fiftyone.core.stages

View stages.

Copyright 2017-2025, Voxel51, Inc.

voxel51.com

Classes:

ViewStage()	Abstract base class for all view stages.
Concat(samples)	Concatenates the contents of the given fiftyone.core.collections.SampleCollection to this collection.
Exclude(sample_ids)	Excludes the samples with the given IDs from a collection.
ExcludeBy(field, values)	Excludes the samples with the given field values from a collection.
ExcludeFields([field_names, meta_filter, ...])	Excludes the fields with the given names from the samples in a collection.
ExcludeFrames(frame_ids[, omit_empty])	Excludes the frames with the given IDs from a video collection.
ExcludeGroups(group_ids[, ordered])	Excludes the groups with the given IDs from a grouped collection.
ExcludeLabels([labels, ids, instance_ids, ...])	Excludes the specified labels from a collection.
Exists(field[, bool])	Returns a view containing the samples in a collection that have (or do not have) a non-None value for the given field or embedded field.
FilterField(field, filter[, only_matches, ...])	Filters the values of a given field or embedded field of each sample in a collection.
FilterLabels(field, filter[, only_matches, ...])	Filters the fiftyone.core.labels.Label field of each sample in a collection.
FilterKeypoints(field[, filter, labels, ...])	Filters the individual fiftyone.core.labels.Keypoint.points elements in the specified keypoints field of each sample in the collection.
GeoNear(point[, location_field, ...])	Sorts the samples in a collection by their proximity to a specified geolocation.
GeoWithin(boundary[, location_field, ...])	Filters the samples in a collection to only match samples whose geolocation is within a specified boundary.
GroupBy(field_or_expr[, order_by, reverse, ...])	Creates a view that groups the samples in a collection by a specified field or expression.
Flatten([stages])	Returns a flattened view that contains all samples in a dynamic grouped collection.
Limit(limit)	Creates a view with at most the given number of samples.
LimitLabels(field, limit)	Limits the number of fiftyone.core.labels.Label instances in the specified labels list field of each sample in a collection.
MapLabels(field, map)	Maps the label values of a fiftyone.core.labels.Label field to new values for each sample in a collection.
MapValues(field, map)	Maps the values in the given field to new values for each sample in a collection.
SetField(field, expr[, _allow_missing, ...])	Sets a field or embedded field on each sample in a collection by evaluating the given expression.
Match(filter)	Filters the samples in the collection by the given filter.
SelectGroupSlices([slices, media_type, ...])	Selects the specified group slice(s) from a grouped collection.
ExcludeGroupSlices([slices, media_type])	Excludes the specified group slice(s) from a grouped collection.
MatchFrames(filter[, omit_empty])	Filters the frames in a video collection by the given filter.
MatchLabels([labels, ids, instance_ids, ...])	Selects the samples from a collection that contain (or do not contain) at least one label that matches the specified criteria.
MatchTags(tags[, bool, all])	Returns a view containing the samples in the collection that have or don't have any/all of the given tag(s).
Mongo(pipeline[, _needs_frames, _group_slices])	A view stage defined by a raw MongoDB aggregation pipeline.
Select(sample_ids[, ordered])	Selects the samples with the given IDs from a collection.
SelectBy(field, values[, ordered])	Selects the samples with the given field values from a collection.
SelectFields([field_names, meta_filter, ...])	Selects only the fields with the given names from the samples in the collection.
SelectFrames(frame_ids[, omit_empty])	Selects the frames with the given IDs from a video collection.
SelectGroups(group_ids[, ordered])	Selects the groups with the given IDs from a grouped collection.
SelectLabels([labels, ids, instance_ids, ...])	Selects only the specified labels from a collection.
Shuffle([seed, _randint])	Randomly shuffles the samples in a collection.
Skip(skip)	Omits the given number of samples from the head of a collection.
SortBy(field_or_expr[, reverse, create_index])	Sorts the samples in a collection by the given field(s) or expression(s).
SortBySimilarity(query[, k, reverse, ...])	Sorts a collection by similarity to a specified query.
Take(size[, seed, _randint])	Randomly samples the given number of samples from a collection.
ToPatches(field[, config, _state])	Creates a view that contains one sample per object patch in the specified field of a collection.
ToEvaluationPatches(eval_key[, config, _state])	Creates a view based on the results of the evaluation with the given key that contains one sample for each true positive, false positive, and false negative example in the collection, respectively.
ToClips(field_or_expr[, config, _state])	Creates a view that contains one sample per clip defined by the given field or expression in a video collection.
ToTrajectories(field[, config, _state])	Creates a view that contains one clip for each unique object trajectory defined by their (label, index) in a frame-level field of a video collection.
ToFrames([config, _state])	Creates a view that contains one sample per frame in a video collection.

Exceptions:

ViewStageError

An error raised when a problem with a ViewStage is encountered.

class fiftyone.core.stages.ViewStage

Bases: object

Abstract base class for all view stages.

ViewStage instances represent logical operations to apply to fiftyone.core.collections.SampleCollection instances, which may decide what subset of samples in the collection should pass though the stage, and also what subset of the contents of each fiftyone.core.sample.Sample should be passed. The output of view stages are represented by a fiftyone.core.view.DatasetView.

Attributes:

has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

exception fiftyone.core.stages.ViewStageError

Bases: Exception

An error raised when a problem with a ViewStage is encountered.

Methods:

add_note	Exception.add_note(note) -- add a note to the exception
with_traceback	Exception.with_traceback(tb) -- set self.__traceback__ to tb and return self.

Attributes:

args

add_note()

Exception.add_note(note) – add a note to the exception

args

with_traceback()

Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.

class fiftyone.core.stages.Concat(samples)

Bases: ViewStage

Concatenates the contents of the given fiftyone.core.collections.SampleCollection to this collection.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("quickstart")

#
# Concatenate two views
#

view1 = dataset.match(F("uniqueness") < 0.2)
view2 = dataset.match(F("uniqueness") > 0.7)

stage = fo.Concat(view2)
view = view1.add_stage(stage)

print(view1)
print(view2)
print(view)

#
# Concatenate two patches views
#

gt_objects = dataset.to_patches("ground_truth")

patches1 = gt_objects[:50]
patches2 = gt_objects[-50:]

stage = fo.Concat(patches2)
patches = patches1.add_stage(stage)

print(patches1)
print(patches2)
print(patches)

Parameters:

samples – a fiftyone.core.collections.SampleCollection whose contents to append to this collection

Attributes:

samples	The fiftyone.core.collections.SampleCollection whose contents to append to this collection.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property samples

The fiftyone.core.collections.SampleCollection whose contents to append to this collection.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.Exclude(sample_ids)

Bases: ViewStage

Excludes the samples with the given IDs from a collection.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(filepath="/path/to/image1.png"),
        fo.Sample(filepath="/path/to/image2.png"),
        fo.Sample(filepath="/path/to/image3.png"),
    ]
)

#
# Exclude the first sample from the dataset
#

sample_id = dataset.first().id
stage = fo.Exclude(sample_id)
view = dataset.add_stage(stage)

#
# Exclude the first and last samples from the dataset
#

sample_ids = [dataset.first().id, dataset.last().id]
stage = fo.Exclude(sample_ids)
view = dataset.add_stage(stage)

Parameters:

sample_ids –

the samples to exclude. Can be any of the following:

• a sample ID

• an iterable of sample IDs

• a fiftyone.core.sample.Sample or fiftyone.core.sample.SampleView

• an iterable of fiftyone.core.sample.Sample or fiftyone.core.sample.SampleView instances

• a fiftyone.core.collections.SampleCollection

Attributes:

sample_ids	The list of sample IDs to exclude.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property sample_ids

The list of sample IDs to exclude.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.ExcludeBy(field, values)

Bases: ViewStage

Excludes the samples with the given field values from a collection.

This stage is typically used to work with categorical fields (strings, ints, and bools). If you want to exclude samples based on floating point fields, use Match.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(filepath="image%d.jpg" % i, int=i, str=str(i))
        for i in range(10)
    ]
)

#
# Create a view excluding samples whose `int` field have the given
# values
#

stage = fo.ExcludeBy("int", [1, 9, 3, 7, 5])
view = dataset.add_stage(stage)
print(view.head(5))

#
# Create a view excluding samples whose `str` field have the given
# values
#

stage = fo.ExcludeBy("str", ["1", "9", "3", "7", "5"])
view = dataset.add_stage(stage)
print(view.head(5))

Parameters:

• field – a field or embedded.field.name

• values – a value or iterable of values to exclude by

Attributes:

field	The field whose values to exclude by.
values	The list of values to exclude by.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property field

The field whose values to exclude by.

property values

The list of values to exclude by.

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.ExcludeFields(field_names=None, meta_filter=None, _allow_missing=False)

Bases: ViewStage

Excludes the fields with the given names from the samples in a collection.

Note that default fields cannot be excluded.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            ground_truth=fo.Classification(label="cat"),
            predictions=fo.Classification(
                label="cat",
                confidence=0.9,
                mood="surly",
            ),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            ground_truth=fo.Classification(label="dog"),
            predictions=fo.Classification(
                label="dog",
                confidence=0.8,
                mood="happy",
            ),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
        ),
    ]
)

#
# Exclude the `predictions` field from all samples
#

stage = fo.ExcludeFields("predictions")
view = dataset.add_stage(stage)

#
# Exclude the `mood` attribute from all classifications in the
# `predictions` field
#

stage = fo.ExcludeFields("predictions.mood")
view = dataset.add_stage(stage)

#
# Exclude the `predictions` field from all samples
#

Parameters:

• field_names (None) – a field name or iterable of field names to exclude. May contain embedded.field.name as well

• meta_filter (None) –

  a filter that dynamically excludes fields in the collection’s schema according to the specified rule, which can be matched against the field’s name, type, description, and/or info. For example:

  • Use meta_filter="2023" or meta_filter={"any": "2023"} to exclude fields that have the string “2023” anywhere in their name, type, description, or info

  • Use meta_filter={"type": "StringField"} or meta_filter={"type": "Classification"} to exclude all string or classification fields, respectively

  • Use meta_filter={"description": "my description"} to exclude fields whose description contains the string “my description”

  • Use meta_filter={"info": "2023"} to exclude fields that have the string “2023” anywhere in their info

  • Use meta_filter={"info.key": "value"}} to exclude fields that have a specific key/value pair in their info

  • Include meta_filter={"include_nested_fields": True, ...} in your meta filter to include all nested fields in the filter

Attributes:

field_names	A list of field names to exclude.
meta_filter	A filter that dynamically excludes fields.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property field_names

A list of field names to exclude.

property meta_filter

A filter that dynamically excludes fields.

