ComfyUI Node: Blur Image (Fast)

Blur Image (Fast):

The BlurImageFast node is designed to apply a fast Gaussian blur to images, which is particularly useful for smoothing out details and reducing noise. This node is ideal for AI artists who want to quickly soften images without delving into complex configurations. By leveraging the efficient Gaussian blur algorithm, it ensures that the blurring process is both quick and effective, making it a valuable tool for enhancing the visual quality of images in various creative projects.

Blur Image (Fast) Input Parameters:

images

This parameter accepts the images you want to blur. The input should be in the form of an image tensor. The images will undergo a Gaussian blur based on the specified radii.

radius_x

This integer parameter defines the horizontal radius of the blur effect. A larger value results in a more pronounced horizontal blur. The minimum value is 0, the maximum is 1023, and the default is 1. Setting this to 0 will disable horizontal blurring.

radius_y

This integer parameter defines the vertical radius of the blur effect. A larger value results in a more pronounced vertical blur. The minimum value is 0, the maximum is 1023, and the default is 1. Setting this to 0 will disable vertical blurring.

Blur Image (Fast) Output Parameters:

IMAGE

The output is the blurred image tensor. This image will have the same dimensions as the input but with the applied Gaussian blur effect, making it smoother and less detailed based on the specified radii.

Blur Image (Fast) Usage Tips:

• To achieve a subtle blur effect, use small values for radius_x and radius_y, such as 1 or 2.
• For a more dramatic blur, increase the values of radius_x and radius_y. Experiment with different values to find the optimal blur level for your project.
• If you only want to blur in one direction (horizontal or vertical), set the other radius to 0.

Blur Image (Fast) Common Errors and Solutions:

TypeError: 'NoneType' object is not subscriptable

• Explanation: This error may occur if the input image tensor is not properly loaded or is None.
• Solution: Ensure that the input image tensor is correctly loaded and passed to the node.

ValueError: kernel size must be positive and odd

• Explanation: This error occurs if the calculated kernel size for the Gaussian blur is invalid.
• Solution: Verify that the radius_x and radius_y values are within the valid range and not causing the kernel size to be zero or even.

RuntimeError: CUDA error: out of memory

• Explanation: This error may occur if the input image is too large for the available GPU memory.
• Solution: Try reducing the image size or processing the image in smaller batches to fit within the GPU memory limits.