ComfyUI Node: 🐯 YFG Histograms Generator

🐯 YFG Histograms Generator:

The image_histograms_node is a versatile tool designed to generate various types of histograms from an image, providing valuable insights into the image's color distribution and luminosity. This node is particularly useful for AI artists who want to analyze and manipulate images by understanding their color channels and brightness levels. By converting image data into histograms, you can visualize the intensity distribution of colors and luminosity, which can be crucial for tasks such as image enhancement, color correction, and artistic effects. The node supports generating filled histograms, line histograms, and individual channel histograms (red, green, blue), as well as a luminosity histogram, offering a comprehensive set of tools for image analysis.

🐯 YFG Histograms Generator Input Parameters:

image

The image parameter expects a tensor representation of the image you want to analyze. This tensor should be in the format of a 4D tensor with dimensions corresponding to batch size, height, width, and color channels. The image tensor is the primary input from which the histograms will be generated. Ensure that the image tensor is correctly formatted to avoid errors during processing.

histogram_size

The histogram_size parameter determines the resolution of the generated histograms. It accepts three possible values: "small", "medium", and "large". The resolution impacts the clarity and detail of the histogram images, with "small" providing a lower resolution and "large" offering a higher resolution. The default value is "medium". Choose the appropriate size based on your need for detail and the performance considerations of your workflow.

histogram_type

The histogram_type parameter specifies the type of histogram to generate. Options include "RGB Histogram Filled", "RGB Histogram Lines", "Red Channel", "Green Channel", "Blue Channel", and "Luminosity". Each type provides a different perspective on the image's color and brightness distribution. The default value is "RGB Histogram Filled". Select the histogram type that best suits your analysis or artistic requirements.

preview

The preview parameter is a boolean that determines whether a preview of the histogram should be displayed. When set to True, a preview image will be generated, allowing you to quickly assess the histogram without saving it. The default value is True. Use this option to streamline your workflow by quickly visualizing the results.

display

The display parameter defines how the histogram should be displayed. It accepts the value "histogram", which indicates that the output will be a histogram image. This parameter ensures that the node's output is correctly formatted for your intended use.

prompt

The prompt parameter allows you to provide a textual prompt that can be used for additional context or metadata when saving the histogram images. This can be useful for organizing and annotating your results. The default value is None.

extra_pnginfo

The extra_pnginfo parameter is used to include additional metadata in the saved PNG files. This can be any extra information you want to embed in the histogram images, such as processing details or contextual notes. The default value is None.

🐯 YFG Histograms Generator Output Parameters:

original_image

The original_image output parameter returns the original image tensor that was input into the node. This allows you to retain and use the original image alongside the generated histograms for further processing or comparison.

histogram_filled

The histogram_filled output parameter provides the filled RGB histogram image tensor. This histogram shows the distribution of red, green, and blue color intensities with filled areas under the curves, offering a clear visualization of color distribution.

histogram_lines

The histogram_lines output parameter provides the line RGB histogram image tensor. This histogram displays the color intensity distribution using lines, which can be useful for a more precise analysis of color variations.

red_hist

The red_hist output parameter returns the histogram image tensor for the red color channel. This histogram isolates the red channel, allowing you to analyze the intensity distribution of red tones in the image.

green_hist

The green_hist output parameter returns the histogram image tensor for the green color channel. This histogram isolates the green channel, enabling you to examine the intensity distribution of green tones in the image.

blue_hist

The blue_hist output parameter returns the histogram image tensor for the blue color channel. This histogram isolates the blue channel, facilitating the analysis of the intensity distribution of blue tones in the image.

lum_hist

The lum_hist output parameter provides the luminosity histogram image tensor. This histogram shows the distribution of brightness levels in the image, which is useful for understanding the overall lightness and contrast.

🐯 YFG Histograms Generator Usage Tips:

• Use the histogram_size parameter to balance between detail and performance. For quick previews, "small" may be sufficient, while "large" is ideal for detailed analysis.
• Experiment with different histogram_type settings to gain various insights into your image's color and brightness characteristics.
• Utilize the preview option to quickly visualize histograms without saving them, speeding up your workflow.
• Leverage the prompt and extra_pnginfo parameters to add context and metadata to your saved histogram images, making it easier to organize and reference them later.

🐯 YFG Histograms Generator Common Errors and Solutions:

"Invalid image tensor format"

• Explanation: The input image tensor is not in the expected 4D format.
• Solution: Ensure that your image tensor has the correct dimensions: batch size, height, width, and color channels.

"Unsupported histogram type"

• Explanation: The specified histogram_type is not recognized.
• Solution: Verify that the histogram_type parameter is set to one of the supported values: "RGB Histogram Filled", "RGB Histogram Lines", "Red Channel", "Green Channel", "Blue Channel", or "Luminosity".

"Image tensor is empty"

• Explanation: The input image tensor has no data.
• Solution: Check that the image tensor is correctly loaded and contains valid image data before passing it to the node.

"Error saving histogram image"

• Explanation: There was an issue saving the generated histogram image.
• Solution: Ensure that the file path and permissions are correct, and that there is enough disk space to save the image.