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.ExcludeFrames(frame_ids, omit_empty=True)

Bases: ViewStage

Excludes the frames with the given IDs from a video collection.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart-video")

#
# Exclude some specific frames
#

frame_ids = [
    dataset.first().frames.first().id,
    dataset.last().frames.last().id,
]

stage = fo.ExcludeFrames(frame_ids)
view = dataset.add_stage(stage)

print(dataset.count("frames"))
print(view.count("frames"))

Parameters:

• frame_ids –

  the frames to exclude. Can be any of the following:

  • a frame ID

  • an iterable of frame IDs

  • a fiftyone.core.frame.Frame or fiftyone.core.frame.FrameView

  • an iterable of fiftyone.core.frame.Frame or fiftyone.core.frame.FrameView instances

  • a fiftyone.core.collections.SampleCollection whose frames to exclude

• omit_empty (True) – whether to omit samples that have no frames after excluding the specified frames

Attributes:

frame_ids	The list of frame IDs to exclude.
omit_empty	Whether to omit samples that have no frames after filtering.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property frame_ids

The list of frame IDs to exclude.

property omit_empty

Whether to omit samples that have no frames after filtering.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.ExcludeGroups(group_ids, ordered=False)

Bases: ViewStage

Excludes the groups with the given IDs from a grouped collection.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart-groups")

#
# Exclude some specific groups by ID
#

view = dataset.take(2)
group_ids = view.values("group.id")

stage = fo.ExcludeGroups(group_ids)
other_groups = dataset.add_stage(stage)

assert len(set(group_ids) & set(other_groups.values("group.id"))) == 0

Parameters:

groups_ids –

the groups to select. Can be any of the following:

• a group ID

• an iterable of group IDs

• a fiftyone.core.sample.Sample or fiftyone.core.sample.SampleView

• a group dict returned by get_group()

• an iterable of fiftyone.core.sample.Sample or fiftyone.core.sample.SampleView instances

• an iterable of group dicts returned by get_group()

• a fiftyone.core.collections.SampleCollection

Attributes:

group_ids	The list of group IDs to exclude.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property group_ids

The list of group IDs to exclude.

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.ExcludeLabels(labels=None, ids=None, instance_ids=None, tags=None, fields=None, omit_empty=True)

Bases: ViewStage

Excludes the specified labels from a collection.

The returned view will omit samples, sample fields, and individual labels that do not match the specified selection criteria.

You can perform an exclusion via one or more of the following methods:

• Provide the labels argument, which should contain a list of dicts in the format returned by fiftyone.core.session.Session.selected_labels, to exclude specific labels

• Provide the ids argument to exclude labels with specific IDs

• Provide the instance_ids argument to exclude labels with specific instance IDs

• Provide the tags argument to exclude labels with specific tags

If multiple criteria are specified, labels must match all of them in order to be excluded.

By default, the exclusion is applied to all fiftyone.core.labels.Label fields, but you can provide the fields argument to explicitly define the field(s) in which to exclude.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")

#
# Exclude the labels currently selected in the App
#

session = fo.launch_app(dataset)

# Select some labels in the App...

stage = fo.ExcludeLabels(labels=session.selected_labels)
view = dataset.add_stage(stage)

#
# Exclude labels with the specified IDs
#

# Grab some label IDs
ids = [
    dataset.first().ground_truth.detections[0].id,
    dataset.last().predictions.detections[0].id,
]

stage = fo.ExcludeLabels(ids=ids)
view = dataset.add_stage(stage)

print(dataset.count("ground_truth.detections"))
print(view.count("ground_truth.detections"))

print(dataset.count("predictions.detections"))
print(view.count("predictions.detections"))

#
# Exclude labels with the specified tags
#

# Grab some label IDs
ids = [
    dataset.first().ground_truth.detections[0].id,
    dataset.last().predictions.detections[0].id,
]

# Give the labels a "test" tag
dataset = dataset.clone()  # create copy since we're modifying data
dataset.select_labels(ids=ids).tag_labels("test")

print(dataset.count_values("ground_truth.detections.tags"))
print(dataset.count_values("predictions.detections.tags"))

# Exclude the labels via their tag
stage = fo.ExcludeLabels(tags="test")
view = dataset.add_stage(stage)

print(dataset.count("ground_truth.detections"))
print(view.count("ground_truth.detections"))

print(dataset.count("predictions.detections"))
print(view.count("predictions.detections"))

Parameters:

• labels (None) – a list of dicts specifying the labels to exclude in the format returned by fiftyone.core.session.Session.selected_labels

• ids (None) – an ID or iterable of IDs of the labels to exclude

• instance_ids (None) – an instance ID or iterable of instance IDs of the labels to exclude

• tags (None) – a tag or iterable of tags of labels to exclude

• fields (None) – a field or iterable of fields from which to exclude

• omit_empty (True) – whether to omit samples that have no labels after filtering

Attributes:

labels	A list of dicts specifying the labels to exclude.
ids	A list of IDs of labels to exclude.
instance_ids	A list of instance IDs of labels to exclude.
tags	A list of tags of labels to exclude.
fields	A list of fields from which labels are being excluded.
omit_empty	Whether to omit samples that have no labels after filtering.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property labels

A list of dicts specifying the labels to exclude.

property ids

A list of IDs of labels to exclude.

property instance_ids

A list of instance IDs of labels to exclude.

property tags

A list of tags of labels to exclude.

property fields

A list of fields from which labels are being excluded.

property omit_empty

Whether to omit samples that have no labels after filtering.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.Exists(field, bool=None)

Bases: ViewStage

Returns a view containing the samples in a collection that have (or do not have) a non-None value for the given field or embedded field.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            ground_truth=fo.Classification(label="cat"),
            predictions=fo.Classification(label="cat", confidence=0.9),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            ground_truth=fo.Classification(label="dog"),
            predictions=fo.Classification(label="dog", confidence=0.8),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            ground_truth=fo.Classification(label="dog"),
            predictions=fo.Classification(label="dog"),
        ),
        fo.Sample(
            filepath="/path/to/image4.png",
            ground_truth=None,
            predictions=None,
        ),
        fo.Sample(filepath="/path/to/image5.png"),
    ]
)

#
# Only include samples that have a value in their `predictions` field
#

stage = fo.Exists("predictions")
view = dataset.add_stage(stage)

#
# Only include samples that do NOT have a value in their `predictions`
# field
#

stage = fo.Exists("predictions", False)
view = dataset.add_stage(stage)

#
# Only include samples that have prediction confidences
#

stage = fo.Exists("predictions.confidence")
view = dataset.add_stage(stage)

Parameters:

• field – the field name or embedded.field.name

• bool (True) – whether to check if the field exists (None or True) or does not exist (False)

Attributes:

field	The field to check for existence.
bool	Whether to check if the field exists (True) or does not exist (False).
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property field

The field to check for existence.

property bool

Whether to check if the field exists (True) or does not exist (False).

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.FilterField(field, filter, only_matches=True, _new_field=None)

Bases: ViewStage

Filters the values of a given field or embedded field of each sample in a collection.

Values of field for which filter returns False are replaced with None.

Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            ground_truth=fo.Classification(label="cat"),
            predictions=fo.Classification(label="cat", confidence=0.9),
            numeric_field=1.0,
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            ground_truth=fo.Classification(label="dog"),
            predictions=fo.Classification(label="dog", confidence=0.8),
            numeric_field=-1.0,
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            ground_truth=None,
            predictions=None,
            numeric_field=None,
        ),
    ]
)

#
# Only include classifications in the `predictions` field
# whose `label` is "cat"
#

stage = fo.FilterField("predictions", F("label") == "cat")
view = dataset.add_stage(stage)

#
# Only include samples whose `numeric_field` value is positive
#

stage = fo.FilterField("numeric_field", F() > 0)
view = dataset.add_stage(stage)

Parameters:

• field – the field name or embedded.field.name

• filter – a fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that returns a boolean describing the filter to apply

• only_matches (True) – whether to only include samples that match the filter (True) or include all samples (False)

Attributes:

field	The field to filter.
filter	The filter expression.
only_matches	Whether to only include samples that match the filter.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property field

The field to filter.

property filter

The filter expression.

property only_matches

Whether to only include samples that match the filter.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.FilterLabels(field, filter, only_matches=True, trajectories=False, _new_field=None, _validate=True)

Bases: ViewStage

Filters the fiftyone.core.labels.Label field of each sample in a collection.

If the specified field is a single fiftyone.core.labels.Label type, fields for which filter returns False are replaced with None:

• fiftyone.core.labels.Classification

• fiftyone.core.labels.Detection

• fiftyone.core.labels.Polyline

• fiftyone.core.labels.Keypoint

If the specified field is a fiftyone.core.labels.Label list type, the label elements for which filter returns False are omitted from the view:

• fiftyone.core.labels.Classifications

• fiftyone.core.labels.Detections

• fiftyone.core.labels.Polylines

• fiftyone.core.labels.Keypoints

Classifications Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            predictions=fo.Classification(label="cat", confidence=0.9),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            predictions=fo.Classification(label="dog", confidence=0.8),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            predictions=fo.Classification(label="rabbit"),
        ),
        fo.Sample(
            filepath="/path/to/image4.png",
            predictions=None,
        ),
    ]
)

#
# Only include classifications in the `predictions` field whose
# `confidence` is greater than 0.8
#

stage = fo.FilterLabels("predictions", F("confidence") > 0.8)
view = dataset.add_stage(stage)

#
# Only include classifications in the `predictions` field whose `label`
# is "cat" or "dog"
#

stage = fo.FilterLabels("predictions", F("label").is_in(["cat", "dog"]))
view = dataset.add_stage(stage)

Detections Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.1, 0.1, 0.5, 0.5],
                        confidence=0.9,
                    ),
                    fo.Detection(
                        label="dog",
                        bounding_box=[0.2, 0.2, 0.3, 0.3],
                        confidence=0.8,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.5, 0.5, 0.4, 0.4],
                        confidence=0.95,
                    ),
                    fo.Detection(label="rabbit"),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="squirrel",
                        bounding_box=[0.25, 0.25, 0.5, 0.5],
                        confidence=0.5,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image4.png",
            predictions=None,
        ),
    ]
)

#
# Only include detections in the `predictions` field whose `confidence`
# is greater than 0.8
#

stage = fo.FilterLabels("predictions", F("confidence") > 0.8)
view = dataset.add_stage(stage)

#
# Only include detections in the `predictions` field whose `label` is
# "cat" or "dog"
#

stage = fo.FilterLabels("predictions", F("label").is_in(["cat", "dog"]))
view = dataset.add_stage(stage)

#
# Only include detections in the `predictions` field whose bounding box
# area is smaller than 0.2
#

# Bboxes are in [top-left-x, top-left-y, width, height] format
bbox_area = F("bounding_box")[2] * F("bounding_box")[3]

stage = fo.FilterLabels("predictions", bbox_area < 0.2)
view = dataset.add_stage(stage)

