Image Luminance

Documentation

• Class name: ImageLuminanceDetector
• Category: ControlNet Preprocessors/Recolor
• Output node: False

The ImageLuminanceDetector node is designed to analyze and adjust the luminance of images based on gamma correction. It utilizes the Recolorizer from the controlnet_aux library to modify the image's luminance, aiming to enhance image quality or achieve specific visual effects.

Input types

Required

• image
  • The input image to be processed for luminance adjustment.
  • Comfy dtype: IMAGE
  • Python dtype: numpy.ndarray

Optional

• gamma_correction
  • Specifies the gamma correction factor to adjust the image's luminance. A higher value brightens the image, while a lower value darkens it, affecting the overall visual output.
  • Comfy dtype: FLOAT
  • Python dtype: float
• resolution
  • The resolution to which the image is resized before applying the luminance adjustment, affecting the detail level of the output.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • Outputs the modified image with adjusted luminance levels, enhancing or altering the visual appearance based on the gamma correction applied.
  • Python dtype: numpy.ndarray

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class ImageLuminanceDetector:
    @classmethod
    def INPUT_TYPES(s):
        #https://github.com/Mikubill/sd-webui-controlnet/blob/416c345072c9c2066101e225964e3986abe6945e/scripts/processor.py#L1229
        return create_node_input_types(
            gamma_correction=("FLOAT", {"default": 1.0, "min": 0.1, "max": 2.0, "step": 0.001})
        )

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

    CATEGORY = "ControlNet Preprocessors/Recolor"

    def execute(self, image, gamma_correction, resolution=512, **kwargs):
        from controlnet_aux.recolor import Recolorizer
        return (common_annotator_call(Recolorizer(), image, mode="luminance", gamma_correction=gamma_correction , resolution=resolution), )