fiftyone.utils.ultralytics

Utilities for working with Ultralytics.

Copyright 2017-2024, Voxel51, Inc.

voxel51.com

Functions:

convert_ultralytics_model(model)	Converts the given Ultralytics model into a FiftyOne model.
to_detections(results[, confidence_thresh])	Converts ultralytics.YOLO boxes to FiftyOne format.
to_instances(results[, confidence_thresh])	Converts ultralytics.YOLO instance segmentations to FiftyOne format.
obb_to_polylines(results[, …])	Converts ultralytics.YOLO instance segmentations to FiftyOne format.
to_polylines(results[, confidence_thresh, …])	Converts ultralytics.YOLO instance segmentations to FiftyOne format.
to_keypoints(results[, confidence_thresh])	Converts ultralytics.YOLO keypoints to FiftyOne format.

Classes:

FiftyOneYOLOModelConfig(d)	Configuration for a FiftyOneYOLOModel.
FiftyOneYOLOModel(config)	FiftyOne wrapper around an ultralytics.YOLO model.
FiftyOneYOLODetectionModelConfig(d)
FiftyOneYOLODetectionModel(config)	FiftyOne wrapper around an Ultralytics YOLO detection model.
FiftyOneRTDETRModelConfig(d)	Configuration for a FiftyOneRTDETRModel.
FiftyOneRTDETRModel(config)	FiftyOne wrapper around an ultralytics.RTDETR model.
FiftyOneYOLOOBBModelConfig(d)
FiftyOneYOLOOBBModel(config)	FiftyOne wrapper around an Ultralytics YOLO OBB detection model.
FiftyOneYOLOSegmentationModelConfig(d)
FiftyOneYOLOSegmentationModel(config)	FiftyOne wrapper around an Ultralytics YOLO segmentation model.
FiftyOneYOLOPoseModelConfig(d)
FiftyOneYOLOPoseModel(config)	FiftyOne wrapper around an Ultralytics YOLO pose model.
FiftyOneYOLOClassificationModelConfig(d)
FiftyOneYOLOClassificationModel(config)	FiftyOne wrapper around an Ultralytics YOLO classification model.
UltralyticsOutputProcessor([classes])	Converts Ultralytics PyTorch Hub model outputs to FiftyOne format.

fiftyone.utils.ultralytics.convert_ultralytics_model(model)

Converts the given Ultralytics model into a FiftyOne model.

Parameters

model – an ultralytics.YOLO model

Returns

a fiftyone.core.models.Model

Raises

ValueError – if the model could not be converted

fiftyone.utils.ultralytics.to_detections(results, confidence_thresh=None)

Converts ultralytics.YOLO boxes to FiftyOne format.

Parameters

• results – a single or list of ultralytics.engine.results.Results

• confidence_thresh (None) – a confidence threshold to filter boxes

Returns

a single or list of fiftyone.core.labels.Detections

fiftyone.utils.ultralytics.to_instances(results, confidence_thresh=None)

Converts ultralytics.YOLO instance segmentations to FiftyOne format.

Parameters

• results – a single or list of ultralytics.engine.results.Results

• confidence_thresh (None) – a confidence threshold to filter boxes

Returns

a single or list of fiftyone.core.labels.Detections

fiftyone.utils.ultralytics.obb_to_polylines(results, confidence_thresh=None, filled=False)

Converts ultralytics.YOLO instance segmentations to FiftyOne format.

Parameters

• results – a single or list of ultralytics.engine.results.Results

• confidence_thresh (None) – a confidence threshold to filter boxes

• filled (False) – whether the polyline should be filled

Returns

a single or list of fiftyone.core.labels.PolyLines

fiftyone.utils.ultralytics.to_polylines(results, confidence_thresh=None, tolerance=2, filled=True)

Converts ultralytics.YOLO instance segmentations to FiftyOne format.

Parameters

• results – a single or list of ultralytics.engine.results.Results

• confidence_thresh (None) – a confidence threshold to filter boxes

• tolerance (2) – a tolerance, in pixels, when generating approximate polylines for instance masks. Typical values are 1-3 pixels

• filled (True) – whether the polyline should be filled

Returns

a single or list of fiftyone.core.labels.Polylines

fiftyone.utils.ultralytics.to_keypoints(results, confidence_thresh=None)

Converts ultralytics.YOLO keypoints to FiftyOne format.

Parameters

• results – a single or list of ultralytics.engine.results.Results

• confidence_thresh (None) – a confidence threshold to filter keypoints

Returns

a single or list of fiftyone.core.labels.Keypoints

class fiftyone.utils.ultralytics.FiftyOneYOLOModelConfig(d)

Bases: fiftyone.core.config.Config, fiftyone.zoo.models.HasZooModel

Configuration for a FiftyOneYOLOModel.

Parameters

• model (None) – an ultralytics.YOLO model to use

• model_name (None) – the name of an ultralytics.YOLO model to load

• model_path (None) – the path to an ultralytics.YOLO model checkpoint

• classes (None) – an optional list of classes

Methods:

attributes()	Returns a list of class attributes to be serialized.
builder()	Returns a ConfigBuilder instance for this class.
copy()	Returns a deep copy of the object.
custom_attributes([dynamic, private])	Returns a customizable list of class attributes.
default()	Returns the default config instance.
download_model_if_necessary()	Downloads the published model specified by the config, if necessary.
from_dict(d)	Constructs a Config object from a JSON dictionary.
from_json(path, *args, **kwargs)	Constructs a Serializable object from a JSON file.
from_kwargs(**kwargs)	Constructs a Config object from keyword arguments.
from_str(s, *args, **kwargs)	Constructs a Serializable object from a JSON string.
get_class_name()	Returns the fully-qualified class name string of this object.
init(d)	Initializes the published model config.
load_default()	Loads the default config instance from file.
parse_array(d, key[, default])	Parses a raw array attribute.
parse_bool(d, key[, default])	Parses a boolean value.
parse_categorical(d, key, choices[, default])	Parses a categorical JSON field, which must take a value from among the given choices.
parse_dict(d, key[, default])	Parses a dictionary attribute.
parse_int(d, key[, default])	Parses an integer attribute.
parse_mutually_exclusive_fields(fields)	Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.
parse_number(d, key[, default])	Parses a number attribute.
parse_object(d, key, cls[, default])	Parses an object attribute.
parse_object_array(d, key, cls[, default])	Parses an array of objects.
parse_object_dict(d, key, cls[, default])	Parses a dictionary whose values are objects.
parse_path(d, key[, default])	Parses a path attribute.
parse_raw(d, key[, default])	Parses a raw (arbitrary) JSON field.
parse_string(d, key[, default])	Parses a string attribute.
serialize([reflective])	Serializes the object into a dictionary.
to_str([pretty_print])	Returns a string representation of this object.
validate_all_or_nothing_fields(fields)	Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.
write_json(path[, pretty_print])	Serializes the object and writes it to disk.

attributes()

Returns a list of class attributes to be serialized.

This method is called internally by serialize() to determine the class attributes to serialize.

Subclasses can override this method, but, by default, all attributes in vars(self) are returned, minus private attributes, i.e., those starting with “_”. The order of the attributes in this list is preserved when serializing objects, so a common pattern is for subclasses to override this method if they want their JSON files to be organized in a particular way.

Returns

a list of class attributes to be serialized

classmethod builder()

Returns a ConfigBuilder instance for this class.

copy()

Returns a deep copy of the object.

Returns

a Serializable instance

custom_attributes(dynamic=False, private=False)

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

• dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False

• private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod default()

Returns the default config instance.

By default, this method instantiates the class from an empty dictionary, which will only succeed if all attributes are optional. Otherwise, subclasses should override this method to provide the desired default configuration.

download_model_if_necessary()

Downloads the published model specified by the config, if necessary.

After this method is called, the model_path attribute will always contain the path to the model on disk.

classmethod from_dict(d)

Constructs a Config object from a JSON dictionary.

Config subclass constructors accept JSON dictionaries, so this method simply passes the dictionary to cls().

Parameters

d – a dict of fields expected by cls

Returns

an instance of cls

classmethod from_json(path, *args, **kwargs)

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

• path – the path to the JSON file on disk

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_kwargs(**kwargs)

Constructs a Config object from keyword arguments.

Parameters

**kwargs – keyword arguments that define the fields expected by cls

Returns

an instance of cls

classmethod from_str(s, *args, **kwargs)

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

• s – a JSON string representation of a Serializable object

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()

Returns the fully-qualified class name string of this object.

init(d)

Initializes the published model config.

This method should be called by ModelConfig.__init__(), and it performs the following tasks:

• Parses the model_name and model_path parameters

• Populates any default parameters in the provided ModelConfig dict

Parameters

d – a ModelConfig dict

Returns

a ModelConfig dict with any default parameters populated

classmethod load_default()

Loads the default config instance from file.

Subclasses must implement this method if they intend to support default instances.

static parse_array(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw array attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default list to return if key is not present

Returns

a list of raw (untouched) values

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_bool(d, key, default=<eta.core.config.NoDefault object>)

Parses a boolean value.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default bool to return if key is not present

Returns

True/False

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_categorical(d, key, choices, default=<eta.core.config.NoDefault object>)

Parses a categorical JSON field, which must take a value from among the given choices.

Parameters

• d – a JSON dictionary

• key – the key to parse

• choices – either an iterable of possible values or an enum-like class whose attributes define the possible values

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field, which is equal to a value from choices

Raises

ConfigError – if the key was present in the dictionary but its value was not an allowed choice, or if no default value was provided and the key was not found in the dictionary

static parse_dict(d, key, default=<eta.core.config.NoDefault object>)

Parses a dictionary attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default dict to return if key is not present

Returns

a dictionary

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_int(d, key, default=<eta.core.config.NoDefault object>)

Parses an integer attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default integer value to return if key is not present

Returns

an int

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_mutually_exclusive_fields(fields)

Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Returns

the (field, value) that was set

Raises

ConfigError – if zero or more than one truthy value was found

static parse_number(d, key, default=<eta.core.config.NoDefault object>)

Parses a number attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default numeric value to return if key is not present

Returns

a number (e.g. int, float)

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an object attribute.

