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SDXL Settings Pipe (JPS)

Documentation

  • Class name: SDXL Settings Pipe (JPS)
  • Category: JPS Nodes/Pipes
  • Output node: False

The SDXL Settings Pipe node is designed to process and return a comprehensive set of settings for image generation, including resolution, sampling, scheduling, and other configuration parameters. It abstracts the complexity of configuring various aspects of image generation into a simple interface, enabling users to easily specify and retrieve detailed settings for their image generation tasks.

Input types

Required

  • sdxl_settings
    • Serves as the comprehensive input encapsulating all necessary settings for the SDXL image generation process. It is essential for determining the configuration and resultant behavior of the image generation.
    • Comfy dtype: BASIC_PIPE
    • Python dtype: Tuple[int, int, int, int, str, str, int, float, float, int, str, int]

Output types

  • image_res
    • Comfy dtype: INT
    • The resolution of the generated image.
    • Python dtype: int
  • width
    • Comfy dtype: INT
    • The width of the generated image in pixels.
    • Python dtype: int
  • height
    • Comfy dtype: INT
    • The height of the generated image in pixels.
    • Python dtype: int
  • res_factor
    • Comfy dtype: INT
    • A factor influencing the resolution of the generated image.
    • Python dtype: int
  • sampler_name
    • Comfy dtype: COMBO[STRING]
    • The name of the sampling method used for image generation.
    • Python dtype: str
  • scheduler
    • Comfy dtype: COMBO[STRING]
    • The scheduling method used during the image generation process.
    • Python dtype: str
  • steps
    • Comfy dtype: INT
    • The number of steps to be taken in the image generation process.
    • Python dtype: int
  • cfg
    • Comfy dtype: FLOAT
    • A configuration parameter affecting the generation process.
    • Python dtype: float
  • cfg_rescale
    • Comfy dtype: FLOAT
    • A parameter for rescaling the configuration during the generation process.
    • Python dtype: float
  • clip_skip
    • Comfy dtype: INT
    • Indicates the number of clipping steps to skip during the generation process.
    • Python dtype: int
  • filename
    • Comfy dtype: STRING
    • The name of the file where the generated image will be saved.
    • Python dtype: str

Usage tips

  • Infra type: CPU
  • Common nodes: unknown

Source code

class SDXL_Settings_Pipe:

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "sdxl_settings": ("BASIC_PIPE",)
            },
        }
    RETURN_TYPES = ("INT","INT","INT","INT",comfy.samplers.KSampler.SAMPLERS,comfy.samplers.KSampler.SCHEDULERS,"INT","FLOAT","FLOAT","INT","STRING",)
    RETURN_NAMES = ("image_res","width","height","res_factor","sampler_name","scheduler","steps","cfg","cfg_rescale","clip_skip","filename",)
    FUNCTION = "give_values"

    CATEGORY="JPS Nodes/Pipes"

    def give_values(self,sdxl_settings):

        width, height, res_factor, sampler_name, scheduler, steps, cfg, cfg_rescale, clip_skip, filename,image_res = sdxl_settings

        return(int(image_res), int(width), int(height), int (res_factor), sampler_name, scheduler, int(steps), float(cfg), float(cfg_rescale), int(clip_skip), str(filename),)