fiftyone.core.frame#

Video frames.

Copyright 2017-2025, Voxel51, Inc.
voxel51.com

Functions:

get_default_frame_fields([include_private, ...])

Returns the default fields present on all frames.

Classes:

`Frames`(sample)	An ordered dictionary of `Frame` instances keyed by frame number representing the frames of a video `fiftyone.core.sample.Sample`.
`FramesView`(sample_view)	An ordered dictionary of `FrameView` instances keyed by frame number representing the frames of a video `fiftyone.core.sample.SampleView`.
`Frame`(**kwargs)	A frame in a video `fiftyone.core.sample.Sample`.
`FrameView`(doc, view[, selected_fields, ...])	A view into a `Frame` in a video dataset.

fiftyone.core.frame.get_default_frame_fields(include_private=False, use_db_fields=False)#

Returns the default fields present on all frames.

Parameters:

include_private (False) – whether to include fields starting with _
use_db_fields (False) – whether to return database fields rather than user-facing fields, when applicable

Returns:

a tuple of field names

class fiftyone.core.frame.Frames(sample)#

Bases: object

An ordered dictionary of Frame instances keyed by frame number representing the frames of a video fiftyone.core.sample.Sample.

Frames instances behave like defaultdict(Frame) instances; an empty Frame instance is returned when accessing a new frame number.

Frames instances should never be created manually; they are instantiated automatically when video fiftyone.core.sample.Sample instances are created.

Parameters:: sample – the fiftyone.core.sample.Sample to which the frames are attached

Attributes:

field_names

An ordered tuple of the names of the fields on the frames.

Methods:

`first`()	Returns the first `Frame` for the sample.
`last`()	Returns the last `Frame` for the sample.
`head`([num_frames])	Returns a list of the first few frames for the sample.
`tail`([num_frames])	Returns a list of the last few frames for the sample.
`keys`()	Returns an iterator over the frame numbers with labels in the sample.
`items`()	Returns an iterator over the frame numberes and `Frame` instances for the sample.
`values`()	Returns an iterator over the `Frame` instances for the sample.
`add_frame`(frame_number, frame[, ...])	Adds the frame to this instance.
`delete_frame`(frame_number)	Deletes the given frame number from this instance.
`update`(frames[, overwrite, expand_schema, ...])	Adds the frame labels to this instance.
`merge`(frames[, fields, omit_fields, ...])	Merges the given frames into this instance.
`clear`()	Removes all frames from this sample.
`save`()	Saves all frames for the sample to the database.
`reload`([hard])	Reloads all frames for the sample from the database.

property field_names#: An ordered tuple of the names of the fields on the frames.

first()#

Returns the first Frame for the sample.

Returns:: a Frame

last()#

Returns the last Frame for the sample.

Returns:: a Frame

head(num_frames=3)#

Returns a list of the first few frames for the sample.

If fewer than num_frames frames exist, only the available frames are returned.

Parameters:: num_frames (3) – the number of frames
Returns:: a list of Frame objects

tail(num_frames=3)#

Returns a list of the last few frames for the sample.

If fewer than num_frames frames exist, only the available frames are returned.

Parameters:: num_frames (3) – the number of frames
Returns:: a list of Frame objects

keys()#

Returns an iterator over the frame numbers with labels in the sample.

The frames are traversed in ascending order.

Returns:: a generator that emits frame numbers

items()#

Returns an iterator over the frame numberes and Frame instances for the sample.

The frames are traversed in ascending order.

Returns:: a generator that emits (frame_number, Frame) tuples

values()#

Returns an iterator over the Frame instances for the sample.

The frames are traversed in ascending order.

Returns:: a generator that emits Frame instances

add_frame(frame_number, frame, expand_schema=True, validate=True, dynamic=False)#

Adds the frame to this instance.

If an existing frame with the same frame number exists, it is overwritten.

If the provided frame is a Frame instance that does not belong to a dataset, it is updated in-place to reflect its membership in this dataset. Otherwise, the provided frame is not modified.

