aliases (optional)
display_name: Display name (optional, defaults to node_id)
description: Node description (optional)
extra_inputs: List of additional io.Input objects beyond "images" (optional)
is_group_process: None (auto-detect), True (group), or False (individual) (optional)
is_output_list: True (list output) or False (single output) (optional, default True)
is_deprecated: True if the node is deprecated (optional, default False)
Child classes must implement ONE of:
_process(cls, image, **kwargs) -> tensor (for single-item processing)
@ -326,12 +342,13 @@ class ImageProcessingNode(io.ComfyNode):
"""
node_id = None
search_aliases = []
display_name = None
description = None
extra_inputs = []
is_group_process = None # None = auto-detect, True/False = explicit
is_output_list = None # None = auto-detect based on processing mode
is_deprecated = False
@classmethod
def _detect_processing_mode(cls):
"""Detect whether this node uses group or individual processing.
@ -402,8 +419,10 @@ class ImageProcessingNode(io.ComfyNode):
return io.Schema(
node_id=cls.node_id,
search_aliases=cls.search_aliases,
display_name=cls.display_name or cls.node_id,
category="dataset/image",
category=cls.category,
description=cls.description,
is_experimental=True,
is_input_list=is_group, # True for group, False for individual
inputs=inputs,
@ -472,11 +491,13 @@ class TextProcessingNode(io.ComfyNode):
Child classes should set:
node_id: Unique node identifier (required)
search_aliases: List of search aliases (optional)
display_name: Display name (optional, defaults to node_id)
description: Node description (optional)
extra_inputs: List of additional io.Input objects beyond "texts" (optional)
is_group_process: None (auto-detect), True (group), or False (individual) (optional)
is_output_list: True (list output) or False (single output) (optional, default True)
is_deprecated: True if the node is deprecated (optional, default False)
Child classes must implement ONE of:
_process(cls, text, **kwargs) -> str (for single-item processing)
@ -484,12 +505,13 @@ class TextProcessingNode(io.ComfyNode):
"""
node_id = None
search_aliases = []
display_name = None
description = None
extra_inputs = []
is_group_process = None # None = auto-detect, True/False = explicit
is_output_list = None # None = auto-detect based on processing mode
is_deprecated = False
@classmethod
def _detect_processing_mode(cls):
"""Detect whether this node uses group or individual processing.
@ -627,15 +649,17 @@ class TextProcessingNode(io.ComfyNode):
class ResizeImagesByShorterEdgeNode(ImageProcessingNode):
node_id = "ResizeImagesByShorterEdge"
display_name = "Resize Images by Shorter Edge"
description = "Resize images so that the shorter edge matches the specified length while preserving aspect ratio."
display_name = "Resize Images by Shorter Edge (DEPRECATED)"
category = "image/transform"
description = "Resize images so that the shorter edge matches the specified dimension while preserving aspect ratio."
is_deprecated = True # This node is superseded by Resize Image/Mask with resize_type = scale shorter dimension
extra_inputs = [
io.Int.Input(
"shorter_edge",
default=512,
min=1,
max=8192,
tooltip="Target length for the shorter edge.",
tooltip="Target dimension for the shorter edge.",
),
]
@ -655,15 +679,17 @@ class ResizeImagesByShorterEdgeNode(ImageProcessingNode):
class ResizeImagesByLongerEdgeNode(ImageProcessingNode):
node_id = "ResizeImagesByLongerEdge"
display_name = "Resize Images by Longer Edge"
description = "Resize images so that the longer edge matches the specified length while preserving aspect ratio."
display_name = "Resize Images by Longer Edge (DEPRECATED)"
category = "image/transform"
description = "Resize images so that the longer edge matches the specified dimension while preserving aspect ratio."
is_deprecated = True # This node is superseded by Resize Image/Mask with resize_type = scale longer dimension
extra_inputs = [
io.Int.Input(
"longer_edge",
default=1024,
min=1,
max=8192,
tooltip="Target length for the longer edge.",
tooltip="Target dimension for the longer edge.",
),
]
@ -686,8 +712,10 @@ class ResizeImagesByLongerEdgeNode(ImageProcessingNode):
class CenterCropImagesNode(ImageProcessingNode):
node_id = "CenterCropImages"
display_name = "Center Crop Images"
description = "Center crop all images to the specified dimensions."
search_aliases=["crop", "cut", "trim"]
display_name="Crop Image (Center)"
category="image/transform"
description = "Center crop an image to the specified dimensions."
extra_inputs = [
io.Int.Input("width", default=512, min=1, max=8192, tooltip="Crop width."),
io.Int.Input("height", default=512, min=1, max=8192, tooltip="Crop height."),
@ -706,10 +734,11 @@ class CenterCropImagesNode(ImageProcessingNode):
class RandomCropImagesNode(ImageProcessingNode):
node_id = "RandomCropImages"
display_name = "Random Crop Images"
description = (
"Randomly crop all images to the specified dimensions (for data augmentation)."
