# fiftyone.core.models
FiftyOne models.
Copyright 2017-2026, Voxel51, Inc.
[voxel51.com](https://voxel51.com/)
**Functions:**
| [`apply_model`](#fiftyone.core.models.apply_model)(samples, model[, label_field, ...]) | Applies the model to the samples in the collection. |
|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------|
| [`compute_embeddings`](#fiftyone.core.models.compute_embeddings)(samples, model[, ...]) | Computes embeddings for the samples in the collection using the given model. |
| [`compute_patch_embeddings`](#fiftyone.core.models.compute_patch_embeddings)(samples, model, ...) | Computes embeddings for the image patches defined by `patches_field` of the samples in the collection using the given model. |
| [`load_model`](#fiftyone.core.models.load_model)(model_config_dict[, model_path]) | Loads the model specified by the given [`ModelConfig`](#fiftyone.core.models.ModelConfig) dict. |
**Classes:**
| [`ErrorHandlingCollate`](#fiftyone.core.models.ErrorHandlingCollate)(skip_failures, ...[, ...]) | |
|---------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [`ModelConfig`](#fiftyone.core.models.ModelConfig)(d) | Base configuration class that encapsulates the name of a [`Model`](#fiftyone.core.models.Model) and an instance of its associated Config class. |
| [`Model`](#fiftyone.core.models.Model)() | Abstract base class for models. |
| [`LogitsMixin`](#fiftyone.core.models.LogitsMixin)() | Mixin for [`Model`](#fiftyone.core.models.Model) classes that can generate logits for their predictions. |
| [`EmbeddingsMixin`](#fiftyone.core.models.EmbeddingsMixin)() | Mixin for [`Model`](#fiftyone.core.models.Model) classes that can generate embeddings for their predictions. |
| [`PromptMixin`](#fiftyone.core.models.PromptMixin)() | Mixin for [`Model`](#fiftyone.core.models.Model) classes that can generate prompt embeddings. |
| [`SamplesMixin`](#fiftyone.core.models.SamplesMixin)() | Mixin for [`Model`](#fiftyone.core.models.Model) classes that need samples for prediction. |
| [`TorchModelMixin`](#fiftyone.core.models.TorchModelMixin)() | Mixin for [`Model`](#fiftyone.core.models.Model) classes that support feeding data for inference via a [`torch.utils.data.DataLoader`](https://docs.pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader). |
| [`SupportsGetItem`](#fiftyone.core.models.SupportsGetItem)() | Mixin for models that support inference with [`fiftyone.utils.torch.FiftyOneTorchDataset`](fiftyone.utils.torch.md#fiftyone.utils.torch.FiftyOneTorchDataset). |
| [`ModelManagerConfig`](#fiftyone.core.models.ModelManagerConfig)(d) | Config settings for a [`ModelManager`](#fiftyone.core.models.ModelManager). |
| [`ModelManager`](#fiftyone.core.models.ModelManager)(config) | Class for downloading FiftyOne models from the web. |
### fiftyone.core.models.apply_model(samples, model, label_field='predictions', confidence_thresh=None, classes=None, store_logits=False, batch_size=None, num_workers=None, skip_failures=True, output_dir=None, rel_dir=None, progress=None, pin_memory=False, \*\*kwargs)
Applies the model to the samples in the collection.
This method supports all of the following cases:
- Applying an image model to an image collection
- Applying an image model to the frames of a video collection
- Applying a video model to a video collection
* **Parameters:**
* **samples** – a [`fiftyone.core.collections.SampleCollection`](fiftyone.core.collections.md#fiftyone.core.collections.SampleCollection)
* **model** – a [`Model`](#fiftyone.core.models.Model), Hugging Face Transformers model, Ultralytics
model, SuperGradients model, or Lightning Flash model
* **label_field** ( *"predictions"*) – the name of the field in which to store
the model predictions. When performing inference on video frames,
the “frames.” prefix is optional
* **confidence_thresh** (*None*) – an optional confidence threshold to apply to
any applicable labels generated by the model
* **classes** (*None*) – an optional iterable of classes to which to restrict
any applicable labels generated by the model
* **store_logits** (*False*) – whether to store logits for the model
predictions. This is only supported when the provided `model` has
logits, `model.has_logits == True`
* **batch_size** (*None*) – an optional batch size to use, if the model supports
batching
* **num_workers** (*None*) – the number of workers to use when loading images.
Only applicable for Torch-based models
* **skip_failures** (*True*) – whether to gracefully continue without raising an
error if predictions cannot be generated for a sample. Only
applicable to [`Model`](#fiftyone.core.models.Model) instances
* **output_dir** (*None*) – an optional output directory in which to write
segmentation images. Only applicable if the model generates
segmentations. If none is provided, the segmentations are stored in
the database
* **rel_dir** (*None*) – an optional relative directory to strip from each input
filepath to generate a unique identifier that is joined with
`output_dir` to generate an output path for each segmentation
image. This argument allows for populating nested subdirectories in
`output_dir` that match the shape of the input paths. The path is
converted to an absolute path (if necessary) via
[`fiftyone.core.storage.normalize_path()`](fiftyone.core.storage.md#fiftyone.core.storage.normalize_path)
* **progress** (*None*) – whether to render a progress bar (True/False), use the
default value `fiftyone.config.show_progress_bars` (None), or a
progress callback function to invoke instead
* **pin_memory** (*False*) – whether to pin memory when using a DataLoader. Only
applicable for Torch-based models. This setting can have a significant
impact on memory usage, so it is not enabled by default.