Parameters:

frame_number – the frame number
frame – a Frame or FrameView
expand_schema (True) – whether to dynamically add new frame fields encountered to the dataset schema. If False, an error is raised if the frame’s schema is not a subset of the dataset schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

delete_frame(frame_number)#

Deletes the given frame number from this instance.

Parameters:: frame_number – the frame number

update(frames, overwrite=True, expand_schema=True, validate=True, dynamic=False)#

Adds the frame labels to this instance.

Parameters:

frames –
can be any of the following
- a Frames instance
- a dictionary mapping frame numbers to Frame instances
- a dictionary mapping frame numbers to dictionaries mapping label fields to fiftyone.core.labels.Label instances
overwrite (True) – whether to overwrite existing frames
expand_schema (True) – whether to dynamically add new frame fields encountered to the dataset schema. If False, an error is raised if the frame’s schema is not a subset of the dataset schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

merge(frames, fields=None, omit_fields=None, merge_lists=True, merge_embedded_docs=False, overwrite=True, expand_schema=True, validate=True, dynamic=False)#

Merges the given frames into this instance.

The behavior of this method is highly customizable. By default, all top-level fields from the provided frames are merged into existing frames with the same frame numbers (and new frames created as necessary), overwriting any existing values for those fields, with the exception of list fields (e.g., tags) and label list fields (e.g., fiftyone.core.labels.Detections fields), in which case the elements of the lists themselves are merged. In the case of label list fields, labels with the same id in both frames are updated rather than duplicated.

To avoid confusion between missing fields and fields whose value is None, None-valued fields are always treated as missing while merging.

This method can be configured in numerous ways, including:

Whether new fields can be added to the frame schema
Whether list fields should be treated as ordinary fields and merged as a whole rather than merging their elements
Whether to merge only specific fields, or all but certain fields
Mapping input frame fields to different field names of this frame

Parameters:

frames –
can be any of the following
- a Frames instance
- a dictionary mapping frame numbers to Frame instances
- a dictionary mapping frame numbers to dictionaries mapping label fields to fiftyone.core.labels.Label instances
fields (None) – an optional field or iterable of fields to which to restrict the merge. This can also be a dict mapping field names of the input frame to field names of this frame
omit_fields (None) – an optional field or iterable of fields to exclude from the merge
merge_lists (True) – whether to merge the elements of list fields (e.g., tags) and label list fields (e.g., fiftyone.core.labels.Detections fields) rather than merging the entire top-level field like other field types. For label lists fields, existing fiftyone.core.label.Label elements are either replaced (when overwrite is True) or kept (when overwrite is False) when their id matches a label from the provided frames
merge_embedded_docs (False) – whether to merge the attributes of embedded documents (True) rather than merging the entire top-level field (False)
overwrite (True) – whether to overwrite (True) or skip (False) existing fields and label elements
expand_schema (True) – whether to dynamically add new frame fields encountered to the dataset schema. If False, an error is raised if the frame’s schema is not a subset of the dataset schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

clear()#: Removes all frames from this sample.

save()#: Saves all frames for the sample to the database.

reload(hard=False)#

Reloads all frames for the sample from the database.

Parameters:: hard (False) – whether to reload the frame schema in addition to the field values for the frames. This is necessary if new fields may have been added to the dataset’s frame schema

class fiftyone.core.frame.FramesView(sample_view)#

Bases: Frames

An ordered dictionary of FrameView instances keyed by frame number representing the frames of a video fiftyone.core.sample.SampleView.

FramesView instances behave like defaultdict(FrameView) instances; an empty FrameView instance is returned when accessing a new frame number.

FramesView instances should never be created manually; they are instantiated automatically when video fiftyone.core.sample.SampleView instances are created.

Parameters:: sample_view – the fiftyone.core.sample.SampleView to which the frames are attached

Attributes:

field_names

An ordered tuple of the names of the fields on the frames.

