ComfyUI Node: Latent Tile Sampler (Mikey)

Latent Tile Sampler (Mikey):

The MikeyLatentTileSampler node is designed to handle and resample latent images that are larger than a specified tile size. This node is particularly useful for AI artists working with high-resolution images, as it allows for efficient processing by breaking down the image into smaller, more manageable tiles. Each tile is resampled individually and then stitched back together to form the final upscaled latent tensor. This method ensures that the quality and details of the image are preserved while optimizing the computational resources required for processing.

Latent Tile Sampler (Mikey) Input Parameters:

model

This parameter specifies the model to be used for resampling the latent tiles. The model is responsible for generating the new samples based on the input latent image. The choice of model can significantly impact the quality and style of the final image.

add_noise

This boolean parameter determines whether noise should be added during the resampling process. Adding noise can help in generating more diverse and creative outputs. The default value is typically False.

noise_seed

This parameter sets the seed for the noise generation. Using a fixed seed ensures that the noise added is consistent across different runs, which can be useful for reproducibility. The value can be any integer.

cfg

The cfg parameter stands for "classifier-free guidance" and controls the strength of the guidance applied during the resampling process. Higher values result in stronger guidance, which can lead to more coherent and detailed images. The typical range is from 1 to 10, with a default value of 5.

positive

This parameter contains the positive prompts or conditions that guide the resampling process. These prompts help in steering the model towards generating desired features in the output image.

negative

This parameter contains the negative prompts or conditions that the model should avoid during the resampling process. These prompts help in steering the model away from generating undesired features in the output image.

sampler

The sampler parameter specifies the sampling method to be used for resampling the latent tiles. Different sampling methods can produce varying results in terms of image quality and style.

sigmas

This parameter controls the noise levels at different stages of the resampling process. It is typically represented as a list of values, with each value corresponding to a specific stage.

latent_image

This parameter is the input latent image that needs to be resampled. It is usually a tensor containing the latent representation of the image.

tile_size

The tile_size parameter specifies the size of the tiles into which the latent image will be split. Smaller tile sizes can lead to more detailed resampling but may require more computational resources. The typical range is from 256 to 1024 pixels, with a default value of 1024 pixels.

Latent Tile Sampler (Mikey) Output Parameters:

latent

The output parameter latent is the resampled latent image. It is a tensor that contains the upscaled and resampled latent representation of the input image. This output can be further processed or converted back to an image for visualization.

Latent Tile Sampler (Mikey) Usage Tips:

• To achieve the best results, experiment with different tile sizes based on the resolution of your input image. Smaller tiles can capture more details but may increase processing time.
• Use consistent noise seeds if you need reproducible results across different runs.
• Adjust the cfg parameter to balance between creativity and coherence in the generated images. Higher values can produce more detailed and guided outputs.
• Combine positive and negative prompts effectively to steer the model towards generating the desired features while avoiding unwanted artifacts.

Latent Tile Sampler (Mikey) Common Errors and Solutions:

"Invalid tile size"

• Explanation: The specified tile size is not supported or is too large for the input latent image.
• Solution: Ensure that the tile size is within the acceptable range and is smaller than the dimensions of the input latent image.

"Model not found"

• Explanation: The specified model for resampling is not available or not loaded correctly.
• Solution: Verify that the model name is correct and that the model is properly loaded in the environment.

"Insufficient memory"

• Explanation: The resampling process requires more memory than is available.
• Solution: Reduce the tile size or optimize the model and parameters to use less memory. Consider using a machine with more memory if possible.