[FEATURE] injest fiftyone datasets

🚨🚨 Feature Request

• Related to an existing Issue
• A new implementation (Improvement, Extension)

Is your feature request related to a problem?

My problem is being able to ingest fiftyone datasets into deeplake

• exporting would also be an interesting addition

If your feature will improve HUB

Fiftyone is a common dataset import and export tool, integration with deeplake would make such operations easy, and would mean that we do not have to implement such operations from scratch.

Description of the possible solution

import deeplake
import fiftyone

# ideally this would be able to detect the various different types and labels and be able to import these accordingly.
dataset = fiftyone.load_dataset('my_dataset')
deeplake.ingest_51('deeplake_data/my_dataset', dataset)

An alternative solution to the problem can look like

Ingest steps could be written manually. (Fiftyone doesn’t enforce much structure on the datasets so I am not sure if the original ingest function even has a distinct solution, maybe some basic structure would be required).

Teachability, Documentation, Adoption, Migration Strategy Needs discussion first

[istranic]

Got it. Thanks @nmichlo!

[nmichlo]

@istranic no problem, glad to help!

Ideally in the long run I personally would prefer not to use fiftyone, and ingest/export datasets directly.

However, I think there might be merit for both?

• ingesting directly from fiftyone might keep additional information that would otherwise be discarded if there is first an export and then import step.
• this would also allow easier migration to deeplake