Methods:

`add_frame`(frame_number, frame[, ...])	Adds the frame to this instance.
`reload`()	Reloads the view into the frames of the attached sample.
`save`()	Saves all frames for the sample to the database.
`clear`()	Removes all frames from this sample.
`delete_frame`(frame_number)	Deletes the given frame number from this instance.
`first`()	Returns the first `Frame` for the sample.
`head`([num_frames])	Returns a list of the first few frames for the sample.
`items`()	Returns an iterator over the frame numberes and `Frame` instances for the sample.
`keys`()	Returns an iterator over the frame numbers with labels in the sample.
`last`()	Returns the last `Frame` for the sample.
`merge`(frames[, fields, omit_fields, ...])	Merges the given frames into this instance.
`tail`([num_frames])	Returns a list of the last few frames for the sample.
`update`(frames[, overwrite, expand_schema, ...])	Adds the frame labels to this instance.
`values`()	Returns an iterator over the `Frame` instances for the sample.

property field_names#: An ordered tuple of the names of the fields on the frames.

add_frame(frame_number, frame, expand_schema=True, validate=True, dynamic=False)#

Adds the frame to this instance.

If an existing frame with the same frame number exists, it is overwritten.

Unlike Frames.add_frame, the provided frame is never modified in-place. Instead, a new FrameView is constructed internally with the contents of the provided frame.

Parameters:

frame_number – the frame number
frame – a Frame or FrameView
expand_schema (True) – whether to dynamically add new frame fields encountered to the dataset schema. If False, an error is raised if the frame’s schema is not a subset of the dataset schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

reload()#

Reloads the view into the frames of the attached sample.

Calling this method has the following effects:

Clears the in-memory cache of FrameView instances that you have loaded via this object. Any frames that you subsequently access will be loaded directly from the database
Any additions, modifications, or deletions to frame views that you have loaded from this instance but not committed to the database by calling save() will be discarded

Note

FrameView objects are not singletons, so calling this method will not have any effect on FrameView instances that you have previously loaded via this object

Parameters:: hard (False) – whether to reload the frame schema in addition to the field values for the frames. This is necessary if new fields may have been added to the dataset’s frame schema

save()#: Saves all frames for the sample to the database.

clear()#: Removes all frames from this sample.

delete_frame(frame_number)#

Deletes the given frame number from this instance.

Parameters:: frame_number – the frame number

first()#

Returns the first Frame for the sample.

Returns:: a Frame

head(num_frames=3)#

Returns a list of the first few frames for the sample.

If fewer than num_frames frames exist, only the available frames are returned.

Parameters:: num_frames (3) – the number of frames
Returns:: a list of Frame objects

items()#

Returns an iterator over the frame numberes and Frame instances for the sample.

The frames are traversed in ascending order.

Returns:: a generator that emits (frame_number, Frame) tuples

keys()#

Returns an iterator over the frame numbers with labels in the sample.

The frames are traversed in ascending order.

Returns:: a generator that emits frame numbers

last()#

Returns the last Frame for the sample.

Returns:: a Frame

merge(frames, fields=None, omit_fields=None, merge_lists=True, merge_embedded_docs=False, overwrite=True, expand_schema=True, validate=True, dynamic=False)#

Merges the given frames into this instance.

The behavior of this method is highly customizable. By default, all top-level fields from the provided frames are merged into existing frames with the same frame numbers (and new frames created as necessary), overwriting any existing values for those fields, with the exception of list fields (e.g., tags) and label list fields (e.g., fiftyone.core.labels.Detections fields), in which case the elements of the lists themselves are merged. In the case of label list fields, labels with the same id in both frames are updated rather than duplicated.

To avoid confusion between missing fields and fields whose value is None, None-valued fields are always treated as missing while merging.

This method can be configured in numerous ways, including:

Whether new fields can be added to the frame schema
Whether list fields should be treated as ordinary fields and merged as a whole rather than merging their elements
Whether to merge only specific fields, or all but certain fields
Mapping input frame fields to different field names of this frame

