ComfyUI Node: Mask Like Image Size

Mask Like Image Size:

The JWMaskLikeImageSize node is designed to generate a mask that matches the dimensions of a given image. This node is particularly useful when you need to create a mask with a uniform value across the entire image, which can be used in various image processing tasks such as masking, blending, or applying effects selectively. By providing an image and a value, the node produces a mask tensor filled with the specified value, ensuring that the mask has the same height and width as the input image. This functionality is essential for maintaining consistency in image dimensions when applying subsequent operations that require masks.

Mask Like Image Size Input Parameters:

image

The image parameter expects an input of type IMAGE. This parameter is the reference image whose dimensions will be used to create the mask. The mask generated will have the same height and width as this image, ensuring compatibility for further processing steps.

value

The value parameter is a FLOAT that determines the value to fill the mask with. It has a default value of 1.0, with a minimum of 0.0 and a maximum of 1.0, and can be adjusted in steps of 0.01. This value will be uniformly applied across the entire mask, allowing you to control the intensity or effect of the mask in subsequent operations.

Mask Like Image Size Output Parameters:

mask

The mask output is of type MASK. This parameter represents the generated mask tensor, which has the same height and width as the input image and is filled with the specified value. This mask can be used in various image processing tasks where a uniform mask is required.

Mask Like Image Size Usage Tips:

• Use the value parameter to control the intensity of the mask. For example, a value of 1.0 will create a fully opaque mask, while a value of 0.5 will create a semi-transparent mask.
• Ensure that the input image has the correct dimensions and format, as the mask will directly inherit these properties.

Mask Like Image Size Common Errors and Solutions:

AssertionError: image must be a torch.Tensor

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

AssertionError: value must be a float

• Explanation: This error occurs when the value parameter is not a float.
• Solution: Ensure that the value parameter is a float within the specified range (0.0 to 1.0).

ValueError: Invalid image dimensions

• Explanation: This error occurs when the input image does not have the expected dimensions.
• Solution: Verify that the input image has the correct dimensions (height, width) and format before using the node.