ComfyUI Node: Nuke Color Bars

Nuke Color Bars:

The NukeColorBars node is designed to generate standard color bar patterns, which are essential tools for testing and calibrating visual outputs. This node is particularly useful for ensuring that color displays and video outputs are accurately representing colors. By providing a variety of color patterns such as SMPTE, RGB bars, primary colors, and grayscale, the node allows you to test different aspects of color representation and monitor calibration. The generated color bars can be used to verify color accuracy, contrast, and brightness settings, making it a valuable asset for artists and technicians who need to ensure the fidelity of their visual outputs.

Nuke Color Bars Input Parameters:

width

The width parameter specifies the width of the generated color bars image in pixels. It allows you to define the horizontal resolution of the output, which can range from a minimum of 64 pixels to a maximum of 4096 pixels. The default value is set to 512 pixels. Adjusting this parameter impacts the overall size and detail of the color bars, with larger values providing more detailed and expansive patterns.

height

The height parameter determines the height of the color bars image in pixels. Similar to the width parameter, it defines the vertical resolution and can be set between 64 and 4096 pixels, with a default of 512 pixels. This parameter affects the aspect ratio and the vertical detail of the generated pattern, allowing you to tailor the output to specific display requirements.

pattern

The pattern parameter allows you to select the type of color bar pattern to generate. Options include smpte, rgb_bars, primary_colors, and grayscale, with smpte being the default choice. Each pattern serves a different purpose: smpte is used for broadcast testing, rgb_bars for primary color testing, primary_colors for basic color checks, and grayscale for luminance testing. Choosing the appropriate pattern is crucial for the specific testing or calibration task at hand.

batch_size

The batch_size parameter specifies the number of color bar images to generate simultaneously. It ranges from 1 to 64, with a default value of 1. This parameter is particularly useful when you need to produce multiple images for batch processing or testing across different devices or settings. Increasing the batch size can save time and streamline workflows that require multiple outputs.

Nuke Color Bars Output Parameters:

IMAGE

The IMAGE output parameter represents the generated color bar image(s). This output is crucial for visual testing and calibration, providing a reference for color accuracy and display settings. The image includes an alpha channel for transparency and is formatted to be compatible with various display and processing systems. The output can be used directly in visual workflows or as a benchmark for further adjustments and calibrations.

Nuke Color Bars Usage Tips:

• To ensure accurate color calibration, choose the smpte pattern when testing broadcast equipment or displays that require precise color standards.
• Use the grayscale pattern to evaluate the luminance response of a display, which is essential for adjusting brightness and contrast settings.
• Adjust the width and height parameters to match the resolution of the display you are testing, ensuring that the color bars are rendered at the correct size for accurate assessment.

Nuke Color Bars Common Errors and Solutions:

Invalid pattern selection

• Explanation: This error occurs when a pattern type is selected that is not supported by the node.
• Solution: Ensure that the pattern parameter is set to one of the supported options: smpte, rgb_bars, primary_colors, or grayscale.

Image size out of range

• Explanation: This error happens when the width or height parameters are set outside the allowed range of 64 to 4096 pixels.
• Solution: Adjust the width and height parameters to fall within the specified range to ensure proper image generation.

Batch size too large

• Explanation: This error is triggered when the batch_size exceeds the maximum limit of 64.
• Solution: Reduce the batch_size to 64 or fewer to comply with the node's constraints and ensure successful image generation.