Parameters:

frames –
can be any of the following
- a Frames instance
- a dictionary mapping frame numbers to Frame instances
- a dictionary mapping frame numbers to dictionaries mapping label fields to fiftyone.core.labels.Label instances
fields (None) – an optional field or iterable of fields to which to restrict the merge. This can also be a dict mapping field names of the input frame to field names of this frame
omit_fields (None) – an optional field or iterable of fields to exclude from the merge
merge_lists (True) – whether to merge the elements of list fields (e.g., tags) and label list fields (e.g., fiftyone.core.labels.Detections fields) rather than merging the entire top-level field like other field types. For label lists fields, existing fiftyone.core.label.Label elements are either replaced (when overwrite is True) or kept (when overwrite is False) when their id matches a label from the provided frames
merge_embedded_docs (False) – whether to merge the attributes of embedded documents (True) rather than merging the entire top-level field (False)
overwrite (True) – whether to overwrite (True) or skip (False) existing fields and label elements
expand_schema (True) – whether to dynamically add new frame fields encountered to the dataset schema. If False, an error is raised if the frame’s schema is not a subset of the dataset schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

tail(num_frames=3)#

Returns a list of the last few frames for the sample.

If fewer than num_frames frames exist, only the available frames are returned.

Parameters:: num_frames (3) – the number of frames
Returns:: a list of Frame objects

update(frames, overwrite=True, expand_schema=True, validate=True, dynamic=False)#

Adds the frame labels to this instance.

Parameters:

frames –
can be any of the following
- a Frames instance
- a dictionary mapping frame numbers to Frame instances
- a dictionary mapping frame numbers to dictionaries mapping label fields to fiftyone.core.labels.Label instances
overwrite (True) – whether to overwrite existing frames
expand_schema (True) – whether to dynamically add new frame fields encountered to the dataset schema. If False, an error is raised if the frame’s schema is not a subset of the dataset schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

values()#

Returns an iterator over the Frame instances for the sample.

The frames are traversed in ascending order.

Returns:: a generator that emits Frame instances

class fiftyone.core.frame.Frame(**kwargs)#

Bases: Document

A frame in a video fiftyone.core.sample.Sample.

Frames store all information associated with a particular frame of a video, including one or more sets of labels (ground truth, user-provided, or FiftyOne-generated) as well as additional features associated with subsets of the data and/or label sets.

Note

Frame instances that are attached to samples in datasets are singletons, i.e., sample.frames[frame_number] will always return the same Frame instance.

Parameters:: **kwargs – frame fields and values

Attributes:

`dataset_id`
`sample_id`
`dataset`	The dataset to which this document belongs, or `None` if it has not been added to a dataset.
`field_names`	An ordered tuple of the public field names of this document.
`in_dataset`	Whether the document has been added to a dataset.

Methods:

`save`()	Saves the frame to the database.
`clear_field`(field_name)	Clears the value of a field of the document.
`copy`([fields, omit_fields])	Returns a deep copy of the document that has not been added to the database.
`from_dict`(d)	Loads the document from a JSON dictionary.
`from_doc`(doc[, dataset])	Creates a document backed by the given database document.
`from_json`(s)	Loads the document from a JSON string.
`get_field`(field_name)	Gets the value of a field of the document.
`has_field`(field_name)	Determines whether the document has the given field.
`iter_fields`([include_id, include_timestamps])	Returns an iterator over the `(name, value)` pairs of the public fields of the document.
`merge`(document[, fields, omit_fields, ...])	Merges the fields of the document into this document.
`reload`([hard])	Reloads the document from the database.
`set_field`(field_name, value[, create, ...])	Sets the value of a field of the document.
`to_dict`([include_private])	Serializes the document to a JSON dictionary.
`to_json`([pretty_print])	Serializes the document to a JSON string.
`to_mongo_dict`([include_id])	Serializes the document to a BSON dictionary equivalent to the representation that would be stored in the database.
`update_fields`(fields_dict[, expand_schema, ...])	Sets the dictionary of fields on the document.

property dataset_id#

property sample_id#

save()#: Saves the frame to the database.

clear_field(field_name)#

Clears the value of a field of the document.

Parameters:: field_name – the name of the field to clear
Raises:: AttributeError – if the field does not exist

copy(fields=None, omit_fields=None)#

Returns a deep copy of the document that has not been added to the database.

Parameters:

fields (None) – an optional field or iterable of fields to which to restrict the copy. This can also be a dict mapping existing field names to new field names
omit_fields (None) – an optional field or iterable of fields to exclude from the copy

Returns:

a Document

property dataset#: The dataset to which this document belongs, or None if it has not been added to a dataset.

property field_names#: An ordered tuple of the public field names of this document.

classmethod from_dict(d)#

Loads the document from a JSON dictionary.

