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dataset.py
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dataset.py
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"""
FiftyOne datasets.
| Copyright 2017-2023, Voxel51, Inc.
| `voxel51.com <https://voxel51.com/>`_
|
"""
from collections import defaultdict
import contextlib
from datetime import datetime
import fnmatch
import itertools
import logging
import numbers
import os
import random
import string
from bson import json_util, ObjectId, DBRef
import cachetools
from deprecated import deprecated
import mongoengine.errors as moe
from pymongo import DeleteMany, InsertOne, ReplaceOne, UpdateMany, UpdateOne
from pymongo.errors import CursorNotFound, BulkWriteError
import eta.core.serial as etas
import eta.core.utils as etau
import fiftyone as fo
import fiftyone.constants as focn
import fiftyone.core.collections as foc
import fiftyone.core.expressions as foe
import fiftyone.core.fields as fof
import fiftyone.core.frame as fofr
import fiftyone.core.groups as fog
import fiftyone.core.labels as fol
import fiftyone.core.media as fom
import fiftyone.core.metadata as fome
from fiftyone.core.odm.dataset import SampleFieldDocument
from fiftyone.core.odm.dataset import DatasetAppConfig
import fiftyone.migrations as fomi
import fiftyone.core.odm as foo
import fiftyone.core.sample as fos
import fiftyone.core.storage as fost
from fiftyone.core.singletons import DatasetSingleton
import fiftyone.core.utils as fou
import fiftyone.core.view as fov
fot = fou.lazy_import("fiftyone.core.stages")
foud = fou.lazy_import("fiftyone.utils.data")
logger = logging.getLogger(__name__)
def list_datasets(glob_patt=None, tags=None, info=False):
"""Lists the available FiftyOne datasets.
Args:
glob_patt (None): an optional glob pattern of names to return
tags (None): only include datasets that have the specified tag or list
of tags
info (False): whether to return info dicts describing each dataset
rather than just their names
Returns:
a list of dataset names or info dicts
"""
if info:
return _list_datasets_info(glob_patt=glob_patt, tags=tags)
return _list_datasets(glob_patt=glob_patt, tags=tags)
def dataset_exists(name):
"""Checks if the dataset exists.
Args:
name: the name of the dataset
Returns:
True/False
"""
conn = foo.get_db_conn()
return bool(list(conn.datasets.find({"name": name}, {"_id": 1}).limit(1)))
def _validate_dataset_name(name, skip=None):
"""Validates that the given dataset name is available.
Args:
name: a dataset name
skip (None): an optional :class:`Dataset` to ignore
Returns:
the slug
Raises:
ValueError: if the name is not available
"""
slug = fou.to_slug(name)
query = {"$or": [{"name": name}, {"slug": slug}]}
if skip is not None:
query = {"$and": [query, {"_id": {"$ne": skip._doc.id}}]}
conn = foo.get_db_conn()
if bool(list(conn.datasets.find(query, {"_id": 1}).limit(1))):
raise ValueError("Dataset name '%s' is not available" % name)
return slug
def load_dataset(name):
"""Loads the FiftyOne dataset with the given name.
To create a new dataset, use the :class:`Dataset` constructor.
.. note::
:class:`Dataset` instances are singletons keyed by their name, so all
calls to this method with a given dataset ``name`` in a program will
return the same object.
Args:
name: the name of the dataset
Returns:
a :class:`Dataset`
"""
return Dataset(name, _create=False)
def get_default_dataset_name():
"""Returns a default dataset name based on the current time.
Returns:
a dataset name
"""
now = datetime.now()
name = now.strftime("%Y.%m.%d.%H.%M.%S")
if name in _list_datasets(include_private=True):
name = now.strftime("%Y.%m.%d.%H.%M.%S.%f")
return name
def make_unique_dataset_name(root):
"""Makes a unique dataset name with the given root name.