The value of d[key] can be either an instance of cls or a serialized dict from an instance of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of d[key]

• default – a default cls instance to return if key is not present

Returns

an instance of cls

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_array(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an array of objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the elements of list d[key]

• default – the default list to return if key is not present

Returns

a list of cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_dict(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses a dictionary whose values are objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the values of dictionary d[key]

• default – the default dict of cls instances to return if key is not present

Returns

a dictionary whose values are cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_path(d, key, default=<eta.core.config.NoDefault object>)

Parses a path attribute.

The path is converted to an absolute path if necessary via os.path.abspath(os.path.expanduser(value)).

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a path string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_raw(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw (arbitrary) JSON field.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field

Raises

ConfigError – if no default value was provided and the key was not found in the dictionary

static parse_string(d, key, default=<eta.core.config.NoDefault object>)

Parses a string attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

serialize(reflective=False)

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters

reflective – whether to include reflective attributes when serializing the object. By default, this is False

Returns

a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)

Returns a string representation of this object.

Parameters

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True

• **kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

static validate_all_or_nothing_fields(fields)

Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Raises

ConfigError – if some values are truth and some are not

write_json(path, pretty_print=False, **kwargs)

Serializes the object and writes it to disk.

Parameters

• path – the output path

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False

• **kwargs – optional keyword arguments for self.serialize()

class fiftyone.utils.ultralytics.FiftyOneYOLOModel(config)

Bases: fiftyone.core.models.Model

FiftyOne wrapper around an ultralytics.YOLO model.

Parameters

config – a FiftyOneYOLOModelConfig

Attributes:

media_type	The media type processed by the model.
ragged_batches	True/False whether transforms() may return tensors of different sizes.
transforms	The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.
preprocess	Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).
can_embed_prompts	Whether this instance can generate prompt embeddings.
has_embeddings	Whether this instance can generate embeddings.
has_logits	Whether this instance can generate logits for its predictions.

Methods:

predict(arg)	Performs prediction on the given data.
from_config(config)	Instantiates a Configurable class from a <cls>Config instance.
from_dict(d)	Instantiates a Configurable class from a <cls>Config dict.
from_json(json_path)	Instantiates a Configurable class from a <cls>Config JSON file.
from_kwargs(**kwargs)	Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.
parse(class_name[, module_name])	Parses a Configurable subclass name string.
predict_all(args)	Performs prediction on the given iterable of data.
validate(config)	Validates that the given config is an instance of <cls>Config.

property media_type

The media type processed by the model.

Supported values are “image” and “video”.

property ragged_batches

True/False whether transforms() may return tensors of different sizes. If True, then passing ragged lists of data to predict_all() is not allowed.

property transforms

The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

property preprocess

Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).

predict(arg)

Performs prediction on the given data.

Image models should support, at minimum, processing arg values that are uint8 numpy arrays (HWC).

Video models should support, at minimum, processing arg values that are eta.core.video.VideoReader instances.

Parameters

arg – the data

Returns

a fiftyone.core.labels.Label instance or dict of fiftyone.core.labels.Label instances containing the predictions

property can_embed_prompts

Whether this instance can generate prompt embeddings.

This method returns False by default. Methods that can generate prompt embeddings will override this via implementing the PromptMixin interface.

classmethod from_config(config)

Instantiates a Configurable class from a <cls>Config instance.

classmethod from_dict(d)

Instantiates a Configurable class from a <cls>Config dict.

Parameters

d – a dict to construct a <cls>Config

Returns

an instance of cls

classmethod from_json(json_path)

Instantiates a Configurable class from a <cls>Config JSON file.

Parameters

json_path – path to a JSON file for type <cls>Config

Returns

an instance of cls

classmethod from_kwargs(**kwargs)

Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.

Parameters

**kwargs – keyword arguments that define the fields of a <cls>Config dict

Returns

an instance of cls

property has_embeddings

Whether this instance can generate embeddings.

This method returns False by default. Methods that can generate embeddings will override this via implementing the EmbeddingsMixin interface.

property has_logits

Whether this instance can generate logits for its predictions.

This method returns False by default. Methods that can generate logits will override this via implementing the LogitsMixin interface.

static parse(class_name, module_name=None)

Parses a Configurable subclass name string.

Assumes both the Configurable class and the Config class are defined in the same module. The module containing the classes will be loaded if necessary.

Parameters

• class_name – a string containing the name of the Configurable class, e.g. “ClassName”, or a fully-qualified class name, e.g. “eta.core.config.ClassName”

• module_name – a string containing the fully-qualified module name, e.g. “eta.core.config”, or None if class_name includes the module name. Set module_name = __name__ to load a class from the calling module

Returns

the Configurable class config_cls: the Config class associated with cls

Return type

cls

predict_all(args)

Performs prediction on the given iterable of data.

Image models should support, at minimum, processing args values that are either lists of uint8 numpy arrays (HWC) or numpy array tensors (NHWC).

Video models should support, at minimum, processing args values that are lists of eta.core.video.VideoReader instances.

Subclasses can override this method to increase efficiency, but, by default, this method simply iterates over the data and applies predict() to each.

Parameters

args – an iterable of data

Returns

a list of fiftyone.core.labels.Label instances or a list of dicts of fiftyone.core.labels.Label instances containing the predictions

classmethod validate(config)

Validates that the given config is an instance of <cls>Config.

Raises

ConfigurableError – if config is not an instance of <cls>Config

class fiftyone.utils.ultralytics.FiftyOneYOLODetectionModelConfig(d)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModelConfig

Methods:

attributes()	Returns a list of class attributes to be serialized.
builder()	Returns a ConfigBuilder instance for this class.
copy()	Returns a deep copy of the object.
custom_attributes([dynamic, private])	Returns a customizable list of class attributes.
default()	Returns the default config instance.
download_model_if_necessary()	Downloads the published model specified by the config, if necessary.
from_dict(d)	Constructs a Config object from a JSON dictionary.
from_json(path, *args, **kwargs)	Constructs a Serializable object from a JSON file.
from_kwargs(**kwargs)	Constructs a Config object from keyword arguments.
from_str(s, *args, **kwargs)	Constructs a Serializable object from a JSON string.
get_class_name()	Returns the fully-qualified class name string of this object.
init(d)	Initializes the published model config.
load_default()	Loads the default config instance from file.
parse_array(d, key[, default])	Parses a raw array attribute.
parse_bool(d, key[, default])	Parses a boolean value.
parse_categorical(d, key, choices[, default])	Parses a categorical JSON field, which must take a value from among the given choices.
parse_dict(d, key[, default])	Parses a dictionary attribute.
parse_int(d, key[, default])	Parses an integer attribute.
parse_mutually_exclusive_fields(fields)	Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.
parse_number(d, key[, default])	Parses a number attribute.
parse_object(d, key, cls[, default])	Parses an object attribute.
parse_object_array(d, key, cls[, default])	Parses an array of objects.
parse_object_dict(d, key, cls[, default])	Parses a dictionary whose values are objects.
parse_path(d, key[, default])	Parses a path attribute.
parse_raw(d, key[, default])	Parses a raw (arbitrary) JSON field.
parse_string(d, key[, default])	Parses a string attribute.
serialize([reflective])	Serializes the object into a dictionary.
to_str([pretty_print])	Returns a string representation of this object.
validate_all_or_nothing_fields(fields)	Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.
write_json(path[, pretty_print])	Serializes the object and writes it to disk.

attributes()

Returns a list of class attributes to be serialized.

This method is called internally by serialize() to determine the class attributes to serialize.

Subclasses can override this method, but, by default, all attributes in vars(self) are returned, minus private attributes, i.e., those starting with “_”. The order of the attributes in this list is preserved when serializing objects, so a common pattern is for subclasses to override this method if they want their JSON files to be organized in a particular way.

Returns

a list of class attributes to be serialized

classmethod builder()

Returns a ConfigBuilder instance for this class.

copy()

Returns a deep copy of the object.

Returns

a Serializable instance

custom_attributes(dynamic=False, private=False)

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

• dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False

• private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod default()

Returns the default config instance.

By default, this method instantiates the class from an empty dictionary, which will only succeed if all attributes are optional. Otherwise, subclasses should override this method to provide the desired default configuration.

download_model_if_necessary()

Downloads the published model specified by the config, if necessary.

After this method is called, the model_path attribute will always contain the path to the model on disk.

classmethod from_dict(d)

Constructs a Config object from a JSON dictionary.

Config subclass constructors accept JSON dictionaries, so this method simply passes the dictionary to cls().

Parameters

d – a dict of fields expected by cls

Returns

an instance of cls

classmethod from_json(path, *args, **kwargs)

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

• path – the path to the JSON file on disk

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_kwargs(**kwargs)

Constructs a Config object from keyword arguments.

Parameters

**kwargs – keyword arguments that define the fields expected by cls

Returns

an instance of cls

classmethod from_str(s, *args, **kwargs)

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

• s – a JSON string representation of a Serializable object

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()

Returns the fully-qualified class name string of this object.

init(d)

Initializes the published model config.

This method should be called by ModelConfig.__init__(), and it performs the following tasks:

• Parses the model_name and model_path parameters

• Populates any default parameters in the provided ModelConfig dict

Parameters

d – a ModelConfig dict

Returns

a ModelConfig dict with any default parameters populated

classmethod load_default()

Loads the default config instance from file.

Subclasses must implement this method if they intend to support default instances.

static parse_array(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw array attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default list to return if key is not present

Returns

a list of raw (untouched) values

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_bool(d, key, default=<eta.core.config.NoDefault object>)

Parses a boolean value.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default bool to return if key is not present

Returns

True/False

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_categorical(d, key, choices, default=<eta.core.config.NoDefault object>)

Parses a categorical JSON field, which must take a value from among the given choices.

