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https://github.com/comfyanonymous/ComfyUI.git
synced 2026-05-11 01:32:31 +08:00
Update node categories and display names
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6bcd8b96ab
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2edcd9a880
@ -10,6 +10,7 @@ class AudioEncoderLoader(io.ComfyNode):
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def define_schema(cls) -> io.Schema:
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return io.Schema(
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node_id="AudioEncoderLoader",
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display_name="Load Audio Encoder",
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category="loaders",
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inputs=[
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io.Combo.Input(
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@ -153,7 +153,7 @@ class WanCameraEmbedding(io.ComfyNode):
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def define_schema(cls):
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return io.Schema(
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node_id="WanCameraEmbedding",
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category="camera",
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category="conditioning/video_models",
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inputs=[
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io.Combo.Input(
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"camera_pose",
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@ -10,7 +10,7 @@ class ContextWindowsManualNode(io.ComfyNode):
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return io.Schema(
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node_id="ContextWindowsManual",
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display_name="Context Windows (Manual)",
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category="context",
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category="model_patches",
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description="Manually set context windows.",
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inputs=[
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io.Model.Input("model", tooltip="The model to apply context windows to during sampling."),
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@ -131,6 +131,8 @@ class HunyuanVideo15SuperResolution(io.ComfyNode):
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def define_schema(cls):
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return io.Schema(
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node_id="HunyuanVideo15SuperResolution",
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display_name="Hunyuan Video 1.5 Super Resolution",
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category="conditioning/video_models",
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inputs=[
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io.Conditioning.Input("positive"),
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io.Conditioning.Input("negative"),
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@ -381,6 +383,8 @@ class HunyuanRefinerLatent(io.ComfyNode):
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def define_schema(cls):
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return io.Schema(
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node_id="HunyuanRefinerLatent",
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display_name="Hunyuan Latent Refiner",
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category="conditioning/video_models",
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inputs=[
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io.Conditioning.Input("positive"),
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io.Conditioning.Input("negative"),
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@ -40,7 +40,7 @@ class Hunyuan3Dv2Conditioning(IO.ComfyNode):
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def define_schema(cls):
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return IO.Schema(
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node_id="Hunyuan3Dv2Conditioning",
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category="conditioning/video_models",
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category="conditioning/3d_models",
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inputs=[
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IO.ClipVisionOutput.Input("clip_vision_output"),
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],
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@ -65,7 +65,7 @@ class Hunyuan3Dv2ConditioningMultiView(IO.ComfyNode):
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def define_schema(cls):
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return IO.Schema(
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node_id="Hunyuan3Dv2ConditioningMultiView",
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category="conditioning/video_models",
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category="conditioning/3d_models",
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inputs=[
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IO.ClipVisionOutput.Input("front", optional=True),
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IO.ClipVisionOutput.Input("left", optional=True),
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@ -102,6 +102,7 @@ class HypernetworkLoader(IO.ComfyNode):
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def define_schema(cls):
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return IO.Schema(
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node_id="HypernetworkLoader",
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display_name="Load Hypernetwork",
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category="loaders",
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inputs=[
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IO.Model.Input("model"),
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@ -70,7 +70,7 @@ class MathExpressionNode(io.ComfyNode):
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return io.Schema(
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node_id="ComfyMathExpression",
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display_name="Math Expression",
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category="math",
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category="logic",
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search_aliases=[
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"expression", "formula", "calculate", "calculator",
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"eval", "math",
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@ -21,7 +21,7 @@ class NumberConvertNode(io.ComfyNode):
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return io.Schema(
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node_id="ComfyNumberConvert",
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display_name="Number Convert",
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category="math",
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category="utils",
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search_aliases=[
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"int to float", "float to int", "number convert",
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"int2float", "float2int", "cast", "parse number",
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@ -116,6 +116,7 @@ class Quantize(io.ComfyNode):
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def define_schema(cls):
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return io.Schema(
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node_id="ImageQuantize",
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display_name="Quantize Image",
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category="image/postprocessing",
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inputs=[
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io.Image.Input("image"),
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@ -181,6 +182,7 @@ class Sharpen(io.ComfyNode):
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def define_schema(cls):
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return io.Schema(
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node_id="ImageSharpen",
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display_name="Sharpen Image",
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category="image/postprocessing",
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inputs=[
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io.Image.Input("image"),