)
search_aliases=["crop", "cut", "trim"]
display_name = "Crop Image (Random)"
category="image/transform"
description = "Randomly crop an image to the specified dimensions."
extra_inputs = [
io.Int.Input("width", default=512, min=1, max=8192, tooltip="Crop width."),
io.Int.Input("height", default=512, min=1, max=8192, tooltip="Crop height."),
@ -734,7 +763,9 @@ class RandomCropImagesNode(ImageProcessingNode):
class NormalizeImagesNode(ImageProcessingNode):
node_id = "NormalizeImages"
display_name = "Normalize Images"
search_aliases=["normalize", "normalize colors"]
display_name = "Normalize Image Colors"
category = "image/color"
description = "Normalize images using mean and standard deviation."
extra_inputs = [
io.Float.Input(
@ -762,8 +793,10 @@ class NormalizeImagesNode(ImageProcessingNode):
class AdjustBrightnessNode(ImageProcessingNode):
node_id = "AdjustBrightness"
search_aliases=["brightness"]
display_name = "Adjust Brightness"
description = "Adjust brightness of all images."
category="image/adjustments"
description = "Adjust the brightness of an image."
extra_inputs = [
io.Float.Input(
"factor",
@ -781,8 +814,10 @@ class AdjustBrightnessNode(ImageProcessingNode):
class AdjustContrastNode(ImageProcessingNode):
node_id = "AdjustContrast"
search_aliases=["contrast"]
display_name = "Adjust Contrast"
description = "Adjust contrast of all images."
category="image/adjustments"
description = "Adjust the contrast of an image."
extra_inputs = [
io.Float.Input(
"factor",
@ -800,8 +835,10 @@ class AdjustContrastNode(ImageProcessingNode):
class ShuffleDatasetNode(ImageProcessingNode):
node_id = "ShuffleDataset"
display_name = "Shuffle Image Dataset"
description = "Randomly shuffle the order of images in the dataset."
search_aliases=["shuffle", "randomize", "mix"]
display_name = "Shuffle Images List"
category = "image/batch"
description = "Randomly shuffle the order of images in a list."
is_group_process = True # Requires full list to shuffle
extra_inputs = [
io.Int.Input(
@ -823,13 +860,15 @@ class ShuffleImageTextDatasetNode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="ShuffleImageTextDataset",
display_name="Shuffle Image-Text Dataset",
category="dataset/image",
search_aliases=["shuffle", "randomize", "mix"],
display_name = "Shuffle Pairs of Image-Text",
category = "image/batch",
description = "Randomly shuffle the order of pairs of image-text in a list.",
is_experimental=True,
is_input_list=True,
inputs=[
io.Image.Input("images", tooltip="List of images to shuffle."),
io.String.Input("texts", tooltip="List of texts to shuffle."),
io.String.Input("texts", tooltip="List of texts to shuffle.", force_input=True),
io.Int.Input(
"seed",
default=0,
@ -865,8 +904,11 @@ class ShuffleImageTextDatasetNode(io.ComfyNode):
class TextToLowercaseNode(TextProcessingNode):
node_id = "TextToLowercase"
display_name = "Text to Lowercase"
description = "Convert all texts to lowercase."
search_aliases=["lowercase"]
display_name = "Convert Text to Lowercase (DEPRECATED)"
category = "text"
description = "Convert text to lowercase."
is_deprecated = True # This node is superseded by the Convert Text Case node
@classmethod
def _process(cls, text):
@ -875,8 +917,11 @@ class TextToLowercaseNode(TextProcessingNode):
class TextToUppercaseNode(TextProcessingNode):
node_id = "TextToUppercase"
display_name = "Text to Uppercase"
description = "Convert all texts to uppercase."
search_aliases=["uppercase"]
display_name = "Convert Text to Uppercase (DEPRECATED)"
category = "text"
description = "Convert text to uppercase."
is_deprecated = True # This node is superseded by the Convert Text Case node
@classmethod
def _process(cls, text):
@ -885,8 +930,10 @@ class TextToUppercaseNode(TextProcessingNode):
class TruncateTextNode(TextProcessingNode):
node_id = "TruncateText"
search_aliases=["truncate", "cut", "shorten"]
display_name = "Truncate Text"
description = "Truncate all texts to a maximum length."
category = "text"
description = "Truncate text to a maximum length."
extra_inputs = [
io.Int.Input(
"max_length", default=77, min=1, max=10000, tooltip="Maximum text length."
