fiftyone.zoo.datasets.torch.VOC2012Dataset

class documentation

class VOC2012Dataset(TorchVisionDataset): (source)

The dataset for the PASCAL Visual Object Classes Challenge 2012 (VOC2012) for the Classification and Detection competitions.

A total of 11,540 images are included in this dataset, where each image contains a set of objects, out of 20 different classes, making a total of 27,450 annotated objects. In the classification competition, the goal is to predict the set of labels contained in the image, while in the detection competition the goal is to predict the bounding box and label of each individual object.

Example usage:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("voc-2012", split="validation")

session = fo.launch_app(dataset)

Dataset size: 3.59 GB
Source: http://host.robots.ox.ac.uk/pascal/VOC/voc2012

Property	`name`	The name of the dataset.
Property	`supported_splits`	A tuple of supported splits for the dataset, or None if the dataset does not have splits.
Property	`tags`	A tuple of tags for the dataset.
Method	`_download_and_prepare`	Internal implementation of downloading the dataset and preparing it for use in the given directory.

Inherited from ZooDataset (via TorchVisionDataset):

Static Method	`get_info_path`	Returns the path to the `ZooDatasetInfo` for the dataset.
Static Method	`has_info`	Determines whether the directory contains `ZooDatasetInfo`.
Static Method	`load_info`	Loads the `ZooDatasetInfo` from the given dataset directory.
Method	`download_and_prepare`	Downloads the dataset and prepares it for use.
Method	`get_split_dir`	Returns the directory for the given split of the dataset.
Method	`has_split`	Whether the dataset has the given split.
Method	`has_tag`	Whether the dataset has the given tag.
Property	`has_patches`	Whether the dataset has patches that may need to be applied to already downloaded files.
Property	`has_splits`	Whether the dataset has splits.
Property	`has_tags`	Whether the dataset has tags.
Property	`importer_kwargs`	A dict of default kwargs to pass to this dataset's `fiftyone.utils.data.importers.DatasetImporter`.
Property	`is_remote`	Whether the dataset is remotely-sourced.
Property	`parameters`	An optional dict of parameters describing the configuration of the zoo dataset when it was downloaded.
Property	`requires_manual_download`	Whether this dataset requires some files to be manually downloaded by the user before the dataset can be loaded.
Property	`supports_partial_downloads`	Whether the dataset supports downloading partial subsets of its splits.
Method	`_get_splits_to_download`	Undocumented
Method	`_is_dataset_ready`	Undocumented
Method	`_is_split_ready`	Undocumented
Method	`_patch_if_necessary`	Internal method called when an already downloaded dataset may need to be patched.

@property
name = (source) ¶

overrides fiftyone.zoo.datasets.ZooDataset.name

The name of the dataset.

@property
supported_splits = (source) ¶

overrides fiftyone.zoo.datasets.ZooDataset.supported_splits

A tuple of supported splits for the dataset, or None if the dataset does not have splits.

@property
tags = (source) ¶

overrides fiftyone.zoo.datasets.ZooDataset.tags

A tuple of tags for the dataset.

def _download_and_prepare(self, dataset_dir, scratch_dir, split): (source) ¶

overrides fiftyone.zoo.datasets.ZooDataset._download_and_prepare

Internal implementation of downloading the dataset and preparing it for use in the given directory.

Parameters
dataset_dir	the directory in which to construct the dataset. If a `split` is provided, this is the directory for the split
scratch_dir	a scratch directory to use to download and prepare any required intermediate files
split	the split to download, or None if the dataset does not have splits
Returns
tuple of	dataset_type: the `fiftyone.types.Dataset` type of the dataset num_samples: the number of samples in the split. For datasets that support partial downloads, this can be `None`, which indicates that all content was already downloaded classes: an optional list of class label strings