Parameters

• d – a JSON dictionary

• key – the key to parse

• choices – either an iterable of possible values or an enum-like class whose attributes define the possible values

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field, which is equal to a value from choices

Raises

ConfigError – if the key was present in the dictionary but its value was not an allowed choice, or if no default value was provided and the key was not found in the dictionary

static parse_dict(d, key, default=<eta.core.config.NoDefault object>)

Parses a dictionary attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default dict to return if key is not present

Returns

a dictionary

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_int(d, key, default=<eta.core.config.NoDefault object>)

Parses an integer attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default integer value to return if key is not present

Returns

an int

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_mutually_exclusive_fields(fields)

Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Returns

the (field, value) that was set

Raises

ConfigError – if zero or more than one truthy value was found

static parse_number(d, key, default=<eta.core.config.NoDefault object>)

Parses a number attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default numeric value to return if key is not present

Returns

a number (e.g. int, float)

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an object attribute.

The value of d[key] can be either an instance of cls or a serialized dict from an instance of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of d[key]

• default – a default cls instance to return if key is not present

Returns

an instance of cls

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_array(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an array of objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the elements of list d[key]

• default – the default list to return if key is not present

Returns

a list of cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_dict(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses a dictionary whose values are objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the values of dictionary d[key]

• default – the default dict of cls instances to return if key is not present

Returns

a dictionary whose values are cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_path(d, key, default=<eta.core.config.NoDefault object>)

Parses a path attribute.

The path is converted to an absolute path if necessary via os.path.abspath(os.path.expanduser(value)).

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a path string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_raw(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw (arbitrary) JSON field.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field

Raises

ConfigError – if no default value was provided and the key was not found in the dictionary

static parse_string(d, key, default=<eta.core.config.NoDefault object>)

Parses a string attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

serialize(reflective=False)

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters

reflective – whether to include reflective attributes when serializing the object. By default, this is False

Returns

a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)

Returns a string representation of this object.

Parameters

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True

• **kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

static validate_all_or_nothing_fields(fields)

Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Raises

ConfigError – if some values are truth and some are not

write_json(path, pretty_print=False, **kwargs)

Serializes the object and writes it to disk.

Parameters

• path – the output path

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False

• **kwargs – optional keyword arguments for self.serialize()

class fiftyone.utils.ultralytics.FiftyOneYOLODetectionModel(config)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModel

FiftyOne wrapper around an Ultralytics YOLO detection model.

Parameters

config – a FiftyOneYOLODetectionModelConfig

Methods:

predict_all(args)	Performs prediction on the given iterable of data.
from_config(config)	Instantiates a Configurable class from a <cls>Config instance.
from_dict(d)	Instantiates a Configurable class from a <cls>Config dict.
from_json(json_path)	Instantiates a Configurable class from a <cls>Config JSON file.
from_kwargs(**kwargs)	Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.
parse(class_name[, module_name])	Parses a Configurable subclass name string.
predict(arg)	Performs prediction on the given data.
validate(config)	Validates that the given config is an instance of <cls>Config.

Attributes:

can_embed_prompts	Whether this instance can generate prompt embeddings.
has_embeddings	Whether this instance can generate embeddings.
has_logits	Whether this instance can generate logits for its predictions.
media_type	The media type processed by the model.
preprocess	Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).
ragged_batches	True/False whether transforms() may return tensors of different sizes.
transforms	The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

predict_all(args)

Performs prediction on the given iterable of data.

Image models should support, at minimum, processing args values that are either lists of uint8 numpy arrays (HWC) or numpy array tensors (NHWC).

Video models should support, at minimum, processing args values that are lists of eta.core.video.VideoReader instances.

Subclasses can override this method to increase efficiency, but, by default, this method simply iterates over the data and applies predict() to each.

Parameters

args – an iterable of data

Returns

a list of fiftyone.core.labels.Label instances or a list of dicts of fiftyone.core.labels.Label instances containing the predictions

property can_embed_prompts

Whether this instance can generate prompt embeddings.

This method returns False by default. Methods that can generate prompt embeddings will override this via implementing the PromptMixin interface.

classmethod from_config(config)

Instantiates a Configurable class from a <cls>Config instance.

classmethod from_dict(d)

Instantiates a Configurable class from a <cls>Config dict.

Parameters

d – a dict to construct a <cls>Config

Returns

an instance of cls

classmethod from_json(json_path)

Instantiates a Configurable class from a <cls>Config JSON file.

Parameters

json_path – path to a JSON file for type <cls>Config

Returns

an instance of cls

classmethod from_kwargs(**kwargs)

Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.

Parameters

**kwargs – keyword arguments that define the fields of a <cls>Config dict

Returns

an instance of cls

property has_embeddings

Whether this instance can generate embeddings.

This method returns False by default. Methods that can generate embeddings will override this via implementing the EmbeddingsMixin interface.

property has_logits

Whether this instance can generate logits for its predictions.

This method returns False by default. Methods that can generate logits will override this via implementing the LogitsMixin interface.

property media_type

The media type processed by the model.

Supported values are “image” and “video”.

static parse(class_name, module_name=None)

Parses a Configurable subclass name string.

Assumes both the Configurable class and the Config class are defined in the same module. The module containing the classes will be loaded if necessary.

Parameters

• class_name – a string containing the name of the Configurable class, e.g. “ClassName”, or a fully-qualified class name, e.g. “eta.core.config.ClassName”

• module_name – a string containing the fully-qualified module name, e.g. “eta.core.config”, or None if class_name includes the module name. Set module_name = __name__ to load a class from the calling module

Returns

the Configurable class config_cls: the Config class associated with cls

Return type

cls

predict(arg)

Performs prediction on the given data.

Image models should support, at minimum, processing arg values that are uint8 numpy arrays (HWC).

Video models should support, at minimum, processing arg values that are eta.core.video.VideoReader instances.

Parameters

arg – the data

Returns

a fiftyone.core.labels.Label instance or dict of fiftyone.core.labels.Label instances containing the predictions

property preprocess

Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).

property ragged_batches

True/False whether transforms() may return tensors of different sizes. If True, then passing ragged lists of data to predict_all() is not allowed.

property transforms

The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

classmethod validate(config)

Validates that the given config is an instance of <cls>Config.

Raises

ConfigurableError – if config is not an instance of <cls>Config

class fiftyone.utils.ultralytics.FiftyOneRTDETRModelConfig(d)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModelConfig

Configuration for a FiftyOneRTDETRModel.

Parameters

• model (None) – an ultralytics.RTDETR model to use

• model_name (None) – the name of an ultralytics.RTDETR model to load

• model_path (None) – the path to an ultralytics.RTDETR model checkpoint

Methods:

attributes()	Returns a list of class attributes to be serialized.
builder()	Returns a ConfigBuilder instance for this class.
copy()	Returns a deep copy of the object.
custom_attributes([dynamic, private])	Returns a customizable list of class attributes.
default()	Returns the default config instance.
download_model_if_necessary()	Downloads the published model specified by the config, if necessary.
from_dict(d)	Constructs a Config object from a JSON dictionary.
from_json(path, *args, **kwargs)	Constructs a Serializable object from a JSON file.
from_kwargs(**kwargs)	Constructs a Config object from keyword arguments.
from_str(s, *args, **kwargs)	Constructs a Serializable object from a JSON string.
get_class_name()	Returns the fully-qualified class name string of this object.
init(d)	Initializes the published model config.
load_default()	Loads the default config instance from file.
parse_array(d, key[, default])	Parses a raw array attribute.
parse_bool(d, key[, default])	Parses a boolean value.
parse_categorical(d, key, choices[, default])	Parses a categorical JSON field, which must take a value from among the given choices.
parse_dict(d, key[, default])	Parses a dictionary attribute.
parse_int(d, key[, default])	Parses an integer attribute.
parse_mutually_exclusive_fields(fields)	Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.
parse_number(d, key[, default])	Parses a number attribute.
parse_object(d, key, cls[, default])	Parses an object attribute.
parse_object_array(d, key, cls[, default])	Parses an array of objects.
parse_object_dict(d, key, cls[, default])	Parses a dictionary whose values are objects.
parse_path(d, key[, default])	Parses a path attribute.
parse_raw(d, key[, default])	Parses a raw (arbitrary) JSON field.
parse_string(d, key[, default])	Parses a string attribute.
serialize([reflective])	Serializes the object into a dictionary.
to_str([pretty_print])	Returns a string representation of this object.
validate_all_or_nothing_fields(fields)	Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.
write_json(path[, pretty_print])	Serializes the object and writes it to disk.

attributes()

Returns a list of class attributes to be serialized.

This method is called internally by serialize() to determine the class attributes to serialize.

Subclasses can override this method, but, by default, all attributes in vars(self) are returned, minus private attributes, i.e., those starting with “_”. The order of the attributes in this list is preserved when serializing objects, so a common pattern is for subclasses to override this method if they want their JSON files to be organized in a particular way.

Returns

a list of class attributes to be serialized

classmethod builder()

Returns a ConfigBuilder instance for this class.

copy()

Returns a deep copy of the object.

Returns

a Serializable instance

custom_attributes(dynamic=False, private=False)

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

• dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False

• private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod default()

Returns the default config instance.

By default, this method instantiates the class from an empty dictionary, which will only succeed if all attributes are optional. Otherwise, subclasses should override this method to provide the desired default configuration.

download_model_if_necessary()

Downloads the published model specified by the config, if necessary.

After this method is called, the model_path attribute will always contain the path to the model on disk.

classmethod from_dict(d)

Constructs a Config object from a JSON dictionary.

Config subclass constructors accept JSON dictionaries, so this method simply passes the dictionary to cls().

Parameters

d – a dict of fields expected by cls

Returns

an instance of cls

classmethod from_json(path, *args, **kwargs)

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

• path – the path to the JSON file on disk

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_kwargs(**kwargs)

Constructs a Config object from keyword arguments.

Parameters

**kwargs – keyword arguments that define the fields expected by cls

Returns

an instance of cls

classmethod from_str(s, *args, **kwargs)

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

• s – a JSON string representation of a Serializable object

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()

Returns the fully-qualified class name string of this object.

init(d)

Initializes the published model config.

This method should be called by ModelConfig.__init__(), and it performs the following tasks:

• Parses the model_name and model_path parameters

• Populates any default parameters in the provided ModelConfig dict

Parameters

d – a ModelConfig dict

Returns

a ModelConfig dict with any default parameters populated

classmethod load_default()

Loads the default config instance from file.

