EasyUse¶

Documentation¶

Class name: easy XYInputs: Denoise
Category: EasyUse/XY Inputs
Output node: False

This node is designed to facilitate the exploration and visualization of denoising effects in generative models. It allows users to adjust denoising parameters over a batch of data, providing a graphical representation of the impact of different denoising levels on the generated outputs.

Input types¶

Required¶

batch_count
- Specifies the number of batches to process, allowing for the examination of denoising effects across multiple sets of data.
- Comfy dtype: INT
- Python dtype: int
first_denoise
- Sets the initial denoising level, marking the starting point for the exploration of denoising effects.
- Comfy dtype: FLOAT
- Python dtype: float
last_denoise
- Defines the final denoising level, enabling users to observe how increasing or decreasing denoising intensity affects the output.
- Comfy dtype: FLOAT
- Python dtype: float

Output types¶

X or Y
- Comfy dtype: X_Y
- Provides a graphical representation of the denoising process, illustrating the effects of different denoising levels on the data.
- Python dtype: Dict[str, Any]

Usage tips¶

Infra type: CPU
Common nodes: unknown

Source code¶

class XYplot_Denoise:

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "batch_count": ("INT", {"default": 3, "min": 0, "max": 50}),
                "first_denoise": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.1}),
                "last_denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.1}),
            }
        }

    RETURN_TYPES = ("X_Y",)
    RETURN_NAMES = ("X or Y",)
    FUNCTION = "xy_value"
    CATEGORY = "EasyUse/XY Inputs"

    def xy_value(self, batch_count, first_denoise, last_denoise):
        axis = "advanced: Denoise"
        values = generate_floats(batch_count, first_denoise, last_denoise)
        return ({"axis": axis, "values": values},) if values else (None,)