* **\*\*kwargs** – optional model-specific keyword arguments passed through
to the underlying inference implementation
### *class* fiftyone.core.models.ErrorHandlingCollate(skip_failures, ragged_batches, use_numpy, user_collate_fn=None)
Bases: `object`
**Methods:**
| [`handle_errors`](#fiftyone.core.models.ErrorHandlingCollate.handle_errors)(batch) | |
|--------------------------------------------------------------------------------------|----|
#### *static* handle_errors(batch)
### fiftyone.core.models.compute_embeddings(samples, model, embeddings_field=None, batch_size=None, num_workers=None, skip_failures=True, progress=None, pin_memory=False, \*\*kwargs)
Computes embeddings for the samples in the collection using the given
model.
This method supports all the following cases:
- Using an image model to compute embeddings for an image collection
- Using an image model to compute frame embeddings for a video collection
- Using a video model to compute embeddings for a video collection
The `model` must expose embeddings, i.e., [`Model.has_embeddings()`](#fiftyone.core.models.Model.has_embeddings)
must return `True`.
If an `embeddings_field` is provided, the embeddings are saved to the
samples; otherwise, the embeddings are returned in-memory.
* **Parameters:**
* **samples** – a [`fiftyone.core.collections.SampleCollection`](fiftyone.core.collections.md#fiftyone.core.collections.SampleCollection)
* **model** – a [`Model`](#fiftyone.core.models.Model), Hugging Face Transformers model, Ultralytics
model, SuperGradients model, or Lightning Flash model
* **embeddings_field** (*None*) – the name of a field in which to store the
embeddings. When computing video frame embeddings, the “frames.”
prefix is optional
* **batch_size** (*None*) – an optional batch size to use, if the model supports
batching
* **num_workers** (*None*) – the number of workers to use when loading images.
Only applicable for Torch-based models
* **skip_failures** (*True*) – whether to gracefully continue without raising an
error if embeddings cannot be generated for a sample. Only
applicable to [`Model`](#fiftyone.core.models.Model) instances
* **progress** (*None*) – whether to render a progress bar (True/False), use the
default value `fiftyone.config.show_progress_bars` (None), or a
progress callback function to invoke instead
* **pin_memory** (*False*) – whether to pin memory when using a DataLoader. Only
applicable for Torch-based models. This setting can have a significant
impact on memory usage, so it is not enabled by default.
* **\*\*kwargs** – optional model-specific keyword arguments passed through
to the underlying inference implementation
* **Returns:**
- `None`, if an `embeddings_field` is provided
- a `num_samples x num_dim` array of embeddings, when computing
embeddings for image/video collections with image/video models,
respectively, and no `embeddings_field` is provided. If
`skip_failures` is `True` and any errors are detected, a list
of length `num_samples` is returned instead containing all
successfully computed embedding vectors along with `None` entries
for samples for which embeddings could not be computed
- a dictionary mapping sample IDs to `num_frames x num_dim` arrays
of embeddings, when computing frame embeddings for video
collections using an image model. If `skip_failures` is `True`
and any errors are detected, the values of this dictionary will
contain arrays of embeddings for all frames 1, 2, … until the
error occurred, or `None` if no embeddings were computed at all
* **Return type:**
one of the following
### fiftyone.core.models.compute_patch_embeddings(samples, model, patches_field, embeddings_field=None, force_square=False, alpha=None, handle_missing='skip', batch_size=None, num_workers=None, skip_failures=True, progress=None)
Computes embeddings for the image patches defined by `patches_field`
of the samples in the collection using the given model.
This method supports all the following cases:
- Using an image model to compute patch embeddings for an image
collection
- Using an image model to compute frame patch embeddings for a video
collection
The `model` must expose embeddings, i.e., [`Model.has_embeddings()`](#fiftyone.core.models.Model.has_embeddings)
must return `True`.
If an `embeddings_field` is provided, the embeddings are saved to the
samples; otherwise, the embeddings are returned in-memory.
* **Parameters:**
* **samples** – a [`fiftyone.core.collections.SampleCollection`](fiftyone.core.collections.md#fiftyone.core.collections.SampleCollection)
* **model** – a [`Model`](#fiftyone.core.models.Model), Hugging Face Transformers model, Ultralytics
model, SuperGradients model, or Lightning Flash model
* **patches_field** – the name of the field defining the image patches in each
sample to embed. Must be of type
[`fiftyone.core.labels.Detection`](fiftyone.core.labels.md#fiftyone.core.labels.Detection),
[`fiftyone.core.labels.Detections`](fiftyone.core.labels.md#fiftyone.core.labels.Detections),
[`fiftyone.core.labels.Polyline`](fiftyone.core.labels.md#fiftyone.core.labels.Polyline), or
[`fiftyone.core.labels.Polylines`](fiftyone.core.labels.md#fiftyone.core.labels.Polylines). When computing video frame
embeddings, the “frames.” prefix is optional
* **embeddings_field** (*None*) – the name of a label attribute in which to
store the embeddings
* **force_square** (*False*) – whether to minimally manipulate the patch
bounding boxes into squares prior to extraction
* **alpha** (*None*) – an optional expansion/contraction to apply to the patches
before extracting them, in `[-1, inf)`. If provided, the length
and width of the box are expanded (or contracted, when
`alpha < 0`) by `(100 * alpha)%`. For example, set
`alpha = 0.1` to expand the boxes by 10%, and set
`alpha = -0.1` to contract the boxes by 10%
* **handle_missing** ( *"skip"*) –
how to handle images with no patches.