Subclasses must implement this method if they intend to support default instances.

static parse_array(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw array attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default list to return if key is not present

Returns

a list of raw (untouched) values

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_bool(d, key, default=<eta.core.config.NoDefault object>)

Parses a boolean value.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default bool to return if key is not present

Returns

True/False

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_categorical(d, key, choices, default=<eta.core.config.NoDefault object>)

Parses a categorical JSON field, which must take a value from among the given choices.

Parameters

• d – a JSON dictionary

• key – the key to parse

• choices – either an iterable of possible values or an enum-like class whose attributes define the possible values

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field, which is equal to a value from choices

Raises

ConfigError – if the key was present in the dictionary but its value was not an allowed choice, or if no default value was provided and the key was not found in the dictionary

static parse_dict(d, key, default=<eta.core.config.NoDefault object>)

Parses a dictionary attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default dict to return if key is not present

Returns

a dictionary

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_int(d, key, default=<eta.core.config.NoDefault object>)

Parses an integer attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default integer value to return if key is not present

Returns

an int

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_mutually_exclusive_fields(fields)

Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Returns

the (field, value) that was set

Raises

ConfigError – if zero or more than one truthy value was found

static parse_number(d, key, default=<eta.core.config.NoDefault object>)

Parses a number attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default numeric value to return if key is not present

Returns

a number (e.g. int, float)

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an object attribute.

The value of d[key] can be either an instance of cls or a serialized dict from an instance of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of d[key]

• default – a default cls instance to return if key is not present

Returns

an instance of cls

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_array(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an array of objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the elements of list d[key]

• default – the default list to return if key is not present

Returns

a list of cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_dict(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses a dictionary whose values are objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the values of dictionary d[key]

• default – the default dict of cls instances to return if key is not present

Returns

a dictionary whose values are cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_path(d, key, default=<eta.core.config.NoDefault object>)

Parses a path attribute.

The path is converted to an absolute path if necessary via os.path.abspath(os.path.expanduser(value)).

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a path string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_raw(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw (arbitrary) JSON field.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field

Raises

ConfigError – if no default value was provided and the key was not found in the dictionary

static parse_string(d, key, default=<eta.core.config.NoDefault object>)

Parses a string attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

serialize(reflective=False)

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters

reflective – whether to include reflective attributes when serializing the object. By default, this is False

Returns

a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)

Returns a string representation of this object.

Parameters

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True

• **kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

static validate_all_or_nothing_fields(fields)

Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Raises

ConfigError – if some values are truth and some are not

write_json(path, pretty_print=False, **kwargs)

Serializes the object and writes it to disk.

Parameters

• path – the output path

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False

• **kwargs – optional keyword arguments for self.serialize()

class fiftyone.utils.ultralytics.FiftyOneRTDETRModel(config)

Bases: fiftyone.core.models.Model

FiftyOne wrapper around an ultralytics.RTDETR model.

Parameters

config – a FiftyOneRTDETRModelConfig

Attributes:

media_type	The media type processed by the model.
ragged_batches	True/False whether transforms() may return tensors of different sizes.
transforms	The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.
preprocess	Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).
can_embed_prompts	Whether this instance can generate prompt embeddings.
has_embeddings	Whether this instance can generate embeddings.
has_logits	Whether this instance can generate logits for its predictions.

Methods:

predict(arg)	Performs prediction on the given data.
from_config(config)	Instantiates a Configurable class from a <cls>Config instance.
from_dict(d)	Instantiates a Configurable class from a <cls>Config dict.
from_json(json_path)	Instantiates a Configurable class from a <cls>Config JSON file.
from_kwargs(**kwargs)	Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.
parse(class_name[, module_name])	Parses a Configurable subclass name string.
predict_all(args)	Performs prediction on the given iterable of data.
validate(config)	Validates that the given config is an instance of <cls>Config.

property media_type

The media type processed by the model.

Supported values are “image” and “video”.

property ragged_batches

True/False whether transforms() may return tensors of different sizes. If True, then passing ragged lists of data to predict_all() is not allowed.

property transforms

The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

property preprocess

Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).

predict(arg)

Performs prediction on the given data.

Image models should support, at minimum, processing arg values that are uint8 numpy arrays (HWC).

Video models should support, at minimum, processing arg values that are eta.core.video.VideoReader instances.

Parameters

arg – the data

Returns

a fiftyone.core.labels.Label instance or dict of fiftyone.core.labels.Label instances containing the predictions

property can_embed_prompts

Whether this instance can generate prompt embeddings.

This method returns False by default. Methods that can generate prompt embeddings will override this via implementing the PromptMixin interface.

classmethod from_config(config)

Instantiates a Configurable class from a <cls>Config instance.

classmethod from_dict(d)

Instantiates a Configurable class from a <cls>Config dict.

Parameters

d – a dict to construct a <cls>Config

Returns

an instance of cls

classmethod from_json(json_path)

Instantiates a Configurable class from a <cls>Config JSON file.

Parameters

json_path – path to a JSON file for type <cls>Config

Returns

an instance of cls

classmethod from_kwargs(**kwargs)

Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.

Parameters

**kwargs – keyword arguments that define the fields of a <cls>Config dict

Returns

an instance of cls

property has_embeddings

Whether this instance can generate embeddings.

This method returns False by default. Methods that can generate embeddings will override this via implementing the EmbeddingsMixin interface.

property has_logits

Whether this instance can generate logits for its predictions.

This method returns False by default. Methods that can generate logits will override this via implementing the LogitsMixin interface.

static parse(class_name, module_name=None)

Parses a Configurable subclass name string.

Assumes both the Configurable class and the Config class are defined in the same module. The module containing the classes will be loaded if necessary.

Parameters

• class_name – a string containing the name of the Configurable class, e.g. “ClassName”, or a fully-qualified class name, e.g. “eta.core.config.ClassName”

• module_name – a string containing the fully-qualified module name, e.g. “eta.core.config”, or None if class_name includes the module name. Set module_name = __name__ to load a class from the calling module

Returns

the Configurable class config_cls: the Config class associated with cls

Return type

cls

predict_all(args)

Performs prediction on the given iterable of data.

Image models should support, at minimum, processing args values that are either lists of uint8 numpy arrays (HWC) or numpy array tensors (NHWC).

Video models should support, at minimum, processing args values that are lists of eta.core.video.VideoReader instances.

Subclasses can override this method to increase efficiency, but, by default, this method simply iterates over the data and applies predict() to each.

Parameters

args – an iterable of data

Returns

a list of fiftyone.core.labels.Label instances or a list of dicts of fiftyone.core.labels.Label instances containing the predictions

classmethod validate(config)

Validates that the given config is an instance of <cls>Config.

Raises

ConfigurableError – if config is not an instance of <cls>Config

class fiftyone.utils.ultralytics.FiftyOneYOLOOBBModelConfig(d)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModelConfig

Methods:

attributes()	Returns a list of class attributes to be serialized.
builder()	Returns a ConfigBuilder instance for this class.
copy()	Returns a deep copy of the object.
custom_attributes([dynamic, private])	Returns a customizable list of class attributes.
default()	Returns the default config instance.
download_model_if_necessary()	Downloads the published model specified by the config, if necessary.
from_dict(d)	Constructs a Config object from a JSON dictionary.
from_json(path, *args, **kwargs)	Constructs a Serializable object from a JSON file.
from_kwargs(**kwargs)	Constructs a Config object from keyword arguments.
from_str(s, *args, **kwargs)	Constructs a Serializable object from a JSON string.
get_class_name()	Returns the fully-qualified class name string of this object.
init(d)	Initializes the published model config.
load_default()	Loads the default config instance from file.
parse_array(d, key[, default])	Parses a raw array attribute.
parse_bool(d, key[, default])	Parses a boolean value.
parse_categorical(d, key, choices[, default])	Parses a categorical JSON field, which must take a value from among the given choices.
parse_dict(d, key[, default])	Parses a dictionary attribute.
parse_int(d, key[, default])	Parses an integer attribute.
parse_mutually_exclusive_fields(fields)	Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.
parse_number(d, key[, default])	Parses a number attribute.
parse_object(d, key, cls[, default])	Parses an object attribute.
parse_object_array(d, key, cls[, default])	Parses an array of objects.
parse_object_dict(d, key, cls[, default])	Parses a dictionary whose values are objects.
parse_path(d, key[, default])	Parses a path attribute.
parse_raw(d, key[, default])	Parses a raw (arbitrary) JSON field.
parse_string(d, key[, default])	Parses a string attribute.
serialize([reflective])	Serializes the object into a dictionary.
to_str([pretty_print])	Returns a string representation of this object.
validate_all_or_nothing_fields(fields)	Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.
write_json(path[, pretty_print])	Serializes the object and writes it to disk.

attributes()

Returns a list of class attributes to be serialized.

This method is called internally by serialize() to determine the class attributes to serialize.

Subclasses can override this method, but, by default, all attributes in vars(self) are returned, minus private attributes, i.e., those starting with “_”. The order of the attributes in this list is preserved when serializing objects, so a common pattern is for subclasses to override this method if they want their JSON files to be organized in a particular way.

Returns

a list of class attributes to be serialized

classmethod builder()

Returns a ConfigBuilder instance for this class.

copy()

Returns a deep copy of the object.

Returns

a Serializable instance

custom_attributes(dynamic=False, private=False)

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

• dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False

• private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod default()

Returns the default config instance.

By default, this method instantiates the class from an empty dictionary, which will only succeed if all attributes are optional. Otherwise, subclasses should override this method to provide the desired default configuration.

download_model_if_necessary()

Downloads the published model specified by the config, if necessary.

After this method is called, the model_path attribute will always contain the path to the model on disk.

classmethod from_dict(d)

Constructs a Config object from a JSON dictionary.

Config subclass constructors accept JSON dictionaries, so this method simply passes the dictionary to cls().

