The correct option is Cloud Storage because it is a highly durable and elastically scalable object store for unstructured data such as image files and it integrates seamlessly with Vertex AI training. It can comfortably hold a single repository of about 32 TB.

This service offers bucket level durability and availability with regional or multi regional placement for resilience. It provides simple object access using gs paths that Vertex AI training jobs can read directly. It also supports lifecycle management, versioning and granular access control which are all valuable when managing large image datasets for machine learning.

Vertex AI Model Registry is for tracking models and their versions and metadata rather than storing raw training datasets. It does not function as a large scale object repository for images.

BigQuery is a data warehouse for analytics on structured and semi structured data in tables. It is not intended for storing large unstructured objects such as image files and would not be used as an object store for this use case.

Cloud SQL is a managed relational database for transactional workloads. It is not appropriate for storing terabytes of image objects and is not an object storage service, which makes it inefficient and costly for this requirement.

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