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from ..utils import common_annotator_call, create_node_input_types
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import comfy.model_management as model_management
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import numpy as np
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class MLSD_Preprocessor:
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@classmethod
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def INPUT_TYPES(s):
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return create_node_input_types(
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score_threshold = ("FLOAT", {"default": 0.1, "min": 0.01, "max": 2.0, "step": 0.01}),
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dist_threshold = ("FLOAT", {"default": 0.1, "min": 0.01, "max": 20.0, "step": 0.01})
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)
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "execute"
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CATEGORY = "ControlNet Preprocessors/Line Extractors"
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def execute(self, image, score_threshold, dist_threshold, resolution=512, **kwargs):
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from controlnet_aux.mlsd import MLSDdetector
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model = MLSDdetector.from_pretrained().to(model_management.get_torch_device())
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out = common_annotator_call(model, image, resolution=resolution, thr_v=score_threshold, thr_d=dist_threshold)
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return (out, )
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NODE_CLASS_MAPPINGS = {
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"M-LSDPreprocessor": MLSD_Preprocessor
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"M-LSDPreprocessor": "M-LSD Lines"
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} |