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Update latent categories

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This commit is contained in:
Alexis Rolland 2026-06-14 10:31:25 +08:00
parent 43025e865e
commit 63781373ea
19 changed files with 34 additions and 31 deletions
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4
comfy_extras/nodes_ace.py
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@ -67,7 +67,7 @@ class EmptyAceStepLatentAudio(IO.ComfyNode):
return IO.Schema(
node_id="EmptyAceStepLatentAudio",
display_name="Empty Ace Step 1.0 Latent Audio",
category="model/latent/audio",
category="model/latent/ace",
inputs=[
IO.Float.Input("seconds", default=120.0, min=1.0, max=1000.0, step=0.1),
IO.Int.Input(
@ -90,7 +90,7 @@ class EmptyAceStep15LatentAudio(IO.ComfyNode):
return IO.Schema(
node_id="EmptyAceStep1.5LatentAudio",
display_name="Empty Ace Step 1.5 Latent Audio",
category="model/latent/audio",
category="model/latent/ace",
inputs=[
IO.Float.Input("seconds", default=120.0, min=1.0, max=1000.0, step=0.01),
IO.Int.Input(

2
comfy_extras/nodes_ar_video.py
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@ -19,7 +19,7 @@ class EmptyARVideoLatent(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="EmptyARVideoLatent",
category="model/latent/video",
category="model/latent/autoregressive",
inputs=[
io.Int.Input("width", default=832, min=16, max=8192, step=16),
io.Int.Input("height", default=480, min=16, max=8192, step=16),

8
comfy_extras/nodes_audio.py
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@ -16,7 +16,7 @@ class EmptyLatentAudio(IO.ComfyNode):
return IO.Schema(
node_id="EmptyLatentAudio",
display_name="Empty Latent Audio",
category="model/latent/audio",
category="model/latent",
essentials_category="Audio",
inputs=[
IO.Float.Input("seconds", default=47.6, min=1.0, max=1000.0, step=0.1),
@ -70,7 +70,7 @@ class VAEEncodeAudio(IO.ComfyNode):
node_id="VAEEncodeAudio",
search_aliases=["audio to latent"],
display_name="VAE Encode Audio",
category="model/latent/audio",
category="model/latent",
inputs=[
IO.Audio.Input("audio"),
IO.Vae.Input("vae"),
@ -115,7 +115,7 @@ class VAEDecodeAudio(IO.ComfyNode):
node_id="VAEDecodeAudio",
search_aliases=["latent to audio"],
display_name="VAE Decode Audio",
category="model/latent/audio",
category="model/latent",
inputs=[
IO.Latent.Input("samples"),
IO.Vae.Input("vae"),
@ -137,7 +137,7 @@ class VAEDecodeAudioTiled(IO.ComfyNode):
node_id="VAEDecodeAudioTiled",
search_aliases=["latent to audio"],
display_name="VAE Decode Audio (Tiled)",
category="model/latent/audio",
category="model/latent",
inputs=[
IO.Latent.Input("samples"),
IO.Vae.Input("vae"),

2
comfy_extras/nodes_chroma_radiance.py
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@ -13,7 +13,7 @@ class EmptyChromaRadianceLatentImage(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="EmptyChromaRadianceLatentImage",
category="model/latent/chroma_radiance",
category="model/latent/chroma radiance",
inputs=[
io.Int.Input(id="width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input(id="height", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),

2
comfy_extras/nodes_cosmos.py
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@ -13,7 +13,7 @@ class EmptyCosmosLatentVideo(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="EmptyCosmosLatentVideo",
category="model/latent/video",
category="model/latent/cosmos",
inputs=[
io.Int.Input("width", default=1280, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=704, min=16, max=nodes.MAX_RESOLUTION, step=16),

2
comfy_extras/nodes_flux.py
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@ -40,7 +40,7 @@ class EmptyFlux2LatentImage(io.ComfyNode):
return io.Schema(
node_id="EmptyFlux2LatentImage",
display_name="Empty Flux 2 Latent",
category="model/latent",
category="model/latent/flux",
inputs=[
io.Int.Input("width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),

