Configuring FiftyOne¶

FiftyOne can be configured in various ways. This guide covers the various options that exist, how to view your current config, and how to customize your config as desired.

Configuration options¶

FiftyOne supports the configuration options described below:

Config field	Environment variable	Default value	Description
`database_admin`	`FIFTYONE_DATABASE_ADMIN`	`True`	Whether the client is allowed to trigger database migrations. See this section for more information.
`database_dir`	`FIFTYONE_DATABASE_DIR`	`~/.fiftyone/var/lib/mongo`	The directory in which to store FiftyOne’s backing database. Only applicable if `database_uri` is not defined.
`database_name`	`FIFTYONE_DATABASE_NAME`	`fiftyone`	A name to use for FiftyOne’s backing database in your MongoDB instance. The database is automatically created if necessary.
`database_uri`	`FIFTYONE_DATABASE_URI`	`None`	A MongoDB URI to specifying a custom MongoDB database to which to connect. See this section for more information.
`database_validation`	`FIFTYONE_DATABASE_VALIDATION`	`True`	Whether to validate the compatibility of database before connecting to it. See this section for more information.
`dataset_zoo_dir`	`FIFTYONE_DATASET_ZOO_DIR`	`~/fiftyone`	The default directory in which to store datasets that are downloaded from the FiftyOne Dataset Zoo.
`dataset_zoo_manifest_paths`	`FIFTYONE_ZOO_MANIFEST_PATHS`	`None`	A list of manifest JSON files specifying additional zoo datasets. See adding datasets to the zoo for more information.
`default_dataset_dir`	`FIFTYONE_DEFAULT_DATASET_DIR`	`~/fiftyone`	The default directory to use when performing FiftyOne operations that require writing dataset contents to disk, such as ingesting datasets via `ingest_labeled_images()`.
`default_ml_backend`	`FIFTYONE_DEFAULT_ML_BACKEND`	`torch`	The default ML backend to use when performing operations such as downloading datasets from the FiftyOne Dataset Zoo that support multiple ML backends. Supported values are `torch` and `tensorflow`. By default, `torch` is used if PyTorch is installed in your Python environment, and `tensorflow` is used if TensorFlow is installed. If no supported backend is detected, this defaults to `None`, and any operation that requires an installed ML backend will raise an informative error message if invoked in this state.
`default_batch_size`	`FIFTYONE_DEFAULT_BATCH_SIZE`	`None`	A default batch size to use when applying models to datasets.
`default_sequence_idx`	`FIFTYONE_DEFAULT_SEQUENCE_IDX`	`%06d`	The default numeric string pattern to use when writing sequential lists of files.
`default_image_ext`	`FIFTYONE_DEFAULT_IMAGE_EXT`	`.jpg`	The default image format to use when writing images to disk.
`default_video_ext`	`FIFTYONE_DEFAULT_VIDEO_EXT`	`.mp4`	The default video format to use when writing videos to disk.
`default_app_port`	`FIFTYONE_DEFAULT_APP_PORT`	`5151`	The default port to use to serve the FiftyOne App.
`default_app_address`	`FIFTYONE_DEFAULT_APP_ADDRESS`	`None`	The default address to use to serve the FiftyOne App. This may be either an IP address or hostname. If it’s a hostname, the App will listen to all IP addresses associated with the name. The default is `None`, which means the App will listen on all available interfaces. See this page for more information.
`desktop_app`	`FIFTYONE_DESKTOP_APP`	`False`	Whether to launch the FiftyOne App in the browser (False) or as a desktop App (True) by default. If True, the FiftyOne Desktop App must be installed.
`do_not_track`	`FIFTYONE_DO_NOT_TRACK`	`False`	Controls whether UUID based import and App usage events are tracked.
`model_zoo_dir`	`FIFTYONE_MODEL_ZOO_DIR`	`~/fiftyone/__models__`	The default directory in which to store models that are downloaded from the FiftyOne Model Zoo.
`model_zoo_manifest_paths`	`FIFTYONE_MODEL_ZOO_MANIFEST_PATHS`	`None`	A list of manifest JSON files specifying additional zoo models. See adding models to the zoo for more information.
`module_path`	`FIFTYONE_MODULE_PATH`	`None`	A list of modules that should be automatically imported whenever FiftyOne is imported. See this page for an example usage.
`requirement_error_level`	`FIFTYONE_REQUIREMENT_ERROR_LEVEL`	`0`	A default error level to use when ensuring/installing requirements such as third-party packages. See loading zoo models for an example usage.
`show_progress_bars`	`FIFTYONE_SHOW_PROGRESS_BARS`	`True`	Controls whether progress bars are printed to the terminal when performing operations such reading/writing large datasets or activiating FiftyOne Brain methods on datasets.
`timezone`	`FIFTYONE_TIMEZONE`	`None`	An optional timzone string. If provided, all datetimes read from FiftyOne datasets will be expressed in this timezone. See this section for more information.