Parameters

d – a dict of fields expected by cls

Returns

an instance of cls

classmethod from_json(path, *args, **kwargs)

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

• path – the path to the JSON file on disk

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_kwargs(**kwargs)

Constructs a Config object from keyword arguments.

Parameters

**kwargs – keyword arguments that define the fields expected by cls

Returns

an instance of cls

classmethod from_str(s, *args, **kwargs)

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

• s – a JSON string representation of a Serializable object

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()

Returns the fully-qualified class name string of this object.

init(d)

Initializes the published model config.

This method should be called by ModelConfig.__init__(), and it performs the following tasks:

• Parses the model_name and model_path parameters

• Populates any default parameters in the provided ModelConfig dict

Parameters

d – a ModelConfig dict

Returns

a ModelConfig dict with any default parameters populated

classmethod load_default()

Loads the default config instance from file.

Subclasses must implement this method if they intend to support default instances.

static parse_array(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw array attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default list to return if key is not present

Returns

a list of raw (untouched) values

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_bool(d, key, default=<eta.core.config.NoDefault object>)

Parses a boolean value.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default bool to return if key is not present

Returns

True/False

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_categorical(d, key, choices, default=<eta.core.config.NoDefault object>)

Parses a categorical JSON field, which must take a value from among the given choices.

Parameters

• d – a JSON dictionary

• key – the key to parse

• choices – either an iterable of possible values or an enum-like class whose attributes define the possible values

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field, which is equal to a value from choices

Raises

ConfigError – if the key was present in the dictionary but its value was not an allowed choice, or if no default value was provided and the key was not found in the dictionary

static parse_dict(d, key, default=<eta.core.config.NoDefault object>)

Parses a dictionary attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default dict to return if key is not present

Returns

a dictionary

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_int(d, key, default=<eta.core.config.NoDefault object>)

Parses an integer attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default integer value to return if key is not present

Returns

an int

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_mutually_exclusive_fields(fields)

Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Returns

the (field, value) that was set

Raises

ConfigError – if zero or more than one truthy value was found

static parse_number(d, key, default=<eta.core.config.NoDefault object>)

Parses a number attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default numeric value to return if key is not present

Returns

a number (e.g. int, float)

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an object attribute.

The value of d[key] can be either an instance of cls or a serialized dict from an instance of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of d[key]

• default – a default cls instance to return if key is not present

Returns

an instance of cls

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_array(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an array of objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the elements of list d[key]

• default – the default list to return if key is not present

Returns

a list of cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_dict(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses a dictionary whose values are objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the values of dictionary d[key]

• default – the default dict of cls instances to return if key is not present

Returns

a dictionary whose values are cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_path(d, key, default=<eta.core.config.NoDefault object>)

Parses a path attribute.

The path is converted to an absolute path if necessary via os.path.abspath(os.path.expanduser(value)).

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a path string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_raw(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw (arbitrary) JSON field.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field

Raises

ConfigError – if no default value was provided and the key was not found in the dictionary

static parse_string(d, key, default=<eta.core.config.NoDefault object>)

Parses a string attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

serialize(reflective=False)

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters

reflective – whether to include reflective attributes when serializing the object. By default, this is False

Returns

a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)

Returns a string representation of this object.

Parameters

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True

• **kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

static validate_all_or_nothing_fields(fields)

Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Raises

ConfigError – if some values are truth and some are not

write_json(path, pretty_print=False, **kwargs)

Serializes the object and writes it to disk.

Parameters

• path – the output path

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False

• **kwargs – optional keyword arguments for self.serialize()

class fiftyone.utils.ultralytics.FiftyOneYOLOOBBModel(config)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModel

FiftyOne wrapper around an Ultralytics YOLO OBB detection model.

Parameters

config – a FiftyOneYOLOConfig

Methods:

predict_all(args)	Performs prediction on the given iterable of data.
from_config(config)	Instantiates a Configurable class from a <cls>Config instance.
from_dict(d)	Instantiates a Configurable class from a <cls>Config dict.
from_json(json_path)	Instantiates a Configurable class from a <cls>Config JSON file.
from_kwargs(**kwargs)	Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.
parse(class_name[, module_name])	Parses a Configurable subclass name string.
predict(arg)	Performs prediction on the given data.
validate(config)	Validates that the given config is an instance of <cls>Config.

Attributes:

can_embed_prompts	Whether this instance can generate prompt embeddings.
has_embeddings	Whether this instance can generate embeddings.
has_logits	Whether this instance can generate logits for its predictions.
media_type	The media type processed by the model.
preprocess	Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).
ragged_batches	True/False whether transforms() may return tensors of different sizes.
transforms	The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

predict_all(args)

Performs prediction on the given iterable of data.

Image models should support, at minimum, processing args values that are either lists of uint8 numpy arrays (HWC) or numpy array tensors (NHWC).

Video models should support, at minimum, processing args values that are lists of eta.core.video.VideoReader instances.

Subclasses can override this method to increase efficiency, but, by default, this method simply iterates over the data and applies predict() to each.

Parameters

args – an iterable of data

Returns

a list of fiftyone.core.labels.Label instances or a list of dicts of fiftyone.core.labels.Label instances containing the predictions

property can_embed_prompts

Whether this instance can generate prompt embeddings.

This method returns False by default. Methods that can generate prompt embeddings will override this via implementing the PromptMixin interface.

classmethod from_config(config)

Instantiates a Configurable class from a <cls>Config instance.

classmethod from_dict(d)

Instantiates a Configurable class from a <cls>Config dict.

Parameters

d – a dict to construct a <cls>Config

Returns

an instance of cls

classmethod from_json(json_path)

Instantiates a Configurable class from a <cls>Config JSON file.

Parameters

json_path – path to a JSON file for type <cls>Config

Returns

an instance of cls

classmethod from_kwargs(**kwargs)

Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.

Parameters

**kwargs – keyword arguments that define the fields of a <cls>Config dict

Returns

an instance of cls

property has_embeddings

Whether this instance can generate embeddings.

This method returns False by default. Methods that can generate embeddings will override this via implementing the EmbeddingsMixin interface.

property has_logits

Whether this instance can generate logits for its predictions.

This method returns False by default. Methods that can generate logits will override this via implementing the LogitsMixin interface.

property media_type

The media type processed by the model.

Supported values are “image” and “video”.

static parse(class_name, module_name=None)

Parses a Configurable subclass name string.

Assumes both the Configurable class and the Config class are defined in the same module. The module containing the classes will be loaded if necessary.

Parameters

• class_name – a string containing the name of the Configurable class, e.g. “ClassName”, or a fully-qualified class name, e.g. “eta.core.config.ClassName”

• module_name – a string containing the fully-qualified module name, e.g. “eta.core.config”, or None if class_name includes the module name. Set module_name = __name__ to load a class from the calling module

Returns

the Configurable class config_cls: the Config class associated with cls

Return type

cls

predict(arg)

Performs prediction on the given data.

Image models should support, at minimum, processing arg values that are uint8 numpy arrays (HWC).

Video models should support, at minimum, processing arg values that are eta.core.video.VideoReader instances.

Parameters

arg – the data

Returns

a fiftyone.core.labels.Label instance or dict of fiftyone.core.labels.Label instances containing the predictions

property preprocess

Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).

property ragged_batches

True/False whether transforms() may return tensors of different sizes. If True, then passing ragged lists of data to predict_all() is not allowed.

property transforms

The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

classmethod validate(config)

Validates that the given config is an instance of <cls>Config.

Raises

ConfigurableError – if config is not an instance of <cls>Config

class fiftyone.utils.ultralytics.FiftyOneYOLOSegmentationModelConfig(d)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModelConfig

Methods:

attributes()	Returns a list of class attributes to be serialized.
builder()	Returns a ConfigBuilder instance for this class.
copy()	Returns a deep copy of the object.
custom_attributes([dynamic, private])	Returns a customizable list of class attributes.
default()	Returns the default config instance.
download_model_if_necessary()	Downloads the published model specified by the config, if necessary.
from_dict(d)	Constructs a Config object from a JSON dictionary.
from_json(path, *args, **kwargs)	Constructs a Serializable object from a JSON file.
from_kwargs(**kwargs)	Constructs a Config object from keyword arguments.
from_str(s, *args, **kwargs)	Constructs a Serializable object from a JSON string.
get_class_name()	Returns the fully-qualified class name string of this object.
init(d)	Initializes the published model config.
load_default()	Loads the default config instance from file.
parse_array(d, key[, default])	Parses a raw array attribute.
parse_bool(d, key[, default])	Parses a boolean value.
parse_categorical(d, key, choices[, default])	Parses a categorical JSON field, which must take a value from among the given choices.
parse_dict(d, key[, default])	Parses a dictionary attribute.
parse_int(d, key[, default])	Parses an integer attribute.
parse_mutually_exclusive_fields(fields)	Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.
parse_number(d, key[, default])	Parses a number attribute.
parse_object(d, key, cls[, default])	Parses an object attribute.
parse_object_array(d, key, cls[, default])	Parses an array of objects.
parse_object_dict(d, key, cls[, default])	Parses a dictionary whose values are objects.
parse_path(d, key[, default])	Parses a path attribute.
parse_raw(d, key[, default])	Parses a raw (arbitrary) JSON field.
parse_string(d, key[, default])	Parses a string attribute.
serialize([reflective])	Serializes the object into a dictionary.
to_str([pretty_print])	Returns a string representation of this object.
validate_all_or_nothing_fields(fields)	Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.
write_json(path[, pretty_print])	Serializes the object and writes it to disk.

attributes()

Returns a list of class attributes to be serialized.

This method is called internally by serialize() to determine the class attributes to serialize.

Subclasses can override this method, but, by default, all attributes in vars(self) are returned, minus private attributes, i.e., those starting with “_”. The order of the attributes in this list is preserved when serializing objects, so a common pattern is for subclasses to override this method if they want their JSON files to be organized in a particular way.

Returns

a list of class attributes to be serialized

classmethod builder()

Returns a ConfigBuilder instance for this class.

copy()

Returns a deep copy of the object.

Returns

a Serializable instance

custom_attributes(dynamic=False, private=False)

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

• dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False

• private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod default()

Returns the default config instance.

