ComfyUI Node: Resize image by edge

Resize image by edge:

LF_ResizeImageByEdge is a node designed to resize images based on a specified edge length, either the longest or shortest edge. This node is particularly useful for AI artists who need to standardize image dimensions while maintaining the aspect ratio. By focusing on one edge, the node ensures that the resized images fit within a desired size constraint without distortion. This capability is essential for preparing images for further processing, ensuring consistency across datasets, or optimizing images for display on various platforms. The node provides flexibility in choosing the resizing method, allowing you to select the most appropriate technique for your specific needs.

Resize image by edge Input Parameters:

node_id

This parameter uniquely identifies the node instance being executed. It is used internally to track and manage the node's operations and is essential for logging and debugging purposes.

image

This parameter represents the input image or a list of images to be resized. The images should be in a tensor format, and the node will process each image individually if a list is provided. The quality and resolution of the input images will directly impact the results of the resizing operation.

longest_edge

This boolean parameter determines whether the resizing should be based on the longest edge of the image. If set to True, the node will resize the image such that the longest edge matches the specified new size. If set to False, the shortest edge will be resized to the new size. This parameter allows you to control the aspect ratio preservation during resizing.

new_size

This integer parameter specifies the target size for the edge selected by the longest_edge parameter. The value should be a positive integer representing the number of pixels. The new size will dictate the final dimensions of the resized image, ensuring it fits within the specified constraints.

resize_method

This string parameter defines the method used for resizing the image. Common methods include nearest, bilinear, bicubic, etc. Each method has its own characteristics in terms of speed and quality, allowing you to choose the most suitable one for your specific application. The choice of method can affect the sharpness and smoothness of the resized image.

Resize image by edge Output Parameters:

resized_image

This parameter represents the output image or list of images that have been resized according to the specified parameters. The resized images will have dimensions that match the new size specified for the selected edge, with the aspect ratio preserved. This output is crucial for ensuring that the images are ready for subsequent processing or display.

Resize image by edge Usage Tips:

• To maintain the aspect ratio while resizing, ensure that the longest_edge parameter is set correctly based on your requirements.
• Experiment with different resize_method values to find the best balance between speed and image quality for your specific use case.
• When processing a batch of images, provide them as a list to the image parameter to ensure consistent resizing across all images.

Resize image by edge Common Errors and Solutions:

"Invalid image format"

• Explanation: The input image is not in the expected tensor format.
• Solution: Ensure that the input image is correctly formatted as a tensor before passing it to the node.

"Invalid new_size value"

• Explanation: The new_size parameter is not a positive integer.
• Solution: Verify that the new_size parameter is set to a positive integer value representing the desired edge length in pixels.

"Unsupported resize method"

• Explanation: The resize_method parameter contains an unrecognized value.
• Solution: Check the available resizing methods and ensure that the resize_method parameter is set to one of the supported values such as nearest, bilinear, or bicubic.