Skip to content

Migrations

This page describes how to migrate between FiftyOne Teams versions, both for admins migrating the core Teams App infrastructure and individual users who need to install a new version of the Teams Python SDK.

Refer to this section to see how to migrate existing datasets from open source to Teams.

Upgrading your Python SDK

Users can upgrade their FiftyOne Teams Python client to the latest version as follows:

pip install --index-url https://${TOKEN}@pypi.fiftyone.ai –-upgrade fiftyone

A specific FiftyOne Teams client version can be installed like so:

pip install --index-url https://${TOKEN}@pypi.fiftyone.ai fiftyone==${VERSION}

Note

You can find your TOKEN by logging into the FiftyOne Teams App and clicking on the account icon in the upper right.

Upgrading your deployment

The basic admin workflow for upgrading a FiftyOne Teams deployment is:

  • Upgrade all automated services and individual user workflows that use the Teams Python SDK to an appropriate SDK version

  • Upgrade your core Teams App infrastructure (via Kubernetes, Docker, etc)

  • Upgrade your database’s version, as described below

Note

Contact your Voxel51 CS Engineer for all relevant upgrade information, including compatible SDK versions, deployment assets, and upgrade assistance.

New FiftyOne Teams versions occasionally introduce data model changes that require database migrations when upgrading your deployment.

Admins can check a deployment’s current version via the Python SDK as shown below:

$ fiftyone migrate --info
FiftyOne Teams version: 0.7.1
FiftyOne compatibility version: 0.15.1
Database version: 0.15.1

...

Note

Individual datasets have versions as well. They are lazily upgraded the first time they are loaded under a new database version. Often there is no migration required, but there could be.

Unlike open source FiftyOne, a Teams database is not automatically upgraded when a user connects to the database with a newer Python client version. Instead, an admin must manually upgrade your Teams database by installing the newest version of the Teams SDK locally, assuming admin privileges, and running the command shown below:

export FIFTYONE_DATABASE_ADMIN=true

# Option 1: update the database version only (datasets lazily migrated on load)
fiftyone migrate

# Option 2: migrate the database and all datasets
fiftyone migrate --all

Note

Once the database is upgraded, all users must upgrade their Python SDK to a compatible version. Any connections from incompatible Python clients will be refused and an informative error message will be displayed.

Downgrading your deployment

Admins can also downgrade their FiftyOne Teams deployment to an older version if necessary.

The steps are the same as when upgrading, except that you’ll need to know the appropriate database version to migrate down to. Each version of Teams corresponds to a version of open source FiftyOne called its “open source compatibility version”, and this versioning system is used to set the database version.

For example, you can downgrade to Teams v0.10 like so:

OS_COMPAT_VERSION=0.18.0  # OS compatibility version for Teams v0.10.0

export FIFTYONE_DATABASE_ADMIN=true
fiftyone migrate --all -v ${OS_COMPAT_VERSION}

Note

The above command must be run with the newer SDK version installed.

Note

Contact your Voxel51 CS engineer if you need to know the open source compatibility version for a particular Teams version that you wish to downgrade to.

Migrating datasets to Teams

Any datasets that you have created via open source FiftyOne can be migrated to your Teams deployment by exporting them in FiftyOneDataset format:

# Open source SDK
import fiftyone as fo

dataset = fo.load_dataset(...)

dataset.export(
    export_dir="/tmp/dataset",
    dataset_type=fo.types.FiftyOneDataset,
    export_media=False,
)

and then re-importing them with the Teams SDK connected to your Teams deployment:

# Teams SDK
import fiftyone as fo

dataset = fo.Dataset.from_dir(
    dataset_dir="/tmp/dataset",
    dataset_type=fo.types.FiftyOneDataset,
    persistent=True,
)

Note that you’ll need to update any local filepaths to cloud paths in order to use the dataset in Teams.

If you need to upload the local media to the cloud, the Teams SDK provides a builtin utility for this:

import fiftyone.core.storage as fos

fos.upload_media(
    dataset,
    "s3://path/for/media",
    update_filepaths=True,
    progress=True,
)

Note

By default, the above method only uploads the media in the filepath field of your samples. If your dataset contains other media fields (e.g. thumbnails, segmentations, or heatmaps) simply run the above command multiple times, using the media_field argument to specify the appropriate fields to upload.

If any media fields use the same filenames as other fields, be sure to provide different remote_dir paths each time you call the above method to avoid overwriting existing media.

If the files already exist in cloud buckets, you can manually update the filepaths on the dataset:

cloud_paths = []
for filepath in dataset.values("filepath"):
    cloud_path = get_cloud_path(filepath)  # your function
    cloud_paths.append(cloud_path)

dataset.set_values("filepath", cloud_paths)

When you’re finished, delete the local export of the dataset:

shutil.rmtree("/tmp/dataset")