ComfyUI Node: ◎ Radiance Grade Match

◎ Radiance Grade Match:

RadianceGradeMatch is a powerful node designed to harmonize the color statistics of a source image with those of a reference image. This node is particularly useful for achieving consistent visual aesthetics across multiple images by matching their color characteristics. It utilizes LAB mean and standard deviation matching to ensure that the source image adopts the color profile of the reference image, resulting in a seamless and cohesive look. This process is essential for tasks such as color grading in film and photography, where maintaining a consistent color palette is crucial. By adjusting the color statistics, RadianceGradeMatch helps you achieve professional-grade color matching, enhancing the visual appeal and coherence of your image collections.

◎ Radiance Grade Match Input Parameters:

source

The source parameter represents the image that you want to modify to match the color statistics of the reference image. It is crucial for this image to be in a format that supports color channels, as the node will adjust these channels to achieve the desired match. The source image should be a tensor with at least three color channels to ensure accurate color matching.

reference

The reference parameter is the target image whose color profile you wish to apply to the source image. This image serves as the benchmark for color matching, and its color statistics will be used to adjust the source image. Like the source, the reference image should also be a tensor with at least three color channels to provide a comprehensive color profile for matching.

strength

The strength parameter controls the degree to which the source image is adjusted to match the reference image. It is a floating-point value ranging from 0.0 to 1.0, where 0.0 means no change is applied to the source image, and 1.0 means a full match to the reference image's color profile. The default value is 1.0, allowing for complete color matching, but you can adjust this to blend the original and matched colors to your preference.

◎ Radiance Grade Match Output Parameters:

matched_image

The matched_image output is the result of the color matching process. It is the source image that has been adjusted to align with the color statistics of the reference image. This output is crucial for ensuring that your images maintain a consistent color palette, enhancing their visual coherence and appeal.

grade_info

The grade_info output provides a JSON string containing the parameters used during the color matching process. This information is valuable for documentation and reproducibility, allowing you to apply the same color adjustments to other images or batches. It can be connected to the ApplyGradeInfo node for batch processing, ensuring consistent color grading across multiple images.

◎ Radiance Grade Match Usage Tips:

• To achieve the best results, ensure that both the source and reference images have similar lighting conditions and exposure levels, as extreme differences can affect the accuracy of the color matching.
• Experiment with the strength parameter to find the right balance between maintaining the original characteristics of the source image and achieving a full color match with the reference image.

◎ Radiance Grade Match Common Errors and Solutions:

[GradeMatch] Failed: <error_message>``

• Explanation: This error occurs when the node fails to compute the grade parameters necessary for matching the source and reference images. It could be due to incompatible image formats or insufficient color channels.
• Solution: Ensure that both the source and reference images are tensors with at least three color channels. Check that the images are correctly formatted and that there are no issues with the input data.

Invalid JSON: <error_message>``

• Explanation: This error indicates that there was an issue with decoding the JSON string used for grade information. It may be caused by malformed JSON data.
• Solution: Verify that the JSON string is correctly formatted and contains all necessary parameters. Use a JSON validator to check for syntax errors and correct any issues before re-running the node.