The returned document will not belong to a dataset.

Returns:: a Document

classmethod from_doc(doc, dataset=None)#

Creates a document backed by the given database document.

Parameters:

doc – a fiftyone.core.odm.document.Document
dataset (None) – the fiftyone.core.dataset.Dataset that the document belongs to, if any

Returns:

a Document

classmethod from_json(s)#

Loads the document from a JSON string.

The returned document will not belong to a dataset.

Parameters:: s – the JSON string
Returns:: a Document

get_field(field_name)#

Gets the value of a field of the document.

Parameters:: field_name – the field name
Returns:: the field value
Raises:: AttributeError – if the field does not exist

has_field(field_name)#

Determines whether the document has the given field.

Parameters:: field_name – the field name
Returns:: True/False

property in_dataset#: Whether the document has been added to a dataset.

iter_fields(include_id=False, include_timestamps=False)#

Returns an iterator over the (name, value) pairs of the public fields of the document.

Parameters:

include_id (False) – whether to include the id field
include_timestamps (False) – whether to include the created_at and last_modified_at fields

Returns:

an iterator that emits (name, value) tuples

merge(document, fields=None, omit_fields=None, merge_lists=True, merge_embedded_docs=False, overwrite=True, expand_schema=True, validate=True, dynamic=False)#

Merges the fields of the document into this document.

The behavior of this method is highly customizable. By default, all top-level fields from the provided document are merged in, overwriting any existing values for those fields, with the exception of list fields (e.g., tags) and label list fields (e.g., fiftyone.core.labels.Detections fields), in which case the elements of the lists themselves are merged. In the case of label list fields, labels with the same id in both documents are updated rather than duplicated.

To avoid confusion between missing fields and fields whose value is None, None-valued fields are always treated as missing while merging.

This method can be configured in numerous ways, including:

Whether new fields can be added to the document schema
Whether list fields should be treated as ordinary fields and merged as a whole rather than merging their elements
Whether to merge only specific fields, or all but certain fields
Mapping input document fields to different field names of this document

Parameters:

document – a Document or DocumentView of the same type
fields (None) – an optional field or iterable of fields to which to restrict the merge. This can also be a dict mapping field names of the input document to field names of this document
omit_fields (None) – an optional field or iterable of fields to exclude from the merge
merge_lists (True) – whether to merge the elements of top-level list fields (e.g., tags) and label list fields (e.g., fiftyone.core.labels.Detections fields) rather than merging the entire top-level field like other field types. For label lists fields, existing fiftyone.core.label.Label elements are either replaced (when overwrite is True) or kept (when overwrite is False) when their id matches a label from the provided document
merge_embedded_docs (False) – whether to merge the attributes of embedded documents (True) rather than merging the entire top-level field (False)
overwrite (True) – whether to overwrite (True) or skip (False) existing fields and label elements
expand_schema (True) – whether to dynamically add new fields encountered to the document schema. If False, an error is raised if any fields are not in the document schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

Raises:

AttributeError – if expand_schema == False and a field does not exist

reload(hard=False)#

Reloads the document from the database.

Parameters:: hard (False) – whether to reload the document’s schema in addition to its field values. This is necessary if new fields may have been added to the document schema

set_field(field_name, value, create=True, validate=True, dynamic=False)#

Sets the value of a field of the document.

Parameters:

field_name – the field name
value – the field value
create (True) – whether to create the field if it does not exist
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

Raises:

ValueError – if field_name is not an allowed field name
AttributeError – if the field does not exist and create == False

to_dict(include_private=False)#

Serializes the document to a JSON dictionary.

Parameters:: include_private (False) – whether to include private fields
Returns:: a JSON dict

to_json(pretty_print=False)#

Serializes the document to a JSON string.

The document ID and private fields are excluded in this representation.

Parameters:: pretty_print (False) – whether to render the JSON in human readable format with newlines and indentations
Returns:: a JSON string

to_mongo_dict(include_id=False)#

Serializes the document to a BSON dictionary equivalent to the representation that would be stored in the database.