Polylines Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            predictions=fo.Polylines(
                polylines=[
                    fo.Polyline(
                        label="lane",
                        points=[[(0.1, 0.1), (0.1, 0.6)]],
                        filled=False,
                    ),
                    fo.Polyline(
                        label="road",
                        points=[[(0.2, 0.2), (0.5, 0.5), (0.2, 0.5)]],
                        filled=True,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            predictions=fo.Polylines(
                polylines=[
                    fo.Polyline(
                        label="lane",
                        points=[[(0.4, 0.4), (0.9, 0.4)]],
                        filled=False,
                    ),
                    fo.Polyline(
                        label="road",
                        points=[[(0.6, 0.6), (0.9, 0.9), (0.6, 0.9)]],
                        filled=True,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            predictions=None,
        ),
    ]
)

#
# Only include polylines in the `predictions` field that are filled
#

stage = fo.FilterLabels("predictions", F("filled") == True)
view = dataset.add_stage(stage)

#
# Only include polylines in the `predictions` field whose `label` is
# "lane"
#

stage = fo.FilterLabels("predictions", F("label") == "lane")
view = dataset.add_stage(stage)

#
# Only include polylines in the `predictions` field with at least
# 3 vertices
#

num_vertices = F("points").map(F().length()).sum()
stage = fo.FilterLabels("predictions", num_vertices >= 3)
view = dataset.add_stage(stage)

Keypoints Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            predictions=fo.Keypoint(
                label="house",
                points=[(0.1, 0.1), (0.1, 0.9), (0.9, 0.9), (0.9, 0.1)],
            ),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            predictions=fo.Keypoint(
                label="window",
                points=[(0.4, 0.4), (0.5, 0.5), (0.6, 0.6)],
            ),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            predictions=None,
        ),
    ]
)

#
# Only include keypoints in the `predictions` field whose `label` is
# "house"
#

stage = fo.FilterLabels("predictions", F("label") == "house")
view = dataset.add_stage(stage)

#
# Only include keypoints in the `predictions` field with less than four
# points
#

stage = fo.FilterLabels("predictions", F("points").length() < 4)
view = dataset.add_stage(stage)

Parameters:

• field – the label field to filter

• filter –

  a fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that returns a boolean describing the filter to apply

• only_matches (True) – whether to only include samples with at least one label after filtering (True) or include all samples (False)

• trajectories (False) – whether to match entire object trajectories for which the object matches the given filter on at least one frame. Only applicable to video datasets and frame-level label fields whose objects have their index attributes populated

Attributes:

field	The label field to filter.
filter	The filter expression.
only_matches	Whether to only include samples that match the filter.
trajectories	Whether to match entire object trajectories for which the object matches the given filter on at least one frame.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property field

The label field to filter.

property filter

The filter expression.

property only_matches

Whether to only include samples that match the filter.

property trajectories

Whether to match entire object trajectories for which the object matches the given filter on at least one frame.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.FilterKeypoints(field, filter=None, labels=None, only_matches=True, _new_field=None)

Bases: ViewStage

Filters the individual fiftyone.core.labels.Keypoint.points elements in the specified keypoints field of each sample in the collection.

Note

Use FilterLabels if you simply want to filter entire fiftyone.core.labels.Keypoint objects in a field.

Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            predictions=fo.Keypoints(
                keypoints=[
                    fo.Keypoint(
                        label="person",
                        points=[(0.1, 0.1), (0.1, 0.9), (0.9, 0.9), (0.9, 0.1)],
                        confidence=[0.7, 0.8, 0.95, 0.99],
                    )
                ]
            )
        ),
        fo.Sample(filepath="/path/to/image2.png"),
    ]
)

dataset.default_skeleton = fo.KeypointSkeleton(
    labels=["nose", "left eye", "right eye", "left ear", "right ear"],
    edges=[[0, 1, 2, 0], [0, 3], [0, 4]],
)

#
# Only include keypoints in the `predictions` field whose
# `confidence` is greater than 0.9
#

stage = fo.FilterKeypoints("predictions", filter=F("confidence") > 0.9)
view = dataset.add_stage(stage)

#
# Only include keypoints in the `predictions` field with less than
# four points
#

stage = fo.FilterKeypoints("predictions", labels=["left eye", "right eye"])
view = dataset.add_stage(stage)

Parameters:

• field – the fiftyone.core.labels.Keypoint or fiftyone.core.labels.Keypoints field to filter

• filter (None) – a fiftyone.core.expressions.ViewExpression or MongoDB expression that returns a boolean, like F("confidence") > 0.5 or F("occluded") == False, to apply elementwise to the specified field, which must be a list of same length as fiftyone.core.labels.Keypoint.points

• labels (None) – a label or iterable of keypoint skeleton labels to keep

• only_matches (True) – whether to only include keypoints/samples with at least one point after filtering (True) or include all keypoints/samples (False)

Attributes:

filter	The filter expression.
labels	An iterable of keypoint skeleton labels to keep.
only_matches	Whether to only include samples that match the filter.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property filter

The filter expression.

property labels

An iterable of keypoint skeleton labels to keep.

property only_matches

Whether to only include samples that match the filter.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.GeoNear(point, location_field=None, min_distance=None, max_distance=None, query=None, create_index=True)

Bases: _GeoStage

Sorts the samples in a collection by their proximity to a specified geolocation.

Note

This stage must be the first stage in any fiftyone.core.view.DatasetView in which it appears.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

TIMES_SQUARE = [-73.9855, 40.7580]

dataset = foz.load_zoo_dataset("quickstart-geo")

#
# Sort the samples by their proximity to Times Square
#

stage = fo.GeoNear(TIMES_SQUARE)
view = dataset.add_stage(stage)

#
# Sort the samples by their proximity to Times Square, and only
# include samples within 5km
#

stage = fo.GeoNear(TIMES_SQUARE, max_distance=5000)
view = dataset.add_stage(stage)

#
# Sort the samples by their proximity to Times Square, and only
# include samples that are in Manhattan
#

import fiftyone.utils.geojson as foug

in_manhattan = foug.geo_within(
    "location.point",
    [
        [
            [-73.949701, 40.834487],
            [-73.896611, 40.815076],
            [-73.998083, 40.696534],
            [-74.031751, 40.715273],
            [-73.949701, 40.834487],
        ]
    ]
)

stage = fo.GeoNear(
    TIMES_SQUARE, location_field="location", query=in_manhattan
)
view = dataset.add_stage(stage)

Parameters:

• point –

  the reference point to compute distances to. Can be any of the following:

  • A [longitude, latitude] list

  • A GeoJSON dict with Point type

  • A fiftyone.core.labels.GeoLocation instance whose point attribute contains the point

• location_field (None) –

  the location data of each sample to use. Can be any of the following:

  • The name of a fiftyone.core.fields.GeoLocation field whose point attribute to use as location data

  • An embedded.field.name containing GeoJSON data to use as location data

  • None, in which case there must be a single fiftyone.core.fields.GeoLocation field on the samples, which is used by default

• min_distance (None) – filter samples that are less than this distance (in meters) from point

• max_distance (None) – filter samples that are greater than this distance (in meters) from point

• query (None) – an optional dict defining a MongoDB read query that samples must match in order to be included in this view

• create_index (True) – whether to create the required spherical index, if necessary

Attributes:

point	The point to search proximity to.
min_distance	The minimum distance for matches, in meters.
max_distance	The maximum distance for matches, in meters.
query	A query dict specifying a match condition.
create_index	Whether to create the required spherical index, if necessary.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
location_field	The location field.
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_, **__)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property point

The point to search proximity to.

property min_distance

The minimum distance for matches, in meters.

property max_distance

The maximum distance for matches, in meters.

property query

A query dict specifying a match condition.

to_mongo(_, **__)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property create_index

Whether to create the required spherical index, if necessary.

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property location_field

The location field.

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.GeoWithin(boundary, location_field=None, strict=True, create_index=True)

Bases: _GeoStage

Filters the samples in a collection to only match samples whose geolocation is within a specified boundary.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

MANHATTAN = [
    [
        [-73.949701, 40.834487],
        [-73.896611, 40.815076],
        [-73.998083, 40.696534],
        [-74.031751, 40.715273],
        [-73.949701, 40.834487],
    ]
]

dataset = foz.load_zoo_dataset("quickstart-geo")

#
# Create a view that only contains samples in Manhattan
#

stage = fo.GeoWithin(MANHATTAN)
view = dataset.add_stage(stage)

Parameters:

• boundary – a fiftyone.core.labels.GeoLocation, fiftyone.core.labels.GeoLocations, GeoJSON dict, or list of coordinates that define a Polygon or MultiPolygon to search within

• location_field (None) –

  the location data of each sample to use. Can be any of the following:

  • The name of a fiftyone.core.fields.GeoLocation field whose point attribute to use as location data

  • An embedded.field.name that directly contains the GeoJSON location data to use

  • None, in which case there must be a single fiftyone.core.fields.GeoLocation field on the samples, which is used by default

• strict (True) – whether a sample’s location data must strictly fall within boundary (True) in order to match, or whether any intersection suffices (False)

• create_index (True) – whether to create the required spherical index, if necessary

Attributes:

boundary	A GeoJSON dict describing the boundary to match within.
strict	Whether matches must be strictly contained in the boundary.
create_index	Whether to create the required spherical index, if necessary.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
location_field	The location field.
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_, **__)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property boundary

A GeoJSON dict describing the boundary to match within.

property strict

Whether matches must be strictly contained in the boundary.

to_mongo(_, **__)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property create_index

Whether to create the required spherical index, if necessary.

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property location_field

The location field.