Viewing your config¶

You can print your current FiftyOne config at any time via the Python library and the CLI:

import fiftyone as fo

# Print your current config
print(fo.config)

# Print a specific config field
print(fo.config.default_ml_backend)

{
    "database_admin": true,
    "database_dir": "~/.fiftyone/var/lib/mongo",
    "database_name": "fiftyone",
    "database_uri": null,
    "database_validation": true,
    "dataset_zoo_dir": "~/fiftyone",
    "dataset_zoo_manifest_paths": null,
    "default_app_config_path": "~/.fiftyone/app_config.json",
    "default_app_port": 5151,
    "default_app_address": null,
    "default_batch_size": null,
    "default_dataset_dir": "~/fiftyone",
    "default_image_ext": ".jpg",
    "default_ml_backend": "torch",
    "default_sequence_idx": "%06d",
    "default_video_ext": ".mp4",
    "desktop_app": false,
    "do_not_track": false,
    "model_zoo_dir": "~/fiftyone/__models__",
    "model_zoo_manifest_paths": null,
    "module_path": null,
    "requirement_error_level": 0,
    "show_progress_bars": true,
    "timezone": null
}

torch

# Print your current config
fiftyone config

# Print a specific config field
fiftyone config default_ml_backend

{
    "database_admin": true,
    "database_dir": "~/.fiftyone/var/lib/mongo",
    "database_name": "fiftyone",
    "database_uri": null,
    "database_validation": true,
    "dataset_zoo_dir": "~/fiftyone",
    "dataset_zoo_manifest_paths": null,
    "default_app_config_path": "~/.fiftyone/app_config.json",
    "default_app_port": 5151,
    "default_app_address": null,
    "default_batch_size": null,
    "default_dataset_dir": "~/fiftyone",
    "default_image_ext": ".jpg",
    "default_ml_backend": "torch",
    "default_sequence_idx": "%06d",
    "default_video_ext": ".mp4",
    "desktop_app": false,
    "do_not_track": false,
    "model_zoo_dir": "~/fiftyone/__models__",
    "model_zoo_manifest_paths": null,
    "module_path": null,
    "requirement_error_level": 0,
    "show_progress_bars": true,
    "timezone": null
}

torch

Note

If you have customized your FiftyOne config via any of the methods described below, printing your config is a convenient way to ensure that the changes you made have taken effect as you expected.

Modifying your config¶

You can modify your FiftyOne config in a variety of ways. The following sections describe these options in detail.

Order of precedence¶

The following order of precedence is used to assign values to your FiftyOne config settings at runtime:

Config changes applied at runtime by directly editing fiftyone.config
FIFTYONE_XXX environment variables
Settings in your JSON config (~/.fiftyone/config.json)
The default config values

Editing your JSON config¶

You can permanently customize your FiftyOne config by creating a ~/.fiftyone/config.json file on your machine. The JSON file may contain any desired subset of config fields that you wish to customize.

For example, a valid config JSON file is:

{
    "default_ml_backend": "tensorflow",
    "show_progress_bars": true
}

When fiftyone is imported, any options from your JSON config are applied, as per the order of precedence described above.

Note

You can customize the location from which your JSON config is read by setting the FIFTYONE_CONFIG_PATH environment variable.

Setting environment variables¶

FiftyOne config settings may be customized on a per-session basis by setting the FIFTYONE_XXX environment variable(s) for the desired config settings.