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@ -436,7 +438,7 @@ class ResizeImageMaskNode(io.ComfyNode):
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node_id="ResizeImageMaskNode",
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display_name="Resize Image/Mask",
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description="Resize an image or mask using various scaling methods.",
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category="transform",
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category="image/transform",
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search_aliases=["resize", "resize image", "resize mask", "scale", "scale image", "scale mask", "image resize", "change size", "dimensions", "shrink", "enlarge"],
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inputs=[
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io.MatchType.Input("input", template=template),
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@ -15,7 +15,7 @@ class RTDETR_detect(io.ComfyNode):
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return io.Schema(
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node_id="RTDETR_detect",
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display_name="RT-DETR Detect",
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category="detection/",
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category="detection",
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search_aliases=["bbox", "bounding box", "object detection", "coco"],
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inputs=[
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io.Model.Input("model", display_name="model"),
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@ -71,7 +71,7 @@ class DrawBBoxes(io.ComfyNode):
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return io.Schema(
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node_id="DrawBBoxes",
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display_name="Draw BBoxes",
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category="detection/",
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category="detection",
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search_aliases=["bbox", "bounding box", "object detection", "rt_detr", "visualize detections", "coco"],
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inputs=[
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io.Image.Input("image", optional=True),
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@ -93,7 +93,7 @@ class SAM3_Detect(io.ComfyNode):
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return io.Schema(
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node_id="SAM3_Detect",
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display_name="SAM3 Detect",
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category="detection/",
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category="detection",
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search_aliases=["sam3", "segment anything", "open vocabulary", "text detection", "segment"],
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inputs=[
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io.Model.Input("model", display_name="model"),
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@ -265,7 +265,7 @@ class SAM3_VideoTrack(io.ComfyNode):
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return io.Schema(
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node_id="SAM3_VideoTrack",
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display_name="SAM3 Video Track",
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category="detection/",
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category="detection",
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search_aliases=["sam3", "video", "track", "propagate"],
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inputs=[
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io.Image.Input("images", display_name="images", tooltip="Video frames as batched images"),
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@ -321,7 +321,7 @@ class SAM3_TrackPreview(io.ComfyNode):
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return io.Schema(
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node_id="SAM3_TrackPreview",
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display_name="SAM3 Track Preview",
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category="detection/",
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category="detection",
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inputs=[
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SAM3TrackData.Input("track_data", display_name="track_data"),
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io.Image.Input("images", display_name="images", optional=True),
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@ -475,7 +475,7 @@ class SAM3_TrackToMask(io.ComfyNode):
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return io.Schema(
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node_id="SAM3_TrackToMask",
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display_name="SAM3 Track to Mask",
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category="detection/",
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category="detection",
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inputs=[
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SAM3TrackData.Input("track_data", display_name="track_data"),
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io.String.Input("object_indices", display_name="object_indices", default="",
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@ -26,7 +26,7 @@ class TextGenerate(io.ComfyNode):
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return io.Schema(
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node_id="TextGenerate",
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category="textgen",
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category="text",
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search_aliases=["LLM", "gemma"],
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inputs=[
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io.Clip.Input("clip"),
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@ -1361,7 +1361,7 @@ class SaveLoRA(io.ComfyNode):
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node_id="SaveLoRA",
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search_aliases=["export lora"],
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display_name="Save LoRA Weights",
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category="loaders",
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category="advanced/model_merging",
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is_experimental=True,
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is_output_node=True,
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inputs=[
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@ -15,7 +15,7 @@ class ImageOnlyCheckpointLoader:
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RETURN_TYPES = ("MODEL", "CLIP_VISION", "VAE")
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FUNCTION = "load_checkpoint"
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CATEGORY = "loaders/video_models"
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CATEGORY = "loaders"
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def load_checkpoint(self, ckpt_name, output_vae=True, output_clip=True):
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ckpt_path = folder_paths.get_full_path_or_raise("checkpoints", ckpt_name)
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@ -22,7 +22,7 @@ class SaveImageWebsocket:
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OUTPUT_NODE = True
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CATEGORY = "api/image"
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CATEGORY = "image"
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def save_images(self, images):
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pbar = comfy.utils.ProgressBar(images.shape[0])
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1
nodes.py
1
nodes.py
@ -2092,6 +2092,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"StyleModelLoader": "Load Style Model",
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"CLIPVisionLoader": "Load CLIP Vision",
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"UNETLoader": "Load Diffusion Model",
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"unCLIPCheckpointLoader": "Load unCLIP Checkpoint",
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# Conditioning
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"CLIPVisionEncode": "CLIP Vision Encode",
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"StyleModelApply": "Apply Style Model",
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