ComfyUI Node: Image Resize by Shorter Side

Image Resize by Shorter Side:

The JWImageResizeByShorterSide node is designed to resize an image based on its shorter side, ensuring that the aspect ratio is maintained. This node is particularly useful when you want to standardize the size of images without distorting their proportions. By specifying the desired size for the shorter side, the node automatically calculates the corresponding dimension for the longer side, resulting in a resized image that fits within the specified constraints. This functionality is essential for preparing images for various applications, such as machine learning models, where consistent image dimensions are crucial. The node also offers multiple interpolation modes to ensure the resized image maintains high quality.

Image Resize by Shorter Side Input Parameters:

image

This parameter expects an image in the form of a tensor. The image is the primary input that will be resized based on the specified shorter side dimension. The tensor should be in the format of (batch_size, height, width, channels).

size

This integer parameter defines the target size for the shorter side of the image. The node will resize the image such that the shorter side matches this value while maintaining the aspect ratio. The default value is 512, with a minimum of 0 and a maximum of 99999.

interpolation_mode

This parameter specifies the method used for resizing the image. The available options are bicubic, bilinear, nearest, and nearest exact. Each mode offers a different approach to interpolation, affecting the quality and smoothness of the resized image. The choice of interpolation mode can impact the visual quality of the output, with bicubic generally providing the smoothest results.

Image Resize by Shorter Side Output Parameters:

image

The output is a resized image tensor that maintains the original aspect ratio. The shorter side of the image will match the specified size, and the longer side will be adjusted accordingly. This ensures that the image fits within the desired dimensions without distortion.

Image Resize by Shorter Side Usage Tips:

• Use the bicubic interpolation mode for the highest quality resizing, especially when dealing with photographs or images with gradients.
• Ensure that the size parameter is set appropriately to avoid excessively large or small images, which could impact performance or visual quality.
• When preparing images for machine learning models, use this node to standardize the input sizes, ensuring consistent dimensions across your dataset.

Image Resize by Shorter Side Common Errors and Solutions:

AssertionError: expected image to be a torch.Tensor

• Explanation: This error occurs when the input image is not provided as a tensor.
• Solution: Ensure that the input image is correctly formatted as a tensor before passing it to the node.

AssertionError: expected size to be an int

• Explanation: This error occurs when the size parameter is not an integer.
• Solution: Verify that the size parameter is set to an integer value.

AssertionError: expected interpolation_mode to be a str

• Explanation: This error occurs when the interpolation_mode parameter is not a string.
• Solution: Ensure that the interpolation_mode parameter is provided as a string, matching one of the available options.

ValueError: invalid interpolation mode

• Explanation: This error occurs when the specified interpolation mode is not recognized.
• Solution: Check that the interpolation_mode parameter is set to one of the valid options: bicubic, bilinear, nearest, or nearest exact.