ComfyUI > Nodes > ComfyUI > BasicScheduler

ComfyUI Node: BasicScheduler

Class Name

BasicScheduler

Category
sampling/custom_sampling/schedulers
Author
ComfyAnonymous (Account age: 598days)
Extension
ComfyUI
Latest Updated
2024-08-12
Github Stars
45.85K

How to Install ComfyUI

Install this extension via the ComfyUI Manager by searching for ComfyUI
  • 1. Click the Manager button in the main menu
  • 2. Select Custom Nodes Manager button
  • 3. Enter ComfyUI in the search bar
After installation, click the Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.

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BasicScheduler Description

Generate sigma values for denoising in AI art, control steps and intensity, customize image quality and style.

BasicScheduler:

The BasicScheduler node is designed to generate a sequence of sigma values, which are essential for the denoising process in AI art generation. This node allows you to control the number of steps and the denoising intensity, providing flexibility in the sampling process. By adjusting these parameters, you can influence the quality and style of the generated images. The BasicScheduler is particularly useful for fine-tuning the denoising process to achieve the desired artistic effect, making it a valuable tool for AI artists looking to customize their workflows.

BasicScheduler Input Parameters:

model

This parameter specifies the model to be used for generating sigma values. It is essential for the node to understand the characteristics of the model to produce accurate sigma values. The model should be compatible with the sampling process.

scheduler

This parameter determines the type of scheduler to be used. The scheduler influences how the sigma values are calculated and can affect the overall denoising process. Different schedulers may produce different artistic effects.

steps

This integer parameter defines the number of steps in the denoising process. The default value is 20, with a minimum of 1 and a maximum of 10000. Increasing the number of steps can lead to more refined and detailed images, while fewer steps may result in quicker but less detailed outputs.

denoise

This float parameter controls the intensity of the denoising process, with a default value of 1.0. The range is from 0.0 to 1.0, with a step of 0.01. A value of 1.0 means full denoising, while lower values reduce the denoising effect. Adjusting this parameter allows for fine-tuning the balance between noise and detail in the generated images.

BasicScheduler Output Parameters:

SIGMAS

The output of the BasicScheduler node is a sequence of sigma values, represented as a tensor. These sigma values are used in the denoising process to progressively refine the generated image. The sequence of sigma values is crucial for controlling the noise reduction and achieving the desired artistic effect.

BasicScheduler Usage Tips:

  • Experiment with different numbers of steps to find the optimal balance between image quality and processing time.
  • Adjust the denoise parameter to control the level of detail in the generated images. Lower values can preserve more noise, resulting in a more textured look.
  • Use different schedulers to explore various artistic styles and effects.

BasicScheduler Common Errors and Solutions:

ValueError: Denoise value must be greater than 0

  • Explanation: This error occurs when the denoise parameter is set to 0 or a negative value.
  • Solution: Ensure that the denoise parameter is set to a value greater than 0.

TypeError: Model object is not compatible

  • Explanation: This error indicates that the provided model is not compatible with the BasicScheduler node.
  • Solution: Verify that the model is correctly specified and compatible with the sampling process.

IndexError: Steps value out of range

  • Explanation: This error occurs when the steps parameter is set to a value outside the allowed range.
  • Solution: Ensure that the steps parameter is within the range of 1 to 10000.

BasicScheduler Related Nodes

Go back to the extension to check out more related nodes.
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