chores: Update nodes names and categories (#16274)

This commit is contained in:
Alexis Rolland
2026-09-17 19:48:54 -04:00
committed by GitHub
parent fd88b3c412
commit 7de99222f0
9 changed files with 30 additions and 13 deletions
+1
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@@ -13,6 +13,7 @@ class EmptyCosmosLatentVideo(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="EmptyCosmosLatentVideo",
display_name="Empty Cosmos Latent Video",
category="model/latent/cosmos",
inputs=[
io.Int.Input("width", default=1280, min=16, max=nodes.MAX_RESOLUTION, step=16),
+5 -4
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@@ -43,7 +43,7 @@ class EmptyHunyuanLatentVideo(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="EmptyHunyuanLatentVideo",
display_name="Empty HunyuanVideo 1.0 Latent",
display_name="Empty Hunyuan Video 1.0 Latent",
category="model/latent/hunyuan video",
inputs=[
io.Int.Input("width", default=848, min=16, max=nodes.MAX_RESOLUTION, step=16),
@@ -69,7 +69,7 @@ class EmptyHunyuanVideo15Latent(EmptyHunyuanLatentVideo):
def define_schema(cls):
schema = super().define_schema()
schema.node_id = "EmptyHunyuanVideo15Latent"
schema.display_name = "Empty HunyuanVideo 1.5 Latent"
schema.display_name = "Empty Hunyuan Video 1.5 Latent"
schema.category = "model/latent/hunyuan video"
return schema
@@ -233,8 +233,8 @@ class HunyuanVideo15LatentUpscaleWithModel(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="HunyuanVideo15LatentUpscaleWithModel",
display_name="Hunyuan Video 15 Latent Upscale With Model",
category="model/latent/hunyhuan video",
display_name="Hunyuan Video 1.5 Latent Upscale With Model",
category="model/latent/hunyuan video",
inputs=[
io.LatentUpscaleModel.Input("model"),
io.Latent.Input("samples"),
@@ -366,6 +366,7 @@ class EmptyHunyuanImageLatent(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="EmptyHunyuanImageLatent",
display_name="Empty Hunyuan Image Latent",
category="model/latent/hunyuan image",
inputs=[
io.Int.Input("width", default=2048, min=64, max=nodes.MAX_RESOLUTION, step=32),
+2
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@@ -12,6 +12,7 @@ class EmptyLatentHunyuan3Dv2(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="EmptyLatentHunyuan3Dv2",
display_name="Empty Hunyuan 3D v2 Latent",
category="model/latent/hunyuan 3d",
inputs=[
IO.Int.Input("resolution", default=3072, min=1, max=8192),
@@ -97,6 +98,7 @@ class VAEDecodeHunyuan3D(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="VAEDecodeHunyuan3D",
display_name="Hunyuan 3D VAE Decode",
category="model/latent/hunyuan 3d",
inputs=[
IO.Latent.Input("samples"),
+1
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@@ -65,6 +65,7 @@ class EmptyLTXVLatentVideo(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="EmptyLTXVLatentVideo",
display_name="Empty LTXV Latent Video",
category="model/latent/ltxv",
inputs=[
io.Int.Input("width", default=768, min=64, max=nodes.MAX_RESOLUTION, step=32),
+1 -1
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@@ -95,7 +95,7 @@ class LTXVEmptyLatentAudio(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="LTXVEmptyLatentAudio",
display_name="LTXV Empty Latent Audio",
display_name="Empty LTXV Latent Audio",
category="model/latent/ltxv",
inputs=[
io.Int.Input(
+2
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@@ -12,6 +12,7 @@ class TextEncodeQwenImageEdit(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="TextEncodeQwenImageEdit",
display_name="Text Encode Qwen Image Edit",
category="model/conditioning/qwen image",
inputs=[
io.Clip.Input("clip"),
@@ -55,6 +56,7 @@ class TextEncodeQwenImageEditPlus(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="TextEncodeQwenImageEditPlus",
display_name="Text Encode Qwen Image Edit Plus",
category="model/conditioning/qwen image",
inputs=[
io.Clip.Input("clip"),
+2 -2
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@@ -426,7 +426,7 @@ class SeedVR2TemporalChunk(io.ComfyNode):
return io.Schema(
node_id="SeedVR2TemporalChunk",
display_name="Split SeedVR2 Latent",
category="model/latent/batch",
category="model/latent/seedvr",
description="Split a SeedVR2 video latent into overlapping temporal chunks small enough to sample one at a time within VRAM, wiring latents outputs to both Apply SeedVR2 Conditioning and the sampler latent input before recombining with Merge SeedVR2 Latents.",
search_aliases=["seedvr2", "split", "chunk", "temporal", "video upscale", "rebatch"],
inputs=[
@@ -520,7 +520,7 @@ class SeedVR2TemporalMerge(io.ComfyNode):
