nodes/meareabc-ComfyUI-MiniMaxH3-SpatialGuide
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Fix guide preview dimensions and show the first frame

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meareabc
2026-10-28 09:59:54 +08:00
parent 519d7bda8d
commit 2d2a51c02c
6 changed files with 219 additions and 48 deletions
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__init__.py
+17 -4
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@@ -8,7 +8,7 @@ import comfy.conds
import comfy.patcher_extension
import nodes
from comfy.ldm.minimax.model import FRAME_PER_TOKEN
from comfy_api.latest import ComfyExtension, io
from comfy_api.latest import ComfyExtension, io, ui
GUIDE_POSITION = "minimax_h3_spatial_guide"
@@ -132,7 +132,8 @@ class MiniMaxH3GuidePosition(io.ComfyNode):
node_id="MiniMaxH3GuidePosition",
display_name="MiniMax H3 Guide Position",
category="model/conditioning/minimax",
description="Drag the guide rectangle inside the target canvas. Outputs the guide's top-left x/y in target pixels.",
description="Preview the guide's first frame and drag it within the target canvas. Run this node to refresh input dimensions without sampling.",
is_output_node=True,
inputs=[
io.Int.Input("guide_width", default=640, min=1, max=nodes.MAX_RESOLUTION),
io.Int.Input("guide_height", default=480, min=1, max=nodes.MAX_RESOLUTION),
@@ -140,13 +141,25 @@ class MiniMaxH3GuidePosition(io.ComfyNode):
io.Int.Input("canvas_height", default=480, min=1, max=nodes.MAX_RESOLUTION),
io.Int.Input("x", default=0, min=-nodes.MAX_RESOLUTION, max=nodes.MAX_RESOLUTION, socketless=True),
io.Int.Input("y", default=0, min=-nodes.MAX_RESOLUTION, max=nodes.MAX_RESOLUTION, socketless=True),
io.Image.Input("image", optional=True, tooltip="Connect the same image/video batch as Spatial Guide. The first frame determines the guide preview and its actual size."),
io.Latent.Input("latent", optional=True, tooltip="Target H3 AV latent. Uses its actual canvas dimensions, including the latent's size alignment."),
],
outputs=[io.Int.Output(display_name="x"), io.Int.Output(display_name="y")],
)
@classmethod
def execute(cls, guide_width, guide_height, canvas_width, canvas_height, x, y) -> io.NodeOutput:
return io.NodeOutput(x, y, ui={"guide_size": [guide_width, guide_height], "canvas_size": [canvas_width, canvas_height]})
def execute(cls, guide_width, guide_height, canvas_width, canvas_height, x, y, image=None, latent=None) -> io.NodeOutput:
preview = {}
if image is not None:
guide_height, guide_width = image.shape[1:3]
preview["guide_preview"] = ui.PreviewImage(image[:1, ..., :3]).as_dict()["images"]
if latent is not None:
samples = latent["samples"]
if not samples.is_nested or len(samples.tensors) != 2 or samples.tensors[0].ndim != 5 or samples.tensors[0].shape[1] != 24:
raise ValueError("MiniMaxH3GuidePosition expects a MiniMax H3 AV latent")
canvas_height, canvas_width = [size * 16 for size in samples.tensors[0].shape[-2:]]
preview.update({"guide_size": [guide_width, guide_height], "canvas_size": [canvas_width, canvas_height]})
return io.NodeOutput(x, y, ui=preview)
class MiniMaxH3SpatialGuideExtension(ComfyExtension):