ComfyUI Node: ImageEffectsLensVignette

ImageEffectsLensVignette:

The ImageEffectsLensVignette node is designed to simulate the vignette effect commonly seen in photography, where the image's edges gradually darken compared to the center. This effect can add a dramatic focus to the central subject of the image, enhancing its visual appeal. The vignette effect is often used to draw attention to the main subject by subtly reducing the brightness or saturation around the edges. This node allows you to customize various parameters to achieve the desired vignette effect, making it a versatile tool for AI artists looking to add a professional touch to their images.

ImageEffectsLensVignette Input Parameters:

images

This parameter represents the input image or a batch of images to which the vignette effect will be applied. The images should be in a tensor format, typically with dimensions corresponding to batch size, height, width, and color channels.

lens_shape

This parameter defines the shape of the lens used to create the vignette effect. It influences how the vignette is applied across the image, affecting the overall aesthetic of the effect. The exact options for this parameter are not specified, but it typically includes shapes like circular, elliptical, or custom shapes.

lens_edge

This parameter determines the edge style of the vignette effect. Options include "around" for a uniform vignette around the edges and "symmetric" for a symmetrical vignette effect. The choice of edge style can significantly impact the visual outcome of the vignette.

lens_curvy

This parameter controls the curvature of the vignette effect. A higher value results in a more pronounced curvature, affecting how the vignette transitions from the center to the edges. This parameter allows for fine-tuning the smoothness of the vignette effect.

lens_zoom

This parameter adjusts the zoom level of the lens effect. Increasing the lens_zoom value will make the vignette effect more concentrated towards the center, while decreasing it will spread the effect more towards the edges. This parameter helps in controlling the intensity and focus of the vignette.

brightness

This parameter adjusts the brightness of the vignette effect. It allows you to control how much the brightness is reduced around the edges of the image. A higher value will result in a more noticeable darkening effect, while a lower value will produce a subtler vignette.

saturation

This parameter adjusts the saturation of the vignette effect. It controls the intensity of colors around the edges of the image. Increasing the saturation value will enhance the colors, while decreasing it will desaturate the edges, creating a more monochromatic vignette effect.

ImageEffectsLensVignette Output Parameters:

result

This output parameter provides the final image with the applied vignette effect. It is a tensor with the same dimensions as the input image, containing the modified pixel values after the vignette effect has been applied.

mask

This output parameter provides the mask used to create the vignette effect. It is a tensor that represents the intensity of the vignette effect across the image, with values indicating the degree of darkening or desaturation applied to each pixel.

ImageEffectsLensVignette Usage Tips:

• Experiment with different lens_shape and lens_edge settings to achieve various artistic effects and find the one that best suits your image.
• Adjust the lens_curvy parameter to control the smoothness of the vignette transition, making it either more gradual or more abrupt.
• Use the brightness and saturation parameters to fine-tune the visual impact of the vignette effect, ensuring it enhances rather than overwhelms the main subject of the image.

ImageEffectsLensVignette 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 either "around" or "symmetric". Double-check the input value for any typos or unsupported options.

RuntimeError: shape '[...]' is invalid for input of size [...]

• Explanation: This error may occur if the input image dimensions do not match the expected format or if there is a mismatch in tensor shapes during processing.
• Solution: Verify that the input images are in the correct tensor format and that their dimensions are consistent. Ensure that the batch size, height, width, and color channels are correctly specified.