# fiftyone.utils.bdd¶

Utilities for working with datasets in Berkeley DeepDrive (BDD) format.

Classes:

 BDDDatasetExporter([export_dir, data_path, …]) Exporter that writes BDD datasets to disk. BDDDatasetImporter([dataset_dir, data_path, …]) Importer for BDD datasets stored on disk.

Functions:

 load_bdd_annotations(json_path) Loads the BDD annotations from the given JSON file. parse_bdd100k_dataset(source_dir, dataset_dir) Parses the raw BDD100K download files in the specified directory into per-split directories in BDD format.
class fiftyone.utils.bdd.BDDDatasetImporter(dataset_dir=None, data_path=None, labels_path=None, include_all_data=False, extra_attrs=True, shuffle=False, seed=None, max_samples=None)

Importer for BDD datasets stored on disk.

Parameters
• dataset_dir (None) – the dataset directory. If omitted, data_path and/or labels_path must be provided

• data_path (None) –

an optional parameter that enables explicit control over the location of the media. Can be any of the following:

• a folder name like "data" or "data/" specifying a subfolder of dataset_dir where the media files reside

• an absolute directory path where the media files reside. In this case, the dataset_dir has no effect on the location of the data

• a filename like "data.json" specifying the filename of the JSON data manifest file in dataset_dir

• an absolute filepath specifying the location of the JSON data manifest. In this case, dataset_dir has no effect on the location of the data

• a dict mapping filenames to absolute filepaths

If None, this parameter will default to whichever of data/ or data.json exists in the dataset directory

• labels_path (None) –

an optional parameter that enables explicit control over the location of the labels. Can be any of the following:

• a filename like "labels.json" specifying the location of the labels in dataset_dir

• an absolute filepath to the labels. In this case, dataset_dir has no effect on the location of the labels

If None, the parameter will default to labels.json

• include_all_data (False) – whether to generate samples for all images in the data directory (True) rather than only creating samples for images with label entries (False)

• extra_attrs (True) –

whether to load extra annotation attributes onto the imported labels. Supported values are:

• True: load all extra attributes found

• False: do not load extra attributes

• a name or list of names of specific attributes to load

• shuffle (False) – whether to randomly shuffle the order in which the samples are imported

• seed (None) – a random seed to use when shuffling

• max_samples (None) – a maximum number of samples to import. By default, all samples are imported

Methods:

 close(*args) Performs any necessary actions after the last sample has been imported. Returns the dataset info for the dataset. Performs any necessary setup before importing the first sample in the dataset.

Attributes:

 has_dataset_info Whether this importer produces a dataset info dictionary. has_image_metadata Whether this importer produces fiftyone.core.metadata.ImageMetadata instances for each image. label_cls The fiftyone.core.labels.Label class(es) returned by this importer.
property has_dataset_info

Whether this importer produces a dataset info dictionary.

property has_image_metadata

Whether this importer produces fiftyone.core.metadata.ImageMetadata instances for each image.

property label_cls

The fiftyone.core.labels.Label class(es) returned by this importer.

This can be any of the following:

• a fiftyone.core.labels.Label class. In this case, the importer is guaranteed to return labels of this type

• a list or tuple of fiftyone.core.labels.Label classes. In this case, the importer can produce a single label field of any of these types

• a dict mapping keys to fiftyone.core.labels.Label classes. In this case, the importer will return label dictionaries with keys and value-types specified by this dictionary. Not all keys need be present in the imported labels

• None. In this case, the importer makes no guarantees about the labels that it may return

setup()

Performs any necessary setup before importing the first sample in the dataset.

This method is called when the importer’s context manager interface is entered, DatasetImporter.__enter__().

close(*args)

Performs any necessary actions after the last sample has been imported.

This method is called when the importer’s context manager interface is exited, DatasetImporter.__exit__().

Parameters

*args – the arguments to DatasetImporter.__exit__()

get_dataset_info()

Returns the dataset info for the dataset.

By convention, this method should be called after all samples in the dataset have been imported.

Returns

a dict of dataset info

class fiftyone.utils.bdd.BDDDatasetExporter(export_dir=None, data_path=None, labels_path=None, export_media=None, image_format=None, extra_attrs=True)

Exporter that writes BDD datasets to disk.