Parameters:: include_id (False) – whether to include the document ID
Returns:: a BSON dict

update_fields(fields_dict, expand_schema=True, validate=True, dynamic=False)#

Sets the dictionary of fields on the document.

Parameters:

fields_dict – a dict mapping field names to values
expand_schema (True) – whether to dynamically add new fields encountered to the document schema. If False, an error is raised if any fields are not in the document schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

Raises:

AttributeError – if expand_schema == False and a field does not exist

class fiftyone.core.frame.FrameView(doc, view, selected_fields=None, excluded_fields=None, filtered_fields=None)#

Bases: DocumentView

A view into a Frame in a video dataset.

Like Frame instances, the fields of a FrameView instance can be modified, new fields can be created, and any changes can be saved to the database.

FrameView instances differ from Frame instances in the following ways:

A frame view may contain only a subset of the fields of its source frame, either by selecting and/or excluding specific fields
A frame view may contain array fields or embedded array fields that have been filtered, thus containing only a subset of the array elements from the source frame
Excluded fields of a frame view may not be accessed or modified

Note

FrameView.save() will not delete any excluded fields or filtered array elements from the source frame.

Frame views should never be created manually; they are generated when accessing the frames in a fiftyone.core.view.DatasetView.

Parameters:

doc – a fiftyone.core.odm.frame.DatasetFrameDocument
view – the fiftyone.core.view.DatasetView that the frame belongs to
selected_fields (None) – a set of field names that this frame view is restricted to, if any
excluded_fields (None) – a set of field names that are excluded from this frame view, if any
filtered_fields (None) – a set of field names of list fields that are filtered in this frame view, if any

Attributes:

`dataset_id`
`sample_id`
`dataset`	The dataset to which this document belongs, or `None` if it has not been added to a dataset.
`excluded_field_names`	The set of field names that are excluded on this document view, or `None` if no fields are explicitly excluded.
`field_names`	An ordered tuple of field names of this document view.
`filtered_field_names`	The set of field names or `embedded.field.names` that have been filtered on this document view, or `None` if no fields are filtered.
`in_dataset`	Whether the document has been added to a dataset.
`selected_field_names`	The set of field names that are selected on this document view, or `None` if no fields are explicitly selected.

Methods:

`clear_field`(field_name)	Clears the value of a field of the document.
`copy`([fields, omit_fields])	Returns a deep copy of the document that has not been added to the database.
`get_field`(field_name)	Gets the value of a field of the document.
`has_field`(field_name)	Determines whether the document has the given field.
`iter_fields`([include_id, include_timestamps])	Returns an iterator over the `(name, value)` pairs of the public fields of the document.
`merge`(document[, fields, omit_fields, ...])	Merges the fields of the document into this document.
`save`()	Saves the document view to the database.
`set_field`(field_name, value[, create, ...])	Sets the value of a field of the document.
`to_dict`([include_private])	Serializes the document to a JSON dictionary.
`to_json`([pretty_print])	Serializes the document to a JSON string.
`to_mongo_dict`([include_id])	Serializes the document to a BSON dictionary equivalent to the representation that would be stored in the database.
`update_fields`(fields_dict[, expand_schema, ...])	Sets the dictionary of fields on the document.

property dataset_id#

property sample_id#

clear_field(field_name)#

Clears the value of a field of the document.

Parameters:: field_name – the name of the field to clear
Raises:: AttributeError – if the field does not exist

copy(fields=None, omit_fields=None)#

Returns a deep copy of the document that has not been added to the database.

Parameters:

fields (None) – an optional field or iterable of fields to which to restrict the copy. This can also be a dict mapping existing field names to new field names
omit_fields (None) – an optional field or iterable of fields to exclude from the copy

Returns:

a Document

property dataset#: The dataset to which this document belongs, or None if it has not been added to a dataset.

property excluded_field_names#: The set of field names that are excluded on this document view, or None if no fields are explicitly excluded.

property field_names#

An ordered tuple of field names of this document view.