Args:
root: the root name for the dataset
Returns:
the dataset name
"""
if not root:
return get_default_dataset_name()
name = root
dataset_names = _list_datasets(include_private=True)
if name in dataset_names:
name += "_" + _get_random_characters(6)
while name in dataset_names:
name += _get_random_characters(1)
return name
def get_default_dataset_dir(name):
"""Returns the default dataset directory for the dataset with the given
name.
Args:
name: the dataset name
Returns:
the default directory for the dataset
"""
return os.path.join(fo.config.default_dataset_dir, name)
def delete_dataset(name, verbose=False):
"""Deletes the FiftyOne dataset with the given name.
Args:
name: the name of the dataset
verbose (False): whether to log the name of the deleted dataset
"""
dataset = load_dataset(name)
dataset.delete()
if verbose:
logger.info("Dataset '%s' deleted", name)
def delete_datasets(glob_patt, verbose=False):
"""Deletes all FiftyOne datasets whose names match the given glob pattern.
Args:
glob_patt: a glob pattern of datasets to delete
verbose (False): whether to log the names of deleted datasets
"""
for name in _list_datasets(glob_patt=glob_patt):
delete_dataset(name, verbose=verbose)
def delete_non_persistent_datasets(verbose=False):
"""Deletes all non-persistent datasets.
Args:
verbose (False): whether to log the names of deleted datasets
"""
_delete_non_persistent_datasets(verbose=verbose)
def _delete_non_persistent_datasets(verbose=False):
conn = foo.get_db_conn()
for name in conn.datasets.find({"persistent": False}).distinct("name"):
try:
dataset = Dataset(name, _create=False, _virtual=True)
except:
# If the dataset can't be loaded, it likely requires migration,
# which means it is persistent, so we don't worry about it here
continue
if not dataset.persistent and not dataset.deleted:
dataset._delete()
if verbose:
logger.info("Dataset '%s' deleted", name)
class Dataset(foc.SampleCollection, metaclass=DatasetSingleton):
"""A FiftyOne dataset.
Datasets represent an ordered collection of
:class:`fiftyone.core.sample.Sample` instances that describe a particular
type of raw media (e.g., images or videos) together with a user-defined set
of fields.
FiftyOne datasets ingest and store the labels for all samples internally;
raw media is stored on disk and the dataset provides paths to the data.
See :ref:`this page <using-datasets>` for an overview of working with
FiftyOne datasets.
Args:
name (None): the name of the dataset. By default,
:func:`get_default_dataset_name` is used
persistent (False): whether the dataset should persist in the database
after the session terminates
overwrite (False): whether to overwrite an existing dataset of the same
name
"""
def __init__(
self,
name=None,
persistent=False,
overwrite=False,
_create=True,
_virtual=False,
**kwargs,
):
if name is None and _create:
name = get_default_dataset_name()
if overwrite and dataset_exists(name):
delete_dataset(name)
if _create:
doc, sample_doc_cls, frame_doc_cls = _create_dataset(
self, name, persistent=persistent, **kwargs
)
else:
doc, sample_doc_cls, frame_doc_cls = _load_dataset(
self, name, virtual=_virtual
)
self._doc = doc
self._sample_doc_cls = sample_doc_cls
self._frame_doc_cls = frame_doc_cls
self._group_slice = doc.default_group_slice
self._annotation_cache = cachetools.LRUCache(5)
self._brain_cache = cachetools.LRUCache(5)
self._evaluation_cache = cachetools.LRUCache(5)
self._run_cache = cachetools.LRUCache(5)
self._deleted = False
if not _virtual:
self._update_last_loaded_at()
def __eq__(self, other):
return type(other) == type(self) and self.name == other.name
def __copy__(self):
return self # datasets are singletons
def __deepcopy__(self, memo):
return self # datasets are singletons
def __len__(self):
return self.count()
def __getitem__(self, id_filepath_slice):
if isinstance(id_filepath_slice, numbers.Integral):
raise ValueError(
"Accessing dataset samples by numeric index is not supported. "