@ -900,8 +947,10 @@ class TruncateTextNode(TextProcessingNode):
class AddTextPrefixNode(TextProcessingNode):
node_id = "AddTextPrefix"
display_name = "Add Text Prefix"
display_name = "Add Text Prefix (DEPRECATED)"
category = "text"
description = "Add a prefix to all texts."
is_deprecated = True # This node is superseded by the Concatenate Text node
extra_inputs = [
io.String.Input("prefix", default="", tooltip="Prefix to add."),
]
@ -913,8 +962,10 @@ class AddTextPrefixNode(TextProcessingNode):
class AddTextSuffixNode(TextProcessingNode):
node_id = "AddTextSuffix"
display_name = "Add Text Suffix"
display_name = "Add Text Suffix (DEPRECATED)"
category = "text"
description = "Add a suffix to all texts."
is_deprecated = True # This node is superseded by the Concatenate Text node
extra_inputs = [
io.String.Input("suffix", default="", tooltip="Suffix to add."),
]
@ -926,8 +977,10 @@ class AddTextSuffixNode(TextProcessingNode):
class ReplaceTextNode(TextProcessingNode):
node_id = "ReplaceText"
display_name = "Replace Text"
display_name = "Replace Text (DEPRECATED)"
category = "text"
description = "Replace text in all texts."
is_deprecated = True # This node is superseded by the other Replace Text node
extra_inputs = [
io.String.Input("find", default="", tooltip="Text to find."),
io.String.Input("replace", default="", tooltip="Text to replace with."),
@ -940,8 +993,10 @@ class ReplaceTextNode(TextProcessingNode):
class StripWhitespaceNode(TextProcessingNode):
node_id = "StripWhitespace"
display_name = "Strip Whitespace"
display_name = "Strip Whitespace (DEPRECATED)"
category = "text"
description = "Strip leading and trailing whitespace from all texts."
is_deprecated = True # This node is superseded by the Trim Text node
@classmethod
def _process(cls, text):
@ -952,11 +1007,13 @@ class StripWhitespaceNode(TextProcessingNode):
class ImageDeduplicationNode(ImageProcessingNode):
"""Remove duplicate or very similar images from the dataset using perceptual hashing."""
"""Remove duplicate or very similar images from a list using perceptual hashing."""
node_id = "ImageDeduplication"
display_name = "Image Deduplication"
description = "Remove duplicate or very similar images from the dataset."
search_aliases=["deduplicate", "remove duplicates", "similarity filter"]
display_name = "Deduplicate Images"
category = "image/batch"
description = "Remove duplicate or very similar images from a list."
is_group_process = True # Requires full list to compare images
extra_inputs = [
io.Float.Input(
@ -1026,7 +1083,9 @@ class ImageGridNode(ImageProcessingNode):
"""Combine multiple images into a single grid/collage."""
node_id = "ImageGrid"
display_name = "Image Grid"
search_aliases=["grid", "collage", "combine"]
display_name = "Make Image Grid"
category="image/batch"
description = "Arrange multiple images into a grid layout."
is_group_process = True # Requires full list to create grid
is_output_list = False # Outputs single grid image
@ -1102,9 +1161,12 @@ class MergeImageListsNode(ImageProcessingNode):
"""Merge multiple image lists into a single list."""
node_id = "MergeImageLists"
display_name = "Merge Image Lists"
search_aliases=["list", "merge list", "make list"]
display_name = "Merge Image Lists (DEPRECATED)"
category = "image/batch"
description = "Concatenate multiple image lists into one."
is_group_process = True # Receives images as list
is_deprecated = True # This node is superseded by the Create List node
@classmethod
def _group_process(cls, images):
@ -1119,9 +1181,11 @@ class MergeTextListsNode(TextProcessingNode):
"""Merge multiple text lists into a single list."""
node_id = "MergeTextLists"
display_name = "Merge Text Lists"
display_name = "Merge Text Lists (DEPRECATED)"
category = "text"
description = "Concatenate multiple text lists into one."