2
comfy_extras/nodes_hidream_o1.py
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@ -14,7 +14,7 @@ class EmptyHiDreamO1LatentImage(io.ComfyNode):
return io.Schema(
node_id="EmptyHiDreamO1LatentImage",
display_name="Empty HiDream-O1 Latent Image",
category="model/latent/image",
category="model/latent/hidream",
description=(
"Empty pixel-space latent for HiDream-O1-Image. The model was "
"trained at ~4 megapixels; lower resolutions go off-distribution "

5
comfy_extras/nodes_hunyuan.py
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@ -41,7 +41,7 @@ class EmptyHunyuanLatentVideo(io.ComfyNode):
return io.Schema(
node_id="EmptyHunyuanLatentVideo",
display_name="Empty HunyuanVideo 1.0 Latent",
category="model/latent/video",
category="model/latent/hunyuan video",
inputs=[
io.Int.Input("width", default=848, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=480, min=16, max=nodes.MAX_RESOLUTION, step=16),
@ -67,6 +67,7 @@ class EmptyHunyuanVideo15Latent(EmptyHunyuanLatentVideo):
schema = super().define_schema()
schema.node_id = "EmptyHunyuanVideo15Latent"
schema.display_name = "Empty HunyuanVideo 1.5 Latent"
schema.category = "model/latent/hunyuan video"
return schema
@classmethod
@ -359,7 +360,7 @@ class EmptyHunyuanImageLatent(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="EmptyHunyuanImageLatent",
category="model/latent",
category="model/latent/hunyuan image",
inputs=[
io.Int.Input("width", default=2048, min=64, max=nodes.MAX_RESOLUTION, step=32),
io.Int.Input("height", default=2048, min=64, max=nodes.MAX_RESOLUTION, step=32),

4
comfy_extras/nodes_hunyuan3d.py
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@ -12,7 +12,7 @@ class EmptyLatentHunyuan3Dv2(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="EmptyLatentHunyuan3Dv2",
category="model/latent/3d",
category="model/latent/hunyuan 3d",
inputs=[
IO.Int.Input("resolution", default=3072, min=1, max=8192),
IO.Int.Input("batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch."),
@ -97,7 +97,7 @@ class VAEDecodeHunyuan3D(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="VAEDecodeHunyuan3D",
category="model/latent/3d",
category="model/latent/hunyuan 3d",
inputs=[
IO.Latent.Input("samples"),
IO.Vae.Input("vae"),

2
comfy_extras/nodes_latent.py
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@ -262,6 +262,7 @@ class LatentBatch(io.ComfyNode):
return io.Schema(
node_id="LatentBatch",
search_aliases=["combine latents", "merge latents", "join latents"],
display_name="Batch Latents (DEPRECATED)",
category="model/latent/batch",
is_deprecated=True,
inputs=[
@ -447,6 +448,7 @@ class ReplaceVideoLatentFrames(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="ReplaceVideoLatentFrames",
display_name="Replace Video Latent Frames",
category="model/latent/batch",
inputs=[
io.Latent.Input("destination", tooltip="The destination latent where frames will be replaced."),

2
comfy_extras/nodes_lt.py
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@ -62,7 +62,7 @@ class EmptyLTXVLatentVideo(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="EmptyLTXVLatentVideo",
category="model/latent/video/ltxv",
category="model/latent/ltxv",
inputs=[
io.Int.Input("width", default=768, min=64, max=nodes.MAX_RESOLUTION, step=32),
io.Int.Input("height", default=512, min=64, max=nodes.MAX_RESOLUTION, step=32),

1
comfy_extras/nodes_mask.py
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@ -53,6 +53,7 @@ class LatentCompositeMasked(IO.ComfyNode):
return IO.Schema(
node_id="LatentCompositeMasked",
search_aliases=["overlay latent", "layer latent", "paste latent", "inpaint latent"],
display_name="Latent Composite Masked",
category="model/latent",
inputs=[
IO.Latent.Input("destination"),

2
comfy_extras/nodes_mochi.py
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@ -10,7 +10,7 @@ class EmptyMochiLatentVideo(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="EmptyMochiLatentVideo",
category="model/latent/video",
category="model/latent/mochi",
inputs=[
io.Int.Input("width", default=848, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=480, min=16, max=nodes.MAX_RESOLUTION, step=16),

