Directory asset is the correct option for registering a publicly available collection of image files because it allows you to point to and manage multiple files together as a single logical dataset.

A Directory asset represents a folder or prefix of files and so it is efficient for organizing many images for training or labeling. It can reference a public URL or a cloud storage prefix and preserves the grouping of files so you can import or process them together instead of handling each image individually.

Tabular asset is intended for structured row and column data like CSV files or tables and not for collections of image files, so it does not fit this use case.

Stream recording asset is meant for time series or streaming media recordings and it does not provide a natural way to group static image files for machine learning.

Single file asset points to one file and is suitable only when the entire dataset is contained in a single archive or file, so it is not efficient for a directory of many separate image files.

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