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.GroupBy(field_or_expr, order_by=None, reverse=False, flat=False, match_expr=None, sort_expr=None, create_index=True, order_by_key=None)

Bases: ViewStage

Creates a view that groups the samples in a collection by a specified field or expression.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("cifar10", split="test")

#
# Take 1000 samples at random and group them by ground truth label
#

stage = fo.GroupBy("ground_truth.label")
view = dataset.take(1000).add_stage(stage)

for group in view.iter_groups():
    print("%s: %d" % (group[0].ground_truth.label, len(group)))

#
# Variation of above operation that arranges the groups in decreasing
# order of size and immediately flattens them
#

from itertools import groupby

stage = fo.GroupBy(
    "ground_truth.label",
    flat=True,
    sort_expr=F().length(),
    reverse=True,
)
view = dataset.take(1000).add_stage(stage)

rle = lambda v: [(k, len(list(g))) for k, g in groupby(v)]
for label, count in rle(view.values("ground_truth.label")):
    print("%s: %d" % (label, count))

Parameters:

• field_or_expr –

  the field or embedded.field.name to group by, or a list of field names defining a compound group key, or a fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that defines the value to group by

• order_by (None) – an optional field by which to order the samples in each group

• reverse (False) – whether to return the results in descending order. Applies to both order_by and sort_expr

• flat (False) – whether to return a grouped collection (False) or a flattened collection (True)

• match_expr (None) –

  an optional fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that defines which groups to include in the output view. If provided, this expression will be evaluated on the list of samples in each group. Only applicable when flat=True

• sort_expr (None) –

  an optional fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that defines how to sort the groups in the output view. If provided, this expression will be evaluated on the list of samples in each group. Only applicable when flat=True

• create_index (True) – whether to create an index, if necessary, to optimize the grouping. Only applicable when grouping by field(s), not expressions

• order_by_key (None) – an optional fixed order_by value representing the first sample in a group. Required for optimized performance. See this guide for more details

Attributes:

outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.
field_or_expr	The field or expression to group by.
order_by	The field by which to order the samples in each group.
order_by_key	The order_by value representing the first sample in a group.
reverse	Whether to sort the groups in descending order.
flat	Whether to generate a flattened collection.
match_expr	An expression to apply to select groups in the output view.
sort_expr	An expression defining how the sort the groups in the output view.
create_index	Whether to create an index, if necessary, to optimize the grouping.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

property field_or_expr

The field or expression to group by.

property order_by

The field by which to order the samples in each group.

property order_by_key

The order_by value representing the first sample in a group.

property reverse

Whether to sort the groups in descending order.

property flat

Whether to generate a flattened collection.

property match_expr

An expression to apply to select groups in the output view.

property sort_expr

An expression defining how the sort the groups in the output view.

property create_index

Whether to create an index, if necessary, to optimize the grouping.

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

class fiftyone.core.stages.Flatten(stages=None)

Bases: ViewStage

Returns a flattened view that contains all samples in a dynamic grouped collection.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("cifar10", split="test")

# Group samples by ground truth label
grouped_view = dataset.take(1000).group_by("ground_truth.label")
print(len(grouped_view))  # 10

# Return a flat view that contains 10 samples from each class
stage = fo.Flatten(fo.Limit(10))
flat_view = grouped_view.add_stage(stage)
print(len(flat_view))  # 100

Parameters:

stages (None) – a ViewStage or list of ViewStage instances to apply to each group’s samples while flattening

Attributes:

outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.
stages	Stage(s) to apply to each group's samples while flattening.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

property stages

Stage(s) to apply to each group’s samples while flattening.

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

class fiftyone.core.stages.Limit(limit)

Bases: ViewStage

Creates a view with at most the given number of samples.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            ground_truth=fo.Classification(label="cat"),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            ground_truth=fo.Classification(label="dog"),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            ground_truth=None,
        ),
    ]
)

#
# Only include the first 2 samples in the view
#

stage = fo.Limit(2)
view = dataset.add_stage(stage)

Parameters:

limit – the maximum number of samples to return. If a non-positive number is provided, an empty view is returned

Attributes:

limit	The maximum number of samples to return.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property limit

The maximum number of samples to return.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.LimitLabels(field, limit)

Bases: ViewStage

Limits the number of fiftyone.core.labels.Label instances in the specified labels list field of each sample in a collection.

The specified field must be one of the following types:

• fiftyone.core.labels.Classifications

• fiftyone.core.labels.Detections

• fiftyone.core.labels.Keypoints

• fiftyone.core.labels.Polylines

Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.1, 0.1, 0.5, 0.5],
                        confidence=0.9,
                    ),
                    fo.Detection(
                        label="dog",
                        bounding_box=[0.2, 0.2, 0.3, 0.3],
                        confidence=0.8,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.5, 0.5, 0.4, 0.4],
                        confidence=0.95,
                    ),
                    fo.Detection(label="rabbit"),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image4.png",
            predictions=None,
        ),
    ]
)

#
# Only include the first detection in the `predictions` field of each
# sample
#

stage = fo.LimitLabels("predictions", 1)
view = dataset.add_stage(stage)

Parameters:

• field – the labels list field to filter

• limit – the maximum number of labels to include in each labels list. If a non-positive number is provided, all lists will be empty

Attributes:

field	The labels field to limit.
limit	The maximum number of labels to allow in each labels list.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property field

The labels field to limit.

property limit

The maximum number of labels to allow in each labels list.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.MapLabels(field, map)

Bases: ViewStage

Maps the label values of a fiftyone.core.labels.Label field to new values for each sample in a collection.

Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            weather=fo.Classification(label="sunny"),
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.1, 0.1, 0.5, 0.5],
                        confidence=0.9,
                    ),
                    fo.Detection(
                        label="dog",
                        bounding_box=[0.2, 0.2, 0.3, 0.3],
                        confidence=0.8,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            weather=fo.Classification(label="cloudy"),
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.5, 0.5, 0.4, 0.4],
                        confidence=0.95,
                    ),
                    fo.Detection(label="rabbit"),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            weather=fo.Classification(label="partly cloudy"),
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="squirrel",
                        bounding_box=[0.25, 0.25, 0.5, 0.5],
                        confidence=0.5,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image4.png",
            predictions=None,
        ),
    ]
)

#
# Map the "partly cloudy" weather label to "cloudy"
#

stage = fo.MapLabels("weather", {"partly cloudy": "cloudy"})
view = dataset.add_stage(stage)

#
# Map "rabbit" and "squirrel" predictions to "other"
#

stage = fo.MapLabels(
    "predictions", {"rabbit": "other", "squirrel": "other"}
)
view = dataset.add_stage(stage)

Parameters:

• field – the labels field to map

• map – a dict mapping label values to new label values

Attributes:

field	The labels field to map.
map	The labels map dict.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property field

The labels field to map.

property map

The labels map dict.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.MapValues(field, map)

Bases: ViewStage

Maps the values in the given field to new values for each sample in a collection.

Examples:

import random

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

ANIMALS = [
    "bear", "bird", "cat", "cow", "dog", "elephant", "giraffe",
    "horse", "sheep", "zebra"
]

dataset = foz.load_zoo_dataset("quickstart")

values = [random.choice(ANIMALS) for _ in range(len(dataset))]
dataset.set_values("str_field", values)
dataset.set_values("list_field", [[v] for v in values])

dataset.set_field("ground_truth.detections.tags", [F("label")]).save()

# Map all animals to string "animal"
mapping = {a: "animal" for a in ANIMALS}

#
# Map values in top-level fields
#

stage = fo.MapValues("str_field", mapping)
view = dataset.add_stage(stage)

print(view.count_values("str_field"))
# {"animal": 200}

stage = fo.MapValues("list_field", mapping)
view = dataset.add_stage(stage)

print(view.count_values("list_field"))
# {"animal": 200}

#
# Map values in nested fields
#

stage = fo.MapValues("ground_truth.detections.label", mapping)
view = dataset.add_stage(stage)

print(view.count_values("ground_truth.detections.label"))
# {"animal": 183, ...}

stage = fo.MapValues("ground_truth.detections.tags", mapping)
view = dataset.add_stage(stage)

print(view.count_values("ground_truth.detections.tags"))
# {"animal": 183, ...}

Parameters:

• field – the field or embedded.field.name to map

• map – a dict mapping values to new values

Attributes:

field	The field to map.
map	The value map dict.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property field

The field to map.

property map

The value map dict.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.SetField(field, expr, _allow_missing=False, _allow_limit=False)

Bases: ViewStage

Sets a field or embedded field on each sample in a collection by evaluating the given expression.

This method can process embedded list fields. To do so, simply append [] to any list component(s) of the field path.

Note

There are two cases where FiftyOne will automatically unwind array fields without requiring you to explicitly specify this via the [] syntax:

Top-level lists: when you specify a field path that refers to a top-level list field of a dataset; i.e., list_field is automatically coerced to list_field[], if necessary.

List fields: When you specify a field path that refers to the list field of a Label class, such as the Detections.detections attribute; i.e., ground_truth.detections.label is automatically coerced to ground_truth.detections[].label, if necessary.

See the examples below for demonstrations of this behavior.

The provided expr is interpreted relative to the document on which the embedded field is being set. For example, if you are setting a nested field field="embedded.document.field", then the expression expr you provide will be applied to the embedded.document document. Note that you can override this behavior by defining an expression that is bound to the root document by prepending "$" to any field name(s) in the expression.

See the examples below for more information.

Note

Note that you cannot set a non-existing top-level field using this stage, since doing so would violate the dataset’s schema. You can, however, first declare a new field via fiftyone.core.dataset.Dataset.add_sample_field() and then populate it in a view via this stage.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("quickstart")

#
# Replace all values of uniqueness that are less than 0.5 with `None`
#

stage = fo.SetField(
    "uniqueness",
    (F("uniqueness") >= 0.5).if_else(F("uniqueness"), None)
)
view = dataset.add_stage(stage)
print(view.bounds("uniqueness"))

#
# Lower bound all object confidences in the `predictions` field by 0.5
#

stage = fo.SetField(
    "predictions.detections.confidence", F("confidence").max(0.5)
)
view = dataset.add_stage(stage)
print(view.bounds("predictions.detections.confidence"))

#
# Add a `num_predictions` property to the `predictions` field that
# contains the number of objects in the field
#

stage = fo.SetField(
    "predictions.num_predictions",
    F("$predictions.detections").length(),
)
view = dataset.add_stage(stage)
print(view.bounds("predictions.num_predictions"))

#
# Set an `is_animal` field on each object in the `predictions` field
# that indicates whether the object is an animal
#

ANIMALS = [
    "bear", "bird", "cat", "cow", "dog", "elephant", "giraffe",
    "horse", "sheep", "zebra"
]

stage = fo.SetField(
    "predictions.detections.is_animal", F("label").is_in(ANIMALS)
)
view = dataset.add_stage(stage)
print(view.count_values("predictions.detections.is_animal"))

Parameters:

• field – the field or embedded.field.name to set

• expr –

  a fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that defines the field value to set

Attributes:

field	The field to set.
expr	The expression to apply.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property field

The field to set.

property expr

The expression to apply.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.Match(filter)

Bases: ViewStage

Filters the samples in the collection by the given filter.

