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_dir	FIFTYONE_DATABASE_DIR	~/.fiftyone/var/lib/mongo	The directory in which to store FiftyOne’s backing database.
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.
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.
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.
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.
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.

Viewing your config

You can print your current FiftyOne config (including any customizations as described in the next section) at any time via the Python library and the CLI.

Python

CLI

import fiftyone as fo

# Print your current config
print(fo.config)

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

{
    "database_dir": "~/.fiftyone/var/lib/mongo",
    "dataset_zoo_dir": "~/fiftyone",
    "dataset_zoo_manifest_paths": null,
    "default_app_config_path": "~/.fiftyone/app_config.json",
    "default_app_port": 5151,
    "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,
    "requirement_error_level": 0,
    "show_progress_bars": true
}

torch

# Print your current config
fiftyone config

# Print a specific config field
fiftyone config default_ml_backend

{
    "database_dir": "~/.fiftyone/var/lib/mongo",
    "dataset_zoo_dir": "~/fiftyone",
    "dataset_zoo_manifest_paths": null,
    "default_app_config_path": "~/.fiftyone/app_config.json",
    "default_app_port": 5151,
    "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,
    "requirement_error_level": 0,
    "show_progress_bars": true
}

torch

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:

1. Config settings applied at runtime via fiftyone.core.config.set_config_settings()

2. FIFTYONE_XXX environment variables

3. Settings in your JSON config (~/.fiftyone/config.json)

4. The default config values described in the table above

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 via the fiftyone.core.config.set_config_settings() method, which accepts keyword arguments of the form (field name, field value) for all available config fields.

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

For example, you can customize your FiftyOne config at runtime as follows:

import fiftyone.core.config as foc

foc.set_config_settings(
    default_ml_backend="tensorflow",
    show_progress_bars=True,
)

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_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).
notebook_height	FIFTYONE_APP_NOTEBOOK_HEIGHT	800	The default height of App instances displayed in notebook cells.
show_attributes	FIFTYONE_APP_SHOW_ATTRIBUTES	False	Whether to show attributes when rendering labels in the App’s expanded sample view.
show_confidence	FIFTYONE_APP_SHOW_CONFIDENCE	True	Whether to show confidences when rendering labels in the App’s expanded sample view.
show_tooltip	FIFTYONE_APP_SHOW_TOOLTIP	True	Whether to show the tooltip when hovering over labels in the App’s expanded sample view.

Viewing your App config

You can print your App config (including any customizations as described in the next section) at any time via the Python library and the CLI.

Python

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_pool": [
        "#ee0000",
        "#999900",
        "#009900",
        "#003300",
        "#009999",
        "#000099",
        "#6600ff",
        "#ee6600",
        "#993300",
        "#996633",
        "#0066ff",
        "#cc33cc",
        "#777799"
    ],
    "notebook_height": 800,
    "show_confidence": true,
    "show_attributes": true
}

True

# Print your current App config
fiftyone app config

# Print a specific App config field
fiftyone app config show_attributes

{
    "color_pool": [
        "#ee0000",
        "#999900",
        "#009900",
        "#003300",
        "#009999",
        "#000099",
        "#6600ff",
        "#ee6600",
        "#993300",
        "#996633",
        "#0066ff",
        "#cc33cc",
        "#777799"
    ],
    "notebook_height": 800,
    "show_confidence": true,
    "show_attributes": true
}

True

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:

1. Config settings of a Session instance in question

2. App config settings applied at runtime via fiftyone.core.config.set_app_config_settings()

3. FIFTYONE_APP_XXX environment variables

4. Settings in your JSON App config (~/.fiftyone/app_config.json)

5. The default App config values described in the table above

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

FiftyOne 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 via the fiftyone.core.config.set_app_config_settings() method, which accepts keyword arguments of the form (field name, field value) for all available config fields.

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

For example, you can customize your App config at runtime as follows:

import fiftyone.core.config as foc

foc.set_app_config_settings(show_confidence=False, show_attributes=False)