Parameters
• export_dir (None) – the directory to write the export. This has no effect if data_path and labels_path are absolute paths

• data_path (None) –

an optional parameter that enables explicit control over the location of the exported media. Can be any of the following:

• a folder name like "data" or "data/" specifying a subfolder of export_dir in which to export the media

• an absolute directory path in which to export the media. In this case, the export_dir has no effect on the location of the data

• a JSON filename like "data.json" specifying the filename of the manifest file in export_dir generated when export_media is "manifest"

• an absolute filepath specifying the location to write the JSON manifest file when export_media is "manifest". In this case, export_dir has no effect on the location of the data

If None, the default value of this parameter will be chosen based on the value of the export_media parameter

• labels_path (None) –

an optional parameter that enables explicit control over the location of the exported labels. Can be any of the following:

• a filename like "labels.json" specifying the location in export_dir in which to export the labels

• an absolute filepath to which to export the labels. In this case, the export_dir has no effect on the location of the labels

If None, the labels will be exported into export_dir using the default filename

• export_media (None) –

controls how to export the raw media. The supported values are:

• True: copy all media files into the output directory

• False: don’t export media

• "move": move all media files into the output directory

• "symlink": create symlinks to the media files in the output directory

• "manifest": create a data.json in the output directory that maps UUIDs used in the labels files to the filepaths of the source media, rather than exporting the actual media

If None, the default value of this parameter will be chosen based on the value of the data_path parameter

• image_format (None) – the image format to use when writing in-memory images to disk. By default, fiftyone.config.default_image_ext is used

• extra_attrs (True) –

whether to include extra object attributes in the exported labels. Supported values are:

• True: export all extra attributes found

• False: do not export extra attributes

• a name or list of names of specific attributes to export

Methods:

 close(*args) Performs any necessary actions after the last sample has been exported. export_sample(image_or_path, labels[, metadata]) Exports the given sample to the dataset. log_collection(sample_collection) Logs any relevant information about the fiftyone.core.collections.SampleCollection whose samples will be exported. Performs any necessary setup before exporting the first sample in the dataset.

Attributes:

 label_cls The fiftyone.core.labels.Label class(es) exported by this exporter. requires_image_metadata Whether this exporter requires fiftyone.core.metadata.ImageMetadata instances for each sample being exported.
property requires_image_metadata

Whether this exporter requires fiftyone.core.metadata.ImageMetadata instances for each sample being exported.

property label_cls

The fiftyone.core.labels.Label class(es) exported by this exporter.

This can be any of the following:

• a fiftyone.core.labels.Label class. In this case, the exporter directly exports labels of this type

• a list or tuple of fiftyone.core.labels.Label classes. In this case, the exporter can export a single label field of any of these types

• a dict mapping keys to fiftyone.core.labels.Label classes. In this case, the exporter can handle label dictionaries with value-types specified by this dictionary. Not all keys need be present in the exported label dicts

• None. In this case, the exporter makes no guarantees about the labels that it can export

setup()

Performs any necessary setup before exporting the first sample in the dataset.

This method is called when the exporter’s context manager interface is entered, DatasetExporter.__enter__().

export_sample(image_or_path, labels, metadata=None)

Exports the given sample to the dataset.

Parameters
close(*args)

Performs any necessary actions after the last sample has been exported.

This method is called when the exporter’s context manager interface is exited, DatasetExporter.__exit__().

Parameters

*args – the arguments to DatasetExporter.__exit__()

log_collection(sample_collection)

Logs any relevant information about the fiftyone.core.collections.SampleCollection whose samples will be exported.

Subclasses can optionally implement this method if their export format can record information such as the fiftyone.core.collections.SampleCollection.info() or fiftyone.core.collections.SampleCollection.classes() of the collection being exported.

By convention, this method must be optional; i.e., if it is not called before the first call to export_sample(), then the exporter must make do without any information about the fiftyone.core.collections.SampleCollection (which may not be available, for example, if the samples being exported are not stored in a collection).

Parameters

sample_collection – the fiftyone.core.collections.SampleCollection whose samples will be exported

fiftyone.utils.bdd.load_bdd_annotations(json_path)

Loads the BDD annotations from the given JSON file.

Parameters

json_path – the path to the annotations JSON file

Returns

a dict mapping filenames to BDD annotation dicts

fiftyone.utils.bdd.parse_bdd100k_dataset(source_dir, dataset_dir, copy_files=True, overwrite=False)

Parses the raw BDD100K download files in the specified directory into per-split directories in BDD format.

This function assumes that the input source_dir contains the following contents:

source_dir/
labels/
bdd100k_labels_images_train.json
bdd100k_labels_images_val.json
images/
100k/
train/
test/
val/
...


and will populate dataset_dir as follows:

dataset_dir/
train/
data/
labels.json
validation/
data/
labels.json
test/
data/

Parameters
• source_dir – the source directory containing the manually dowloaded BDD100K files

• dataset_dir – the directory to construct the output split directories

• copy_files (True) – whether to move (False) or create copies (True) of the source files when populating dataset_dir

• overwrite (False) – whether to overwrite existing files/directories in the output location, if they exist

Raises

OSError – if any required source files are not present