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Facilitates batch loading of image sequences with stop index control for efficient management in projects.
The JWLoadImageSequenceWithStopIndex node is designed to facilitate the batch loading of image sequences from a specified file path pattern, with the added capability of defining a stop index. This node is particularly useful for AI artists who need to work with a series of images in their projects, allowing them to load multiple images efficiently and in a controlled manner. By specifying the start and stop indices, you can precisely control the range of images to be loaded, making it easier to manage large datasets or specific subsets of images. The node also includes options to handle missing images gracefully, ensuring that your workflow is not interrupted by missing files. This functionality is essential for tasks that require sequential image processing, such as animation, video frame analysis, or any project that involves a series of related images.
This parameter specifies the file path pattern for the images to be loaded. It should include a placeholder for the index, such as image_{i}.png, where {i} will be replaced by the actual index values during execution. This pattern allows the node to generate the correct file paths for the images in the sequence.
The start_index parameter defines the starting index of the image sequence to be loaded. It is an integer value with a minimum of 0. This parameter determines the first image in the sequence, allowing you to skip initial images if needed. The default value is typically set to 0.
The stop_index parameter specifies the ending index of the image sequence to be loaded. It is an integer value with a minimum of 0. This parameter determines the last image in the sequence, providing control over the range of images to be included. The default value is typically set to 0.
The inclusive parameter is a boolean option that determines whether the stop_index should be included in the loaded sequence. It accepts values "true" or "false", with the default being "false". When set to "true", the image at the stop_index will be included in the sequence.
This boolean parameter specifies whether to ignore missing images in the sequence. It accepts values "true" or "false", with the default being "false". When set to "true", the node will skip missing images without raising an error, ensuring that the sequence is loaded without interruption.
The images output parameter returns a tensor containing the loaded image sequence. Each image in the sequence is concatenated along the batch dimension, resulting in a single tensor that can be used for further processing. This output is essential for workflows that require batch processing of images, such as neural network training or image analysis tasks.
path_pattern correctly matches the naming convention of your image files to avoid file not found errors.inclusive parameter to include or exclude the stop_index image based on your specific needs.ignore_missing_images to "true" if you anticipate missing files in your sequence to prevent interruptions in your workflow.start_index and stop_index to load only the necessary portion of your image sequence, optimizing memory usage and processing time.<path>path_pattern is correct and that the images exist at the specified locations. Consider setting ignore_missing_images to "true" to skip missing files.start_index, stop_index, and path_pattern to ensure they are correctly specified. Ensure that the images exist within the specified range.{i} in the path_pattern is not correctly formatted.path_pattern includes a properly formatted placeholder for the index, such as image_{i}.png or image_{i}.jpg.RunComfy is the premier ComfyUI platform, offering ComfyUI online environment and services, along with ComfyUI workflows featuring stunning visuals. RunComfy also provides AI Playground, enabling artists to harness the latest AI tools to create incredible art.