is_group_process = True # Receives texts as list
is_deprecated = True # This node is superseded by the Create List node
@classmethod
def _group_process(cls, texts):
@ -1142,8 +1206,10 @@ class ResolutionBucket(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="ResolutionBucket",
search_aliases=["bucket by resolution", "group by resolution", "batch by resolution"],
display_name="Resolution Bucket",
category="dataset",
category="training",
description="Group latents and conditionings into buckets",
is_experimental=True,
is_input_list=True,
inputs=[
@ -1236,7 +1302,8 @@ class MakeTrainingDataset(io.ComfyNode):
node_id="MakeTrainingDataset",
search_aliases=["encode dataset"],
display_name="Make Training Dataset",
category="dataset",
category="training",
description="Encode images with VAE and texts with CLIP to create a training dataset of latents and conditionings.",
is_experimental=True,
is_input_list=True, # images and texts as lists
inputs=[
@ -1251,6 +1318,7 @@ class MakeTrainingDataset(io.ComfyNode):
"texts",
optional=True,
tooltip="List of text captions. Can be length n (matching images), 1 (repeated for all), or omitted (uses empty string).",
force_input=True
),
],
outputs=[
@ -1320,9 +1388,10 @@ class SaveTrainingDataset(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SaveTrainingDataset",
search_aliases=["export training data"],
search_aliases=["export dataset", "save dataset"],
display_name="Save Training Dataset",
category="dataset",
category="training",
description="Save encoded training dataset (latents + conditioning) to disk for efficient loading during training.",
is_experimental=True,
is_output_node=True,
is_input_list=True, # Receive lists
@ -1424,7 +1493,8 @@ class LoadTrainingDataset(io.ComfyNode):
node_id="LoadTrainingDataset",
search_aliases=["import dataset", "training data"],
display_name="Load Training Dataset",
category="dataset",
category="training",
description="Load encoded training dataset (latents + conditioning) from disk for use in training.",
is_experimental=True,
inputs=[
io.String.Input(

View File

@ -419,15 +419,17 @@ class VoxelToMeshBasic(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="VoxelToMeshBasic",
display_name="Voxel to Mesh (Basic)",
display_name="Voxel to Mesh (Basic) (DEPRECATED)",
category="3d",
description="Converts a voxel grid to a mesh.",
is_deprecated=True, # This node is superseded by the Voxel To Mesh node
inputs=[
IO.Voxel.Input("voxel"),
IO.Float.Input("threshold", default=0.6, min=-1.0, max=1.0, step=0.01),
],
outputs=[
IO.Mesh.Output(),
]
],
)
@classmethod
@ -453,9 +455,10 @@ class VoxelToMesh(IO.ComfyNode):
node_id="VoxelToMesh",
display_name="Voxel to Mesh",
category="3d",
description="Converts a voxel grid to a mesh.",
inputs=[
IO.Voxel.Input("voxel"),
IO.Combo.Input("algorithm", options=["surface net", "basic"], advanced=True),
IO.Combo.Input("algorithm", options=["surface net", "basic"]),
IO.Float.Input("threshold", default=0.6, min=-1.0, max=1.0, step=0.01),
],
outputs=[

View File

@ -55,9 +55,10 @@ class ImageCropV2(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="ImageCropV2",
search_aliases=["trim"],
search_aliases=["crop", "cut", "trim"],
display_name="Crop Image",
category="image/transform",
description = "Crop an image to the specified dimensions.",
essentials_category="Image Tools",
has_intermediate_output=True,
inputs=[

View File

@ -11,8 +11,8 @@ class LTXVAudioVAELoader(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="LTXVAudioVAELoader",
display_name="LTXV Audio VAE Loader",
category="audio",
display_name="Load LTXV Audio VAE",
category="loaders",
inputs=[
io.Combo.Input(
"ckpt_name",
@ -40,7 +40,7 @@ class LTXVAudioVAEEncode(VAEEncodeAudio):
return io.Schema(
node_id="LTXVAudioVAEEncode",
display_name="LTXV Audio VAE Encode",
category="audio",
category="latent/audio",
inputs=[
io.Audio.Input("audio", tooltip="The audio to be encoded."),
io.Vae.Input(
@ -63,7 +63,7 @@ class LTXVAudioVAEDecode(io.ComfyNode):
return io.Schema(
node_id="LTXVAudioVAEDecode",
display_name="LTXV Audio VAE Decode",
category="audio",
category="latent/audio",
inputs=[
io.Latent.Input("samples", tooltip="The latent to be decoded."),
io.Vae.Input(