"Use sample IDs, filepaths, slices, boolean arrays, or a "
"boolean ViewExpression instead"
)
if isinstance(id_filepath_slice, slice):
return self.view()[id_filepath_slice]
if isinstance(id_filepath_slice, foe.ViewExpression):
return self.view()[id_filepath_slice]
if etau.is_container(id_filepath_slice):
return self.view()[id_filepath_slice]
try:
oid = ObjectId(id_filepath_slice)
query = {"_id": oid}
except:
oid = None
query = {"filepath": id_filepath_slice}
d = self._sample_collection.find_one(query)
if d is None:
field = "ID" if oid is not None else "filepath"
raise KeyError(
"No sample found with %s '%s'" % (field, id_filepath_slice)
)
doc = self._sample_dict_to_doc(d)
return fos.Sample.from_doc(doc, dataset=self)
def __delitem__(self, samples_or_ids):
self.delete_samples(samples_or_ids)
def __getattribute__(self, name):
#
# The attributes necessary to determine a dataset's name and whether
# it is deleted are always available. If a dataset is deleted, no other
# methods are available
#
if name.startswith("__") or name in (
"name",
"deleted",
"_deleted",
"_doc",
):
return super().__getattribute__(name)
if getattr(self, "_deleted", False):
raise ValueError("Dataset '%s' is deleted" % self.name)
return super().__getattribute__(name)
@property
def _dataset(self):
return self
@property
def _root_dataset(self):
return self
@property
def _is_generated(self):
return self._is_patches or self._is_frames or self._is_clips
@property
def _is_patches(self):
return self._sample_collection_name.startswith("patches.")
@property
def _is_frames(self):
return self._sample_collection_name.startswith(
("frames.", "patches.frames")
)
@property
def _is_clips(self):
return self._sample_collection_name.startswith("clips.")
@property
def _is_dynamic_groups(self):
return False
@property
def media_type(self):
"""The media type of the dataset."""
return self._doc.media_type
@media_type.setter
def media_type(self, media_type):
if media_type == self._doc.media_type:
return
if media_type not in fom.MEDIA_TYPES and media_type != fom.GROUP:
raise ValueError(
"Invalid media_type '%s'. Supported values are %s"
% (media_type, fom.MEDIA_TYPES)
)
if len(self) > 0:
raise ValueError("Cannot set media type of a non-empty dataset")
self._set_media_type(media_type)
def _set_media_type(self, media_type):
self._doc.media_type = media_type
if self._contains_videos(any_slice=True):
self._init_frames()
if media_type == fom.GROUP:
# The `metadata` field of group datasets always stays as the
# generic `Metadata` type because slices may have different types
self.save()
else:
self._update_metadata_field(media_type)
self.save()
self.reload()
def _update_metadata_field(self, media_type):
idx = None
for i, field in enumerate(self._doc.sample_fields):
if field.name == "metadata":
idx = i
if idx is not None:
if media_type == fom.IMAGE:
doc_type = fome.ImageMetadata
elif media_type == fom.VIDEO:
doc_type = fome.VideoMetadata
else:
doc_type = fome.Metadata
field = foo.create_field(
"metadata",
fof.EmbeddedDocumentField,
embedded_doc_type=doc_type,
)
field_doc = foo.SampleFieldDocument.from_field(field)
self._doc.sample_fields[idx] = field_doc
def _init_frames(self):
if self._frame_doc_cls is not None:
# Legacy datasets may not have frame fields declared yet
if not self._doc.frame_fields:
self._doc.frame_fields = [
foo.SampleFieldDocument.from_field(field)
for field in self._frame_doc_cls._fields.values()
]
return
frame_collection_name = _make_frame_collection_name(
self._sample_collection_name
)
frame_doc_cls = _create_frame_document_cls(
self, frame_collection_name, field_docs=self._doc.frame_fields
)
_create_indexes(None, frame_collection_name)
self._doc.frame_collection_name = frame_collection_name
self._doc.frame_fields = [
foo.SampleFieldDocument.from_field(field)
for field in frame_doc_cls._fields.values()
]
self._frame_doc_cls = frame_doc_cls
@property
def group_field(self):
"""The group field of the dataset, or None if the dataset is not
grouped.
