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[Inference.Core] Tile

Documentation

  • Class name: Inference_Core_TilePreprocessor
  • Category: ControlNet Preprocessors/others
  • Output node: False

The Tile Preprocessor node is designed to enhance image inputs for further processing by applying a tiling mechanism. This involves detecting and adjusting image tiles to improve the quality and consistency of the input images for subsequent stages in a pipeline, particularly in control networks.

Input types

Required

  • image
    • The input image to be processed and enhanced through the tiling mechanism. It serves as the primary data upon which the tile detection and adjustment operations are performed.
    • Comfy dtype: IMAGE
    • Python dtype: torch.Tensor

Optional

  • pyrUp_iters
    • Specifies the number of iterations for the pyramid upscaling process, affecting the granularity of the tile adjustment. This parameter plays a crucial role in determining the level of detail and the scale of adjustments applied to the input image.
    • Comfy dtype: INT
    • Python dtype: int
  • resolution
    • The target resolution for the output image, influencing the final size and detail level after processing. It determines how the image is resized as part of the preprocessing steps.
    • Comfy dtype: INT
    • Python dtype: int

Output types

  • image
    • Comfy dtype: IMAGE
    • Produces an enhanced version of the input image, where tiling adjustments have been applied to improve its suitability for further processing steps.
    • Python dtype: torch.Tensor

Usage tips

  • Infra type: CPU
  • Common nodes: unknown

Source code

class Tile_Preprocessor:
    @classmethod
    def INPUT_TYPES(s):
        return create_node_input_types(
            pyrUp_iters = ("INT", {"default": 3, "min": 1, "max": 10, "step": 1})
        )


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

    CATEGORY = "ControlNet Preprocessors/others"

    def execute(self, image, pyrUp_iters, resolution=512, **kwargs):
        from controlnet_aux.tile import TileDetector

        return (common_annotator_call(TileDetector(), image, pyrUp_iters=pyrUp_iters, resolution=resolution),)