Supported values are:
- ”skip”: skip the image and assign its embedding as `None`
- ”image”: use the whole image as a single patch
- ”error”: raise an error
* **batch_size** (*None*) – an optional batch size to use, if the model supports
batching
* **num_workers** (*None*) – the number of workers to use when loading images.
Only applicable for Torch models
* **skip_failures** (*True*) – whether to gracefully continue without raising an
error if embeddings cannot be generated for a sample
* **progress** (*None*) – whether to render a progress bar (True/False), use the
default value `fiftyone.config.show_progress_bars` (None), or a
progress callback function to invoke instead
* **Returns:**
- `None`, if an `embeddings_field` is provided
- a dict mapping sample IDs to `num_patches x num_dim` arrays of
patch embeddings, when computing patch embeddings for image
collections and no `embeddings_field` is provided. If
`skip_failures` is `True` and any errors are detected, this
dictionary will contain `None` values for any samples for which
embeddings could not be computed
- a dict of dicts mapping sample IDs to frame numbers to
`num_patches x num_dim` arrays of patch embeddings, when
computing patch embeddings for the frames of video collections and
no `embeddings_field` is provided. If `skip_failures` is
`True` and any errors are detected, this nested dict will contain
missing or `None` values to indicate uncomputable embeddings
* **Return type:**
one of the following
### fiftyone.core.models.load_model(model_config_dict, model_path=None, \*\*kwargs)
Loads the model specified by the given [`ModelConfig`](#fiftyone.core.models.ModelConfig) dict.
* **Parameters:**
* **model_config_dict** – a [`ModelConfig`](#fiftyone.core.models.ModelConfig) dict
* **model_path** (*None*) – an optional model path to inject into the
`model_path` field of the model’s `Config` instance, which must
implement the `eta.core.learning.HasPublishedModel` interface.
This is useful when working with a model whose weights are stored
locally and do not need to be downloaded
* **\*\*kwargs** – optional keyword arguments to inject into the model’s
`Config` instance
* **Returns:**
a [`Model`](#fiftyone.core.models.Model) instance
### *class* fiftyone.core.models.ModelConfig(d)
Bases: `ModelConfig`
Base configuration class that encapsulates the name of a [`Model`](#fiftyone.core.models.Model)
and an instance of its associated Config class.
* **Parameters:**
* **type** – the fully-qualified class name of the [`Model`](#fiftyone.core.models.Model) subclass
* **config** – an instance of the Config class associated with the model
**Methods:**
| [`attributes`](#fiftyone.core.models.ModelConfig.attributes)() | Returns a list of class attributes to be serialized. |
|----------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
| [`build`](#fiftyone.core.models.ModelConfig.build)() | Factory method that builds the Model instance from the config specified by this class. |
| [`builder`](#fiftyone.core.models.ModelConfig.builder)() | Returns a ConfigBuilder instance for this class. |
| [`copy`](#fiftyone.core.models.ModelConfig.copy)() | Returns a deep copy of the object. |
| [`custom_attributes`](#fiftyone.core.models.ModelConfig.custom_attributes)([dynamic, private]) | Returns a customizable list of class attributes. |
| [`default`](#fiftyone.core.models.ModelConfig.default)() | Returns the default config instance. |
| [`from_dict`](#fiftyone.core.models.ModelConfig.from_dict)(d) | Constructs a Config object from a JSON dictionary. |
| [`from_json`](#fiftyone.core.models.ModelConfig.from_json)(path, \*args, \*\*kwargs) | Constructs a Serializable object from a JSON file. |
| [`from_kwargs`](#fiftyone.core.models.ModelConfig.from_kwargs)(\*\*kwargs) | Constructs a Config object from keyword arguments. |
| [`from_str`](#fiftyone.core.models.ModelConfig.from_str)(s, \*args, \*\*kwargs) | Constructs a Serializable object from a JSON string. |
| [`get_class_name`](#fiftyone.core.models.ModelConfig.get_class_name)() | Returns the fully-qualified class name string of this object. |
| [`load_default`](#fiftyone.core.models.ModelConfig.load_default)() | Loads the default config instance from file. |
| [`parse_array`](#fiftyone.core.models.ModelConfig.parse_array)(d, key[, default]) | Parses a raw array attribute. |
| [`parse_bool`](#fiftyone.core.models.ModelConfig.parse_bool)(d, key[, default]) | Parses a boolean value. |
| [`parse_categorical`](#fiftyone.core.models.ModelConfig.parse_categorical)(d, key, choices[, default]) | Parses a categorical JSON field, which must take a value from among the given choices. |
| [`parse_dict`](#fiftyone.core.models.ModelConfig.parse_dict)(d, key[, default]) | Parses a dictionary attribute. |
| [`parse_int`](#fiftyone.core.models.ModelConfig.parse_int)(d, key[, default]) | Parses an integer attribute. |
| [`parse_mutually_exclusive_fields`](#fiftyone.core.models.ModelConfig.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`](#fiftyone.core.models.ModelConfig.parse_number)(d, key[, default]) | Parses a number attribute. |
| [`parse_object`](#fiftyone.core.models.ModelConfig.parse_object)(d, key, cls[, default]) | Parses an object attribute. |
| [`parse_object_array`](#fiftyone.core.models.ModelConfig.parse_object_array)(d, key, cls[, default]) | Parses an array of objects. |
| [`parse_object_dict`](#fiftyone.core.models.ModelConfig.parse_object_dict)(d, key, cls[, default]) | Parses a dictionary whose values are objects. |
| [`parse_path`](#fiftyone.core.models.ModelConfig.parse_path)(d, key[, default]) | Parses a path attribute. |
| [`parse_raw`](#fiftyone.core.models.ModelConfig.parse_raw)(d, key[, default]) | Parses a raw (arbitrary) JSON field. |
| [`parse_string`](#fiftyone.core.models.ModelConfig.parse_string)(d, key[, default]) | Parses a string attribute. |
| [`serialize`](#fiftyone.core.models.ModelConfig.serialize)([reflective]) | Serializes the object into a dictionary. |
| [`to_str`](#fiftyone.core.models.ModelConfig.to_str)([pretty_print]) | Returns a string representation of this object. |
| [`validate_all_or_nothing_fields`](#fiftyone.core.models.ModelConfig.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`](#fiftyone.core.models.ModelConfig.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
#### build()
Factory method that builds the Model instance from the config
specified by this class.