Examples:

import fiftyone as fo
from fiftyone import ViewField as F

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            weather=fo.Classification(label="sunny"),
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.1, 0.1, 0.5, 0.5],
                        confidence=0.9,
                    ),
                    fo.Detection(
                        label="dog",
                        bounding_box=[0.2, 0.2, 0.3, 0.3],
                        confidence=0.8,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image2.jpg",
            weather=fo.Classification(label="cloudy"),
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.5, 0.5, 0.4, 0.4],
                        confidence=0.95,
                    ),
                    fo.Detection(label="rabbit"),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            weather=fo.Classification(label="partly cloudy"),
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="squirrel",
                        bounding_box=[0.25, 0.25, 0.5, 0.5],
                        confidence=0.5,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image4.jpg",
            predictions=None,
        ),
    ]
)

#
# Only include samples whose `filepath` ends with ".jpg"
#

stage = fo.Match(F("filepath").ends_with(".jpg"))
view = dataset.add_stage(stage)

#
# Only include samples whose `weather` field is "sunny"
#

stage = fo.Match(F("weather").label == "sunny")
view = dataset.add_stage(stage)

#
# Only include samples with at least 2 objects in their `predictions`
# field
#

stage = fo.Match(F("predictions").detections.length() >= 2)
view = dataset.add_stage(stage)

#
# Only include samples whose `predictions` field contains at least one
# object with area smaller than 0.2
#

# Bboxes are in [top-left-x, top-left-y, width, height] format
bbox = F("bounding_box")
bbox_area = bbox[2] * bbox[3]

small_boxes = F("predictions.detections").filter(bbox_area < 0.2)
stage = fo.Match(small_boxes.length() > 0)
view = dataset.add_stage(stage)

Parameters:

filter –

a fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that returns a boolean describing the filter to apply

Attributes:

filter	The filter expression.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property filter

The filter expression.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.SelectGroupSlices(slices=None, media_type=None, flat=True, _allow_mixed=False, _force_mixed=False)

Bases: ViewStage

Selects the specified group slice(s) from a grouped collection.

When flat==True, the returned view is a flattened non-grouped view containing the samples from the slice(s) of interest.

When flat=False, the returned view is a grouped collection containing only the slice(s) of interest.

Note

When flat=True, this stage performs a $lookup that pulls the requested slice(s) for each sample in the input collection from the source dataset. As a result, the stage emits unfiltered samples.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_group_field("group", default="ego")

group1 = fo.Group()
group2 = fo.Group()

dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/left-image1.jpg",
            group=group1.element("left"),
        ),
        fo.Sample(
            filepath="/path/to/video1.mp4",
            group=group1.element("ego"),
        ),
        fo.Sample(
            filepath="/path/to/right-image1.jpg",
            group=group1.element("right"),
        ),
        fo.Sample(
            filepath="/path/to/left-image2.jpg",
            group=group2.element("left"),
        ),
        fo.Sample(
            filepath="/path/to/video2.mp4",
            group=group2.element("ego"),
        ),
        fo.Sample(
            filepath="/path/to/right-image2.jpg",
            group=group2.element("right"),
        ),
    ]
)

#
# Retrieve the samples from the "ego" group slice
#

stage = fo.SelectGroupSlices("ego")
view = dataset.add_stage(stage)

#
# Retrieve the samples from the "left" or "right" group slices
#

stage = fo.SelectGroupSlices(["left", "right"])
view = dataset.add_stage(stage)

#
# Select only the "left" and "right" group slices
#

stage = fo.SelectGroupSlices(["left", "right"], flat=False)
view = dataset.add_stage(stage)

#
# Retrieve all image samples
#

stage = fo.SelectGroupSlices(media_type="image")
view = dataset.add_stage(stage)

Parameters:

• slices (None) – a group slice or iterable of group slices to select. If neither argument is provided, a flattened list of all samples is returned

• media_type (None) – a media type or iterable of media types whose slice(s) to select

• flat (True) – whether to return a flattened collection (True) or a grouped collection (False)

Attributes:

slices	The group slice(s) to select.
media_type	The media type(s) whose slices to select.
flat	Whether to generate a flattened collection.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property slices

The group slice(s) to select.

property media_type

The media type(s) whose slices to select.

property flat

Whether to generate a flattened collection.

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.ExcludeGroupSlices(slices=None, media_type=None)

Bases: ViewStage

Excludes the specified group slice(s) from a grouped collection.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_group_field("group", default="ego")

group1 = fo.Group()
group2 = fo.Group()

dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/left-image1.jpg",
            group=group1.element("left"),
        ),
        fo.Sample(
            filepath="/path/to/video1.mp4",
            group=group1.element("ego"),
        ),
        fo.Sample(
            filepath="/path/to/right-image1.jpg",
            group=group1.element("right"),
        ),
        fo.Sample(
            filepath="/path/to/left-image2.jpg",
            group=group2.element("left"),
        ),
        fo.Sample(
            filepath="/path/to/video2.mp4",
            group=group2.element("ego"),
        ),
        fo.Sample(
            filepath="/path/to/right-image2.jpg",
            group=group2.element("right"),
        ),
    ]
)

#
# Exclude the "ego" group slice
#

stage = fo.ExcludeGroupSlices("ego")
view = dataset.add_stage(stage)

#
# Exclude the "left" and "right" group slices
#

stage = fo.ExcludeGroupSlices(["left", "right"])
view = dataset.add_stage(stage)

#
# Exclude all image slices
#

stage = fo.ExcludeGroupSlices(media_type="image")
view = dataset.add_stage(stage)

Parameters:

• slices (None) – a group slice or iterable of group slices to exclude.

• media_type (None) – a media type or iterable of media types whose slice(s) to exclude

Attributes:

slices	The group slice(s) to exclude.
media_type	The media type(s) whose slices to exclude.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property slices

The group slice(s) to exclude.

property media_type

The media type(s) whose slices to exclude.

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.MatchFrames(filter, omit_empty=True)

Bases: ViewStage

Filters the frames in a video collection by the given filter.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("quickstart-video")

#
# Match frames with at least 10 detections
#

num_objects = F("detections.detections").length()
stage = fo.MatchFrames(num_objects > 10)
view = dataset.add_stage(stage)

print(dataset.count())
print(view.count())

print(dataset.count("frames"))
print(view.count("frames"))

Parameters:

• filter –

  a fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that returns a boolean describing the filter to apply

• omit_empty (True) – whether to omit samples with no frame labels after filtering

Attributes:

filter	The filter expression.
omit_empty	Whether to omit samples that have no frames after filtering.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property filter

The filter expression.

property omit_empty

Whether to omit samples that have no frames after filtering.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.MatchLabels(labels=None, ids=None, instance_ids=None, tags=None, filter=None, fields=None, bool=None)

Bases: ViewStage

Selects the samples from a collection that contain (or do not contain) at least one label that matches the specified criteria.

Note that, unlike SelectLabels and FilterLabels, this stage will not filter the labels themselves; it only selects the corresponding samples.

You can perform a selection via one or more of the following methods:

• Provide the labels argument, which should contain a list of dicts in the format returned by fiftyone.core.session.Session.selected_labels, to match specific labels

• Provide the ids argument to match labels with specific IDs

• Provide the instance_ids argument to match labels with specific instance IDs

• Provide the tags argument to match labels with specific tags

• Provide the filter argument to match labels based on a boolean fiftyone.core.expressions.ViewExpression that is applied to each individual fiftyone.core.labels.Label element

• Pass bool=False to negate the operation and instead match samples that do not contain at least one label matching the specified criteria

If multiple criteria are specified, labels must match all of them in order to trigger a sample match.

By default, the selection is applied to all fiftyone.core.labels.Label fields, but you can provide the fields argument to explicitly define the field(s) in which to search.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("quickstart")

#
# Only show samples whose labels are currently selected in the App
#

session = fo.launch_app(dataset)

# Select some labels in the App...

stage = fo.MatchLabels(labels=session.selected_labels)
view = dataset.add_stage(stage)

#
# Only include samples that contain labels with the specified IDs
#

# Grab some label IDs
ids = [
    dataset.first().ground_truth.detections[0].id,
    dataset.last().predictions.detections[0].id,
]

stage = fo.MatchLabels(ids=ids)
view = dataset.add_stage(stage)

print(len(view))
print(view.count("ground_truth.detections"))
print(view.count("predictions.detections"))

#
# Only include samples that contain labels with the specified tags
#

# Grab some label IDs
ids = [
    dataset.first().ground_truth.detections[0].id,
    dataset.last().predictions.detections[0].id,
]

# Give the labels a "test" tag
dataset = dataset.clone()  # create copy since we're modifying data
dataset.select_labels(ids=ids).tag_labels("test")

print(dataset.count_values("ground_truth.detections.tags"))
print(dataset.count_values("predictions.detections.tags"))

# Retrieve the labels via their tag
stage = fo.MatchLabels(tags="test")
view = dataset.add_stage(stage)

print(len(view))
print(view.count("ground_truth.detections"))
print(view.count("predictions.detections"))

#
# Only include samples that contain labels matching a filter
#

filter = F("confidence") > 0.99
stage = fo.MatchLabels(filter=filter, fields="predictions")
view = dataset.add_stage(stage)

print(len(view))
print(view.count("ground_truth.detections"))
print(view.count("predictions.detections"))

Parameters:

• labels (None) – a list of dicts specifying the labels to select in the format returned by fiftyone.core.session.Session.selected_labels

• ids (None) – an ID or iterable of IDs of the labels to select

• instance_ids (None) – an instance ID or iterable of instance IDs of the labels to select

• tags (None) – a tag or iterable of tags of labels to select

• filter (None) –

  a fiftyone.core.expressions.ViewExpression or MongoDB aggregation expression that returns a boolean describing whether to select a given label. In the case of list fields like fiftyone.core.labels.Detections, the filter is applied to the list elements, not the root field

• fields (None) – a field or iterable of fields from which to select

• bool (None) – whether to match samples that have (None or True) or do not have (False) at least one label that matches the specified criteria

Attributes:

labels	A list of dicts specifying the labels to match.
ids	A list of IDs of labels to match.
instance_ids	A list of instance IDs of labels to match.
tags	A list of tags of labels to match.
filter	A filter expression that defines the labels to match.
fields	A list of fields from which labels are being matched.
bool	Whether to match samples that have (None or True) or do not have (False) at least one label that matches the specified criteria.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property labels

A list of dicts specifying the labels to match.

property ids

A list of IDs of labels to match.

property instance_ids

A list of instance IDs of labels to match.

property tags

A list of tags of labels to match.

property filter

A filter expression that defines the labels to match.

property fields

A list of fields from which labels are being matched.

property bool

Whether to match samples that have (None or True) or do not have (False) at least one label that matches the specified criteria.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.MatchTags(tags, bool=None, all=False)

Bases: ViewStage

Returns a view containing the samples in the collection that have or don’t have any/all of the given tag(s).