This may be a subset of all fields of the document if fields have been selected or excluded.

property filtered_field_names#: The set of field names or embedded.field.names that have been filtered on this document view, or None if no fields are filtered.

get_field(field_name)#

Gets the value of a field of the document.

Parameters:: field_name – the field name
Returns:: the field value
Raises:: AttributeError – if the field does not exist

has_field(field_name)#

Determines whether the document has the given field.

Parameters:: field_name – the field name
Returns:: True/False

property in_dataset#: Whether the document has been added to a dataset.

iter_fields(include_id=False, include_timestamps=False)#

Returns an iterator over the (name, value) pairs of the public fields of the document.

Parameters:

include_id (False) – whether to include the id field
include_timestamps (False) – whether to include the created_at and last_modified_at fields

Returns:

an iterator that emits (name, value) tuples

merge(document, fields=None, omit_fields=None, merge_lists=True, merge_embedded_docs=False, overwrite=True, expand_schema=True, validate=True, dynamic=False)#

Merges the fields of the document into this document.

The behavior of this method is highly customizable. By default, all top-level fields from the provided document are merged in, overwriting any existing values for those fields, with the exception of list fields (e.g., tags) and label list fields (e.g., fiftyone.core.labels.Detections fields), in which case the elements of the lists themselves are merged. In the case of label list fields, labels with the same id in both documents are updated rather than duplicated.

To avoid confusion between missing fields and fields whose value is None, None-valued fields are always treated as missing while merging.

This method can be configured in numerous ways, including:

Whether new fields can be added to the document schema
Whether list fields should be treated as ordinary fields and merged as a whole rather than merging their elements
Whether to merge only specific fields, or all but certain fields
Mapping input document fields to different field names of this document

Parameters:

document – a Document or DocumentView of the same type
fields (None) – an optional field or iterable of fields to which to restrict the merge. This can also be a dict mapping field names of the input document to field names of this document
omit_fields (None) – an optional field or iterable of fields to exclude from the merge
merge_lists (True) – whether to merge the elements of top-level list fields (e.g., tags) and label list fields (e.g., fiftyone.core.labels.Detections fields) rather than merging the entire top-level field like other field types. For label lists fields, existing fiftyone.core.label.Label elements are either replaced (when overwrite is True) or kept (when overwrite is False) when their id matches a label from the provided document
merge_embedded_docs (False) – whether to merge the attributes of embedded documents (True) rather than merging the entire top-level field (False)
overwrite (True) – whether to overwrite (True) or skip (False) existing fields and label elements
expand_schema (True) – whether to dynamically add new fields encountered to the document schema. If False, an error is raised if any fields are not in the document schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

Raises:

AttributeError – if expand_schema == False and a field does not exist

save()#: Saves the document view to the database.

property selected_field_names#: The set of field names that are selected on this document view, or None if no fields are explicitly selected.

set_field(field_name, value, create=True, validate=True, dynamic=False)#

Sets the value of a field of the document.

Parameters:

field_name – the field name
value – the field value
create (True) – whether to create the field if it does not exist
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

Raises:

ValueError – if field_name is not an allowed field name
AttributeError – if the field does not exist and create == False

to_dict(include_private=False)#

Serializes the document to a JSON dictionary.

Parameters:: include_private (False) – whether to include private fields
Returns:: a JSON dict

to_json(pretty_print=False)#

Serializes the document to a JSON string.

The document ID and private fields are excluded in this representation.

Parameters:: pretty_print (False) – whether to render the JSON in human readable format with newlines and indentations
Returns:: a JSON string

to_mongo_dict(include_id=False)#

Serializes the document to a BSON dictionary equivalent to the representation that would be stored in the database.

Parameters:: include_id (False) – whether to include the document ID
Returns:: a BSON dict

update_fields(fields_dict, expand_schema=True, validate=True, dynamic=False)#

Sets the dictionary of fields on the document.

Parameters:

fields_dict – a dict mapping field names to values
expand_schema (True) – whether to dynamically add new fields encountered to the document schema. If False, an error is raised if any fields are not in the document schema
validate (True) – whether to validate values for existing fields
dynamic (False) – whether to declare dynamic embedded document fields

Raises:

AttributeError – if expand_schema == False and a field does not exist