* **Returns:**
a Model instance
#### *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.
#### *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.
#### *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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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**](fiftyone.zoo.md#fiftyone.zoo.ConfigError) – if zero or more than one truthy value was found
#### *static* parse_number(d, key, default=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.ConfigError) – if no default value was provided and the key was not
found in the dictionary
#### *static* parse_string(d, key, default=)
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**](fiftyone.zoo.md#fiftyone.zoo.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**](fiftyone.zoo.md#fiftyone.zoo.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.core.models.Model
Bases: `Model`
Abstract base class for models.
This class declares the following conventions:
1. `Model.__init__()` should take a single `config` argument
that is an instance of `Config`
2. Models implement the context manager interface. This means that
models can optionally use context to perform any necessary setup
and teardown, and so any code that builds a model should use the
`with` syntax
**Attributes:**
| [`media_type`](#fiftyone.core.models.Model.media_type) | The media type processed by the model. |
|----------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [`has_logits`](#fiftyone.core.models.Model.has_logits) | Whether this model can generate logits for its predictions. |
| [`has_embeddings`](#fiftyone.core.models.Model.has_embeddings) | Whether this model can generate embeddings. |
| [`can_embed_prompts`](#fiftyone.core.models.Model.can_embed_prompts) | Whether this model can generate prompt embeddings. |
| [`ragged_batches`](#fiftyone.core.models.Model.ragged_batches) | True/False whether [`transforms()`](#fiftyone.core.models.Model.transforms) may return tensors of different sizes. |
| [`transforms`](#fiftyone.core.models.Model.transforms) | The preprocessing function that will/must be applied to each input before prediction, or `None` if no preprocessing is performed. |
| [`preprocess`](#fiftyone.core.models.Model.preprocess) | Whether to apply [`transforms()`](#fiftyone.core.models.Model.transforms) during inference (True) or to assume that they have already been applied (False). |
**Methods:**
| [`predict`](#fiftyone.core.models.Model.predict)(arg) | Performs prediction on the given data. |
|-------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------|
| [`predict_all`](#fiftyone.core.models.Model.predict_all)(args) | Performs prediction on the given iterable of data. |
| [`from_config`](#fiftyone.core.models.Model.from_config)(config) | Instantiates a Configurable class from a Config instance. |
| [`from_dict`](#fiftyone.core.models.Model.from_dict)(d) | Instantiates a Configurable class from a Config dict. |
| [`from_json`](#fiftyone.core.models.Model.from_json)(json_path) | Instantiates a Configurable class from a Config JSON file. |
| [`from_kwargs`](#fiftyone.core.models.Model.from_kwargs)(\*\*kwargs) | Instantiates a Configurable class from keyword arguments defining the attributes of a Config. |
| [`parse`](#fiftyone.core.models.Model.parse)(class_name[, module_name]) | Parses a Configurable subclass name string. |
| [`validate`](#fiftyone.core.models.Model.validate)(config) | Validates that the given config is an instance of Config. |
#### *property* media_type
The media type processed by the model.
Supported values are “image” and “video”.
#### *property* has_logits
Whether this model can generate logits for its predictions.
This method returns `False` by default. Models that can generate
logits should override this via implementing the
[`LogitsMixin`](#fiftyone.core.models.LogitsMixin) interface.
#### *property* has_embeddings
Whether this model can generate embeddings.
This method returns `False` by default. Models that can generate
embeddings should override this via implementing the
[`EmbeddingsMixin`](#fiftyone.core.models.EmbeddingsMixin) interface.
#### *property* can_embed_prompts
Whether this model can generate prompt embeddings.
This method returns `False` by default. Models that can generate
prompt embeddings should override this via implementing the
[`PromptMixin`](#fiftyone.core.models.PromptMixin) interface.
#### *property* ragged_batches
True/False whether [`transforms()`](#fiftyone.core.models.Model.transforms) may return tensors of
different sizes. If True, then passing ragged lists of data to
[`predict_all()`](#fiftyone.core.models.Model.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()`](#fiftyone.core.models.Model.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`](fiftyone.core.labels.md#fiftyone.core.labels.Label) instance or dict of
[`fiftyone.core.labels.Label`](fiftyone.core.labels.md#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()`](#fiftyone.core.models.Model.predict) to each.