By default, this method instantiates the class from an empty dictionary, which will only succeed if all attributes are optional. Otherwise, subclasses should override this method to provide the desired default configuration.

download_model_if_necessary()

Downloads the published model specified by the config, if necessary.

After this method is called, the model_path attribute will always contain the path to the model on disk.

classmethod from_dict(d)

Constructs a Config object from a JSON dictionary.

Config subclass constructors accept JSON dictionaries, so this method simply passes the dictionary to cls().

Parameters

d – a dict of fields expected by cls

Returns

an instance of cls

classmethod from_json(path, *args, **kwargs)

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

• path – the path to the JSON file on disk

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_kwargs(**kwargs)

Constructs a Config object from keyword arguments.

Parameters

**kwargs – keyword arguments that define the fields expected by cls

Returns

an instance of cls

classmethod from_str(s, *args, **kwargs)

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

• s – a JSON string representation of a Serializable object

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()

Returns the fully-qualified class name string of this object.

init(d)

Initializes the published model config.

This method should be called by ModelConfig.__init__(), and it performs the following tasks:

• Parses the model_name and model_path parameters

• Populates any default parameters in the provided ModelConfig dict

Parameters

d – a ModelConfig dict

Returns

a ModelConfig dict with any default parameters populated

classmethod load_default()

Loads the default config instance from file.

Subclasses must implement this method if they intend to support default instances.

static parse_array(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw array attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default list to return if key is not present

Returns

a list of raw (untouched) values

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_bool(d, key, default=<eta.core.config.NoDefault object>)

Parses a boolean value.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default bool to return if key is not present

Returns

True/False

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_categorical(d, key, choices, default=<eta.core.config.NoDefault object>)

Parses a categorical JSON field, which must take a value from among the given choices.

Parameters

• d – a JSON dictionary

• key – the key to parse

• choices – either an iterable of possible values or an enum-like class whose attributes define the possible values

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field, which is equal to a value from choices

Raises

ConfigError – if the key was present in the dictionary but its value was not an allowed choice, or if no default value was provided and the key was not found in the dictionary

static parse_dict(d, key, default=<eta.core.config.NoDefault object>)

Parses a dictionary attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default dict to return if key is not present

Returns

a dictionary

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_int(d, key, default=<eta.core.config.NoDefault object>)

Parses an integer attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default integer value to return if key is not present

Returns

an int

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_mutually_exclusive_fields(fields)

Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Returns

the (field, value) that was set

Raises

ConfigError – if zero or more than one truthy value was found

static parse_number(d, key, default=<eta.core.config.NoDefault object>)

Parses a number attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default numeric value to return if key is not present

Returns

a number (e.g. int, float)

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an object attribute.

The value of d[key] can be either an instance of cls or a serialized dict from an instance of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of d[key]

• default – a default cls instance to return if key is not present

Returns

an instance of cls

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_array(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an array of objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the elements of list d[key]

• default – the default list to return if key is not present

Returns

a list of cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_dict(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses a dictionary whose values are objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the values of dictionary d[key]

• default – the default dict of cls instances to return if key is not present

Returns

a dictionary whose values are cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_path(d, key, default=<eta.core.config.NoDefault object>)

Parses a path attribute.

The path is converted to an absolute path if necessary via os.path.abspath(os.path.expanduser(value)).

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a path string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_raw(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw (arbitrary) JSON field.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field

Raises

ConfigError – if no default value was provided and the key was not found in the dictionary

static parse_string(d, key, default=<eta.core.config.NoDefault object>)

Parses a string attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

serialize(reflective=False)

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters

reflective – whether to include reflective attributes when serializing the object. By default, this is False

Returns

a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)

Returns a string representation of this object.

Parameters

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True

• **kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

static validate_all_or_nothing_fields(fields)

Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Raises

ConfigError – if some values are truth and some are not

write_json(path, pretty_print=False, **kwargs)

Serializes the object and writes it to disk.

Parameters

• path – the output path

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False

• **kwargs – optional keyword arguments for self.serialize()

class fiftyone.utils.ultralytics.FiftyOneYOLOSegmentationModel(config)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModel

FiftyOne wrapper around an Ultralytics YOLO segmentation model.

Parameters

config – a FiftyOneYOLOSegmentationModelConfig

Attributes:

ragged_batches	True/False whether transforms() may return tensors of different sizes.
can_embed_prompts	Whether this instance can generate prompt embeddings.
has_embeddings	Whether this instance can generate embeddings.
has_logits	Whether this instance can generate logits for its predictions.
media_type	The media type processed by the model.
preprocess	Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).
transforms	The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

Methods:

from_config(config)	Instantiates a Configurable class from a <cls>Config instance.
from_dict(d)	Instantiates a Configurable class from a <cls>Config dict.
from_json(json_path)	Instantiates a Configurable class from a <cls>Config JSON file.
from_kwargs(**kwargs)	Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.
parse(class_name[, module_name])	Parses a Configurable subclass name string.
predict(arg)	Performs prediction on the given data.
predict_all(args)	Performs prediction on the given iterable of data.
validate(config)	Validates that the given config is an instance of <cls>Config.

property ragged_batches

True/False whether transforms() may return tensors of different sizes. If True, then passing ragged lists of data to predict_all() is not allowed.

property can_embed_prompts

Whether this instance can generate prompt embeddings.

This method returns False by default. Methods that can generate prompt embeddings will override this via implementing the PromptMixin interface.

classmethod from_config(config)

Instantiates a Configurable class from a <cls>Config instance.

classmethod from_dict(d)

Instantiates a Configurable class from a <cls>Config dict.

Parameters

d – a dict to construct a <cls>Config

Returns

an instance of cls

classmethod from_json(json_path)

Instantiates a Configurable class from a <cls>Config JSON file.

Parameters

json_path – path to a JSON file for type <cls>Config

Returns

an instance of cls

classmethod from_kwargs(**kwargs)

Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.

Parameters

**kwargs – keyword arguments that define the fields of a <cls>Config dict

Returns

an instance of cls

property has_embeddings

Whether this instance can generate embeddings.

This method returns False by default. Methods that can generate embeddings will override this via implementing the EmbeddingsMixin interface.

property has_logits

Whether this instance can generate logits for its predictions.

This method returns False by default. Methods that can generate logits will override this via implementing the LogitsMixin interface.

property media_type

The media type processed by the model.

Supported values are “image” and “video”.

static parse(class_name, module_name=None)

Parses a Configurable subclass name string.

Assumes both the Configurable class and the Config class are defined in the same module. The module containing the classes will be loaded if necessary.

Parameters

• class_name – a string containing the name of the Configurable class, e.g. “ClassName”, or a fully-qualified class name, e.g. “eta.core.config.ClassName”

• module_name – a string containing the fully-qualified module name, e.g. “eta.core.config”, or None if class_name includes the module name. Set module_name = __name__ to load a class from the calling module

Returns

the Configurable class config_cls: the Config class associated with cls

Return type

cls

predict(arg)

Performs prediction on the given data.

Image models should support, at minimum, processing arg values that are uint8 numpy arrays (HWC).

Video models should support, at minimum, processing arg values that are eta.core.video.VideoReader instances.

Parameters

arg – the data

Returns

a fiftyone.core.labels.Label instance or dict of fiftyone.core.labels.Label instances containing the predictions

predict_all(args)

Performs prediction on the given iterable of data.

Image models should support, at minimum, processing args values that are either lists of uint8 numpy arrays (HWC) or numpy array tensors (NHWC).

Video models should support, at minimum, processing args values that are lists of eta.core.video.VideoReader instances.

Subclasses can override this method to increase efficiency, but, by default, this method simply iterates over the data and applies predict() to each.

Parameters

args – an iterable of data

Returns

a list of fiftyone.core.labels.Label instances or a list of dicts of fiftyone.core.labels.Label instances containing the predictions

property preprocess

Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).

property transforms

The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

classmethod validate(config)

Validates that the given config is an instance of <cls>Config.

Raises

ConfigurableError – if config is not an instance of <cls>Config

class fiftyone.utils.ultralytics.FiftyOneYOLOPoseModelConfig(d)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModelConfig

Methods:

attributes()	Returns a list of class attributes to be serialized.
builder()	Returns a ConfigBuilder instance for this class.
copy()	Returns a deep copy of the object.
custom_attributes([dynamic, private])	Returns a customizable list of class attributes.
default()	Returns the default config instance.
download_model_if_necessary()	Downloads the published model specified by the config, if necessary.
from_dict(d)	Constructs a Config object from a JSON dictionary.
from_json(path, *args, **kwargs)	Constructs a Serializable object from a JSON file.
from_kwargs(**kwargs)	Constructs a Config object from keyword arguments.
from_str(s, *args, **kwargs)	Constructs a Serializable object from a JSON string.
get_class_name()	Returns the fully-qualified class name string of this object.
init(d)	Initializes the published model config.
load_default()	Loads the default config instance from file.
parse_array(d, key[, default])	Parses a raw array attribute.
parse_bool(d, key[, default])	Parses a boolean value.
parse_categorical(d, key, choices[, default])	Parses a categorical JSON field, which must take a value from among the given choices.
parse_dict(d, key[, default])	Parses a dictionary attribute.
parse_int(d, key[, default])	Parses an integer attribute.
parse_mutually_exclusive_fields(fields)	Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.
parse_number(d, key[, default])	Parses a number attribute.
parse_object(d, key, cls[, default])	Parses an object attribute.
parse_object_array(d, key, cls[, default])	Parses an array of objects.
parse_object_dict(d, key, cls[, default])	Parses a dictionary whose values are objects.
parse_path(d, key[, default])	Parses a path attribute.
parse_raw(d, key[, default])	Parses a raw (arbitrary) JSON field.
parse_string(d, key[, default])	Parses a string attribute.
serialize([reflective])	Serializes the object into a dictionary.
to_str([pretty_print])	Returns a string representation of this object.
validate_all_or_nothing_fields(fields)	Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.
write_json(path[, pretty_print])	Serializes the object and writes it to disk.

attributes()

Returns a list of class attributes to be serialized.

