ComfyUI Node: Plasma KSampler

Plasma KSampler:

The JDC_PlasmaSampler node is designed to facilitate the sampling process in AI art generation by leveraging a plasma noise model. This node is particularly useful for artists looking to introduce controlled randomness and noise into their latent images, enhancing the creative possibilities and variability of the generated outputs. By providing a range of configurable parameters, the JDC_PlasmaSampler allows you to fine-tune the sampling process, ensuring that the generated images meet your artistic vision. The node integrates seamlessly with various samplers and schedulers, offering flexibility and precision in the noise application and denoising stages.

Plasma KSampler Input Parameters:

model

This parameter specifies the model to be used for sampling. It is a required input and ensures that the node knows which model to apply the noise and sampling process to.

noise_seed

The noise_seed parameter determines the seed for the noise generation process. It allows for reproducibility of results by using the same seed value. The default value is 0, with a minimum of 0 and a maximum of 0xffffffffffffffff.

steps

The steps parameter defines the number of steps to be taken during the sampling process. More steps generally lead to higher quality results but increase computation time. The default value is 20, with a minimum of 1 and a maximum of 10000.

cfg

The cfg (Classifier-Free Guidance) parameter controls the strength of the guidance applied during sampling. Higher values result in stronger guidance, which can lead to more defined outputs. The default value is 7.0, with a range from 0.0 to 100.0 and a step size of 0.1.

denoise

The denoise parameter specifies the amount of denoising to be applied. A higher value results in smoother images, while a lower value retains more noise. The default value is 0.9, with a range from 0.0 to 1.0 and a step size of 0.01.

latent_noise

The latent_noise parameter controls the amount of noise added to the latent image. This can introduce variability and randomness into the generated images. The default value is 0.05, with a range from 0.0 to 1.0 and a step size of 0.01.

distribution_type

The distribution_type parameter allows you to choose between different noise distribution types. The available options are "default" and "rand". Selecting "rand" introduces random noise distribution.

sampler_name

This parameter specifies the name of the sampler to be used. It integrates with the available samplers in the system, providing flexibility in the sampling process.

scheduler

The scheduler parameter determines the scheduler to be used during the sampling process. It integrates with the available schedulers in the system, allowing for precise control over the sampling schedule.

positive

The positive parameter is used for positive conditioning, guiding the model towards desired features in the generated images.

negative

The negative parameter is used for negative conditioning, guiding the model away from undesired features in the generated images.

latent_image

The latent_image parameter specifies the latent image to which the noise and sampling process will be applied. It is a required input and forms the basis of the generated output.

Plasma KSampler Output Parameters:

LATENT

The output parameter LATENT represents the latent image after the sampling process has been applied. This output contains the modified latent image with the introduced noise and any applied denoising, ready for further processing or final rendering.

Plasma KSampler Usage Tips:

• Experiment with different noise_seed values to achieve unique and reproducible results.
• Adjust the steps parameter to balance between image quality and computation time; more steps generally yield better quality.
• Use the cfg parameter to control the strength of guidance; higher values can lead to more defined and coherent images.
• Fine-tune the denoise and latent_noise parameters to achieve the desired level of smoothness and variability in your images.
• Select the appropriate distribution_type based on the desired noise characteristics; "rand" can introduce more randomness.

Plasma KSampler Common Errors and Solutions:

"Invalid model input"

• Explanation: The model input is either missing or not correctly specified.
• Solution: Ensure that a valid model is provided as input to the node.

"Noise seed out of range"

• Explanation: The noise_seed value is outside the acceptable range.
• Solution: Verify that the noise_seed value is within the range of 0 to 0xffffffffffffffff.

"Steps value out of range"

• Explanation: The steps parameter is set to a value outside the allowed range.
• Solution: Adjust the steps value to be within the range of 1 to 10000.

"CFG value out of range"

• Explanation: The cfg parameter is set to a value outside the allowed range.
• Solution: Ensure that the cfg value is between 0.0 and 100.0.

"Denoise value out of range"

• Explanation: The denoise parameter is set to a value outside the allowed range.
• Solution: Adjust the denoise value to be between 0.0 and 1.0.

"Latent noise value out of range"

• Explanation: The latent_noise parameter is set to a value outside the allowed range.
• Solution: Ensure that the latent_noise value is between 0.0 and 1.0.

"Invalid sampler or scheduler"

• Explanation: The specified sampler or scheduler is not recognized.
• Solution: Verify that the sampler_name and scheduler parameters are set to valid options available in the system.