* **Parameters:**
**args** – an iterable of data
* **Returns:**
a list of [`fiftyone.core.labels.Label`](fiftyone.core.labels.md#fiftyone.core.labels.Label) instances or a list
of dicts of [`fiftyone.core.labels.Label`](fiftyone.core.labels.md#fiftyone.core.labels.Label) instances
containing the predictions
#### *classmethod* from_config(config)
Instantiates a Configurable class from a Config instance.
#### *classmethod* from_dict(d)
Instantiates a Configurable class from a Config dict.
* **Parameters:**
**d** – a dict to construct a Config
* **Returns:**
an instance of cls
#### *classmethod* from_json(json_path)
Instantiates a Configurable class from a Config JSON file.
* **Parameters:**
**json_path** – path to a JSON file for type Config
* **Returns:**
an instance of cls
#### *classmethod* from_kwargs(\*\*kwargs)
Instantiates a Configurable class from keyword arguments defining
the attributes of a Config.
* **Parameters:**
**\*\*kwargs** – keyword arguments that define the fields of a
Config dict
* **Returns:**
an instance of cls
#### *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](fiftyone.brain.internal.core.elasticsearch.md#fiftyone.brain.internal.core.elasticsearch.ElasticsearchSimilarityConfig.cls)
#### *classmethod* validate(config)
Validates that the given config is an instance of Config.
* **Raises:**
**ConfigurableError** – if config is not an instance of Config
### *class* fiftyone.core.models.LogitsMixin
Bases: `object`
Mixin for [`Model`](#fiftyone.core.models.Model) classes that can generate logits for their
predictions.
This mixin allows for the possibility that only some instances of a class
are capable of generating logits, per the value of the
[`has_logits()`](#fiftyone.core.models.LogitsMixin.has_logits) property.
**Attributes:**
| [`store_logits`](#fiftyone.core.models.LogitsMixin.store_logits) | Whether the model should store logits in its predictions. |
|--------------------------------------------------------------------|-------------------------------------------------------------|
| [`has_logits`](#fiftyone.core.models.LogitsMixin.has_logits) | Whether this model can generate logits. |
#### *property* store_logits
Whether the model should store logits in its predictions.
#### *property* has_logits
Whether this model can generate logits.
### *class* fiftyone.core.models.EmbeddingsMixin
Bases: `object`
Mixin for [`Model`](#fiftyone.core.models.Model) classes that can generate embeddings for
their predictions.
This mixin allows for the possibility that only some instances of a class
are capable of generating embeddings, per the value of the
[`has_embeddings()`](#fiftyone.core.models.EmbeddingsMixin.has_embeddings) property.
**Attributes:**
| [`has_embeddings`](#fiftyone.core.models.EmbeddingsMixin.has_embeddings) | Whether this model has embeddings. |
|----------------------------------------------------------------------------|--------------------------------------|
**Methods:**
| [`get_embeddings`](#fiftyone.core.models.EmbeddingsMixin.get_embeddings)() | Returns the embeddings generated by the last forward pass of the model. |
|------------------------------------------------------------------------------|---------------------------------------------------------------------------|
| [`embed`](#fiftyone.core.models.EmbeddingsMixin.embed)(arg) | Generates an embedding for the given data. |
| [`embed_all`](#fiftyone.core.models.EmbeddingsMixin.embed_all)(args) | Generates embeddings for the given iterable of data. |
#### *property* has_embeddings
Whether this model has embeddings.
#### get_embeddings()
Returns the embeddings generated by the last forward pass of the
model.
By convention, this method should always return an array whose first
axis represents batch size (which will always be 1 when `predict()`
was last used).
* **Returns:**
a numpy array containing the embedding(s)
#### embed(arg)
Generates an embedding for the given data.
Subclasses can override this method to increase efficiency, but, by
default, this method simply calls `predict()` and then returns
[`get_embeddings()`](#fiftyone.core.models.EmbeddingsMixin.get_embeddings).
* **Parameters:**
**arg** – the data. See `predict()` for details
* **Returns:**
a numpy array containing the embedding
#### embed_all(args)
Generates embeddings for the given iterable of data.
Subclasses can override this method to increase efficiency, but, by
default, this method simply iterates over the data and applies
[`embed()`](#fiftyone.core.models.EmbeddingsMixin.embed) to each.
* **Parameters:**
**args** – an iterable of data. See `predict_all()` for details
* **Returns:**
a numpy array containing the embeddings stacked along axis 0
### *class* fiftyone.core.models.PromptMixin
Bases: `object`
Mixin for [`Model`](#fiftyone.core.models.Model) classes that can generate prompt embeddings.
This mixin allows for the possibility that only some instances of a class
are capable of generating prompt embeddings, per the value of the
[`can_embed_prompts()`](#fiftyone.core.models.PromptMixin.can_embed_prompts) property.
**Attributes:**
| [`can_embed_prompts`](#fiftyone.core.models.PromptMixin.can_embed_prompts) | Whether this model can generate prompt embeddings. |
|------------------------------------------------------------------------------|------------------------------------------------------|
**Methods:**
| [`embed_prompt`](#fiftyone.core.models.PromptMixin.embed_prompt)(arg) | Generates an embedding for the given prompt. |
|--------------------------------------------------------------------------|------------------------------------------------|
| [`embed_prompts`](#fiftyone.core.models.PromptMixin.embed_prompts)(args) | Generates embeddings for the given prompts. |
#### *property* can_embed_prompts
Whether this model can generate prompt embeddings.
#### embed_prompt(arg)
Generates an embedding for the given prompt.
* **Parameters:**
**arg** – the prompt
* **Returns:**
a numpy array containing the embedding
#### embed_prompts(args)
Generates embeddings for the given prompts.