When fiftyone is imported, all config environment variables are applied, as per the order of precedence described above.

For example, you can customize your FiftyOne config in a Terminal session by issuing the following commands prior to launching your Python interpreter:

export FIFTYONE_DEFAULT_ML_BACKEND=tensorflow
export FIFTYONE_SHOW_PROGRESS_BARS=true

Modifying your config in code¶

You can dynamically modify your FiftyOne config at runtime by editing the fiftyone.config object.

Any changes to your FiftyOne config applied via this manner will immediately take effect for all subsequent calls to fiftyone.config during your current session.

import fiftyone as fo

fo.config.default_ml_backend = "tensorflow"
fo.config.show_progress_bars = True

Configuring a MongoDB connection¶

By default, FiftyOne is installed with its own MongoDB database distribution. This database is managed by FiftyOne automatically as a service that runs whenever at least one FiftyOne Python client is alive.

Alternatively, you can configure FiftyOne to connect to your own self-managed MongoDB instance. To do so, simply set the database_uri property of your FiftyOne config to any valid MongoDB connection string URI.

You can achieve this by adding the following entry to your ~/.fiftyone/config.json file:

{
    "database_uri": "mongodb://[username:password@]host[:port]"
}

or you can set the following environment variable:

export FIFTYONE_DATABASE_URI=mongodb://[username:password@]host[:port]

If you are running MongoDB with authentication enabled (the --auth flag), FiftyOne must connect as a root user.

You can create a root user with the Mongo shell as follows:

mongo --shell
> use admin
> db.createUser({user: "username", pwd: passwordPrompt(), roles: ["root"]})

You must also add ?authSource=admin to your database URI:

mongodb://[username:password@]host[:port]/?authSource=admin

Note

Apple Silicon users: MongoDB does not yet provide a native build for Apple Silicon, so you currently must use dataset_uri with a MongoDB distribution that you have installed yourself.

Users have reported success installing MongoDB v4.4 on Apple Silicon as follows:

brew tap mongodb/brew
brew install mongodb-community@4.4

Using a different MongoDB version¶

FiftyOne is designed for and distributed with MongoDB v4.4.

Users have reported success connecting to MongoDB v5 databases, but if you wish to do this, you should set the feature compatibility version to 4.4 to ensure proper function:

mongo --shell
> db.adminCommand({setFeatureCompatibilityVersion: "4.4"})

If you wish to connect FiftyOne to a MongoDB database whose version is not explicitly supported, you will also need to set the database_validation property of your FiftyOne config to False to suppress a runtime error that will otherwise occur.

You can achieve this by adding the following entry to your ~/.fiftyone/config.json file:

{
    "database_validation": false
}

or you can set the following environment variable:

export FIFTYONE_DATABASE_VALIDATION=false

Controlling database migrations¶

If you are working with a shared MongoDB database, you can use database admin privileges to control which clients are allowed to migrate the shared database.

Example custom database usage¶

In order to use a custom MongoDB database with FiftyOne, you must manually start the database before importing FiftyOne. MongoDB provides a variety of options for this, including running the database as a daemon automatically.

In the simplest case, you can just run mongod in one shell:

mkdir -p /path/for/db
mongod --dbpath /path/for/db

Then, in another shell, configure the database URI and launch FiftyOne:

export FIFTYONE_DATABASE_URI=mongodb://localhost

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")
session = fo.launch_app(dataset)

Database migrations¶

New FiftyOne versions occasionally introduce data model changes that require database migrations when you upgrade or downgrade.

Database upgrades happen automatically in two steps:

Database: when you import FiftyOne for the first time using a newer version of the Python package, the database’s version is automatically updated to match your client version
Datasets are lazily migrated to the current database version on a per-dataset basis whenever you load the dataset for the first time using a newer version of the FiftyOne package

Database downgrades must be manually performed. See this page for instructions.

You can use the fiftyone migrate command to view the current versions of your database and datasets:

# View your client version
fiftyone --version

# View your database and dataset versions
fiftyone migrate --info

Restricting migrations¶

You can use the database_admin config setting to control whether a client is allowed to upgrade/downgrade your FiftyOne database. The default is True, which means that upgrades are automatically peformed when you connect to your database with newer Python client versions.

