xiaden
315666c7b6
- Split flat node modules into categorized subpackages (tagging, detect, edge, pose, segment, restore, compare, judge, transform, utility) - Extract shared internals into _shared/ (bases, tensor, formatting) - Centralize node registration via register_nodes() helper - Clean up: remove dead is_scored return, unnecessary hasattr guard, inline imports
44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
"""CCIP character identity similarity — lower distance = more similar."""
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from comfy_api.latest import io
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from .._shared.tensor import comfy_to_pil
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from ._distance import _distance_label
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CCIP_THRESHOLDS: list[tuple[float, str]] = [
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(0.10, "exact"),
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(0.25, "very similar"),
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(0.40, "similar"),
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(0.60, "different"),
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(0.80, "very different"),
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(float("inf"), "opposite"),
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]
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class ImgUtilsCCIP(io.ComfyNode):
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@classmethod
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def define_schema(cls) -> io.Schema:
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return io.Schema(
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node_id="ImgUtilsCCIP", display_name="Imgutils Compare (CCIP)",
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category="imgutils/compare",
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description="Compare anime character identity using CCIP distance. Lower = more similar.",
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search_aliases=["compare", "ccip", "character", "similarity", "distance"],
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inputs=[
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io.Image.Input("image_a", tooltip="First image to compare."),
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io.Image.Input("image_b", tooltip="Second image for comparison."),
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],
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outputs=[
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io.String.Output(display_name="label"),
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io.Float.Output(display_name="distance"),
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],
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)
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@classmethod
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def execute(cls, image_a, image_b) -> io.NodeOutput:
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from imgutils.metrics import ccip_difference
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pil_a = comfy_to_pil(image_a)
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pil_b = comfy_to_pil(image_b)
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distance = ccip_difference(pil_a, pil_b)
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label = _distance_label(distance, CCIP_THRESHOLDS)
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return io.NodeOutput(label, distance)
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