ComfyUI Node: Duplicate Image Batch 🎥🅥🅗🅢

Duplicate Image Batch 🎥🅥🅗🅢:

The VHS_DuplicateImages node is designed to help you efficiently duplicate a batch of images within your AI art projects. This node is particularly useful when you need to create multiple copies of an image batch for further processing or experimentation. By leveraging this node, you can easily scale up the number of images in your dataset, which can be beneficial for tasks such as data augmentation, testing different model configurations, or generating variations of a particular image set. The node ensures that the duplicated images are concatenated seamlessly, maintaining the integrity and structure of the original batch.

Duplicate Image Batch 🎥🅥🅗🅢 Input Parameters:

images

This parameter accepts a batch of images that you want to duplicate. The images should be provided in a tensor format, which is a common data structure used in AI and machine learning for handling multi-dimensional arrays. The input images will be the source from which duplicates are created.

multiply_by

This integer parameter determines the number of times the input image batch will be duplicated. The default value is 1, meaning no duplication will occur unless this value is increased. The minimum value is 1, and there is no specified maximum value, but it should be within the limits of your system's memory capacity. Adjusting this parameter allows you to control the scale of duplication, with higher values resulting in more copies of the image batch.

Duplicate Image Batch 🎥🅥🅗🅢 Output Parameters:

IMAGE

This output parameter provides the duplicated batch of images. The output is a tensor containing the original images concatenated with their duplicates, based on the multiply_by parameter. This allows you to use the expanded image set for further processing or analysis in your AI art projects.

count

This integer output indicates the total number of images in the duplicated batch. It reflects the original number of images multiplied by the multiply_by parameter, giving you a clear understanding of the size of the resulting image set.

Duplicate Image Batch 🎥🅥🅗🅢 Usage Tips:

• To create a large dataset for training or testing, set the multiply_by parameter to a higher value, ensuring you have enough memory to handle the increased data size.
• Use this node in combination with other image processing nodes to apply different transformations to each duplicated batch, enhancing the diversity of your dataset.
• When experimenting with different model configurations, duplicate your image batch to test various settings without altering the original data.

Duplicate Image Batch 🎥🅥🅗🅢 Common Errors and Solutions:

RuntimeError: CUDA out of memory

• Explanation: This error occurs when the system's GPU memory is insufficient to handle the duplicated image batch.
• Solution: Reduce the multiply_by parameter value or process the images in smaller batches to fit within the available memory.

TypeError: Expected input to be a tensor

• Explanation: This error indicates that the input provided to the images parameter is not in the expected tensor format.
• Solution: Ensure that the input images are converted to a tensor format before passing them to the node.

ValueError: Invalid value for multiply_by

• Explanation: This error occurs when the multiply_by parameter is set to a value less than 1 or a non-integer.
• Solution: Set the multiply_by parameter to an integer value of 1 or higher.