Skip to content

[Inference.Core] Manga Lineart (aka lineart_anime_denoise)

Documentation

  • Class name: Inference_Core_Manga2Anime_LineArt_Preprocessor
  • Category: ControlNet Preprocessors/Line Extractors
  • Output node: False

This node specializes in preprocessing manga images to extract line art, transforming them into a format suitable for anime-style visual enhancements. It leverages a dedicated model to detect and refine manga line art, ensuring the output is optimized for subsequent anime-style rendering processes.

Input types

Required

  • image
    • The input image to be processed for manga line art extraction. This image is transformed to highlight the essential line art, preparing it for anime-style rendering.
    • Comfy dtype: IMAGE
    • Python dtype: torch.Tensor

Optional

  • resolution
    • Specifies the resolution for the output line art image, allowing control over the detail level of the extracted lines.
    • Comfy dtype: INT
    • Python dtype: int

Output types

  • image
    • Comfy dtype: IMAGE
    • The processed image with manga line art extracted, ready for further anime-style rendering.
    • Python dtype: torch.Tensor

Usage tips

  • Infra type: GPU
  • Common nodes: unknown

Source code

class Manga2Anime_LineArt_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.manga_line import LineartMangaDetector

        model = LineartMangaDetector.from_pretrained().to(model_management.get_torch_device())
        out = common_annotator_call(model, image, resolution=resolution)
        del model
        return (out, )