ComfyUI Node: ImageFilterGaussianBlur

ImageFilterGaussianBlur:

The ImageFilterGaussianBlur node is designed to apply a Gaussian blur effect to your images, which is a common technique used to reduce image noise and detail. This node leverages the Gaussian blur method, which smooths the image by averaging the pixel values with a Gaussian kernel. The primary benefit of using this node is to create a softening effect that can help in reducing harsh edges and noise, making the image appear more polished and visually appealing. This is particularly useful in various artistic and photographic applications where a softer look is desired.

ImageFilterGaussianBlur Input Parameters:

images

This parameter accepts the image or images you want to apply the Gaussian blur to. The input should be in the form of an image tensor.

size_x

This parameter defines the width of the Gaussian kernel. The kernel size determines the extent of the blurring effect. A larger value results in a more pronounced blur. The default value is 10, with a minimum value of 2, and it increments in steps of 2.

size_y

This parameter defines the height of the Gaussian kernel. Similar to size_x, it affects the vertical extent of the blur. The default value is 10, with a minimum value of 2, and it increments in steps of 2.

ImageFilterGaussianBlur Output Parameters:

IMAGE

The output is the blurred image, which has undergone the Gaussian blur transformation. This output retains the same dimensions as the input image but with a softened appearance due to the applied blur effect.

ImageFilterGaussianBlur Usage Tips:

• To achieve a subtle blur effect, use smaller values for size_x and size_y. This is useful for slightly softening the image without losing too much detail.
• For a more dramatic blur, increase the values of size_x and size_y. This can be particularly effective for creating background blur effects in portrait images.

ImageFilterGaussianBlur Common Errors and Solutions:

"Kernel size must be positive and odd"

• Explanation: The Gaussian kernel size must be a positive odd number to function correctly.
• Solution: Ensure that the values for size_x and size_y are set to positive odd numbers. If you encounter this error, try adjusting the values to meet this requirement.

"Image input is not valid"

• Explanation: The input provided is not recognized as a valid image tensor.
• Solution: Verify that the input is a correctly formatted image tensor. Ensure that the image data is properly loaded and passed to the node.