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Update Bernini conditioning node

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This commit is contained in:
Alexis Rolland 2026-06-14 09:07:53 +08:00
parent 64cc078069
commit 4fff61ab37
1 changed files with 8 additions and 15 deletions
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23
comfy_extras/nodes_bernini.py
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@ -39,9 +39,9 @@ class BerniniConditioning(io.ComfyNode):
return io.Schema(
node_id="BerniniConditioning",
display_name="Bernini Conditioning",
category="conditioning/video_models",
category="models/conditioning/bernini",
description="Conditioning node for Bernini in-context video/image conditioning. It can be used for the following tasks: t2v (text-to-video), v2v (video-to-video), rv2v (reference-guided video editing), r2v (reference-to-video), ads2v (insert image/video into video)."
"Reference images injected as in-context tokens (r2v, rv2v) are encoded independently at their own native aspect ratio (long edge capped at ref_max_size)",
"Reference images injected as in-context tokens (r2v, rv2v) are encoded independently at their own native aspect ratio (long edge capped at ref_max_size)",
inputs=[
io.Conditioning.Input("positive"),
io.Conditioning.Input("negative"),
@ -50,14 +50,11 @@ class BerniniConditioning(io.ComfyNode):
io.Int.Input("height", default=480, min=16, max=8192, step=16),
io.Int.Input("length", default=81, min=1, max=8192, step=4),
io.Int.Input("batch_size", default=1, min=1, max=4096),
io.Image.Input("source_video", optional=True, tooltip=(
"Source video to edit or restyle (v2v, rv2v). Resized to width/height and trimmed to length.")),
io.Image.Input("reference_video", optional=True, tooltip=(
"Video to insert into the source video (ads2v).")),
io.Image.Input("source_video", optional=True, tooltip=("Source video to edit or restyle (v2v, rv2v). Resized to width/height and trimmed to length.")),
io.Image.Input("reference_video", optional=True, tooltip=("Video to insert into the source video (ads2v).")),
io.Autogrow.Input("reference_images", optional=True,
template=io.Autogrow.TemplatePrefix(
input=io.Image.Input("reference_image", tooltip=(
"Reference image injected as an in-context token (r2v, rv2v).")),
input=io.Image.Input("reference_image", tooltip=("Reference image injected as an in-context token (r2v, rv2v).")),
prefix="reference_image_", min=0, max=8)),
io.Int.Input("ref_max_size", default=848, min=16, max=8192, step=16, optional=True, tooltip=(
"Max size for the long edge of reference_video and reference_images. Resized with preserved aspect ratio and snapped to 16px.")),
@ -70,10 +67,8 @@ class BerniniConditioning(io.ComfyNode):
)
@classmethod
def execute(cls, positive, negative, vae, width, height, length, batch_size,
source_video=None, reference_video=None, reference_images=None, ref_max_size=848) -> io.NodeOutput:
latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8],
device=comfy.model_management.intermediate_device())
def execute(cls, positive, negative, vae, width, height, length, batch_size, source_video=None, reference_video=None, reference_images=None, ref_max_size=848) -> io.NodeOutput:
latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
# source_video (1), reference_video (2), reference_images (3, 4, ...).
context = []
@ -106,9 +101,7 @@ class BerniniConditioning(io.ComfyNode):
class BerniniExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
BerniniConditioning,
]
return [BerniniConditioning,]
async def comfy_entrypoint() -> BerniniExtension: