fiftyone.core.view.DatasetView

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Deletes all samples in the view from the underlying dataset.

Clears the values of the frame-level field from all samples in the view.

The field will remain in the dataset's frame schema, and all frames in the view will have the value None for the field.

You can use dot notation (embedded.field.name) to clear embedded frame fields.

Only applicable to views that contain videos.

Clears the values of the frame-level fields from all samples in the view.

The fields will remain in the dataset's frame schema, and all frames in the view will have the value None for the fields.

You can use dot notation (embedded.field.name) to clear embedded frame fields.

Only applicable to views that contain videos.

Deletes all frame labels from the samples in the view from the underlying dataset.

Clears the values of the field from all samples in the view.

The field will remain in the dataset's schema, and all samples in the view will have the value None for the field.

You can use dot notation (embedded.field.name) to clear embedded fields.

Clears the values of the fields from all samples in the view.

The fields will remain in the dataset's schema, and all samples in the view will have the value None for the fields.

You can use dot notation (embedded.field.name) to clear embedded fields.

Creates a new dataset containing a copy of the contents of the view.

Dataset clones contain deep copies of all samples and dataset-level information in the source collection. The source media files, however, are not copied.

Clones the frame-level field of the view into a new field.

You can use dot notation (embedded.field.name) to clone embedded frame fields.

Only applicable to views that contain videos.

Clones the frame-level fields of the view into new frame-level fields of the dataset.

You can use dot notation (embedded.field.name) to clone embedded frame fields.

Only applicable to views that contain videos.

Clones the given sample field of the view into a new field of the dataset.

You can use dot notation (embedded.field.name) to clone embedded fields.

Clones the given sample fields of the view into new fields of the dataset.

You can use dot notation (embedded.field.name) to clone embedded fields.

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Ensures that the video view contains frame instances for every frame of each sample's source video.

Empty frames will be inserted for missing frames, and already existing frames are left unchanged.

Returns a view containing the samples from a dynamic grouped view with the given group value.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

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

view = dataset.take(1000).group_by("ground_truth.label")

group = view.get_dynamic_group("cat")
print(len(group))  # 104

Returns a schema dictionary describing the fields of the samples in the view.

Returns a schema dictionary describing the fields of the frames of the samples in the view.

Only applicable for views that contain videos.

Returns a dict containing the samples for the given group ID.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

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

group_id = view.take(1).first().group.id
group = view.get_group(group_id)

print(group.keys())
# ['left', 'right', 'pcd']

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Returns an iterator over the dynamic groups in the view.

Examples:

import fiftyone as fo
import fiftyone.zoo as foz

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

view = dataset.take(1000).group_by("ground_truth.label")

for group in view.iter_dynamic_groups():
    group_value = group.first().ground_truth.label
    print("%s: %d" % (group_value, len(group)))

Returns an iterator over the groups in the view.

Examples:

import random as r
import string as s

import fiftyone as fo
import fiftyone.zoo as foz

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

def make_label():
    return "".join(r.choice(s.ascii_letters) for i in range(10))

# No save context
for group in view.iter_groups(progress=True):
    for sample in group.values():
        sample["test"] = make_label()
        sample.save()

# Save using default batching strategy
for group in view.iter_groups(progress=True, autosave=True):
    for sample in group.values():
        sample["test"] = make_label()

# Save in batches of 10
for group in view.iter_groups(
    progress=True, autosave=True, batch_size=10
):
    for sample in group.values():
        sample["test"] = make_label()

# Save every 0.5 seconds
for group in view.iter_groups(
    progress=True, autosave=True, batch_size=0.5
):
    for sample in group.values():
        sample["test"] = make_label()

Returns an iterator over the samples in the view.

Examples:

import random as r
import string as s

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("cifar10", split="test")
view = dataset.shuffle().limit(5000)

def make_label():
    return "".join(r.choice(s.ascii_letters) for i in range(10))

# No save context
for sample in view.iter_samples(progress=True):
    sample.ground_truth.label = make_label()
    sample.save()

# Save using default batching strategy
for sample in view.iter_samples(progress=True, autosave=True):
    sample.ground_truth.label = make_label()

# Save in batches of 10
for sample in view.iter_samples(
    progress=True, autosave=True, batch_size=10
):
    sample.ground_truth.label = make_label()

# Save every 0.5 seconds
for sample in view.iter_samples(
    progress=True, autosave=True, batch_size=0.5
):
    sample.ground_truth.label = make_label()

Deletes all samples that are not in the view from the underlying dataset.

Deletes all fields that are excluded from the view from the underlying dataset.

For each sample in the view, deletes all frames labels that are not in the view from the underlying dataset.

Undocumented

Reloads the view.

Note that fiftyone.core.sample.SampleView instances are not singletons, so any in-memory samples extracted from this view will not be updated by calling this method.

Saves the contents of the view to the database.

This method does not delete samples or frames from the underlying dataset that this view excludes.

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Returns a string summary of the view.

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Returns a JSON dictionary representation of the view.

Returns a copy of this view.