jaidaken
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Includes 30 custom nodes committed directly, 7 Civitai-exclusive loras stored via Git LFS, and a setup script that installs all dependencies and downloads HuggingFace-hosted models on vast.ai. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
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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} |