ComfyUI Node: Color Correct of Utils

Color Correct of Utils:

The ColorCorrectOfUtils node is designed to provide comprehensive post-processing capabilities for image adjustments, making it an essential tool for AI artists looking to fine-tune their creations. This node allows you to manipulate various aspects of an image, such as temperature, brightness, contrast, saturation, and more, to achieve the desired visual effect. By leveraging advanced image processing techniques, it ensures that your images can be adjusted with precision, enhancing their overall quality and aesthetic appeal. Whether you are looking to correct color imbalances, enhance specific tones, or add artistic effects like grain, this node offers a versatile and powerful solution.

Color Correct of Utils Input Parameters:

image

This parameter accepts an image tensor that you want to process. The image serves as the base for all subsequent adjustments.

temperature

This parameter adjusts the color temperature of the image, making it warmer or cooler. A higher value increases the warmth, while a lower value cools the image. The range is from -100 to 100, with a default value of 0.

red

This parameter adjusts the red channel intensity of the image. Positive values increase the red tones, while negative values decrease them. The range is from -100 to 100, with a default value of 0.

green

This parameter adjusts the green channel intensity of the image. Positive values increase the green tones, while negative values decrease them. The range is from -100 to 100, with a default value of 0.

blue

This parameter adjusts the blue channel intensity of the image. Positive values increase the blue tones, while negative values decrease them. The range is from -100 to 100, with a default value of 0.

hue

This parameter shifts the hue of the image, altering the overall color balance. The range is from -90 to 90 degrees, with a default value of 0.

brightness

This parameter adjusts the brightness of the image. Positive values make the image brighter, while negative values make it darker. The range is from -100 to 100, with a default value of 0.

contrast

This parameter adjusts the contrast of the image. Positive values increase the contrast, making the darks darker and the lights lighter, while negative values decrease the contrast. The range is from -100 to 100, with a default value of 0.

saturation

This parameter adjusts the saturation of the image, affecting the intensity of the colors. Positive values make the colors more vivid, while negative values desaturate the image. The range is from -100 to 100, with a default value of 0.

gamma

This parameter adjusts the gamma correction of the image, which affects the overall brightness and contrast. The range is from 0.2 to 2.2, with a default value of 1.

grain

This parameter adds a grain effect to the image, simulating film grain. The range is from 0.0 to 1, with a default value of 0.

Color Correct of Utils Output Parameters:

IMAGE

The output is the processed image tensor, which has undergone all the specified adjustments. This image can be used for further processing or as a final output for display or saving.

Color Correct of Utils Usage Tips:

• To achieve a warmer image, increase the temperature parameter.
• For a vintage look, try increasing the grain parameter and slightly decreasing the saturation.
• Use the gamma parameter to fine-tune the overall brightness and contrast after making other adjustments.
• Adjust hue to correct or creatively alter the color balance of your image.

Color Correct of Utils Common Errors and Solutions:

Image tensor shape mismatch

• Explanation: The input image tensor does not have the expected shape.
• Solution: Ensure that the input image tensor has the correct dimensions, typically (batch_size, height, width, channels).

Invalid parameter range

• Explanation: One or more input parameters are outside their valid range.
• Solution: Check the parameter values and ensure they fall within the specified ranges.

Unsupported image type

• Explanation: The input image is not in a supported format.
• Solution: Convert the image to a supported format, such as a tensor with appropriate dimensions and data type.