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Rename input label
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@ -525,7 +525,7 @@ class SeedVR2TemporalMerge(io.ComfyNode):
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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.",
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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.",
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search_aliases=["seedvr2", "merge", "temporal", "hann", "crossfade"],
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search_aliases=["seedvr2", "merge", "temporal", "hann", "crossfade"],
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inputs=[
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inputs=[
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io.Latent.Input("latent_chunks", tooltip="The sampled temporal chunks in sequence order."),
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io.Latent.Input("latents", tooltip="The sampled temporal chunks in sequence order."),
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io.Int.Input("temporal_overlap", default=0, min=0, max=16384, force_input=True,
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io.Int.Input("temporal_overlap", default=0, min=0, max=16384, force_input=True,
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tooltip="The temporal_overlap output of Split SeedVR2 Latent. 0 = plain concatenation."),
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tooltip="The temporal_overlap output of Split SeedVR2 Latent. 0 = plain concatenation."),
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],
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],
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@ -535,13 +535,13 @@ class SeedVR2TemporalMerge(io.ComfyNode):
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)
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)
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@classmethod
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@classmethod
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def execute(cls, latent_chunks, temporal_overlap) -> io.NodeOutput:
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def execute(cls, latents, temporal_overlap) -> io.NodeOutput:
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temporal_overlap = temporal_overlap[0]
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temporal_overlap = temporal_overlap[0]
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if temporal_overlap < 0:
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if temporal_overlap < 0:
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raise ValueError(
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raise ValueError(
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f"SeedVR2TemporalMerge: temporal_overlap must be >= 0; got {temporal_overlap}."
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f"SeedVR2TemporalMerge: temporal_overlap must be >= 0; got {temporal_overlap}."
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)
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)
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chunks = [entry["samples"] for entry in latent_chunks]
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chunks = [entry["samples"] for entry in latents]
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first = chunks[0]
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first = chunks[0]
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if first.ndim != 5:
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if first.ndim != 5:
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raise ValueError(
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raise ValueError(
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@ -560,7 +560,7 @@ class SeedVR2TemporalMerge(io.ComfyNode):
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f"chunk 0 has {first.shape[2]}; only the final chunk may be shorter."
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f"chunk 0 has {first.shape[2]}; only the final chunk may be shorter."
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)
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)
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out = latent_chunks[0].copy()
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out = latents[0].copy()
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out.pop("noise_mask", None)
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out.pop("noise_mask", None)
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if len(chunks) == 1:
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if len(chunks) == 1:
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