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
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 downloading datasets from the FiftyOne Dataset Zoo or 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_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.
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(co.config.default_ml_backend)

{
    "default_dataset_dir": "~/fiftyone",
    "default_ml_backend": "torch",
    "default_sequence_idx": "%08d",
    "default_image_ext": ".jpg",
    "default_video_ext": ".mp4",
    "show_progress_bars": true
}

torch

# Print your current config
fiftyone config

# Print a specific config field
fiftyone config default_ml_backend

{
    "default_dataset_dir": "~/fiftyone",
    "default_ml_backend": "torch",
    "default_sequence_idx": "%08d",
    "default_image_ext": ".jpg",
    "default_video_ext": ".mp4",
    "show_progress_bars": true
}

torch

Modifying your config

You can modify your FiftyOne config in any of the ways listed below.

The order of precedence for config modifications is as follows:

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

2. FIFTYONE_XXX environment variables

3. Settings in your JSON config at ~/.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",
  "default_sequence_idx": "%08d",
  "default_image_ext": ".png",
  "default_video_ext": ".mp4",
  "show_progress_bars": true
}

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

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_DEFAULT_SEQUENCE_IDX='%08d'
export FIFTYONE_DEFAULT_IMAGE_EXT='.png'
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",
    default_sequence_idx="%08d",
    default_image_ext=".png",
    default_video_ext=".mp4",
    show_progress_bars=True,
)