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(filepath="image1.png", tags=["train"]),
        fo.Sample(filepath="image2.png", tags=["test"]),
        fo.Sample(filepath="image3.png", tags=["train", "test"]),
        fo.Sample(filepath="image4.png"),
    ]
)

#
# Only include samples that have the "test" tag
#

stage = fo.MatchTags("test")
view = dataset.add_stage(stage)

#
# Only include samples that do not have the "test" tag
#

stage = fo.MatchTags("test", bool=False)
view = dataset.add_stage(stage)

#
# Only include samples that have the "test" or "train" tags
#

stage = fo.MatchTags(["test", "train"])
view = dataset.add_stage(stage)

#
# Only include samples that have the "test" and "train" tags
#

stage = fo.MatchTags(["test", "train"], all=True)
view = dataset.add_stage(stage)

#
# Only include samples that do not have the "test" or "train" tags
#

stage = fo.MatchTags(["test", "train"], bool=False)
view = dataset.add_stage(stage)

#
# Only include samples that do not have the "test" and "train" tags
#

stage = fo.MatchTags(["test", "train"], bool=False, all=True)
view = dataset.add_stage(stage)

Parameters:

• tags – the tag or iterable of tags to match

• bool (None) – whether to match samples that have (None or True) or do not have (False) the given tags

• all (False) – whether to match samples that have (or don’t have) all (True) or any (None or False) of the given tags

Attributes:

tags	The list of tags to match.
bool	Whether to match samples that have (True) or do not have (False) any of the given tags.
all	Whether to match samples that have (or don't have) all (True) or any (False) of the given tags.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property tags

The list of tags to match.

property bool

Whether to match samples that have (True) or do not have (False) any of the given tags.

property all

Whether to match samples that have (or don’t have) all (True) or any (False) of the given tags.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.Mongo(pipeline, _needs_frames=None, _group_slices=None)

Bases: ViewStage

A view stage defined by a raw MongoDB aggregation pipeline.

See MongoDB aggregation pipelines for more details.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.1, 0.1, 0.5, 0.5],
                        confidence=0.9,
                    ),
                    fo.Detection(
                        label="dog",
                        bounding_box=[0.2, 0.2, 0.3, 0.3],
                        confidence=0.8,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.5, 0.5, 0.4, 0.4],
                        confidence=0.95,
                    ),
                    fo.Detection(label="rabbit"),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            predictions=fo.Detections(
                detections=[
                    fo.Detection(
                        label="squirrel",
                        bounding_box=[0.25, 0.25, 0.5, 0.5],
                        confidence=0.5,
                    ),
                ]
            ),
        ),
        fo.Sample(
            filepath="/path/to/image4.png",
            predictions=None,
        ),
    ]
)

#
# Extract a view containing the second and third samples in the dataset
#

stage = fo.Mongo([{"$skip": 1}, {"$limit": 2}])
view = dataset.add_stage(stage)

#
# Sort by the number of objects in the `precictions` field
#

stage = fo.Mongo([
    {
        "$addFields": {
            "_sort_field": {
                "$size": {"$ifNull": ["$predictions.detections", []]}
            }
        }
    },
    {"$sort": {"_sort_field": -1}},
    {"$project": {"_sort_field": False}},
])
view = dataset.add_stage(stage)

Parameters:

pipeline – a MongoDB aggregation pipeline (list of dicts)

Attributes:

pipeline	The MongoDB aggregation pipeline.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property pipeline

The MongoDB aggregation pipeline.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.Select(sample_ids, ordered=False)

Bases: ViewStage

Selects the samples with the given IDs from a collection.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")

#
# Create a view containing the currently selected samples in the App
#

session = fo.launch_app(dataset)

# Select samples in the App...

stage = fo.Select(session.selected)
view = dataset.add_stage(stage)

Parameters:

• sample_ids –

  the samples to select. Can be any of the following:

  • a sample ID

  • an iterable of sample IDs

  • an iterable of booleans of same length as the collection encoding which samples to select

  • a fiftyone.core.sample.Sample or fiftyone.core.sample.SampleView

  • an iterable of fiftyone.core.sample.Sample or fiftyone.core.sample.SampleView instances

  • a fiftyone.core.collections.SampleCollection

• ordered (False) – whether to sort the samples in the returned view to match the order of the provided IDs

Attributes:

sample_ids	The list of sample IDs to select.
ordered	Whether to sort the samples in the same order as the IDs.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property sample_ids

The list of sample IDs to select.

property ordered

Whether to sort the samples in the same order as the IDs.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.SelectBy(field, values, ordered=False)

Bases: ViewStage

Selects the samples with the given field values from a collection.

This stage is typically used to work with categorical fields (strings, ints, and bools). If you want to select samples based on floating point fields, use Match.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(filepath="image%d.jpg" % i, int=i, str=str(i))
        for i in range(100)
    ]
)

#
# Create a view containing samples whose `int` field have the given
# values
#

stage = fo.SelectBy("int", [1, 51, 11, 41, 21, 31])
view = dataset.add_stage(stage)
print(view.head(6))

#
# Create a view containing samples whose `str` field have the given
# values, in order
#

stage = fo.SelectBy(
    "str", ["1", "51", "11", "41", "21", "31"], ordered=True
)
view = dataset.add_stage(stage)
print(view.head(6))

Parameters:

• field – a field or embedded.field.name

• values – a value or iterable of values to select by

• ordered (False) – whether to sort the samples in the returned view to match the order of the provided values

Attributes:

field	The field whose values to select by.
values	The list of values to select by.
ordered	Whether to sort the samples in the same order as the IDs.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property field

The field whose values to select by.

property values

The list of values to select by.

property ordered

Whether to sort the samples in the same order as the IDs.

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.SelectFields(field_names=None, meta_filter=None, _allow_missing=False, _media_types=None)

Bases: ViewStage

Selects only the fields with the given names from the samples in the collection. All other fields are excluded.

Note that default sample fields are always selected.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            uniqueness=1.0,
            ground_truth=fo.Detections(
                detections=[
                    fo.Detection(
                        label="cat",
                        bounding_box=[0.1, 0.1, 0.5, 0.5],
                        mood="surly",
                        age=51,
                    ),
                    fo.Detection(
                        label="dog",
                        bounding_box=[0.2, 0.2, 0.3, 0.3],
                        mood="happy",
                        age=52,
                    ),
                ]
            )
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            uniqueness=0.0,
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
        ),
    ]
)

#
# Include only the default fields on each sample
#

stage = fo.SelectFields()
view = dataset.add_stage(stage)

#
# Include only the `uniqueness` field (and the default fields) on each
# sample
#

stage = fo.SelectFields("uniqueness")
view = dataset.add_stage(stage)

#
# Include only the `mood` attribute (and the default attributes) of
# each `Detection` in the `ground_truth` field
#

stage = fo.SelectFields("ground_truth.detections.mood")
view = dataset.add_stage(stage)

Parameters:

• field_names (None) – a field name or iterable of field names to select. May contain embedded.field.name as well

• meta_filter (None) –

  a filter that dynamically selects fields in the collection’s schema according to the specified rule, which can be matched against the field’s name, type, description, and/or info. For example:

  • Use meta_filter="2023" or meta_filter={"any": "2023"} to select fields that have the string “2023” anywhere in their name, type, description, or info

  • Use meta_filter={"type": "StringField"} or meta_filter={"type": "Classification"} to select all string or classification fields, respectively

  • Use meta_filter={"description": "my description"} to select fields whose description contains the string “my description”

  • Use meta_filter={"info": "2023"} to select fields that have the string “2023” anywhere in their info

  • Use meta_filter={"info.key": "value"}} to select fields that have a specific key/value pair in their info

  • Include meta_filter={"include_nested_fields": True, ...} in your meta filter to include all nested fields in the filter

Attributes:

field_names	A list of field names to select.
meta_filter	A filter that dynamically selects fields.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property field_names

A list of field names to select.

property meta_filter

A filter that dynamically selects fields.

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.SelectFrames(frame_ids, omit_empty=True)

Bases: ViewStage

Selects the frames with the given IDs from a video collection.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart-video")

#
# Select some specific frames
#

frame_ids = [
    dataset.first().frames.first().id,
    dataset.last().frames.last().id,
]

stage = fo.SelectFrames(frame_ids)
view = dataset.add_stage(stage)

print(dataset.count())
print(view.count())

print(dataset.count("frames"))
print(view.count("frames"))

Parameters:

• frame_ids –

  the frames to select. Can be any of the following:

  • a frame ID

  • an iterable of frame IDs

  • a fiftyone.core.frame.Frame or fiftyone.core.frame.FrameView

  • an iterable of fiftyone.core.frame.Frame or fiftyone.core.frame.FrameView instances

  • a fiftyone.core.collections.SampleCollection whose frames to select

• omit_empty (True) – whether to omit samples that have no frames after selecting the specified frames

Attributes:

frame_ids	The list of frame IDs to select.
omit_empty	Whether to omit samples that have no labels after filtering.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property frame_ids

The list of frame IDs to select.

property omit_empty

Whether to omit samples that have no labels after filtering.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.SelectGroups(group_ids, ordered=False)

Bases: ViewStage

Selects the groups with the given IDs from a grouped collection.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart-groups")

#
# Select some specific groups by ID
#

group_ids = dataset.take(10).values("group.id")

stage = fo.SelectGroups(group_ids)
view = dataset.add_stage(stage)

assert set(view.values("group.id")) == set(group_ids)

stage = fo.SelectGroups(group_ids, ordered=True)
view = dataset.add_stage(stage)

assert view.values("group.id") == group_ids

Parameters:

• groups_ids –

  the groups to select. Can be any of the following:

  • a group ID

  • an iterable of group IDs

  • a fiftyone.core.sample.Sample or fiftyone.core.sample.SampleView

  • a group dict returned by get_group()

  • an iterable of fiftyone.core.sample.Sample or fiftyone.core.sample.SampleView instances

  • an iterable of group dicts returned by get_group()

  • a fiftyone.core.collections.SampleCollection

• ordered (False) – whether to sort the groups in the returned view to match the order of the provided IDs

Attributes:

group_ids	The list of group IDs to select.
ordered	Whether to sort the groups in the same order as the IDs.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property group_ids

The list of group IDs to select.

property ordered

Whether to sort the groups in the same order as the IDs.

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.SelectLabels(labels=None, ids=None, instance_ids=None, tags=None, fields=None, omit_empty=True)

Bases: ViewStage

Selects only the specified labels from a collection.

The returned view will omit samples, sample fields, and individual labels that do not match the specified selection criteria.

You can perform a selection via one or more of the following methods:

• Provide the labels argument, which should contain a list of dicts in the format returned by fiftyone.core.session.Session.selected_labels, to select specific labels

• Provide the ids argument to select labels with specific IDs

• Provide the instance_ids argument to select labels with specific instance IDs

• Provide the tags argument to select labels with specific tags

If multiple criteria are specified, labels must match all of them in order to be selected.