If you set database_admin to False, your database will refuse connections from your FiftyOne client if its version does not match the database’s current version, and datasets will refuse migrations to versions other than the database’s current version.

You can restrict migrations by adding the following entry to your ~/.fiftyone/config.json file:

{
    "database_admin": false
}

or by setting the following environment variable:

export FIFTYONE_DATABASE_ADMIN=false

Note

A common pattern when working with custom/shared MongoDB databases is to adopt a convention that all non-administrators set their database_admin config setting to False to ensure that they cannot trigger automatic database upgrades by connecting to the database with newer Python client versions.

Configuring a timezone¶

By default, FiftyOne loads all datetimes in FiftyOne datasets as naive datetime objects expressed in UTC time.

However, you can configure FiftyOne to express datetimes in a specific timezone by setting the timezone property of your FiftyOne config.

The timezone property can be set to any timezone string supported by pytz.timezone(), or "local" to use your current local timezone.

For example, you could set the FIFTYONE_TIMEZONE environment variable:

# Local timezone
export FIFTYONE_TIMEZONE=local

# US Eastern timezone
export FIFTYONE_TIMEZONE=US/Eastern

Or, you can even dynamically change the timezone while you work in Python:

from datetime import datetime
import fiftyone as fo

sample = fo.Sample(filepath="image.png", created_at=datetime.utcnow())

dataset = fo.Dataset()
dataset.add_sample(sample)

print(sample.created_at)
# 2021-08-24 20:24:09.723021

fo.config.timezone = "local"
dataset.reload()

print(sample.created_at)
# 2021-08-24 16:24:09.723000-04:00

Note

The timezone setting does not affect the internal database representation of datetimes, which are always stored as UTC timestamps.

Configuring the App¶

The FiftyOne App can also be configured in various ways. A new copy of your App config is applied to each Session object that is created when you launch the App. A session’s config can be inspected and modified via the session.config property.

Note

For changes to a session’s config to take effect in the App, you must call session.refresh() or invoke another state-updating action such as session.view = my_view.

The FiftyOne App can be configured in the ways described below:

Config field	Environment variable	Default value	Description
`color_by`	`FIFTYONE_APP_COLOR_BY`	`"field"`	Whether to color labels by their field name (`"field"`), `label` value (`"label"`), or render each instance ID/trajectory index (`"instance"`).
`color_pool`	`FIFTYONE_APP_COLOR_POOL`	See below	A list of browser supported color strings from which the App should draw from when drawing labels (e.g., object bounding boxes).
`colorscale`	`FIFTYONE_APP_COLORSCALE`	`"viridis"`	The colorscale to use when rendering heatmaps in the App. See this section for more details.
`grid_zoom`	`FIFTYONE_APP_GRID_ZOOM`	`5`	The zoom level of the App’s sample grid. Larger values result in larger samples (and ) (thus fewer samples in the grid). Supported values are `{0, 1, ..., 10}`.
`loop_videos`	`FIFTYONE_APP_LOOP_VIDEOS`	`False`	Whether to loop videos by default in the expanded sample view.
`multicolor_keypoints`	`FIFTYONE_APP_MULTICOLOR_KEYPOINTS`	`False`	Whether to independently coloy keypoint points by their index
`notebook_height`	`FIFTYONE_APP_NOTEBOOK_HEIGHT`	`800`	The height of App instances displayed in notebook cells.
`show_confidence`	`FIFTYONE_APP_SHOW_CONFIDENCE`	`True`	Whether to show confidences when rendering labels in the App’s expanded sample view.
`show_index`	`FIFTYONE_APP_SHOW_INDEX`	`True`	Whether to show indexes when rendering labels in the App’s expanded sample view.
`show_label`	`FIFTYONE_APP_SHOW_LABEL`	`True`	Whether to show the label value when rendering detection labels in the App’s expanded sample view.
`show_skeletons	`FIFTYONE_APP_SHOW_SKELETONS`	`True`	Whether to show keypoint skeletons, if available.
`show_tooltip`	`FIFTYONE_APP_SHOW_TOOLTIP`	`True`	Whether to show the tooltip when hovering over labels in the App’s expanded sample view.
`use_frame_number`	`FIFTYONE_APP_USE_FRAME_NUMBER`	`False`	Whether to use the frame number instead of a timestamp in the expanded sample view. Only applicable to video samples.

