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
35 lines
1.7 KiB
Python
35 lines
1.7 KiB
Python
"""NSFW content auto-censoring — pixelate, blur, or color-fill detected regions."""
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from comfy_api.latest import io
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from .._shared.bases import _ImageToImage
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class ImgUtilsCensor(_ImageToImage):
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"""Detect and censor NSFW regions using pixelation, blur, or solid color fills."""
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METHODS = ["Pixelate", "Blur", "Color"]
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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="ImgUtilsCensor", display_name="Imgutils Censor",
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category="imgutils/transform",
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description="Auto-detect and censor NSFW content. Applies pixelation, blur, or solid color.",
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search_aliases=["censor", "nsfw", "pixelate", "blur", "mosaic"],
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inputs=[
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io.Image.Input("image", tooltip="Input image to censor NSFW content."),
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io.Combo.Input("mode", options=cls.METHODS, default="Pixelate", tooltip="Censoring method."),
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io.Boolean.Input("nipple_f", default=True, tooltip="Censor female nipples."),
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io.Boolean.Input("penis", default=True, tooltip="Censor penises."),
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io.Boolean.Input("pussy", default=True, tooltip="Censor vaginas."),
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io.Float.Input("confidence", default=0.3, min=0.0, max=1.0, step=0.05, tooltip="Detection confidence threshold."),
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],
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outputs=[io.Image.Output(display_name="image")],
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)
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@classmethod
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def execute(cls, image, mode, nipple_f, penis, pussy, confidence) -> io.NodeOutput:
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from imgutils.operate import censor_nsfw
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return cls._run(image, censor_nsfw, method=mode.lower(), nipple_f=nipple_f,
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penis=penis, pussy=pussy, conf_threshold=confidence)
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