ComfyUI Node: ImageFilterEdgeEnhance

ImageFilterEdgeEnhance:

The ImageFilterEdgeEnhance node is designed to enhance the edges within an image, making them more pronounced and defined. This can be particularly useful for highlighting details and creating a more striking visual effect. By applying this filter, you can bring out the contours and boundaries within your artwork, adding a layer of depth and clarity. This node is ideal for artists looking to emphasize the structural elements of their images, making them stand out more vividly.

ImageFilterEdgeEnhance Input Parameters:

images

This parameter accepts the image or set of images that you want to apply the edge enhancement filter to. The input should be in the form of an image tensor. The filter will process these images to enhance their edges, making the contours and boundaries more pronounced.

ImageFilterEdgeEnhance Output Parameters:

IMAGE

The output is the processed image or set of images with enhanced edges. This means that the edges within the image will be more defined and prominent, giving the image a sharper and more detailed appearance. The output retains the same dimensions and format as the input images.

ImageFilterEdgeEnhance Usage Tips:

• Use this node to highlight the structural details in your images, making them more visually striking.
• Combine this filter with other effects to create a layered and complex visual style.
• Adjust the input images' contrast and brightness before applying the edge enhancement to achieve different artistic effects.

ImageFilterEdgeEnhance Common Errors and Solutions:

ValueError: Not existing lens_edge parameter.

• Explanation: This error occurs when an invalid value is provided for the lens_edge parameter.
• Solution: Ensure that the lens_edge parameter is set to a valid value, such as "around" or "symmetric". Double-check the parameter values before running the node.

TypeError: Expected input to be a tensor.

• Explanation: This error occurs when the input provided is not in the expected tensor format.
• Solution: Make sure that the input images are correctly formatted as tensors. Convert your images to the appropriate format before passing them to the node.