ComfyUI Node: Runtime44 Color Match

Runtime44 Color Match:

The Runtime44ColorMatch node is designed to harmonize the colors of one image with another using the histogram matching technique. This process ensures that the color distribution of the target image is adjusted to closely resemble that of the source image, creating a cohesive and visually appealing result. This node leverages advanced libraries such as CuPy for CUDA-enabled devices and NumPy for CPU-based operations, ensuring efficient and accurate color matching regardless of your hardware setup. By utilizing this node, you can achieve consistent color grading across multiple images, which is particularly useful in artistic projects where color harmony is crucial.

Runtime44 Color Match Input Parameters:

source

The source parameter is an image tensor that serves as the reference for color distribution. The colors from this image will be used to adjust the target image, ensuring that the final output matches the color profile of the source. This parameter is essential for defining the desired color palette and directly impacts the visual outcome of the color matching process.

target

The target parameter is an image tensor that will be adjusted to match the color distribution of the source image. This image will undergo histogram matching to align its colors with those of the source, resulting in a visually cohesive output. The target image is the primary subject of the color adjustment process.

Runtime44 Color Match Output Parameters:

IMAGE

The output is an image tensor that has undergone color matching to align with the source image's color distribution. This output image will have its colors adjusted to closely resemble those of the source image, ensuring a consistent and harmonious color palette across your project.

Runtime44 Color Match Usage Tips:

• Ensure that both the source and target images are of similar dimensions and resolutions for optimal color matching results.
• Use high-quality images as the source to achieve the best color distribution and avoid artifacts in the target image.
• Experiment with different source images to find the most visually appealing color match for your target image.

Runtime44 Color Match Common Errors and Solutions:

"CUDA device not available"

• Explanation: This error occurs when the node attempts to use CUDA for processing, but no CUDA-enabled device is detected.
• Solution: Ensure that your system has a CUDA-enabled GPU and that the necessary drivers and libraries are installed. Alternatively, the node will automatically fall back to CPU-based processing if CUDA is not available.

"Input tensors must be of the same shape"

• Explanation: This error occurs when the source and target images have different dimensions or shapes.
• Solution: Ensure that both the source and target images have the same dimensions and shape before passing them to the node.

"Memory allocation failed"

• Explanation: This error occurs when there is insufficient memory to process the images, especially on CUDA-enabled devices.
• Solution: Reduce the size of the input images or free up memory on your device before running the node again. If using a GPU, ensure that no other memory-intensive processes are running simultaneously.