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Scribble Lines

Documentation

  • Class name: ScribblePreprocessor
  • Category: ControlNet Preprocessors/Line Extractors
  • Output node: False

The ScribblePreprocessor node is designed for preprocessing images to detect scribble lines. It utilizes a specific model to analyze and process the input image, aiming to highlight or extract scribble-like patterns.

Input types

Required

  • image
    • The input image to be processed for scribble line detection. This parameter is crucial as it provides the visual data on which the scribble detection model operates.
    • Comfy dtype: IMAGE
    • Python dtype: torch.Tensor

Optional

  • resolution
    • Specifies the resolution to which the input image is resized before processing. This affects the detail level of the scribble line detection.
    • Comfy dtype: INT
    • Python dtype: int

Output types

  • image
    • Comfy dtype: IMAGE
    • The processed image with scribble lines detected or highlighted. This output is useful for further processing or visualization of scribble patterns.
    • Python dtype: torch.Tensor

Usage tips

Source code

class Scribble_Preprocessor:
    @classmethod
    def INPUT_TYPES(s):
        return create_node_input_types()

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "execute"

    CATEGORY = "ControlNet Preprocessors/Line Extractors"

    def execute(self, image, resolution=512, **kwargs):
        from controlnet_aux.scribble import ScribbleDetector

        model = ScribbleDetector()
        return (common_annotator_call(model, image, resolution=resolution), )