Viewing your App config¶

You can print your App config at any time via the Python library and the CLI:

import fiftyone as fo

# Print your current App config
print(fo.app_config)

# Print a specific App config field
print(fo.app_config.show_attributes)

{
    "color_by": "field",
    "color_pool": [
        "#ee0000",
        "#ee6600",
        "#993300",
        "#996633",
        "#999900",
        "#009900",
        "#003300",
        "#009999",
        "#000099",
        "#0066ff",
        "#6600ff",
        "#cc33cc",
        "#777799"
    ],
    "colorscale": "viridis",
    "grid_zoom": 5,
    "loop_videos": false,
    "multicolor_keypoints": false,
    "notebook_height": 800,
    "show_confidence": true,
    "show_index": true,
    "show_label": true,
    "show_skeletons": true,
    "show_tooltip": true,
    "use_frame_number": false
}

True

# Print your current App config
fiftyone app config

# Print a specific App config field
fiftyone app config show_attributes

{
    "color_by": "field",
    "color_pool": [
        "#ee0000",
        "#ee6600",
        "#993300",
        "#996633",
        "#999900",
        "#009900",
        "#003300",
        "#009999",
        "#000099",
        "#0066ff",
        "#6600ff",
        "#cc33cc",
        "#777799"
    ],
    "colorscale": "viridis",
    "grid_zoom": 5,
    "loop_videos": false,
    "multicolor_keypoints": false,
    "notebook_height": 800,
    "show_confidence": true,
    "show_index": true,
    "show_label": true,
    "show_skeletons": true,
    "show_tooltip": true,
    "use_frame_number": false
}

True

Note

If you have customized your App config via any of the methods described below, printing your config is a convenient way to ensure that the changes you made have taken effect as you expected.

Modifying your App config¶

You can modify your App config in a variety of ways. The following sections describe these options in detail.

Order of precedence¶

The following order of precedence is used to assign values to your App config settings at runtime:

Config settings of a Session instance in question
App config settings applied at runtime by directly editing fiftyone.app_config
FIFTYONE_APP_XXX environment variables
Settings in your JSON App config (~/.fiftyone/app_config.json)
The default App config values

Launching the App with a custom config¶

You can launch the FiftyOne App with a customized App config on a one-off basis via the following pattern:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")

# Create a custom App config
app_config = fo.AppConfig()
app_config.show_confidence = False
app_config.show_attributes = False

session = fo.launch_app(dataset, config=app_config)

You can also configure a live Session by editing its session.config property and calling session.refresh() to apply the changes:

# Customize the config of a live Session
session.config.show_confidence = True
session.config.show_attributes = True

# Refresh the session to apply the changes
session.refresh()

Editing your JSON App config¶

You can permanently customize your App config by creating a ~/.fiftyone/app_config.json file on your machine. The JSON file may contain any desired subset of config fields that you wish to customize.

For example, a valid App config JSON file is:

{
    "show_confidence": false,
    "show_attributes": false
}

When fiftyone is imported, any options from your JSON App config are applied, as per the order of precedence described above.

Note

You can customize the location from which your JSON App config is read by setting the FIFTYONE_APP_CONFIG_PATH environment variable.

Setting App environment variables¶

App config settings may be customized on a per-session basis by setting the FIFTYONE_APP_XXX environment variable(s) for the desired App config settings.

When fiftyone is imported, all App config environment variables are applied, as per the order of precedence described above.

For example, you can customize your App config in a Terminal session by issuing the following commands prior to launching your Python interpreter:

export FIFTYONE_APP_SHOW_CONFIDENCE=false
export FIFTYONE_APP_SHOW_ATTRIBUTES=false

Modifying your App config in code¶

You can dynamically modify your App config at runtime by editing the fiftyone.app_config object.

Any changes to your App config applied via this manner will immediately take effect for all subsequent calls to fiftyone.app_config during your current session.

import fiftyone as fo

fo.app_config.show_confidence = False
fo.app_config.show_attributes = False