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from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT |
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import comfy.model_management as model_management |
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class DSINE_Normal_Map_Preprocessor: |
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@classmethod |
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def INPUT_TYPES(s): |
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return define_preprocessor_inputs( |
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fov=INPUT.FLOAT(max=365.0, default=60.0), |
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iterations=INPUT.INT(min=1, max=20, default=5), |
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resolution=INPUT.RESOLUTION() |
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) |
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RETURN_TYPES = ("IMAGE",) |
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FUNCTION = "execute" |
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CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators" |
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def execute(self, image, fov=60.0, iterations=5, resolution=512, **kwargs): |
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from custom_controlnet_aux.dsine import DsineDetector |
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model = DsineDetector.from_pretrained().to(model_management.get_torch_device()) |
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out = common_annotator_call(model, image, fov=fov, iterations=iterations, resolution=resolution) |
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del model |
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return (out,) |
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NODE_CLASS_MAPPINGS = { |
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"DSINE-NormalMapPreprocessor": DSINE_Normal_Map_Preprocessor |
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} |
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NODE_DISPLAY_NAME_MAPPINGS = { |
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"DSINE-NormalMapPreprocessor": "DSINE Normal Map" |
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} |