ComfyUI Node: LatentUpscaleFactor _O

LatentUpscaleFactor _O:

The LatentUpscaleFactor _O node is designed to upscale the latent code by multiplying the width and height by specified factors. This node is particularly useful for AI artists who want to enhance the resolution of their latent images without losing quality. By providing flexible upscale methods and crop options, it allows for precise control over the upscaling process, ensuring that the final output meets the desired specifications. The node's primary function is to take an input latent image and upscale its dimensions according to the provided width and height factors, making it an essential tool for refining and improving the quality of AI-generated images.

LatentUpscaleFactor _O Input Parameters:

samples

This parameter represents the latent image data that you want to upscale. It is a required input and should be of type LATENT. The latent image contains the encoded information that will be processed and upscaled by the node.

upscale_method

This parameter determines the method used for upscaling the latent image. The available options are nearest-exact, bilinear, and area. Each method has its own characteristics: nearest-exact is fast and simple, bilinear provides smoother results, and area is suitable for downscaling but can also be used for upscaling. Choosing the right method can impact the quality and appearance of the upscaled image.

WidthFactor

This parameter specifies the factor by which the width of the latent image will be multiplied. It is a floating-point value with a default of 1.25, a minimum of 0.0, and a maximum of 10.0. Adjusting this factor allows you to control the horizontal scaling of the image, making it wider or narrower as needed.

HeightFactor

This parameter specifies the factor by which the height of the latent image will be multiplied. Similar to WidthFactor, it is a floating-point value with a default of 1.25, a minimum of 0.0, and a maximum of 10.0. This factor controls the vertical scaling of the image, allowing you to make it taller or shorter.

crop

This parameter determines how the image will be cropped after upscaling. The available options are disabled and center. When set to disabled, no cropping is applied. When set to center, the image is cropped to maintain the center portion, which can be useful for focusing on the main subject of the image.

LatentUpscaleFactor _O Output Parameters:

LATENT

The output of this node is the upscaled latent image, which retains the encoded information of the original image but with enhanced resolution. This output can be further processed or decoded to generate a high-resolution image. The upscaled latent image is crucial for achieving better quality and detail in the final output.

LatentUpscaleFactor _O Usage Tips:

• Experiment with different upscale_method options to find the best balance between speed and quality for your specific use case.
• Use WidthFactor and HeightFactor to fine-tune the aspect ratio of your image, ensuring it meets your desired dimensions.
• If you want to focus on a specific part of the image, use the center crop method to maintain the central portion after upscaling.

LatentUpscaleFactor _O Common Errors and Solutions:

"ValueError: WidthFactor or HeightFactor out of range"

• Explanation: This error occurs when the provided WidthFactor or HeightFactor is outside the allowed range (0.0 to 10.0).
• Solution: Ensure that the WidthFactor and HeightFactor values are within the specified range.

"RuntimeError: Exceeded maximum resolution"

• Explanation: This error occurs when the upscaled dimensions exceed the maximum allowed resolution.
• Solution: Adjust the WidthFactor and HeightFactor to ensure the upscaled dimensions do not exceed the maximum resolution limit.

"TypeError: Invalid upscale method"

• Explanation: This error occurs when an invalid upscale_method is provided.
• Solution: Ensure that the upscale_method is one of the allowed options: nearest-exact, bilinear, or area.

"KeyError: Missing samples key in input"

• Explanation: This error occurs when the input samples parameter does not contain the expected key.
• Solution: Verify that the input samples parameter is correctly formatted and contains the necessary data.