Subclasses can override this method to increase efficiency, but, by
default, this method simply iterates over the data and applies
[`embed_prompt()`](#fiftyone.core.models.PromptMixin.embed_prompt) to each.
* **Parameters:**
**args** – an iterable of prompts
* **Returns:**
a numpy array containing the embeddings stacked along axis 0
### *class* fiftyone.core.models.SamplesMixin
Bases: `object`
Mixin for [`Model`](#fiftyone.core.models.Model) classes that need samples for prediction.
Models can implement this mixin to declare that they require one or more
fields of the current sample when performing inference on its media.
The fields are get/set via [`needs_fields()`](#fiftyone.core.models.SamplesMixin.needs_fields), which is a dict that maps
model-specific keys to sample field names:
```default
model.needs_fields = {"key1": "field1", "key2": "field2", ...}
```
**Attributes:**
| [`needs_fields`](#fiftyone.core.models.SamplesMixin.needs_fields) | A dict mapping model-specific keys to sample field names. |
|---------------------------------------------------------------------|-------------------------------------------------------------|
**Methods:**
| [`predict`](#fiftyone.core.models.SamplesMixin.predict)(arg[, sample]) | Performs prediction on the given data. |
|----------------------------------------------------------------------------------|----------------------------------------------------|
| [`predict_all`](#fiftyone.core.models.SamplesMixin.predict_all)(args[, samples]) | Performs prediction on the given iterable of data. |
#### *property* needs_fields
A dict mapping model-specific keys to sample field names.
#### predict(arg, sample=None)
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
* **sample** (*None*) – the [`fiftyone.core.sample.Sample`](fiftyone.core.sample.md#fiftyone.core.sample.Sample) associated
with the data
* **Returns:**
a [`fiftyone.core.labels.Label`](fiftyone.core.labels.md#fiftyone.core.labels.Label) instance or dict of
[`fiftyone.core.labels.Label`](fiftyone.core.labels.md#fiftyone.core.labels.Label) instances containing the
predictions
#### predict_all(args, samples=None)
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()`](#fiftyone.core.models.SamplesMixin.predict) to each.
* **Parameters:**
* **args** – an iterable of data
* **samples** (*None*) – an iterable of [`fiftyone.core.sample.Sample`](fiftyone.core.sample.md#fiftyone.core.sample.Sample)
instances associated with the data
* **Returns:**
a list of [`fiftyone.core.labels.Label`](fiftyone.core.labels.md#fiftyone.core.labels.Label) instances or a list
of dicts of [`fiftyone.core.labels.Label`](fiftyone.core.labels.md#fiftyone.core.labels.Label) instances
containing the predictions
### *class* fiftyone.core.models.TorchModelMixin
Bases: `object`
Mixin for [`Model`](#fiftyone.core.models.Model) classes that support feeding data for inference
via a [`torch.utils.data.DataLoader`](https://docs.pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader).
Models implementing this mixin must expose via their
[`Model.transforms()`](#fiftyone.core.models.Model.transforms) property the
`torchvision:torchvision.transforms` function that will/must be
applied to each input before prediction.
**Attributes:**
| [`has_collate_fn`](#fiftyone.core.models.TorchModelMixin.has_collate_fn) | Whether this model has a custom collate function. |
|----------------------------------------------------------------------------|-----------------------------------------------------|
**Methods:**
| [`collate_fn`](#fiftyone.core.models.TorchModelMixin.collate_fn)(batch) | The collate function to use when creating dataloaders for this model. |
|---------------------------------------------------------------------------|-------------------------------------------------------------------------|
#### *property* has_collate_fn
Whether this model has a custom collate function.
Set this to `True` if you want [`collate_fn()`](#fiftyone.core.models.TorchModelMixin.collate_fn) to be used during
inference.
#### *static* collate_fn(batch)
The collate function to use when creating dataloaders for this
model.
In order to enable this functionality, the model’s
[`has_collate_fn()`](#fiftyone.core.models.TorchModelMixin.has_collate_fn) property must return `True`.
By default, this is the identity function, but subclasses can override
this method as necessary.
Note that this function must be serializable so it is compatible
with multiprocessing for dataloaders.
* **Parameters:**
**batch** – a list of items to collate
* **Returns:**
the collated batch, which will be fed directly to the model
### *class* fiftyone.core.models.SupportsGetItem
Bases: `object`
Mixin for models that support inference with
[`fiftyone.utils.torch.FiftyOneTorchDataset`](fiftyone.utils.torch.md#fiftyone.utils.torch.FiftyOneTorchDataset).
Models that implement this mixin must implement
[`build_get_item()`](#fiftyone.core.models.SupportsGetItem.build_get_item) to build the [`fiftyone.utils.torch.GetItem`](fiftyone.utils.torch.md#fiftyone.utils.torch.GetItem)
instance that defines how their data should be loaded by data loaders.
**Attributes:**
| [`required_keys`](#fiftyone.core.models.SupportsGetItem.required_keys) | The required keys that must be provided as parameters to methods like [`apply_model()`](#fiftyone.core.models.apply_model) and [`compute_embeddings()`](#fiftyone.core.models.compute_embeddings) at runtime. |
|--------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
**Methods:**
| [`build_get_item`](#fiftyone.core.models.SupportsGetItem.build_get_item)([field_mapping]) | Builds the [`fiftyone.utils.torch.GetItem`](fiftyone.utils.torch.md#fiftyone.utils.torch.GetItem) instance that defines how the model's data should be loaded by data loaders. |
|---------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
#### *property* required_keys
The required keys that must be provided as parameters to methods
like [`apply_model()`](#fiftyone.core.models.apply_model) and [`compute_embeddings()`](#fiftyone.core.models.compute_embeddings) at runtime.
