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
79 lines
2.9 KiB
Python
79 lines
2.9 KiB
Python
"""Human pose keypoint detection and visualization using DWPose."""
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from comfy_api.latest import io, ui
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from .._shared.tensor import comfy_to_pil, pil_to_comfy
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from .._shared.formatting import keypoints_to_json
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class ImgUtilsPose(io.ComfyNode):
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"""Detect OpenPose keypoints via DWPose and render skeleton visualization."""
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VISUALIZATION_PRESETS = [
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"Body Only",
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"Body with Face",
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"Body with Hands",
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"Full",
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]
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PRESET_FLAGS = {
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"Body Only": {"draw_body": True, "draw_hands": False, "draw_feet": False, "draw_face": False},
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"Body with Face": {"draw_body": True, "draw_hands": False, "draw_feet": False, "draw_face": True},
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"Body with Hands": {"draw_body": True, "draw_hands": True, "draw_feet": False, "draw_face": False},
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"Full": {"draw_body": True, "draw_hands": True, "draw_feet": True, "draw_face": True},
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}
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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="ImgUtilsPose",
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display_name="Imgutils Pose",
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category="imgutils/pose",
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description=(
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"Detect OpenPose 18-point human keypoints in anime images "
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"using DWPose. Outputs a visualization image and keypoints JSON."
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),
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search_aliases=[
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"pose", "keypoints", "dwpose", "skeleton", "openpose",
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"body", "face", "hands", "feet",
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],
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inputs=[
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io.Image.Input("image", tooltip="Input image for pose detection."),
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io.Combo.Input(
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"mode",
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options=cls.VISUALIZATION_PRESETS,
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default="Full",
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tooltip="Visualization detail: body only, body+face, body+hands, or full skeleton.",
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),
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io.Boolean.Input(
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"auto_detect", default=True,
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tooltip="Auto-detect person bounding boxes. Disable to use full image.",
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),
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],
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outputs=[
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io.Image.Output(display_name="skeleton"),
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io.String.Output(display_name="json"),
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],
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)
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@classmethod
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def execute(cls, image, mode, auto_detect=True) -> io.NodeOutput:
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from imgutils.pose import dwpose_estimate, op18_visualize
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pil_image = comfy_to_pil(image)
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keypoints_list = dwpose_estimate(pil_image, auto_detect=auto_detect)
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json_str = keypoints_to_json(keypoints_list)
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flags = cls.PRESET_FLAGS.get(mode, cls.PRESET_FLAGS["Full"])
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vis_image = op18_visualize(
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pil_image,
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keypoints_list,
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draw_body=flags["draw_body"],
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draw_hands=flags["draw_hands"],
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draw_feet=flags["draw_feet"],
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draw_face=flags["draw_face"],
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)
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vis_tensor = pil_to_comfy(vis_image)
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return io.NodeOutput(vis_tensor, json_str, ui=ui.PreviewImage(vis_tensor, cls=cls))
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