ComfyUI Node: GR Flip Tile Random Red Ring

GR Flip Tile Random Red Ring:

The GR Flip Tile Random Red Ring node is designed to manipulate an image by dividing it into a grid of tiles, flipping one random tile, and adding a distinctive red border around the flipped tile. This node is particularly useful for creating visually striking effects in your artwork by introducing an element of randomness and contrast. The primary goal of this node is to enhance the visual appeal of your images by adding a unique and unexpected twist, making it a valuable tool for AI artists looking to experiment with tile-based transformations and color accents.

GR Flip Tile Random Red Ring Input Parameters:

image

This parameter represents the input image that you want to process. The image will be divided into a grid of tiles, and one of these tiles will be randomly flipped and bordered in red. The quality and resolution of the input image will directly affect the output.

rows

This parameter specifies the number of rows into which the input image will be divided. Increasing the number of rows will result in smaller tiles, while decreasing it will create larger tiles. The minimum value is 1, and there is no strict maximum value, but it should be a positive integer.

columns

This parameter defines the number of columns into which the input image will be divided. Similar to the rows parameter, increasing the number of columns will result in smaller tiles, and decreasing it will create larger tiles. The minimum value is 1, and there is no strict maximum value, but it should be a positive integer.

colour

This parameter allows you to specify the color of the border that will be applied to the flipped tile. The color should be chosen from a predefined set of colors available in the node's color dictionary. The default value is "red".

border

This optional parameter determines whether a border should be applied to the entire image. The default value is 0 (no border), and setting it to 1 will enable the border.

border_thickness

This parameter specifies the thickness of the red border that will be applied to the flipped tile. The default value is 5 pixels, but you can adjust it to achieve the desired visual effect. The minimum value is 1 pixel.

seed

This optional parameter allows you to set a seed for the random number generator, ensuring reproducibility of the random tile flipping. If not provided, the node will generate a random seed.

flipped_tile_image

This optional parameter allows you to provide a custom image to replace the randomly flipped tile. If not provided, the node will simply flip the selected tile horizontally.

GR Flip Tile Random Red Ring Output Parameters:

new_image

This output parameter represents the processed image with one randomly flipped tile and, optionally, a border around the entire image. The flipped tile will have a red border applied to it, creating a visually distinct effect.

red_bordered_image

This output parameter represents the processed image with the red border applied to the flipped tile. This image highlights the flipped tile with a red border, making it stand out from the rest of the image.

GR Flip Tile Random Red Ring Usage Tips:

• Experiment with different values for the rows and columns parameters to achieve various tile sizes and effects.
• Use the seed parameter to ensure reproducibility when you want to achieve consistent results across multiple runs.
• Adjust the border_thickness parameter to create more or less prominent borders around the flipped tile.
• Try using a custom image for the flipped_tile_image parameter to introduce unique elements into your artwork.

GR Flip Tile Random Red Ring Common Errors and Solutions:

"Invalid color specified"

• Explanation: The color specified in the colour parameter is not available in the predefined color dictionary.
• Solution: Ensure that the color you specify is one of the predefined colors in the node's color dictionary.

"Rows and columns must be positive integers"

• Explanation: The values provided for the rows and columns parameters are not positive integers.
• Solution: Verify that the values for rows and columns are positive integers and adjust them accordingly.

"Image tensor dimensions mismatch"

• Explanation: The dimensions of the input image tensor do not match the expected format.
• Solution: Ensure that the input image is correctly formatted and has the appropriate dimensions for processing.