KSampler Efficient Fooocus¶

Documentation¶

Class name: Fooocus_KSamplerEfficient
Category: Art Venture/Sampling
Output node: True

The Fooocus_KSamplerEfficient node enhances the sampling process in art generation by incorporating a sharpness parameter, allowing for more precise control over the texture and detail level of generated images. This node builds upon the foundational sampling capabilities to offer an advanced, efficiency-focused approach to art creation.

Input types¶

Required¶

model
- Specifies the model used for the sampling process, integral to determining the art generation's foundational style and characteristics.
- Comfy dtype: MODEL
- Python dtype: str
seed
- The seed parameter ensures reproducibility in the art generation process by initializing the random number generator to a specific state.
- Comfy dtype: INT
- Python dtype: int
steps
- Defines the number of steps in the sampling process, affecting the detail and quality of the generated art.
- Comfy dtype: INT
- Python dtype: int
cfg
- Configures the conditioning factor for the sampling process, influencing the generation's creativity and coherence.
- Comfy dtype: FLOAT
- Python dtype: float
sampler_name
- Identifies the specific sampler algorithm to be used, affecting the texture and detail of the generated art.
- Comfy dtype: COMBO[STRING]
- Python dtype: str
scheduler
- Specifies the scheduler for controlling the sampling process, impacting the progression and quality of art generation.
- Comfy dtype: COMBO[STRING]
- Python dtype: str
positive
- Defines positive conditioning to guide the art generation towards desired attributes.
- Comfy dtype: CONDITIONING
- Python dtype: str
negative
- Sets negative conditioning to avoid certain attributes in the generated art.
- Comfy dtype: CONDITIONING
- Python dtype: str
latent_image
- Provides the initial latent image to be transformed by the sampling process.
- Comfy dtype: LATENT
- Python dtype: object
denoise
- Adjusts the level of denoising applied to the generated art, affecting clarity and detail.
- Comfy dtype: FLOAT
- Python dtype: float
preview_method
- unknown
- Comfy dtype: COMBO[STRING]
- Python dtype: unknown
vae_decode
- unknown
- Comfy dtype: COMBO[STRING]
- Python dtype: unknown

Optional¶

optional_vae
- unknown
- Comfy dtype: VAE
- Python dtype: unknown
script
- unknown
- Comfy dtype: SCRIPT
- Python dtype: unknown
sharpness
- The sharpness parameter allows users to adjust the level of detail and texture in the generated art, providing a means to fine-tune the visual output for more precise artistic control.
- Comfy dtype: FLOAT
- Python dtype: float

Output types¶

MODEL
- Comfy dtype: MODEL
- unknown
- Python dtype: unknown
CONDITIONING+
- Comfy dtype: CONDITIONING
- unknown
- Python dtype: unknown
CONDITIONING-
- Comfy dtype: CONDITIONING
- unknown
- Python dtype: unknown
LATENT
- Comfy dtype: LATENT
- The output latent image represents the final generated art, encapsulating the visual characteristics specified through the input parameters.
- Python dtype: object
VAE
- Comfy dtype: VAE
- unknown
- Python dtype: unknown
IMAGE
- Comfy dtype: IMAGE
- unknown
- Python dtype: unknown

Usage tips¶

Infra type: CPU
Common nodes: unknown

Source code¶

    class KSamplerEfficientWithSharpness(TSC_KSampler):
        @classmethod
        def INPUT_TYPES(cls):
            inputs = TSC_KSampler.INPUT_TYPES()
            inputs["optional"]["sharpness"] = (
                "FLOAT",
                {"default": 2.0, "min": 0.0, "max": 100.0, "step": 0.01},
            )

            return inputs

        CATEGORY = "Art Venture/Sampling"

        def sample(self, *args, sharpness=2.0, **kwargs):
            patch.sharpness = sharpness
            patch.patch_all()
            results = super().sample(*args, **kwargs)
            patch.unpatch_all()
            return results