Upscale Model Switch

Documentation

• Class name: Upscale Model Switch
• Category: WAS Suite/Logic
• Output node: False

This node facilitates the dynamic selection between two upscale models based on a boolean condition, enabling the choice of an appropriate model for image upscaling within a workflow. It exemplifies conditional logic in model selection, optimizing the upscaling process for varying requirements.

Input types

Required

• upscale_model_a
  • Specifies the first upscale model option for enhancing image resolution, playing a pivotal role in the conditional selection process.
  • Comfy dtype: UPSCALE_MODEL
  • Python dtype: torch.nn.Module
• upscale_model_b
  • Defines the second upscale model option, offering an alternative for conditional selection based on the boolean input, thus affecting the upscaling outcome.
  • Comfy dtype: UPSCALE_MODEL
  • Python dtype: torch.nn.Module
• boolean
  • A boolean condition that determines which upscale model (A or B) is selected for the upscaling process, directly influencing the node's execution path and the quality of the output image.
  • Comfy dtype: BOOLEAN
  • Python dtype: bool

Output types

• upscale_model
  • Comfy dtype: UPSCALE_MODEL
  • The selected upscale model based on the boolean condition, ready for use in the image upscaling process.
  • Python dtype: torch.nn.Module
• ui
  • A user interface component that may reflect the result of the upscale model switch, showcasing the enhanced images or relevant information.

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class WAS_Upscale_Model_Input_Switch:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "upscale_model_a": ("UPSCALE_MODEL",),
                "upscale_model_b": ("UPSCALE_MODEL",),
                "boolean": ("BOOLEAN", {"forceInput": True}),
            }
        }

    RETURN_TYPES = ("UPSCALE_MODEL",)
    FUNCTION = "upscale_model_switch"

    CATEGORY = "WAS Suite/Logic"

    def upscale_model_switch(self, upscale_model_a, upscale_model_b, boolean=True):

        if boolean:
            return (upscale_model_a, )
        else:
            return (upscale_model_b, )