TTPlanet Tile Simple

Documentation

• Class name: TTPlanet_TileSimple_Preprocessor
• Category: ControlNet Preprocessors/tile
• Output node: False

This node is designed for preprocessing images by applying a simple tiling effect, which involves scaling and blurring to enhance or modify the image's appearance for further processing or analysis.

Input types

Required

• image
  • The input image to be processed. It serves as the primary data for the tiling effect application.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• scale_factor
  • Determines the scaling factor for the image, affecting the size of the tiles in the processed image.
  • Comfy dtype: FLOAT
  • Python dtype: float
• blur_strength
  • Adjusts the strength of the blur applied to the image, influencing the smoothness of the tile edges.
  • Comfy dtype: FLOAT
  • Python dtype: float

Output types

• image
  • Comfy dtype: IMAGE
  • The processed image with the applied tiling effect, ready for further processing or analysis.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class TTPlanet_TileSimple_Preprocessor:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": ("IMAGE",),
                "scale_factor": ("FLOAT", {"default": 1.00, "min": 1.00, "max": 8.00, "step": 0.05}),
                "blur_strength": ("FLOAT", {"default": 2.0, "min": 1.0, "max": 10.0, "step": 0.1}),
            }
        }

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

    CATEGORY = "ControlNet Preprocessors/tile"

    def execute(self, image, scale_factor, blur_strength):
        from controlnet_aux.tile import TTPLanet_Tile_Detector_Simple

        return (common_annotator_call(TTPLanet_Tile_Detector_Simple(), image, scale_factor=scale_factor, blur_strength=blur_strength),)