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.

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:

Config settings applied at runtime via fiftyone.core.config.set_config_settings()
FIFTYONE_XXX environment variables
Settings in your JSON config (~/.fiftyone/config.json)
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).
`default_grid_zoom`	`FIFTYONE_APP_DEFAULT_GRID_ZOOM`	`5`	The default 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}`.
`notebook_height`	`FIFTYONE_APP_NOTEBOOK_HEIGHT`	`800`	The 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.

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"
    ],
    "default_grid_zoom": 5,
    "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"
    ],
    "default_grid_zoom": 5,
    "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:

Config settings of a Session instance in question
App config settings applied at runtime via fiftyone.core.config.set_app_config_settings()
FIFTYONE_APP_XXX environment variables
Settings in your JSON App config (~/.fiftyone/app_config.json)
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)

Configuring FiftyOne¶

Configuration options¶

Viewing your config¶

Modifying your config¶

Order of precedence¶

Editing your JSON config¶

Setting environment variables¶

Modifying your config in code¶

Configuring the App¶

Viewing your App config¶

Modifying your App config¶

Order of precedence¶

Launching the App with a custom config¶

Editing your JSON App config¶

Setting App environment variables¶

Modifying your App config in code¶

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