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Facilitates custom sampling for AI art generation by generating sigma values for noise scheduling in diffusion models.
The GITSScheduler
node is designed to facilitate custom sampling in AI art generation by providing a flexible and efficient way to generate sigma values, which are crucial for noise scheduling in diffusion models. This node allows you to control the noise levels and the number of steps in the sampling process, ensuring that you can fine-tune the denoising process to achieve the desired artistic effect. By adjusting parameters such as the coefficient, steps, and denoise level, you can influence the smoothness and quality of the generated images, making this node an essential tool for AI artists looking to optimize their workflows and achieve high-quality results.
The coeff
parameter is a floating-point value that influences the noise levels used during the sampling process. It allows you to adjust the intensity of the noise, which can affect the texture and details of the generated images. The default value is 1.20, with a minimum of 0.80 and a maximum of 1.50, and it can be adjusted in steps of 0.05.
The steps
parameter is an integer that determines the number of steps in the sampling process. More steps generally lead to higher quality images but require more computational resources. The default value is 10, with a minimum of 2 and a maximum of 1000.
The denoise
parameter is a floating-point value that controls the level of denoising applied during the sampling process. A value of 1.0 means full denoising, while lower values reduce the denoising effect, potentially preserving more details but also more noise. The default value is 1.0, with a minimum of 0.0 and a maximum of 1.0, adjustable in steps of 0.01.
The SIGMAS
output parameter is a tensor of sigma values that represent the noise levels at each step of the sampling process. These values are crucial for the denoising process in diffusion models, as they determine the amount of noise to be added or removed at each step. The output sigmas help in achieving the desired balance between noise and detail in the generated images.
coeff
parameter to fine-tune the noise intensity for different artistic effects. Higher values can add more texture, while lower values can smooth out the image.steps
parameter to find the optimal balance between image quality and computational efficiency. More steps generally improve quality but require more processing time.denoise
parameter to control the level of detail preservation. Lower values can retain more details but may also keep more noise, while higher values provide cleaner images.denoise
parameter was set to 0 or a negative value, which is not allowed.denoise
parameter is set to a value greater than 0.steps
parameter was set to a value outside the allowed range (2 to 1000).steps
parameter to be within the valid range of 2 to 1000.coeff
parameter was set to a value outside the allowed range (0.80 to 1.50).coeff
parameter to be within the valid range of 0.80 to 1.50.© Copyright 2024 RunComfy. All Rights Reserved.