ComfyUI Node: Image Resize to Square

Image Resize to Square:

The JWImageResizeToSquare node is designed to resize an image to a square format, ensuring that both the height and width of the image are equal to a specified size. This node is particularly useful for standardizing image dimensions, which can be essential for various artistic and technical applications, such as preparing images for machine learning models, creating uniform thumbnails, or ensuring consistency in a digital art project. By leveraging different interpolation modes, this node provides flexibility in how the resizing is performed, allowing you to choose the method that best preserves the quality and details of the original image.

Image Resize to Square Input Parameters:

image

This parameter expects an image in the form of a tensor. The image is the primary input that will be resized to a square format. The tensor should be in the shape of (batch_size, height, width, channels).

size

The size parameter determines the dimensions of the output square image. Both the height and width of the resulting image will be set to this value. The size is an integer with a default value of 512, a minimum value of 0, and a maximum value of 99999. Adjusting this parameter allows you to control the resolution of the output image.

interpolation_mode

This parameter specifies the method used to interpolate pixel values when resizing the image. The available options are "bicubic", "bilinear", "nearest", and "nearest exact". Each mode has its own characteristics: "bicubic" and "bilinear" provide smoother results, while "nearest" and "nearest exact" are faster but may produce more pixelated images. The choice of interpolation mode can impact the visual quality of the resized image.

Image Resize to Square Output Parameters:

image

The output is a tensor representing the resized square image. The dimensions of this image will be (batch_size, size, size, channels), where the size is determined by the input parameter. This output can be used directly in subsequent nodes or processes that require a standardized image size.

Image Resize to Square Usage Tips:

• Use the "bicubic" interpolation mode for high-quality image resizing, especially when dealing with photographs or detailed artwork.
• If speed is a priority and slight pixelation is acceptable, consider using the "nearest" or "nearest exact" interpolation modes.
• Ensure that the input image tensor is correctly formatted (batch_size, height, width, channels) to avoid unexpected results.

Image Resize to Square Common Errors and Solutions:

AssertionError: image must be a torch.Tensor

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

AssertionError: size must be an int

• Explanation: This error occurs if the size parameter is not an integer.
• Solution: Verify that the size parameter is an integer value within the allowed range.

AssertionError: interpolation_mode must be a str

• Explanation: This error occurs if the interpolation_mode parameter is not a string.
• Solution: Ensure that the interpolation_mode is specified as a string and matches one of the allowed options ("bicubic", "bilinear", "nearest", "nearest exact").