Standard Lineart

Documentation

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

The LineartStandardPreprocessor node is designed for extracting line art from images using a standard approach. It preprocesses images to highlight and refine line details, making it suitable for applications requiring clear line delineation, such as digital art and animation.

Input types

Required

• image
  • The input image to be processed for line art extraction.
  • Comfy dtype: IMAGE
  • Python dtype: Image

Optional

• guassian_sigma
  • Specifies the sigma value for the Gaussian blur applied to the image, affecting the smoothness of the lines extracted.
  • Comfy dtype: FLOAT
  • Python dtype: float
• intensity_threshold
  • Determines the threshold for intensity differentiation, influencing the distinction between line art and the background.
  • Comfy dtype: INT
  • Python dtype: int
• resolution
  • The resolution to which the input image is resized before processing, affecting the detail level of the extracted line art.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • Produces an image with enhanced and refined line art, suitable for further processing or direct use in various applications.
  • Python dtype: Image

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class Lineart_Standard_Preprocessor:
    @classmethod
    def INPUT_TYPES(s):
        return create_node_input_types(
            guassian_sigma=("FLOAT", {"default": 6.0, "min": 0.0, "max": 100.0}),
            intensity_threshold=("INT", {"default": 8, "min": 0, "max": 16})
        )

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

    CATEGORY = "ControlNet Preprocessors/Line Extractors"

    def execute(self, image, guassian_sigma, intensity_threshold, resolution=512, **kwargs):
        from controlnet_aux.lineart_standard import LineartStandardDetector
        return (common_annotator_call(LineartStandardDetector(), image, guassian_sigma=guassian_sigma, intensity_threshold=intensity_threshold, resolution=resolution), )