fiftyone.core.aggregations.Values

Extracts the values of the field from all samples in a collection.

Values aggregations are useful for efficiently extracting a slice of field or embedded field values across all samples in a collection. See the examples below for more details.

The dual function of Values is set_values(), which can be used to efficiently set a field or embedded field of all samples in a collection by providing lists of values of same structure returned by this aggregation.

Examples:

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

dataset = fo.Dataset()
dataset.add_samples(
    [
        fo.Sample(
            filepath="/path/to/image1.png",
            numeric_field=1.0,
            numeric_list_field=[1, 2, 3],
        ),
        fo.Sample(
            filepath="/path/to/image2.png",
            numeric_field=4.0,
            numeric_list_field=[1, 2],
        ),
        fo.Sample(
            filepath="/path/to/image3.png",
            numeric_field=None,
            numeric_list_field=None,
        ),
    ]
)

#
# Get all values of a field
#

aggregation = fo.Values("numeric_field")
values = dataset.aggregate(aggregation)
print(values)  # [1.0, 4.0, None]

#
# Get all values of a list field
#

aggregation = fo.Values("numeric_list_field")
values = dataset.aggregate(aggregation)
print(values)  # [[1, 2, 3], [1, 2], None]

#
# Get all values of transformed field
#

aggregation = fo.Values(2 * (F("numeric_field") + 1))
values = dataset.aggregate(aggregation)
print(values)  # [4.0, 10.0, None]

#
# Get values from a label list field
#

dataset = foz.load_zoo_dataset("quickstart")

# list of `Detections`
aggregation = fo.Values("ground_truth")
detections = dataset.aggregate(aggregation)

# list of lists of `Detection` instances
aggregation = fo.Values("ground_truth.detections")
detections = dataset.aggregate(aggregation)

# list of lists of detection labels
aggregation = fo.Values("ground_truth.detections.label")
labels = dataset.aggregate(aggregation)