ComfyUI Node: Mikey Sampler Base Only

Mikey Sampler Base Only:

The Mikey Sampler Base Only node is designed to provide a streamlined and efficient sampling process for AI-generated art. This node focuses on the core functionalities required for sampling without additional advanced features, making it ideal for users who need a straightforward and reliable sampling method. It leverages a base model and conditioning inputs to generate latent samples, which are then processed through a variational autoencoder (VAE). The node offers various configuration options to control the denoising process, number of steps, and other parameters, ensuring flexibility and customization to meet different artistic needs. By simplifying the sampling process, the Mikey Sampler Base Only node helps you achieve high-quality results with minimal complexity.

Mikey Sampler Base Only Input Parameters:

base_model

This parameter specifies the model to be used for sampling. It is essential as it defines the underlying architecture and capabilities of the sampling process. The model influences the quality and style of the generated output.

positive_cond_base

This parameter provides the positive conditioning input, which guides the sampling process towards desired features or styles. It helps in emphasizing certain aspects of the generated art based on the provided conditioning.

negative_cond_base

This parameter provides the negative conditioning input, which helps in steering the sampling process away from undesired features or styles. It is useful for refining the output by suppressing unwanted elements.

samples

This parameter represents the latent samples that will be processed by the node. These samples are the initial input that undergoes transformation through the sampling process.

vae

This parameter specifies the variational autoencoder (VAE) to be used for decoding the latent samples into the final output. The VAE plays a crucial role in determining the quality and fidelity of the generated images.

add_noise

This parameter controls whether noise should be added during the sampling process. It has two options: "enable" and "disable," with the default being "enable." Adding noise can help in generating more diverse and creative outputs.

denoise

This parameter sets the denoising level for the sampling process. It is a float value with a default of 1.0, a minimum of 0.0, and a maximum of 1.0, adjustable in steps of 0.01. Denoising helps in refining the output by reducing unwanted noise.

steps

This parameter defines the number of steps to be taken during the sampling process. It is an integer value with a default of 31, a minimum of 1, and a maximum of 1000. More steps can lead to higher quality but may increase processing time.

smooth_step

This parameter sets the smooth step value, which can influence the smoothness of transitions in the generated output. It is an integer with a default of 0, a minimum of -1, and a maximum of 100.

cfg_1

This parameter is a float value that sets the first configuration parameter for the sampling process. It has a default of 5.0, a minimum of 0.1, and a maximum of 100.0, adjustable in steps of 0.1. It helps in fine-tuning the sampling behavior.

cfg_2

This parameter is a float value that sets the second configuration parameter for the sampling process. It has a default of 9.5, a minimum of 0.1, and a maximum of 100.0, adjustable in steps of 0.1. It provides additional control over the sampling process.

sampler_name

This parameter specifies the name of the sampler to be used. It offers various options from the comfy.samplers.KSampler.SAMPLERS list, with the default being 'dpmpp_3m_sde_gpu.' The choice of sampler can affect the quality and style of the output.

scheduler

This parameter sets the scheduler for the sampling process. It offers options from the comfy.samplers.KSampler.SCHEDULERS list, with the default being 'exponential.' The scheduler influences the progression of the sampling steps.

upscale_model

This parameter specifies the model to be used for upscaling the generated output. Upscaling can enhance the resolution and details of the final image.

seed

This parameter sets the seed value for the sampling process. It is an integer with a default of 0, a minimum of 0, and a maximum of 0xffffffffffffffff. The seed ensures reproducibility of the generated output.

upscale_by

This parameter defines the scaling factor for upscaling the generated output. It is a float value with a default of 1.0, a minimum of 0.0, and a maximum of 10.0, adjustable in steps of 0.1. Upscaling can improve the resolution of the final image.

hires_denoise

This parameter sets the denoising level for high-resolution outputs. It is a float value with a default of 0.4, a minimum of 0.0, and a maximum of 1.0, adjustable in steps of 0.01. High-resolution denoising helps in maintaining quality at larger scales.

Mikey Sampler Base Only Output Parameters:

samples

This output parameter provides the processed latent samples, which are the result of the sampling process. These samples can be further decoded or used in subsequent nodes to generate the final image.

Mikey Sampler Base Only Usage Tips:

• Experiment with different base models to see how they influence the style and quality of the generated output.
• Use positive and negative conditioning inputs to guide the sampling process towards desired features and away from unwanted elements.
• Adjust the number of steps to balance between quality and processing time. More steps generally lead to better quality but take longer to process.
• Utilize the denoise parameter to refine the output by reducing unwanted noise, especially in high-resolution images.
• Try different samplers and schedulers to find the combination that works best for your specific artistic needs.

Mikey Sampler Base Only Common Errors and Solutions:

"Invalid model specified"

• Explanation: The base model provided is not recognized or supported.
• Solution: Ensure that the model name is correct and that it is available in the system.

"Conditioning input missing"

• Explanation: One or both of the conditioning inputs (positive or negative) are not provided.
• Solution: Provide the necessary conditioning inputs to guide the sampling process.

"Latent samples not provided"

• Explanation: The latent samples input is missing.
• Solution: Ensure that the latent samples are correctly passed to the node.

"VAE model not specified"

• Explanation: The VAE model required for decoding the latent samples is not specified.
• Solution: Provide a valid VAE model to decode the latent samples into the final output.

"Invalid denoise value"

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

"Steps value out of range"

• Explanation: The number of steps is set to a value outside the allowed range.
• Solution: Set the steps parameter to a value between 1 and 1000.

"Invalid seed value"

• Explanation: The seed value is not within the valid range.
• Solution: Ensure the seed value is between 0 and 0xffffffffffffffff.