Examples::
import fiftyone as fo
import fiftyone.zoo as foz
dataset = foz.load_zoo_dataset("quickstart-groups")
print(dataset.group_field)
# group
"""
return self._doc.group_field
@property
def group_slice(self):
"""The current group slice of the dataset, or None if the dataset is
not grouped.
Examples::
import fiftyone as fo
import fiftyone.zoo as foz
dataset = foz.load_zoo_dataset("quickstart-groups")
print(dataset.group_slices)
# ['left', 'right', 'pcd']
print(dataset.group_slice)
# left
# Change the current group slice
dataset.group_slice = "right"
print(dataset.group_slice)
# right
"""
return self._group_slice
@group_slice.setter
def group_slice(self, slice_name):
if self.media_type != fom.GROUP:
raise ValueError("Dataset has no groups")
if slice_name is None:
slice_name = self._doc.default_group_slice
if slice_name not in self._doc.group_media_types:
raise ValueError("Dataset has no group slice '%s'" % slice_name)
self._group_slice = slice_name
@property
def group_slices(self):
"""The list of group slices of the dataset, or None if the dataset is
not grouped.
Examples::
import fiftyone as fo
import fiftyone.zoo as foz
dataset = foz.load_zoo_dataset("quickstart-groups")
print(dataset.group_slices)
# ['left', 'right', 'pcd']
"""
if self.media_type != fom.GROUP:
return None
return list(self._doc.group_media_types.keys())
@property
def group_media_types(self):
"""A dict mapping group slices to media types, or None if the dataset
is not grouped.
Examples::
import fiftyone as fo
import fiftyone.zoo as foz
dataset = foz.load_zoo_dataset("quickstart-groups")
print(dataset.group_media_types)
# {'left': 'image', 'right': 'image', 'pcd': 'point-cloud'}
"""
if self.media_type != fom.GROUP:
return None
return self._doc.group_media_types
@property
def default_group_slice(self):
"""The default group slice of the dataset, or None if the dataset is
not grouped.
Examples::
import fiftyone as fo
import fiftyone.zoo as foz
dataset = foz.load_zoo_dataset("quickstart-groups")
print(dataset.default_group_slice)
# left
# Change the default group slice
dataset.default_group_slice = "right"
print(dataset.default_group_slice)
# right
"""
if self.media_type != fom.GROUP:
return None
return self._doc.default_group_slice
@default_group_slice.setter
def default_group_slice(self, slice_name):
if self.media_type != fom.GROUP:
raise ValueError("Dataset has no groups")
if slice_name not in self._doc.group_media_types:
raise ValueError("Dataset has no group slice '%s'" % slice_name)
self._doc.default_group_slice = slice_name
self.save()
if self._group_slice is None:
self._group_slice = slice_name
@property
def version(self):
"""The version of the ``fiftyone`` package for which the dataset is
formatted.
"""
return self._doc.version
@property
def name(self):
"""The name of the dataset."""
return self._doc.name
@name.setter
def name(self, name):
_name = self._doc.name
if name == _name:
return
slug = _validate_dataset_name(name, skip=self)
self._doc.name = name
self._doc.slug = slug
self.save()
# Update singleton
self._instances.pop(_name, None)
self._instances[name] = self
@property
def slug(self):
"""The slug of the dataset."""
return self._doc.slug
@property
def created_at(self):
"""The datetime that the dataset was created."""
return self._doc.created_at
@property
def last_loaded_at(self):
"""The datetime that the dataset was last loaded."""
return self._doc.last_loaded_at
@property
def persistent(self):
"""Whether the dataset persists in the database after a session is
terminated.