2
comfy_extras/nodes_post_processing.py
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@ -616,7 +616,7 @@ class BatchLatentsNode(io.ComfyNode):
node_id="BatchLatentsNode",
search_aliases=["combine latents", "stack latents", "merge latents"],
display_name="Batch Latents",
category="model/latent",
category="model/latent/batch",
inputs=[
io.Autogrow.Input("latents", template=autogrow_template)
],

2
comfy_extras/nodes_sd3.py
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@ -41,7 +41,7 @@ class EmptySD3LatentImage(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="EmptySD3LatentImage",
category="model/latent/sd3",
category="model/latent/stable diffusion",
inputs=[
io.Int.Input("width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),

4
comfy_extras/nodes_stable_cascade.py
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@ -29,7 +29,7 @@ class StableCascade_EmptyLatentImage(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="StableCascade_EmptyLatentImage",
category="model/latent/stable_cascade",
category="model/latent/stable cascade",
inputs=[
io.Int.Input("width", default=1024, min=256, max=nodes.MAX_RESOLUTION, step=8),
io.Int.Input("height", default=1024, min=256, max=nodes.MAX_RESOLUTION, step=8),
@ -58,7 +58,7 @@ class StableCascade_StageC_VAEEncode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="StableCascade_StageC_VAEEncode",
category="model/latent/stable_cascade",
category="model/latent/stable cascade",
inputs=[
io.Image.Input("image"),
io.Vae.Input("vae"),

4
comfy_extras/nodes_void.py
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@ -288,7 +288,7 @@ class VOIDWarpedNoise(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="VOIDWarpedNoise",
category="model/latent/video",
category="model/latent/void",
inputs=[
OpticalFlow.Input(
"optical_flow",
@ -393,7 +393,7 @@ class VOIDWarpedNoiseSource(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="VOIDWarpedNoiseSource",
category="model/sampling/noise",
category="model/sampling/void",
inputs=[
io.Latent.Input("warped_noise",
tooltip="Warped noise latent from VOIDWarpedNoise"),

5
comfy_extras/nodes_wan.py
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@ -256,7 +256,7 @@ class WanFunInpaintToVideo(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="WanFunInpaintToVideo",
category="model/conditioning/wan/inpaint",
category="model/conditioning/wan/fun inpaint",
inputs=[
io.Conditioning.Input("positive"),
io.Conditioning.Input("negative"),
@ -375,7 +375,8 @@ class TrimVideoLatent(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="TrimVideoLatent",
category="model/latent/video",
display_name="Trim Video Latent",
category="model/latent",
inputs=[
io.Latent.Input("samples"),
io.Int.Input("trim_amount", default=0, min=0, max=99999),

10
nodes.py
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@ -389,7 +389,7 @@ class VAEEncodeForInpaint:
RETURN_TYPES = ("LATENT",)
FUNCTION = "encode"
CATEGORY = "model/latent/inpaint"
CATEGORY = "model/latent"
def encode(self, vae, pixels, mask, grow_mask_by=6):
downscale_ratio = vae.spacial_compression_encode()
@ -1518,13 +1518,11 @@ class LatentCrop:
class SetLatentNoiseMask:
@classmethod
def INPUT_TYPES(s):
return {"required": { "samples": ("LATENT",),
"mask": ("MASK",),
}}
return {"required": { "samples": ("LATENT",), "mask": ("MASK",), }}
RETURN_TYPES = ("LATENT",)
FUNCTION = "set_mask"
CATEGORY = "model/latent/inpaint"
CATEGORY = "model/latent"
def set_mask(self, samples, mask):
s = samples.copy()
@ -2135,7 +2133,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"LatentUpscaleBy": "Upscale Latent By",
"LatentComposite": "Latent Composite",
"LatentBlend": "Latent Blend",
"LatentFromBatch" : "Latent From Batch",
"LatentFromBatch" : "Get Latent From Batch",
"RepeatLatentBatch": "Repeat Latent Batch",
# Image
"EmptyImage": "Empty Image",