#### build_get_item(field_mapping=None)
Builds the [`fiftyone.utils.torch.GetItem`](fiftyone.utils.torch.md#fiftyone.utils.torch.GetItem) instance that
defines how the model’s data should be loaded by data loaders.
* **Parameters:**
**field_mapping** (*None*) – a user-provided dict mapping required keys to
dataset field names
* **Returns:**
a [`fiftyone.utils.torch.GetItem`](fiftyone.utils.torch.md#fiftyone.utils.torch.GetItem) instance
### *class* fiftyone.core.models.ModelManagerConfig(d)
Bases: `ModelManagerConfig`
Config settings for a [`ModelManager`](#fiftyone.core.models.ModelManager).
* **Parameters:**
* **url** (*None*) – the URL of the file
* **google_drive_id** (*None*) – the ID of the file in Google Drive
* **extract_archive** (*None*) – whether to extract the downloaded model, which
is assumed to be an archive
* **delete_archive** (*None*) – whether to delete the archive after extracting
it, if applicable
**Methods:**
| [`attributes`](#fiftyone.core.models.ModelManagerConfig.attributes)() | Returns a list of attributes to be serialized. |
|-----------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
| [`builder`](#fiftyone.core.models.ModelManagerConfig.builder)() | Returns a ConfigBuilder instance for this class. |
| [`copy`](#fiftyone.core.models.ModelManagerConfig.copy)() | Returns a deep copy of the object. |
| [`custom_attributes`](#fiftyone.core.models.ModelManagerConfig.custom_attributes)([dynamic, private]) | Returns a customizable list of class attributes. |
| [`default`](#fiftyone.core.models.ModelManagerConfig.default)() | Returns the default config instance. |
| [`from_dict`](#fiftyone.core.models.ModelManagerConfig.from_dict)(d) | Constructs a Config object from a JSON dictionary. |
| [`from_json`](#fiftyone.core.models.ModelManagerConfig.from_json)(path, \*args, \*\*kwargs) | Constructs a Serializable object from a JSON file. |
| [`from_kwargs`](#fiftyone.core.models.ModelManagerConfig.from_kwargs)(\*\*kwargs) | Constructs a Config object from keyword arguments. |
| [`from_str`](#fiftyone.core.models.ModelManagerConfig.from_str)(s, \*args, \*\*kwargs) | Constructs a Serializable object from a JSON string. |
| [`get_class_name`](#fiftyone.core.models.ModelManagerConfig.get_class_name)() | Returns the fully-qualified class name string of this object. |
| [`load_default`](#fiftyone.core.models.ModelManagerConfig.load_default)() | Loads the default config instance from file. |
| [`parse_array`](#fiftyone.core.models.ModelManagerConfig.parse_array)(d, key[, default]) | Parses a raw array attribute. |
| [`parse_bool`](#fiftyone.core.models.ModelManagerConfig.parse_bool)(d, key[, default]) | Parses a boolean value. |
| [`parse_categorical`](#fiftyone.core.models.ModelManagerConfig.parse_categorical)(d, key, choices[, default]) | Parses a categorical JSON field, which must take a value from among the given choices. |
| [`parse_dict`](#fiftyone.core.models.ModelManagerConfig.parse_dict)(d, key[, default]) | Parses a dictionary attribute. |
| [`parse_int`](#fiftyone.core.models.ModelManagerConfig.parse_int)(d, key[, default]) | Parses an integer attribute. |
| [`parse_mutually_exclusive_fields`](#fiftyone.core.models.ModelManagerConfig.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`](#fiftyone.core.models.ModelManagerConfig.parse_number)(d, key[, default]) | Parses a number attribute. |
| [`parse_object`](#fiftyone.core.models.ModelManagerConfig.parse_object)(d, key, cls[, default]) | Parses an object attribute. |
| [`parse_object_array`](#fiftyone.core.models.ModelManagerConfig.parse_object_array)(d, key, cls[, default]) | Parses an array of objects. |
| [`parse_object_dict`](#fiftyone.core.models.ModelManagerConfig.parse_object_dict)(d, key, cls[, default]) | Parses a dictionary whose values are objects. |
| [`parse_path`](#fiftyone.core.models.ModelManagerConfig.parse_path)(d, key[, default]) | Parses a path attribute. |
| [`parse_raw`](#fiftyone.core.models.ModelManagerConfig.parse_raw)(d, key[, default]) | Parses a raw (arbitrary) JSON field. |
| [`parse_string`](#fiftyone.core.models.ModelManagerConfig.parse_string)(d, key[, default]) | Parses a string attribute. |
| [`serialize`](#fiftyone.core.models.ModelManagerConfig.serialize)([reflective]) | Serializes the object into a dictionary. |
| [`to_str`](#fiftyone.core.models.ModelManagerConfig.to_str)([pretty_print]) | Returns a string representation of this object. |
| [`validate_all_or_nothing_fields`](#fiftyone.core.models.ModelManagerConfig.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`](#fiftyone.core.models.ModelManagerConfig.write_json)(path[, pretty_print]) | Serializes the object and writes it to disk. |
#### attributes()
Returns a list of attributes to be serialized.
