ComfyUI Node: Load Image And Resize To Fit (FS)

Load Image And Resize To Fit (FS):

The FS: Load Image And Resize To Fit node is designed to streamline the process of loading an image and resizing it to fit within a specified maximum dimension while maintaining its aspect ratio. This node is particularly useful for AI artists who need to prepare images for further processing or analysis, ensuring that the images are appropriately scaled without distortion. By leveraging advanced resampling techniques and optional upscaling, this node provides a flexible and efficient solution for handling images of various sizes and resolutions. The primary goal of this node is to simplify image preparation, making it easier to work with images in different AI and machine learning workflows.

Load Image And Resize To Fit (FS) Input Parameters:

image

This parameter specifies the image to be loaded and resized. The image can be provided as a file path or an image tensor. The node will handle the loading and conversion of the image to the appropriate format for processing.

max_size

This parameter defines the maximum dimension (either width or height) to which the image should be resized. The default value is 768, and it can be adjusted in steps of 8. This ensures that the image fits within the specified size while maintaining its aspect ratio.

resampling

This parameter determines the resampling method used for resizing the image. Available options are lanczos, nearest, bilinear, and bicubic. The default method is bicubic, which provides a good balance between quality and performance. Different resampling methods can affect the sharpness and smoothness of the resized image.

upscale

This parameter indicates whether the image should be upscaled if its dimensions are smaller than the specified max_size. The options are false and true, with the default being false. Upscaling can be useful for ensuring that smaller images meet the required size for further processing.

batch_size

This parameter specifies the number of times the latent vectors should be repeated in the output. The default value is 1, with a minimum of 1 and a maximum of 64. This is useful for batch processing in machine learning workflows.

add_noise

This parameter allows for the addition of noise to the latent vectors. It is a float value ranging from 0 to 1, with a default of 0. Adding noise can be useful for certain types of data augmentation or for testing the robustness of models.

Load Image And Resize To Fit (FS) Output Parameters:

Latent

This output is the latent representation of the resized image, which can be used for further processing in machine learning models. The latent vector is repeated according to the specified batch_size.

Image

This output is the resized image in tensor format. It can be used for visualization or as input to other nodes in the workflow.

Fit Width

This output is the width of the resized image. It provides information about the new dimensions of the image after resizing.

Fit Height

This output is the height of the resized image. It provides information about the new dimensions of the image after resizing.

Aspect Ratio

This output is the aspect ratio of the resized image. It helps in understanding how the image's proportions have been maintained during the resizing process.

Load Image And Resize To Fit (FS) Usage Tips:

• To achieve the best quality for resized images, use the bicubic resampling method, which provides a good balance between sharpness and smoothness.
• If you need to ensure that smaller images meet a specific size requirement, set the upscale parameter to true to enable upscaling.
• For batch processing, adjust the batch_size parameter to match the number of images you need to process simultaneously.
• Use the add_noise parameter to introduce variability in the latent vectors, which can be useful for data augmentation or robustness testing.

Load Image And Resize To Fit (FS) Common Errors and Solutions:

Invalid image file: <image_path>

• Explanation: The specified image file could not be found or is not a valid image format.
• Solution: Ensure that the image file path is correct and that the file is a valid image format (e.g., JPEG, PNG).

Unsupported resampling method: <resampling_method>

• Explanation: The specified resampling method is not one of the supported options (lanczos, nearest, bilinear, bicubic).
• Solution: Choose a valid resampling method from the supported options.

Batch size out of range: <batch_size>

• Explanation: The specified batch size is outside the allowed range (1 to 64).
• Solution: Adjust the batch size to be within the allowed range.

Add noise value out of range: <add_noise>

• Explanation: The specified add noise value is outside the allowed range (0 to 1).
• Solution: Adjust the add noise value to be within the allowed range.