This method is called internally by serialize() to determine the class attributes to serialize.

Subclasses can override this method, but, by default, all attributes in vars(self) are returned, minus private attributes, i.e., those starting with “_”. The order of the attributes in this list is preserved when serializing objects, so a common pattern is for subclasses to override this method if they want their JSON files to be organized in a particular way.

Returns

a list of class attributes to be serialized

classmethod builder()

Returns a ConfigBuilder instance for this class.

copy()

Returns a deep copy of the object.

Returns

a Serializable instance

custom_attributes(dynamic=False, private=False)

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

• dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False

• private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod default()

Returns the default config instance.

By default, this method instantiates the class from an empty dictionary, which will only succeed if all attributes are optional. Otherwise, subclasses should override this method to provide the desired default configuration.

download_model_if_necessary()

Downloads the published model specified by the config, if necessary.

After this method is called, the model_path attribute will always contain the path to the model on disk.

classmethod from_dict(d)

Constructs a Config object from a JSON dictionary.

Config subclass constructors accept JSON dictionaries, so this method simply passes the dictionary to cls().

Parameters

d – a dict of fields expected by cls

Returns

an instance of cls

classmethod from_json(path, *args, **kwargs)

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

• path – the path to the JSON file on disk

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_kwargs(**kwargs)

Constructs a Config object from keyword arguments.

Parameters

**kwargs – keyword arguments that define the fields expected by cls

Returns

an instance of cls

classmethod from_str(s, *args, **kwargs)

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

• s – a JSON string representation of a Serializable object

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()

Returns the fully-qualified class name string of this object.

init(d)

Initializes the published model config.

This method should be called by ModelConfig.__init__(), and it performs the following tasks:

• Parses the model_name and model_path parameters

• Populates any default parameters in the provided ModelConfig dict

Parameters

d – a ModelConfig dict

Returns

a ModelConfig dict with any default parameters populated

classmethod load_default()

Loads the default config instance from file.

Subclasses must implement this method if they intend to support default instances.

static parse_array(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw array attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default list to return if key is not present

Returns

a list of raw (untouched) values

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_bool(d, key, default=<eta.core.config.NoDefault object>)

Parses a boolean value.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default bool to return if key is not present

Returns

True/False

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_categorical(d, key, choices, default=<eta.core.config.NoDefault object>)

Parses a categorical JSON field, which must take a value from among the given choices.

Parameters

• d – a JSON dictionary

• key – the key to parse

• choices – either an iterable of possible values or an enum-like class whose attributes define the possible values

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field, which is equal to a value from choices

Raises

ConfigError – if the key was present in the dictionary but its value was not an allowed choice, or if no default value was provided and the key was not found in the dictionary

static parse_dict(d, key, default=<eta.core.config.NoDefault object>)

Parses a dictionary attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default dict to return if key is not present

Returns

a dictionary

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_int(d, key, default=<eta.core.config.NoDefault object>)

Parses an integer attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default integer value to return if key is not present

Returns

an int

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_mutually_exclusive_fields(fields)

Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Returns

the (field, value) that was set

Raises

ConfigError – if zero or more than one truthy value was found

static parse_number(d, key, default=<eta.core.config.NoDefault object>)

Parses a number attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default numeric value to return if key is not present

Returns

a number (e.g. int, float)

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an object attribute.

The value of d[key] can be either an instance of cls or a serialized dict from an instance of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of d[key]

• default – a default cls instance to return if key is not present

Returns

an instance of cls

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_array(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an array of objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the elements of list d[key]

• default – the default list to return if key is not present

Returns

a list of cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_dict(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses a dictionary whose values are objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the values of dictionary d[key]

• default – the default dict of cls instances to return if key is not present

Returns

a dictionary whose values are cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_path(d, key, default=<eta.core.config.NoDefault object>)

Parses a path attribute.

The path is converted to an absolute path if necessary via os.path.abspath(os.path.expanduser(value)).

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a path string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_raw(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw (arbitrary) JSON field.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field

Raises

ConfigError – if no default value was provided and the key was not found in the dictionary

static parse_string(d, key, default=<eta.core.config.NoDefault object>)

Parses a string attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

serialize(reflective=False)

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters

reflective – whether to include reflective attributes when serializing the object. By default, this is False

Returns

a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)

Returns a string representation of this object.

Parameters

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True

• **kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

static validate_all_or_nothing_fields(fields)

Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Raises

ConfigError – if some values are truth and some are not

write_json(path, pretty_print=False, **kwargs)

Serializes the object and writes it to disk.

Parameters

• path – the output path

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False

• **kwargs – optional keyword arguments for self.serialize()

class fiftyone.utils.ultralytics.FiftyOneYOLOPoseModel(config)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModel

FiftyOne wrapper around an Ultralytics YOLO pose model.

Parameters

config – a FiftyOneYOLOPoseModelConfig

Methods:

predict_all(args)	Performs prediction on the given iterable of data.
from_config(config)	Instantiates a Configurable class from a <cls>Config instance.
from_dict(d)	Instantiates a Configurable class from a <cls>Config dict.
from_json(json_path)	Instantiates a Configurable class from a <cls>Config JSON file.
from_kwargs(**kwargs)	Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.
parse(class_name[, module_name])	Parses a Configurable subclass name string.
predict(arg)	Performs prediction on the given data.
validate(config)	Validates that the given config is an instance of <cls>Config.

Attributes:

can_embed_prompts	Whether this instance can generate prompt embeddings.
has_embeddings	Whether this instance can generate embeddings.
has_logits	Whether this instance can generate logits for its predictions.
media_type	The media type processed by the model.
preprocess	Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).
ragged_batches	True/False whether transforms() may return tensors of different sizes.
transforms	The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

predict_all(args)

Performs prediction on the given iterable of data.

Image models should support, at minimum, processing args values that are either lists of uint8 numpy arrays (HWC) or numpy array tensors (NHWC).

Video models should support, at minimum, processing args values that are lists of eta.core.video.VideoReader instances.

Subclasses can override this method to increase efficiency, but, by default, this method simply iterates over the data and applies predict() to each.

Parameters

args – an iterable of data

Returns

a list of fiftyone.core.labels.Label instances or a list of dicts of fiftyone.core.labels.Label instances containing the predictions

property can_embed_prompts

Whether this instance can generate prompt embeddings.

This method returns False by default. Methods that can generate prompt embeddings will override this via implementing the PromptMixin interface.

classmethod from_config(config)

Instantiates a Configurable class from a <cls>Config instance.

classmethod from_dict(d)

Instantiates a Configurable class from a <cls>Config dict.

Parameters

d – a dict to construct a <cls>Config

Returns

an instance of cls

classmethod from_json(json_path)

Instantiates a Configurable class from a <cls>Config JSON file.

Parameters

json_path – path to a JSON file for type <cls>Config

Returns

an instance of cls

classmethod from_kwargs(**kwargs)

Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.

Parameters

**kwargs – keyword arguments that define the fields of a <cls>Config dict

Returns

an instance of cls

property has_embeddings

Whether this instance can generate embeddings.

This method returns False by default. Methods that can generate embeddings will override this via implementing the EmbeddingsMixin interface.

property has_logits

Whether this instance can generate logits for its predictions.

This method returns False by default. Methods that can generate logits will override this via implementing the LogitsMixin interface.

property media_type

The media type processed by the model.

Supported values are “image” and “video”.

static parse(class_name, module_name=None)

Parses a Configurable subclass name string.

Assumes both the Configurable class and the Config class are defined in the same module. The module containing the classes will be loaded if necessary.

Parameters

• class_name – a string containing the name of the Configurable class, e.g. “ClassName”, or a fully-qualified class name, e.g. “eta.core.config.ClassName”

• module_name – a string containing the fully-qualified module name, e.g. “eta.core.config”, or None if class_name includes the module name. Set module_name = __name__ to load a class from the calling module

Returns

the Configurable class config_cls: the Config class associated with cls

Return type

cls

predict(arg)

Performs prediction on the given data.

Image models should support, at minimum, processing arg values that are uint8 numpy arrays (HWC).

Video models should support, at minimum, processing arg values that are eta.core.video.VideoReader instances.

Parameters

arg – the data

Returns

a fiftyone.core.labels.Label instance or dict of fiftyone.core.labels.Label instances containing the predictions

property preprocess

Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).

property ragged_batches

True/False whether transforms() may return tensors of different sizes. If True, then passing ragged lists of data to predict_all() is not allowed.

property transforms

The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

classmethod validate(config)

Validates that the given config is an instance of <cls>Config.

Raises

ConfigurableError – if config is not an instance of <cls>Config

class fiftyone.utils.ultralytics.FiftyOneYOLOClassificationModelConfig(d)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModelConfig

Methods:

attributes()	Returns a list of class attributes to be serialized.
builder()	Returns a ConfigBuilder instance for this class.
copy()	Returns a deep copy of the object.
custom_attributes([dynamic, private])	Returns a customizable list of class attributes.
default()	Returns the default config instance.
download_model_if_necessary()	Downloads the published model specified by the config, if necessary.
from_dict(d)	Constructs a Config object from a JSON dictionary.
from_json(path, *args, **kwargs)	Constructs a Serializable object from a JSON file.
from_kwargs(**kwargs)	Constructs a Config object from keyword arguments.
from_str(s, *args, **kwargs)	Constructs a Serializable object from a JSON string.
get_class_name()	Returns the fully-qualified class name string of this object.
init(d)	Initializes the published model config.
load_default()	Loads the default config instance from file.
parse_array(d, key[, default])	Parses a raw array attribute.
parse_bool(d, key[, default])	Parses a boolean value.
parse_categorical(d, key, choices[, default])	Parses a categorical JSON field, which must take a value from among the given choices.
parse_dict(d, key[, default])	Parses a dictionary attribute.
parse_int(d, key[, default])	Parses an integer attribute.
parse_mutually_exclusive_fields(fields)	Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.
parse_number(d, key[, default])	Parses a number attribute.
parse_object(d, key, cls[, default])	Parses an object attribute.
parse_object_array(d, key, cls[, default])	Parses an array of objects.
parse_object_dict(d, key, cls[, default])	Parses a dictionary whose values are objects.
parse_path(d, key[, default])	Parses a path attribute.
parse_raw(d, key[, default])	Parses a raw (arbitrary) JSON field.
parse_string(d, key[, default])	Parses a string attribute.
serialize([reflective])	Serializes the object into a dictionary.
to_str([pretty_print])	Returns a string representation of this object.
validate_all_or_nothing_fields(fields)	Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.
write_json(path[, pretty_print])	Serializes the object and writes it to disk.

attributes()

Returns a list of class attributes to be serialized.