* **Returns:**
a list of attributes
#### *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.
#### *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.
#### *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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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**](fiftyone.zoo.md#fiftyone.zoo.ConfigError) – if zero or more than one truthy value was found
#### *static* parse_number(d, key, default=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.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=)
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**](fiftyone.zoo.md#fiftyone.zoo.ConfigError) – if no default value was provided and the key was not
found in the dictionary
#### *static* parse_string(d, key, default=)
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**](fiftyone.zoo.md#fiftyone.zoo.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**](fiftyone.zoo.md#fiftyone.zoo.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.core.models.ModelManager(config)
Bases: `ModelManager`
Class for downloading FiftyOne models from the web.
**Methods:**
| [`attributes`](#fiftyone.core.models.ModelManager.attributes)() | Returns a list of attributes to be serialized. |
|---------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------|
| [`copy`](#fiftyone.core.models.ModelManager.copy)() | Returns a deep copy of the object. |
| [`custom_attributes`](#fiftyone.core.models.ModelManager.custom_attributes)([dynamic, private]) | Returns a customizable list of class attributes. |
| [`download_model`](#fiftyone.core.models.ModelManager.download_model)(model_path[, force]) | Downloads the model to the given local path. |
| [`flush_model`](#fiftyone.core.models.ModelManager.flush_model)(model_path) | Flushes the copy of the model at the given local path, if necessary. |
| [`from_config`](#fiftyone.core.models.ModelManager.from_config)(config) | Instantiates a Configurable class from a Config instance. |
| [`from_dict`](#fiftyone.core.models.ModelManager.from_dict)(d) | Builds the ModelManager subclass from a JSON dictionary. |
| [`from_json`](#fiftyone.core.models.ModelManager.from_json)(json_path) | Instantiates a Configurable class from a Config JSON file. |
| [`from_kwargs`](#fiftyone.core.models.ModelManager.from_kwargs)(\*\*kwargs) | Instantiates a Configurable class from keyword arguments defining the attributes of a Config. |
| [`from_str`](#fiftyone.core.models.ModelManager.from_str)(s, \*args, \*\*kwargs) | Constructs a Serializable object from a JSON string. |
| [`get_class_name`](#fiftyone.core.models.ModelManager.get_class_name)() | Returns the fully-qualified class name string of this object. |
| [`is_model_downloaded`](#fiftyone.core.models.ModelManager.is_model_downloaded)(model_path) | Determines whether the model is downloaded to the given location. |
| [`parse`](#fiftyone.core.models.ModelManager.parse)(class_name[, module_name]) | Parses a Configurable subclass name string. |
| [`serialize`](#fiftyone.core.models.ModelManager.serialize)([reflective]) | Serializes the object into a dictionary. |
| [`to_str`](#fiftyone.core.models.ModelManager.to_str)([pretty_print]) | Returns a string representation of this object. |
| [`validate`](#fiftyone.core.models.ModelManager.validate)(config) | Validates that the given config is an instance of Config. |
| [`write_json`](#fiftyone.core.models.ModelManager.write_json)(path[, pretty_print]) | Serializes the object and writes it to disk. |
| [`upload_model`](#fiftyone.core.models.ModelManager.upload_model)(model_path, \*args, \*\*kwargs) | |
| [`delete_model`](#fiftyone.core.models.ModelManager.delete_model)() | Deletes the model from remote storage. |
#### attributes()
Returns a list of attributes to be serialized.
* **Returns:**
a list of attributes
#### 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
#### download_model(model_path, force=False)
Downloads the model to the given local path.
If the download is forced, any existing model is overwritten. If the
download is not forced, the model will only be downloaded if it does
not already exist locally.
* **Parameters:**
* **model_path** – the path to which to download the model
* **force** – whether to force download the model. If True, the model is
always downloaded. If False, the model is only downloaded if
necessary. The default is False
* **Raises:**
**ModelError** – if model downloading is not currently allowed
#### flush_model(model_path)
Flushes the copy of the model at the given local path, if necessary.
* **Parameters:**
**model_path** – the path on disk for the model
#### *classmethod* from_config(config)
Instantiates a Configurable class from a Config instance.
#### *classmethod* from_dict(d)
Builds the ModelManager subclass from a JSON dictionary.
* **Parameters:**
**d** – a JSON dictionary
* **Returns:**
a ModelManager instance
#### *classmethod* from_json(json_path)
Instantiates a Configurable class from a Config JSON file.
* **Parameters:**
**json_path** – path to a JSON file for type Config
* **Returns:**
an instance of cls
#### *classmethod* from_kwargs(\*\*kwargs)
Instantiates a Configurable class from keyword arguments defining
the attributes of a Config.
* **Parameters:**
**\*\*kwargs** – keyword arguments that define the fields of a
Config dict
* **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.
#### is_model_downloaded(model_path)
Determines whether the model is downloaded to the given location.
If `model_path` is an archive, this method will also return `True` if a
directory with the same basename as `model_path` exists.
* **Parameters:**
**model_path** – the path on disk for the model
* **Returns:**
True/False
#### *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](fiftyone.brain.internal.core.elasticsearch.md#fiftyone.brain.internal.core.elasticsearch.ElasticsearchSimilarityConfig.cls)
#### 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
#### *classmethod* validate(config)
Validates that the given config is an instance of Config.
* **Raises:**
**ConfigurableError** – if config is not an instance of Config
#### 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()`
#### *static* upload_model(model_path, \*args, \*\*kwargs)
#### delete_model()
Deletes the model from remote storage.