"""
return self._doc.persistent
@persistent.setter
def persistent(self, value):
self._doc.persistent = value
self.save()
@property
def tags(self):
"""A list of tags on the dataset.
Examples::
import fiftyone as fo
dataset = fo.Dataset()
# Add some tags
dataset.tags = ["test", "projectA"]
# Edit the tags
dataset.tags.pop()
dataset.tags.append("projectB")
dataset.save() # must save after edits
"""
return self._doc.tags
@tags.setter
def tags(self, value):
self._doc.tags = value
self.save()
@property
def description(self):
"""A string description on the dataset.
Examples::
import fiftyone as fo
dataset = fo.Dataset()
# Store a description on the dataset
dataset.description = "Your description here"
"""
return self._doc.description
@description.setter
def description(self, description):
self._doc.description = description
self.save()
@property
def info(self):
"""A user-facing dictionary of information about the dataset.
Examples::
import fiftyone as fo
dataset = fo.Dataset()
# Store a class list in the dataset's info
dataset.info = {"classes": ["cat", "dog"]}
# Edit the info
dataset.info["other_classes"] = ["bird", "plane"]
dataset.save() # must save after edits
"""
return self._doc.info
@info.setter
def info(self, info):
self._doc.info = info
self.save()
@property
def app_config(self):
"""A :class:`fiftyone.core.odm.dataset.DatasetAppConfig` that
customizes how this dataset is visualized in the
:ref:`FiftyOne App <fiftyone-app>`.
Examples::
import fiftyone as fo
import fiftyone.utils.image as foui
import fiftyone.zoo as foz
dataset = foz.load_zoo_dataset("quickstart")
# View the dataset's current App config
print(dataset.app_config)
# Generate some thumbnail images
foui.transform_images(
dataset,
size=(-1, 32),
output_field="thumbnail_path",
output_dir="/tmp/thumbnails",
)
# Modify the dataset's App config
dataset.app_config.media_fields = ["filepath", "thumbnail_path"]
dataset.app_config.grid_media_field = "thumbnail_path"
dataset.save() # must save after edits
session = fo.launch_app(dataset)
"""
return self._doc.app_config
@app_config.setter
def app_config(self, config):
if config is None:
config = DatasetAppConfig()
self._doc.app_config = config
self.save()
@property
def classes(self):
"""A dict mapping field names to list of class label strings for the
corresponding fields of the dataset.
Examples::
import fiftyone as fo
dataset = fo.Dataset()
# Set classes for the `ground_truth` and `predictions` fields
dataset.classes = {
"ground_truth": ["cat", "dog"],
"predictions": ["cat", "dog", "other"],
}
# Edit an existing classes list
dataset.classes["ground_truth"].append("other")
dataset.save() # must save after edits
"""
return self._doc.classes
@classes.setter
def classes(self, classes):
self._doc.classes = classes
self.save()
@property
def default_classes(self):
"""A list of class label strings for all
:class:`fiftyone.core.labels.Label` fields of this dataset that do not
have customized classes defined in :meth:`classes`.
Examples::
import fiftyone as fo
dataset = fo.Dataset()
# Set default classes
dataset.default_classes = ["cat", "dog"]
# Edit the default classes
dataset.default_classes.append("rabbit")
dataset.save() # must save after edits
"""
return self._doc.default_classes
@default_classes.setter
def default_classes(self, classes):
self._doc.default_classes = classes
self.save()
@property
def mask_targets(self):
"""A dict mapping field names to mask target dicts, each of which
defines a mapping between pixel values (2D masks) or RGB hex strings
(3D masks) and label strings for the segmentation masks in the
corresponding field of the dataset.