By default, the selection is applied to all fiftyone.core.labels.Label fields, but you can provide the fields argument to explicitly define the field(s) in which to select.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")

#
# Only include the labels currently selected in the App
#

session = fo.launch_app(dataset)

# Select some labels in the App...

stage = fo.SelectLabels(labels=session.selected_labels)
view = dataset.add_stage(stage)

#
# Only include labels with the specified IDs
#

# Grab some label IDs
ids = [
    dataset.first().ground_truth.detections[0].id,
    dataset.last().predictions.detections[0].id,
]

stage = fo.SelectLabels(ids=ids)
view = dataset.add_stage(stage)

print(view.count("ground_truth.detections"))
print(view.count("predictions.detections"))

#
# Only include labels with the specified tags
#

# Grab some label IDs
ids = [
    dataset.first().ground_truth.detections[0].id,
    dataset.last().predictions.detections[0].id,
]

# Give the labels a "test" tag
dataset = dataset.clone()  # create copy since we're modifying data
dataset.select_labels(ids=ids).tag_labels("test")

print(dataset.count_values("ground_truth.detections.tags"))
print(dataset.count_values("predictions.detections.tags"))

# Retrieve the labels via their tag
stage = fo.SelectLabels(tags="test")
view = dataset.add_stage(stage)

print(view.count("ground_truth.detections"))
print(view.count("predictions.detections"))

Parameters:

• labels (None) – a list of dicts specifying the labels to select in the format returned by fiftyone.core.session.Session.selected_labels

• ids (None) – an ID or iterable of IDs of the labels to select

• instance_ids (None) – an instance ID or iterable of instance IDs of the labels to select

• tags (None) – a tag or iterable of tags of labels to select

• fields (None) – a field or iterable of fields from which to select

• omit_empty (True) – whether to omit samples that have no labels after filtering

Attributes:

labels	A list of dicts specifying the labels to select.
ids	A list of IDs of labels to select.
instance_ids	A list of instance IDs of labels to select.
tags	A list of tags of labels to select.
fields	A list of fields from which labels are being selected.
omit_empty	Whether to omit samples that have no labels after filtering.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property labels

A list of dicts specifying the labels to select.

property ids

A list of IDs of labels to select.

property instance_ids

A list of instance IDs of labels to select.

property tags

A list of tags of labels to select.

property fields

A list of fields from which labels are being selected.

property omit_empty

Whether to omit samples that have no labels after filtering.

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.Shuffle(seed=None, _randint=None)

Bases: ViewStage

Randomly shuffles the samples in a collection.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            ground_truth=fo.Classification(label="cat"),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            ground_truth=fo.Classification(label="dog"),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            ground_truth=None,
        ),
    ]
)

#
# Return a view that contains a randomly shuffled version of the
# samples in the dataset
#

stage = fo.Shuffle()
view = dataset.add_stage(stage)

#
# Shuffle the samples with a fixed random seed
#

stage = fo.Shuffle(seed=51)
view = dataset.add_stage(stage)

Parameters:

seed (None) – an optional random seed to use when shuffling the samples

Attributes:

seed	The random seed to use, or None.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property seed

The random seed to use, or None.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.Skip(skip)

Bases: ViewStage

Omits the given number of samples from the head of a collection.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            ground_truth=fo.Classification(label="cat"),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            ground_truth=fo.Classification(label="dog"),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            ground_truth=fo.Classification(label="rabbit"),
        ),
        fo.Sample(
            filepath="/path/to/image4.png",
            ground_truth=None,
        ),
    ]
)

#
# Omit the first two samples from the dataset
#

stage = fo.Skip(2)
view = dataset.add_stage(stage)

Parameters:

skip – the number of samples to skip. If a non-positive number is provided, no samples are omitted

Attributes:

skip	The number of samples to skip.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property skip

The number of samples to skip.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.SortBy(field_or_expr, reverse=False, create_index=True)

Bases: ViewStage

Sorts the samples in a collection by the given field(s) or expression(s).

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("quickstart")

#
# Sort the samples by their `uniqueness` field in ascending order
#

stage = fo.SortBy("uniqueness", reverse=False)
view = dataset.add_stage(stage)

#
# Sorts the samples in descending order by the number of detections in
# their `predictions` field whose bounding box area is less than 0.2
#

# Bboxes are in [top-left-x, top-left-y, width, height] format
bbox = F("bounding_box")
bbox_area = bbox[2] * bbox[3]

small_boxes = F("predictions.detections").filter(bbox_area < 0.2)
stage = fo.SortBy(small_boxes.length(), reverse=True)
view = dataset.add_stage(stage)

#
# Performs a compound sort where samples are first sorted in descending
# order by number of detections and then in ascending order of
# uniqueness for samples with the same number of predictions
#

stage = fo.SortBy(
    [
        (F("predictions.detections").length(), -1),
        ("uniqueness", 1),
    ]
)
view = dataset.add_stage(stage)

num_objects, uniqueness = view[:5].values(
    [F("predictions.detections").length(), "uniqueness"]
)
print(list(zip(num_objects, uniqueness)))

Parameters:

• field_or_expr –

  the field(s) or expression(s) to sort by. This can be any of the following:

  • a field to sort by

  • an embedded.field.name to sort by

  • a fiftyone.core.expressions.ViewExpression or a MongoDB aggregation expression that defines the quantity to sort by

  • a list of (field_or_expr, order) tuples defining a compound sort criteria, where field_or_expr is a field or expression as defined above, and order can be 1 or any string starting with “a” for ascending order, or -1 or any string starting with “d” for descending order

• reverse (False) – whether to return the results in descending order

• create_index (True) – whether to create an index, if necessary, to optimize the sort. Only applicable when sorting by field(s), not expressions

Attributes:

field_or_expr	The field or expression to sort by.
reverse	Whether to return the results in descending order.
create_index	Whether to create an index, if necessary, to optimize the sort.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property field_or_expr

The field or expression to sort by.

property reverse

Whether to return the results in descending order.

property create_index

Whether to create an index, if necessary, to optimize the sort.

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.SortBySimilarity(query, k=None, reverse=False, dist_field=None, brain_key=None, _state=None)

Bases: ViewStage

Sorts a collection by similarity to a specified query.

In order to use this stage, you must first use fiftyone.brain.compute_similarity() to index your dataset by similarity.

Examples:

import fiftyone as fo
import fiftyone.brain as fob
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")

fob.compute_similarity(
    dataset, model="clip-vit-base32-torch", brain_key="clip"
)

#
# Sort samples by their similarity to a sample by its ID
#

query_id = dataset.first().id

stage = fo.SortBySimilarity(query_id, k=5)
view = dataset.add_stage(stage)

#
# Sort samples by their similarity to a manually computed vector
#

model = foz.load_zoo_model("clip-vit-base32-torch")
embeddings = dataset.take(2, seed=51).compute_embeddings(model)
query = embeddings.mean(axis=0)

stage = fo.SortBySimilarity(query, k=5)
view = dataset.add_stage(stage)

#
# Sort samples by their similarity to a text prompt
#

query = "kites high in the air"

stage = fo.SortBySimilarity(query, k=5)
view = dataset.add_stage(stage)

Parameters:

• query –

  the query, which can be any of the following:

  • an ID or iterable of IDs

  • a num_dims vector or num_queries x num_dims array of vectors

  • a prompt or iterable of prompts (if supported by the index)

• k (None) – the number of matches to return. By default, the entire collection is sorted

• reverse (False) – whether to sort by least similarity (True) or greatest similarity (False). Some backends may not support least similarity

• dist_field (None) – the name of a float field in which to store the distance of each example to the specified query. The field is created if necessary

• brain_key (None) – the brain key of an existing fiftyone.brain.compute_similarity() run on the dataset. If not specified, the dataset must have an applicable run, which will be used by default

Attributes:

query	The query.
k	The number of matches to return.
reverse	Whether to sort by least similarity.
dist_field	The field to store similarity distances, if any.
brain_key	The brain key of the similarity index to use.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.

property query

The query.

property k

The number of matches to return.

property reverse

Whether to sort by least similarity.

property dist_field

The field to store similarity distances, if any.

property brain_key

The brain key of the similarity index to use.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

class fiftyone.core.stages.Take(size, seed=None, _randint=None)

Bases: ViewStage

Randomly samples the given number of samples from a collection.

Examples:

import fiftyone as fo

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            ground_truth=fo.Classification(label="cat"),
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            ground_truth=fo.Classification(label="dog"),
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            ground_truth=fo.Classification(label="rabbit"),
        ),
        fo.Sample(
            filepath="/path/to/image4.png",
            ground_truth=None,
        ),
    ]
)

#
# Take two random samples from the dataset
#

stage = fo.Take(2)
view = dataset.add_stage(stage)

#
# Take two random samples from the dataset with a fixed seed
#

stage = fo.Take(2, seed=51)
view = dataset.add_stage(stage)

Parameters:

• size – the number of samples to return. If a non-positive number is provided, an empty view is returned

• seed (None) – an optional random seed to use when selecting the samples

Attributes:

size	The number of samples to return.
seed	The random seed to use, or None.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

to_mongo(_)	Returns the MongoDB aggregation pipeline for the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property size

The number of samples to return.

property seed

The random seed to use, or None.

to_mongo(_)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.ToPatches(field, config=None, _state=None, **kwargs)

Bases: ViewStage

Creates a view that contains one sample per object patch in the specified field of a collection.

A sample_id field will be added that records the sample ID from which each patch was taken.

By default, fields other than field and the default sample fields will not be included in the returned view.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")

session = fo.launch_app(dataset)

#
# Create a view containing the ground truth patches
#

stage = fo.ToPatches("ground_truth")
view = dataset.add_stage(stage)
print(view)

session.view = view

Parameters:

• field – the patches field, which must be of type fiftyone.core.labels.Detections, fiftyone.core.labels.Polylines, or fiftyone.core.labels.Keypoints

• config (None) – an optional dict of keyword arguments for fiftyone.core.patches.make_patches_dataset() specifying how to perform the conversion

• **kwargs – optional keyword arguments for fiftyone.core.patches.make_patches_dataset() specifying how to perform the conversion

Attributes:

has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
field	The patches field.
config	Parameters specifying how to perform the conversion.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

property field

The patches field.

property config

Parameters specifying how to perform the conversion.

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.ToEvaluationPatches(eval_key, config=None, _state=None, **kwargs)

Bases: ViewStage

Creates a view based on the results of the evaluation with the given key that contains one sample for each true positive, false positive, and false negative example in the collection, respectively.

True positive examples will result in samples with both their ground truth and predicted fields populated, while false positive/negative examples wilL only have one of their corresponding predicted/ground truth fields populated, respectively.

If multiple predictions are matched to a ground truth object (e.g., if the evaluation protocol includes a crowd attribute), then all matched predictions will be stored in the single sample along with the ground truth object.

The returned dataset will also have top-level type and iou fields populated based on the evaluation results for that example, as well as a sample_id field recording the sample ID of the example, and a crowd field if the evaluation protocol defines a crowd attribute.

Note

The returned view will contain patches for the contents of this collection, which may differ from the view on which the eval_key evaluation was performed. This may exclude some labels that were evaluated and/or include labels that were not evaluated.