This method is called internally by serialize() to determine the class attributes to serialize.

Subclasses can override this method, but, by default, all attributes in vars(self) are returned, minus private attributes, i.e., those starting with “_”. The order of the attributes in this list is preserved when serializing objects, so a common pattern is for subclasses to override this method if they want their JSON files to be organized in a particular way.

Returns

a list of class attributes to be serialized

classmethod builder()

Returns a ConfigBuilder instance for this class.

copy()

Returns a deep copy of the object.

Returns

a Serializable instance

custom_attributes(dynamic=False, private=False)

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

• dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False

• private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod default()

Returns the default config instance.

By default, this method instantiates the class from an empty dictionary, which will only succeed if all attributes are optional. Otherwise, subclasses should override this method to provide the desired default configuration.

download_model_if_necessary()

Downloads the published model specified by the config, if necessary.

After this method is called, the model_path attribute will always contain the path to the model on disk.

classmethod from_dict(d)

Constructs a Config object from a JSON dictionary.

Config subclass constructors accept JSON dictionaries, so this method simply passes the dictionary to cls().

Parameters

d – a dict of fields expected by cls

Returns

an instance of cls

classmethod from_json(path, *args, **kwargs)

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

• path – the path to the JSON file on disk

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_kwargs(**kwargs)

Constructs a Config object from keyword arguments.

Parameters

**kwargs – keyword arguments that define the fields expected by cls

Returns

an instance of cls

classmethod from_str(s, *args, **kwargs)

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

• s – a JSON string representation of a Serializable object

• *args – optional positional arguments for self.from_dict()

• **kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()

Returns the fully-qualified class name string of this object.

init(d)

Initializes the published model config.

This method should be called by ModelConfig.__init__(), and it performs the following tasks:

• Parses the model_name and model_path parameters

• Populates any default parameters in the provided ModelConfig dict

Parameters

d – a ModelConfig dict

Returns

a ModelConfig dict with any default parameters populated

classmethod load_default()

Loads the default config instance from file.

Subclasses must implement this method if they intend to support default instances.

static parse_array(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw array attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default list to return if key is not present

Returns

a list of raw (untouched) values

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_bool(d, key, default=<eta.core.config.NoDefault object>)

Parses a boolean value.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default bool to return if key is not present

Returns

True/False

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_categorical(d, key, choices, default=<eta.core.config.NoDefault object>)

Parses a categorical JSON field, which must take a value from among the given choices.

Parameters

• d – a JSON dictionary

• key – the key to parse

• choices – either an iterable of possible values or an enum-like class whose attributes define the possible values

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field, which is equal to a value from choices

Raises

ConfigError – if the key was present in the dictionary but its value was not an allowed choice, or if no default value was provided and the key was not found in the dictionary

static parse_dict(d, key, default=<eta.core.config.NoDefault object>)

Parses a dictionary attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default dict to return if key is not present

Returns

a dictionary

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_int(d, key, default=<eta.core.config.NoDefault object>)

Parses an integer attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default integer value to return if key is not present

Returns

an int

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_mutually_exclusive_fields(fields)

Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Returns

the (field, value) that was set

Raises

ConfigError – if zero or more than one truthy value was found

static parse_number(d, key, default=<eta.core.config.NoDefault object>)

Parses a number attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default numeric value to return if key is not present

Returns

a number (e.g. int, float)

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an object attribute.

The value of d[key] can be either an instance of cls or a serialized dict from an instance of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of d[key]

• default – a default cls instance to return if key is not present

Returns

an instance of cls

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_array(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses an array of objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the elements of list d[key]

• default – the default list to return if key is not present

Returns

a list of cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_dict(d, key, cls, default=<eta.core.config.NoDefault object>)

Parses a dictionary whose values are objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

• d – a JSON dictionary

• key – the key to parse

• cls – the class of the values of dictionary d[key]

• default – the default dict of cls instances to return if key is not present

Returns

a dictionary whose values are cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_path(d, key, default=<eta.core.config.NoDefault object>)

Parses a path attribute.

The path is converted to an absolute path if necessary via os.path.abspath(os.path.expanduser(value)).

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a path string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_raw(d, key, default=<eta.core.config.NoDefault object>)

Parses a raw (arbitrary) JSON field.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field

Raises

ConfigError – if no default value was provided and the key was not found in the dictionary

static parse_string(d, key, default=<eta.core.config.NoDefault object>)

Parses a string attribute.

Parameters

• d – a JSON dictionary

• key – the key to parse

• default – a default string to return if key is not present

Returns

a string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

serialize(reflective=False)

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters

reflective – whether to include reflective attributes when serializing the object. By default, this is False

Returns

a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)

Returns a string representation of this object.

Parameters

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True

• **kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

static validate_all_or_nothing_fields(fields)

Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.

Parameters

fields – a dictionary of pre-parsed fields

Raises

ConfigError – if some values are truth and some are not

write_json(path, pretty_print=False, **kwargs)

Serializes the object and writes it to disk.

Parameters

• path – the output path

• pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False

• **kwargs – optional keyword arguments for self.serialize()

class fiftyone.utils.ultralytics.FiftyOneYOLOClassificationModel(config)

Bases: fiftyone.utils.ultralytics.FiftyOneYOLOModel

FiftyOne wrapper around an Ultralytics YOLO classification model.

Parameters

config – a FiftyOneYOLOClassificationModelConfig

Attributes:

can_embed_prompts	Whether this instance can generate prompt embeddings.
has_embeddings	Whether this instance can generate embeddings.
has_logits	Whether this instance can generate logits for its predictions.
media_type	The media type processed by the model.
preprocess	Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).
ragged_batches	True/False whether transforms() may return tensors of different sizes.
transforms	The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

Methods:

from_config(config)	Instantiates a Configurable class from a <cls>Config instance.
from_dict(d)	Instantiates a Configurable class from a <cls>Config dict.
from_json(json_path)	Instantiates a Configurable class from a <cls>Config JSON file.
from_kwargs(**kwargs)	Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.
parse(class_name[, module_name])	Parses a Configurable subclass name string.
predict(arg)	Performs prediction on the given data.
predict_all(args)	Performs prediction on the given iterable of data.
validate(config)	Validates that the given config is an instance of <cls>Config.

property can_embed_prompts

Whether this instance can generate prompt embeddings.

This method returns False by default. Methods that can generate prompt embeddings will override this via implementing the PromptMixin interface.

classmethod from_config(config)

Instantiates a Configurable class from a <cls>Config instance.

classmethod from_dict(d)

Instantiates a Configurable class from a <cls>Config dict.

Parameters

d – a dict to construct a <cls>Config

Returns

an instance of cls

classmethod from_json(json_path)

Instantiates a Configurable class from a <cls>Config JSON file.

Parameters

json_path – path to a JSON file for type <cls>Config

Returns

an instance of cls

classmethod from_kwargs(**kwargs)

Instantiates a Configurable class from keyword arguments defining the attributes of a <cls>Config.

Parameters

**kwargs – keyword arguments that define the fields of a <cls>Config dict

Returns

an instance of cls

property has_embeddings

Whether this instance can generate embeddings.

This method returns False by default. Methods that can generate embeddings will override this via implementing the EmbeddingsMixin interface.

property has_logits

Whether this instance can generate logits for its predictions.

This method returns False by default. Methods that can generate logits will override this via implementing the LogitsMixin interface.

property media_type

The media type processed by the model.

Supported values are “image” and “video”.

static parse(class_name, module_name=None)

Parses a Configurable subclass name string.

Assumes both the Configurable class and the Config class are defined in the same module. The module containing the classes will be loaded if necessary.

Parameters

• class_name – a string containing the name of the Configurable class, e.g. “ClassName”, or a fully-qualified class name, e.g. “eta.core.config.ClassName”

• module_name – a string containing the fully-qualified module name, e.g. “eta.core.config”, or None if class_name includes the module name. Set module_name = __name__ to load a class from the calling module

Returns

the Configurable class config_cls: the Config class associated with cls

Return type

cls

predict(arg)

Performs prediction on the given data.

Image models should support, at minimum, processing arg values that are uint8 numpy arrays (HWC).

Video models should support, at minimum, processing arg values that are eta.core.video.VideoReader instances.

Parameters

arg – the data

Returns

a fiftyone.core.labels.Label instance or dict of fiftyone.core.labels.Label instances containing the predictions

predict_all(args)

Performs prediction on the given iterable of data.

Image models should support, at minimum, processing args values that are either lists of uint8 numpy arrays (HWC) or numpy array tensors (NHWC).

Video models should support, at minimum, processing args values that are lists of eta.core.video.VideoReader instances.

Subclasses can override this method to increase efficiency, but, by default, this method simply iterates over the data and applies predict() to each.

Parameters

args – an iterable of data

Returns

a list of fiftyone.core.labels.Label instances or a list of dicts of fiftyone.core.labels.Label instances containing the predictions

property preprocess

Whether to apply transforms() during inference (True) or to assume that they have already been applied (False).

property ragged_batches

True/False whether transforms() may return tensors of different sizes. If True, then passing ragged lists of data to predict_all() is not allowed.

property transforms

The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.

classmethod validate(config)

Validates that the given config is an instance of <cls>Config.

Raises

ConfigurableError – if config is not an instance of <cls>Config

class fiftyone.utils.ultralytics.UltralyticsOutputProcessor(classes=None, **kwargs)

Bases: fiftyone.utils.torch.OutputProcessor

Converts Ultralytics PyTorch Hub model outputs to FiftyOne format.