Examples::
import fiftyone as fo
#
# 2D masks
#
dataset = fo.Dataset()
# Set mask targets for the `ground_truth` and `predictions` fields
dataset.mask_targets = {
"ground_truth": {1: "cat", 2: "dog"},
"predictions": {1: "cat", 2: "dog", 255: "other"},
}
# Or, for RGB mask targets
dataset.mask_targets = {
"segmentations": {"#3f0a44": "road", "#eeffee": "building", "#ffffff": "other"}
}
# Edit an existing mask target
dataset.mask_targets["ground_truth"][255] = "other"
dataset.save() # must save after edits
#
# 3D masks
#
dataset = fo.Dataset()
# Set mask targets for the `ground_truth` and `predictions` fields
dataset.mask_targets = {
"ground_truth": {"#499CEF": "cat", "#6D04FF": "dog"},
"predictions": {
"#499CEF": "cat", "#6D04FF": "dog", "#FF6D04": "person"
},
}
# Edit an existing mask target
dataset.mask_targets["ground_truth"]["#FF6D04"] = "person"
dataset.save() # must save after edits
"""
return self._doc.mask_targets
@mask_targets.setter
def mask_targets(self, targets):
self._doc.mask_targets = targets
self.save()
@property
def default_mask_targets(self):
"""A dict defining a default mapping between pixel values (2D masks) or
RGB hex strings (3D masks) and label strings for the segmentation masks
of all :class:`fiftyone.core.labels.Segmentation` fields of this
dataset that do not have customized mask targets defined in
:meth:`mask_targets`.
Examples::
import fiftyone as fo
#
# 2D masks
#
dataset = fo.Dataset()
# Set default mask targets
dataset.default_mask_targets = {1: "cat", 2: "dog"}
# Or, for RGB mask targets
dataset.default_mask_targets = {"#3f0a44": "road", "#eeffee": "building", "#ffffff": "other"}
# Edit the default mask targets
dataset.default_mask_targets[255] = "other"
dataset.save() # must save after edits
#
# 3D masks
#
dataset = fo.Dataset()
# Set default mask targets
dataset.default_mask_targets = {"#499CEF": "cat", "#6D04FF": "dog"}
# Edit the default mask targets
dataset.default_mask_targets["#FF6D04"] = "person"
dataset.save() # must save after edits
"""
return self._doc.default_mask_targets
@default_mask_targets.setter
def default_mask_targets(self, targets):
self._doc.default_mask_targets = targets
self.save()
@property
def skeletons(self):
"""A dict mapping field names to
:class:`fiftyone.core.odm.dataset.KeypointSkeleton` instances, each of
which defines the semantic labels and point connectivity for the
:class:`fiftyone.core.labels.Keypoint` instances in the corresponding
field of the dataset.
Examples::
import fiftyone as fo
dataset = fo.Dataset()
# Set keypoint skeleton for the `ground_truth` field
dataset.skeletons = {
"ground_truth": fo.KeypointSkeleton(
labels=[
"left hand" "left shoulder", "right shoulder", "right hand",
"left eye", "right eye", "mouth",
],
edges=[[0, 1, 2, 3], [4, 5, 6]],
)
}
# Edit an existing skeleton
dataset.skeletons["ground_truth"].labels[-1] = "lips"
dataset.save() # must save after edits
"""
return self._doc.skeletons
@skeletons.setter
def skeletons(self, skeletons):
self._doc.skeletons = skeletons
self.save()
@property
def default_skeleton(self):
"""A default :class:`fiftyone.core.odm.dataset.KeypointSkeleton`
defining the semantic labels and point connectivity for all
:class:`fiftyone.core.labels.Keypoint` fields of this dataset that do
not have customized skeletons defined in :meth:`skeleton`.
Examples::
import fiftyone as fo
dataset = fo.Dataset()
# Set default keypoint skeleton
dataset.default_skeleton = fo.KeypointSkeleton(
labels=[
"left hand" "left shoulder", "right shoulder", "right hand",
"left eye", "right eye", "mouth",
],
edges=[[0, 1, 2, 3], [4, 5, 6]],