return io.Schema(
node_id="SeedVR2TemporalMerge",
display_name="Merge SeedVR2 Latents",
category="model/latent/batch",
category="model/latent/seedvr",
is_input_list=True,
description="Recombine sampled SeedVR2 latent temporal chunks into one latent, crossfading each overlap with a Hann window sized by the temporal_overlap wired from Split SeedVR2 Latent.",
search_aliases=["seedvr2", "merge", "temporal", "hann", "crossfade"],
+2
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@@ -29,6 +29,7 @@ class StableCascade_EmptyLatentImage(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="StableCascade_EmptyLatentImage",
display_name="Empty Stable Cascade Latent Image",
category="model/latent/stable cascade",
inputs=[
io.Int.Input("width", default=1024, min=256, max=nodes.MAX_RESOLUTION, step=8),
@@ -58,6 +59,7 @@ class StableCascade_StageC_VAEEncode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="StableCascade_StageC_VAEEncode",
display_name="Stable Cascade Stage C VAE Encode",
category="model/latent/stable cascade",
inputs=[
io.Image.Input("image"),
+14 -6
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@@ -118,6 +118,7 @@ class VaeDecodeShapeTrellis(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="VaeDecodeShapeTrellis",
display_name="Trellis2 VAE Decode Shape",
category="model/latent/trellis",
inputs=[
IO.Latent.Input("samples"),
@@ -196,6 +197,7 @@ class VaeDecodeTextureTrellis(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="VaeDecodeTextureTrellis",
display_name="Trellis2 VAE Decode Texture",
category="model/latent/trellis",
inputs=[
IO.Latent.Input("samples"),
@@ -277,6 +279,7 @@ class VaeDecodeStructureTrellis2(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="VaeDecodeStructureTrellis2",
display_name="Trellis2 VAE Decode Structure",
category="model/latent/trellis",
inputs=[
IO.Latent.Input("samples"),
@@ -318,7 +321,7 @@ class Trellis2UpsampleStage(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="Trellis2UpsampleStage",
category="model/conditioning/trellis2",
category="model/conditioning/trellis",
display_name="Trellis2 Upsample Stage",
inputs=[
IO.Conditioning.Input("positive"),
@@ -440,7 +443,8 @@ class Trellis2Conditioning(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="Trellis2Conditioning",
category="model/conditioning/trellis2",
display_name="Trellis2 Conditioning",
category="model/conditioning/trellis",
inputs=[
IO.ClipVision.Input("clip_vision_model"),
IO.Image.Input("image", tooltip="Preprocessed image from ImageCropToMask (pad_factor=1.0 for TRELLIS.2)."),
@@ -501,7 +505,8 @@ class Trellis2ShapeStage(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="Trellis2ShapeStage",
category="model/conditioning/trellis2",
display_name="Trellis2 Shape Stage",
category="model/conditioning/trellis",
inputs=[
IO.Conditioning.Input("positive"),
IO.Conditioning.Input("negative"),
@@ -567,7 +572,8 @@ class Trellis2TextureStage(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="Trellis2TextureStage",
category="model/conditioning/trellis2",
display_name="Trellis2 Texture Stage",
category="model/conditioning/trellis",
inputs=[
IO.Conditioning.Input("positive"),
IO.Conditioning.Input("negative"),
@@ -623,6 +629,7 @@ class EmptyTrellis2LatentStructure(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="EmptyTrellis2LatentStructure",
display_name="Empty Trellis2 Latent Structure",
category="model/latent/trellis",
inputs=[
IO.Int.Input("batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch."),
@@ -764,7 +771,8 @@ class Pixal3DConditioning(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="Pixal3DConditioning",
category="model/conditioning/trellis2",
display_name="Pixal3D Conditioning",
category="model/conditioning/trellis",
inputs=[
IO.ClipVision.Input("clip_vision_model", tooltip="DINOv3 ViT-L/16 ClipVision."),
IO.Image.Input("image", tooltip="Preprocessed image from ImageCropToMask (pad_factor=1.1 for Pixal3D)."),
@@ -824,7 +832,7 @@ class Pixal3DMultiViewConditioning(IO.ComfyNode):
return IO.Schema(
node_id="Pixal3DMultiViewConditioning",
display_name="Pixal3D Multi-View Conditioning",
category="model/conditioning/trellis2",
category="model/conditioning/trellis",
inputs=[IO.ClipVision.Input("clip_vision_model", tooltip="DINOv3 ViT-L/16 ClipVision with bundled NAF weights."),
IO.Float.Input("fov", default=20.0, min=1.0, max=170.0, step=0.01, round=False,
tooltip="Horizontal FOV in degrees of the views as framed: 20 for rig renders and most "