fiftyone.zoo.datasets.base

module documentation

(source)

FiftyOne Zoo Datasets provided natively by the library.

Class	`ActivityNet100Dataset`	ActivityNet is a large-scale video dataset for human activity understanding supporting the tasks of global video classification, trimmed activity classification, and temporal activity detection.
Class	`ActivityNet200Dataset`	ActivityNet is a large-scale video dataset for human activity understanding supporting the tasks of global video classification, trimmed activity classification, and temporal activity detection.
Class	`BDD100KDataset`	The Berkeley Deep Drive (BDD) dataset is one of the largest and most diverse video datasets for autonomous vehicles.
Class	`Caltech101Dataset`	The Caltech-101 dataset of images.
Class	`Caltech256Dataset`	The Caltech-256 dataset of images.
Class	`CityscapesDataset`	Cityscapes is a large-scale dataset that contains a diverse set of stereo video sequences recorded in street scenes from 50 different cities, with high quality pixel-level annotations of 5,000 frames in addition to a larger set of 20,000 weakly annotated frames.
Class	`COCO2014Dataset`	COCO is a large-scale object detection, segmentation, and captioning dataset.
Class	`COCO2017Dataset`	COCO is a large-scale object detection, segmentation, and captioning dataset.
Class	`FiftyOneDataset`	Base class for zoo datasets that are provided natively by FiftyOne.
Class	`FIWDataset`	Families in the Wild is a public benchmark for recognizing families via facial images. The dataset contains over 26,642 images of 5,037 faces collected from 978 families. A unique Family ID (FID) is assigned per family, ranging from F0001-F1018 (i...
Class	`HMDB51Dataset`	HMDB51 is an action recognition dataset containing a total of 6,766 clips distributed across 51 action classes.
Class	`ImageNetSampleDataset`	A small sample of images from the ImageNet 2012 dataset.
Class	`Kinetics400Dataset`	Kinetics is a collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover 400/600/700 human action classes, depending on the dataset version. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging...
Class	`Kinetics600Dataset`	Kinetics is a collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover 400/600/700 human action classes, depending on the dataset version. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging...
Class	`Kinetics7002020Dataset`	Kinetics is a collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover 400/600/700 human action classes, depending on the dataset version. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging...
Class	`Kinetics700Dataset`	Kinetics is a collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover 400/600/700 human action classes, depending on the dataset version. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging...
Class	`KITTIDataset`	KITTI contains a suite of vision tasks built using an autonomous driving platform.
Class	`KITTIMultiviewDataset`	KITTI contains a suite of vision tasks built using an autonomous driving platform.
Class	`LabeledFacesInTheWildDataset`	Labeled Faces in the Wild is a public benchmark for face verification, also known as pair matching.
Class	`OpenImagesV6Dataset`	Open Images V6 is a dataset of ~9 million images, roughly 2 million of which are annotated and available via this zoo dataset.
Class	`OpenImagesV7Dataset`	Open Images V7 is a dataset of ~9 million images, roughly 2 million of which are annotated and available via this zoo dataset.
Class	`PlacesDataset`	Places is a scene recognition dataset of 10 million images comprising ~400 unique scene categories.
Class	`Quickstart3DDataset`	A small 3D dataset with meshes, point clouds, and oriented bounding boxes.
Class	`QuickstartDataset`	A small dataset with ground truth bounding boxes and predictions.
Class	`QuickstartGeoDataset`	A small dataset with geolocation data.
Class	`QuickstartGroupsDataset`	A small dataset with grouped image and point cloud data.
Class	`QuickstartVideoDataset`	A small video dataset with dense annotations.
Class	`SamaCOCODataset`	Sama-COCO is a large-scale object detection, segmentation, and captioning dataset based on COCO2017. It is a relabeling of the original training and validation sets with tighter polygons and more individually annotated crowds.
Class	`UCF101Dataset`	UCF101 is an action recognition data set of realistic action videos, collected from YouTube, having 101 action categories. This data set is an extension of UCF50 data set which has 50 action categories.
Constant	`AVAILABLE_DATASETS`	Undocumented
Variable	`logger`	Undocumented
Function	`_download_and_extract_archive`	Undocumented
Function	`_move_dir`	Undocumented
Function	`_should_patch_pcd`	Undocumented

AVAILABLE_DATASETS = (source) ¶

Undocumented

Value

{'activitynet-100': ActivityNet100Dataset,
 'activitynet-200': ActivityNet200Dataset,
 'bdd100k': BDD100KDataset,
 'caltech101': Caltech101Dataset,
 'caltech256': Caltech256Dataset,
 'cityscapes': CityscapesDataset,
 'coco-2014': COCO2014Dataset,
...

logger = (source) ¶

Undocumented

def _download_and_extract_archive(fid, archive_name, dir_in_archive, dataset_dir, scratch_dir): (source) ¶

Undocumented

def _move_dir(src, dst): (source) ¶

Undocumented

def _should_patch_pcd(dataset_dir): (source) ¶

Undocumented