If you would like to see patches for the exact view on which an evaluation was performed, first call load_evaluation_view() to load the view and then convert to patches.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")
dataset.evaluate_detections("predictions", eval_key="eval")

session = fo.launch_app(dataset)

#
# Create a patches view for the evaluation results
#

stage = fo.ToEvaluationPatches("eval")
view = dataset.add_stage(stage)
print(view)

session.view = view

Parameters:

• eval_key – an evaluation key that corresponds to the evaluation of ground truth/predicted fields that are of type fiftyone.core.labels.Detections, fiftyone.core.labels.Polylines, or :class:`fiftyone.core.labels.Keypoints

• config (None) – an optional dict of keyword arguments for fiftyone.core.patches.make_evaluation_patches_dataset() specifying how to perform the conversion

• **kwargs – optional keyword arguments for fiftyone.core.patches.make_evaluation_patches_dataset() specifying how to perform the conversion

Attributes:

has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
eval_key	The evaluation key to extract patches for.
config	Parameters specifying how to perform the conversion.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

property eval_key

The evaluation key to extract patches for.

property config

Parameters specifying how to perform the conversion.

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.ToClips(field_or_expr, config=None, _state=None, **kwargs)

Bases: ViewStage

Creates a view that contains one sample per clip defined by the given field or expression in a video collection.

The returned view will contain:

• A sample_id field that records the sample ID from which each clip was taken

• A support field that records the [first, last] frame support of each clip

• All frame-level information from the underlying dataset of the input collection

Refer to fiftyone.core.clips.make_clips_dataset() to see the available configuration options for generating clips.

Note

The clip generation logic will respect any frame-level modifications defined in the input collection, but the output clips will always contain all frame-level labels.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("quickstart-video")

#
# Create a clips view that contains one clip for each contiguous
# segment that contains at least one road sign in every frame
#

stage1 = fo.FilterLabels("frames.detections", F("label") == "road sign")
stage2 = fo.ToClips("frames.detections")
clips = dataset.add_stage(stage1).add_stage(stage2)
print(clips)

#
# Create a clips view that contains one clip for each contiguous
# segment that contains at least two road signs in every frame
#

signs = F("detections.detections").filter(F("label") == "road sign")
stage = fo.ToClips(signs.length() >= 2)
clips = dataset.add_stage(stage)
print(clips)

Parameters:

• field_or_expr –

  can be any of the following:

  • a fiftyone.core.labels.TemporalDetection, fiftyone.core.labels.TemporalDetections, fiftyone.core.fields.FrameSupportField, or list of fiftyone.core.fields.FrameSupportField field

  • a frame-level label list field of any of the following types:

    • fiftyone.core.labels.Classifications

    • fiftyone.core.labels.Detections

    • fiftyone.core.labels.Polylines

    • fiftyone.core.labels.Keypoints

  • a fiftyone.core.expressions.ViewExpression that returns a boolean to apply to each frame of the input collection to determine if the frame should be clipped

  • a list of [(first1, last1), (first2, last2), ...] lists defining the frame numbers of the clips to extract from each sample

• config (None) – an optional dict of keyword arguments for fiftyone.core.clips.make_clips_dataset() specifying how to perform the conversion

• **kwargs – optional keyword arguments for fiftyone.core.clips.make_clips_dataset() specifying how to perform the conversion

Attributes:

has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
field_or_expr	The field or expression defining how to extract the clips.
config	Parameters specifying how to perform the conversion.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

property field_or_expr

The field or expression defining how to extract the clips.

property config

Parameters specifying how to perform the conversion.

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.ToTrajectories(field, config=None, _state=None, **kwargs)

Bases: ViewStage

Creates a view that contains one clip for each unique object trajectory defined by their (label, index) in a frame-level field of a video collection.

The returned view will contain:

• A sample_id field that records the sample ID from which each clip was taken

• A support field that records the [first, last] frame support of each clip

• A sample-level label field that records the label and index of each trajectory

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("quickstart-video")

#
# Create a trajectories view for the vehicles in the dataset
#

stage1 = fo.FilterLabels("frames.detections", F("label") == "vehicle")
stage2 = fo.ToTrajectories("frames.detections")
trajectories = dataset.add_stage(stage1).add_stage(stage2)

print(trajectories)

Parameters:

• field –

  a frame-level label list field of any of the following types:

  • fiftyone.core.labels.Detections

  • fiftyone.core.labels.Polylines

  • fiftyone.core.labels.Keypoints

• config (None) – an optional dict of keyword arguments for fiftyone.core.clips.make_clips_dataset() specifying how to perform the conversion

• **kwargs – optional keyword arguments for fiftyone.core.clips.make_clips_dataset() specifying how to perform the conversion

Attributes:

has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
field	The label field for which to extract trajectories.
config	Parameters specifying how to perform the conversion.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

property field

The label field for which to extract trajectories.

property config

Parameters specifying how to perform the conversion.

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection

class fiftyone.core.stages.ToFrames(config=None, _state=None, **kwargs)

Bases: ViewStage

Creates a view that contains one sample per frame in a video collection.

The returned view will contain all frame-level fields and the tags of each video as sample-level fields, as well as a sample_id field that records the IDs of the parent sample for each frame.

By default, sample_frames is False and this method assumes that the frames of the input collection have filepath fields populated pointing to each frame image. Any frames without a filepath populated will be omitted from the returned view.

When sample_frames is True, this method samples each video in the collection into a directory of per-frame images and stores the filepaths in the filepath frame field of the source dataset. By default, each folder of images is written using the same basename as the input video. For example, if frames_patt = "%%06d.jpg", then videos with the following paths:

/path/to/video1.mp4
/path/to/video2.mp4
...

would be sampled as follows:

/path/to/video1/
    000001.jpg
    000002.jpg
    ...
/path/to/video2/
    000001.jpg
    000002.jpg
    ...

However, you can use the optional output_dir and rel_dir parameters to customize the location and shape of the sampled frame folders. For example, if output_dir = "/tmp" and rel_dir = "/path/to", then videos with the following paths:

/path/to/folderA/video1.mp4
/path/to/folderA/video2.mp4
/path/to/folderB/video3.mp4
...

would be sampled as follows:

/tmp/folderA/
    video1/
        000001.jpg
        000002.jpg
        ...
    video2/
        000001.jpg
        000002.jpg
        ...
/tmp/folderB/
    video3/
        000001.jpg
        000002.jpg
        ...

By default, samples will be generated for every video frame at full resolution, but this method provides a variety of parameters that can be used to customize the sampling behavior.

Note

If this method is run multiple times with sample_frames set to True, existing frames will not be resampled unless you set force_sample to True.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset("quickstart-video")

session = fo.launch_app(dataset)

#
# Create a frames view for an entire video dataset
#

stage = fo.ToFrames(sample_frames=True)
frames = dataset.add_stage(stage)
print(frames)

session.view = frames

#
# Create a frames view that only contains frames with at least 10
# objects, sampled at a maximum frame rate of 1fps
#

num_objects = F("detections.detections").length()
view = dataset.match_frames(num_objects > 10)

stage = fo.ToFrames(max_fps=1)
frames = view.add_stage(stage)
print(frames)

session.view = frames

Parameters:

• config (None) – an optional dict of keyword arguments for fiftyone.core.video.make_frames_dataset() specifying how to perform the conversion

• **kwargs – optional keyword arguments for fiftyone.core.video.make_frames_dataset() specifying how to perform the conversion

Attributes:

has_view	Whether this stage's output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().
config	Parameters specifying how to perform the conversion.
flattens_groups	Whether this stage flattens groups into a non-grouped collection.
outputs_dynamic_groups	Whether this stage outputs or flattens dynamic groups.

Methods:

load_view(sample_collection[, reload])	Loads the fiftyone.core.view.DatasetView containing the output of the stage.
get_edited_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.
get_excluded_fields(sample_collection[, frames])	Returns a list of fields that have been excluded by the stage, if any.
get_filtered_fields(sample_collection[, frames])	Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.
get_group_expr(sample_collection)	Returns the dynamic group expression for the given stage, if any.
get_group_media_types(sample_collection)	Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.
get_media_type(sample_collection)	Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.
get_selected_fields(sample_collection[, frames])	Returns a list of fields that have been selected by the stage, if any.
to_mongo(sample_collection)	Returns the MongoDB aggregation pipeline for the stage.
validate(sample_collection)	Validates that the stage can be applied to the given collection.

property has_view

Whether this stage’s output view should be loaded via load_view() rather than appending stages to an aggregation pipeline via to_mongo().

property config

Parameters specifying how to perform the conversion.

load_view(sample_collection, reload=False)

Loads the fiftyone.core.view.DatasetView containing the output of the stage.

Only usable if has_view() is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• reload (False) – whether to force reload generated collections, if necessary

Returns:

a fiftyone.core.view.DatasetView

property flattens_groups

Whether this stage flattens groups into a non-grouped collection.

The possible return values are:

• True: this stage flattens groups

• False: this stage does not flatten groups

• None: this stage does not change group status

get_edited_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that may have been edited by the stage, if any.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been edited

get_excluded_fields(sample_collection, frames=False)

Returns a list of fields that have been excluded by the stage, if any.

View stages only need to report excluded fields if they insist that excluded fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

get_filtered_fields(sample_collection, frames=False)

Returns a list of names of fields or embedded fields that contain arrays have been filtered by the stage, if any.

For example, if a stage filters a fiftyone.core.labels.Detections field called "predictions", it should include "predictions.detections" in the returned list.

The "frames." prefix should be omitted when frames is True.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been filtered

get_group_expr(sample_collection)

Returns the dynamic group expression for the given stage, if any.

Only usable if outputs_dynamic_groups() is True.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a tuple of

• the group expression, or None if the stage does not generate dynamic groups

• whether the group expression is an ObjectId field, or None

get_group_media_types(sample_collection)

Returns the group media types outputted by this stage, if any, when applied to the given collection, if and only if they are different from the input collection.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a dict mapping slice names to media types, or None if the stage does not change the types

get_media_type(sample_collection)

Returns the media type outputted by this stage when applied to the given collection, if and only if it is different from the input type.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

the media type, or None if the stage does not change the type

get_selected_fields(sample_collection, frames=False)

Returns a list of fields that have been selected by the stage, if any.

View stages only need to report selected fields if they insist that non-selected fields not appear in the schema of the returned view.

Parameters:

• sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

• frames (False) – whether to return sample-level (False) or frame-level (True) fields

Returns:

a list of fields, or None if no fields have been selected

property outputs_dynamic_groups

Whether this stage outputs or flattens dynamic groups.

The possible return values are:

• True: this stage dynamically groups the input collection

• False: this stage flattens dynamic groups

• None: this stage does not change group status

to_mongo(sample_collection)

Returns the MongoDB aggregation pipeline for the stage.

Only usable if has_view() is False.

Parameters:

sample_collection – the fiftyone.core.collections.SampleCollection to which the stage is being applied

Returns:

a MongoDB aggregation pipeline (list of dicts)

validate(sample_collection)

Validates that the stage can be applied to the given collection.

Parameters:

sample_collection – a fiftyone.core.collections.SampleCollection

Raises:

ViewStageError – if the stage cannot be applied to the collection