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Generate placeholder image for missing primary image data in AI art pipelines, ensuring workflow continuity.
The FallbackImagePreviewer node is designed to handle scenarios where image previews are required but the primary image data is unavailable or invalid. This node ensures that a fallback mechanism is in place to generate a placeholder image, maintaining the workflow's continuity and preventing interruptions. It is particularly useful in AI art generation pipelines where image previews are essential for iterative design processes. By providing a fallback image, it helps you visualize the output even when the primary image data is missing, thus enhancing the robustness and reliability of your image processing tasks.
This parameter accepts the primary image data that you want to preview. If valid images are provided, they will be used for generating the preview. If this parameter is None
, the node will proceed to generate a fallback image. This parameter is crucial as it determines whether the node will use the actual image data or create a placeholder.
This parameter specifies the width of the fallback image to be generated if the primary image data is unavailable. It ensures that the generated placeholder image has the correct dimensions. The width should be a positive integer, and a value of 0
indicates that no valid fallback image will be generated.
This parameter specifies the height of the fallback image to be generated if the primary image data is unavailable. Similar to fallback_width
, it ensures that the generated placeholder image has the correct dimensions. The height should be a positive integer, and a value of 0
indicates that no valid fallback image will be generated.
This boolean parameter determines whether the generated image (either primary or fallback) should be saved to disk. If set to True
, the image will be saved, and additional parameters like filename_prefix
will be used to determine the file name and location.
This parameter is used to specify the prefix for the filename when saving the image. It helps in organizing and identifying the saved images, especially when multiple images are generated in a batch process. This parameter is only relevant if save_image
is set to True
.
This parameter is used to provide additional context or metadata for the image being generated. It can be useful for documentation or for embedding extra information within the image file. This parameter is optional and is primarily used for informational purposes.
This parameter allows you to embed additional PNG metadata into the generated image. It is useful for storing extra information that can be retrieved later, enhancing the image's utility in various applications. This parameter is optional and is only relevant if save_image
is set to True
.
This output parameter contains a dictionary with the key images
, which holds the generated image(s). The images can be either the primary images provided as input or the fallback images generated by the node. This output is essential for further processing or visualization in the workflow.
This output parameter returns a tuple containing the original images provided as input. If no valid images were provided, it returns None
. This output is useful for debugging and for ensuring that the original input data is preserved and can be accessed later in the workflow.
fallback_width
and fallback_height
parameters are set to appropriate values to generate a meaningful fallback image when the primary image data is unavailable.save_image
parameter wisely to save only the necessary images, as saving every generated image can consume significant disk space.filename_prefix
parameter to organize your saved images effectively, especially when working with batch processes.fallback_width
and fallback_height
are set to 0
.fallback_width
and fallback_height
to generate a fallback image.fallback_width
and fallback_height
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