waymo_open_dataset

• Description:

The Waymo Open Dataset is comprised of high resolution sensor data collected by Waymo self-driving cars in a wide variety of conditions. This data is licensed for non-commercial use.

Warning: this dataset requires additional authorization and registration. Please look at tfds documentation for accessing GCS, and afterwards, please register via https://waymo.com/open/licensing/

• Additional Documentation: Explore on Papers With Code

• Homepage: http://www.waymo.com/open/

• Source code: tfds.object_detection.WaymoOpenDataset

• Versions:

  • 0.2.0 (default): No release notes.

• Download size: Unknown size

• Auto-cached (documentation): No

• Feature structure:

FeaturesDict({
    'camera_FRONT': FeaturesDict({
        'image': Image(shape=(1280, 1920, 3), dtype=uint8),
        'labels': Sequence({
            'bbox': BBoxFeature(shape=(4,), dtype=float32),
            'type': ClassLabel(shape=(), dtype=int64, num_classes=5),
        }),
    }),
    'camera_FRONT_LEFT': FeaturesDict({
        'image': Image(shape=(1280, 1920, 3), dtype=uint8),
        'labels': Sequence({
            'bbox': BBoxFeature(shape=(4,), dtype=float32),
            'type': ClassLabel(shape=(), dtype=int64, num_classes=5),
        }),
    }),
    'camera_FRONT_RIGHT': FeaturesDict({
        'image': Image(shape=(1280, 1920, 3), dtype=uint8),
        'labels': Sequence({
            'bbox': BBoxFeature(shape=(4,), dtype=float32),
            'type': ClassLabel(shape=(), dtype=int64, num_classes=5),
        }),
    }),
    'camera_SIDE_LEFT': FeaturesDict({
        'image': Image(shape=(886, 1920, 3), dtype=uint8),
        'labels': Sequence({
            'bbox': BBoxFeature(shape=(4,), dtype=float32),
            'type': ClassLabel(shape=(), dtype=int64, num_classes=5),
        }),
    }),
    'camera_SIDE_RIGHT': FeaturesDict({
        'image': Image(shape=(886, 1920, 3), dtype=uint8),
        'labels': Sequence({
            'bbox': BBoxFeature(shape=(4,), dtype=float32),
            'type': ClassLabel(shape=(), dtype=int64, num_classes=5),
        }),
    }),
    'context': FeaturesDict({
        'name': Text(shape=(), dtype=string),
    }),
    'timestamp_micros': int64,
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
camera_FRONT	FeaturesDict
camera_FRONT/image	Image	(1280, 1920, 3)	uint8
camera_FRONT/labels	Sequence
camera_FRONT/labels/bbox	BBoxFeature	(4,)	float32
camera_FRONT/labels/type	ClassLabel		int64
camera_FRONT_LEFT	FeaturesDict
camera_FRONT_LEFT/image	Image	(1280, 1920, 3)	uint8
camera_FRONT_LEFT/labels	Sequence
camera_FRONT_LEFT/labels/bbox	BBoxFeature	(4,)	float32
camera_FRONT_LEFT/labels/type	ClassLabel		int64
camera_FRONT_RIGHT	FeaturesDict
camera_FRONT_RIGHT/image	Image	(1280, 1920, 3)	uint8
camera_FRONT_RIGHT/labels	Sequence
camera_FRONT_RIGHT/labels/bbox	BBoxFeature	(4,)	float32
camera_FRONT_RIGHT/labels/type	ClassLabel		int64
camera_SIDE_LEFT	FeaturesDict
camera_SIDE_LEFT/image	Image	(886, 1920, 3)	uint8
camera_SIDE_LEFT/labels	Sequence
camera_SIDE_LEFT/labels/bbox	BBoxFeature	(4,)	float32
camera_SIDE_LEFT/labels/type	ClassLabel		int64
camera_SIDE_RIGHT	FeaturesDict
camera_SIDE_RIGHT/image	Image	(886, 1920, 3)	uint8
camera_SIDE_RIGHT/labels	Sequence
camera_SIDE_RIGHT/labels/bbox	BBoxFeature	(4,)	float32
camera_SIDE_RIGHT/labels/type	ClassLabel		int64
context	FeaturesDict
context/name	Text		string
timestamp_micros	Tensor		int64

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Citation:

@InProceedings{Sun_2020_CVPR,
author = {Sun, Pei and Kretzschmar, Henrik and Dotiwalla, Xerxes and Chouard, Aurelien and Patnaik, Vijaysai and Tsui, Paul and Guo, James and Zhou, Yin and Chai, Yuning and Caine, Benjamin and Vasudevan, Vijay and Han, Wei and Ngiam, Jiquan and Zhao, Hang and Timofeev, Aleksei and Ettinger, Scott and Krivokon, Maxim and Gao, Amy and Joshi, Aditya and Zhang, Yu and Shlens, Jonathon and Chen, Zhifeng and Anguelov, Dragomir},
title = {Scalability in Perception for Autonomous Driving: Waymo Open Dataset},
booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}

waymo_open_dataset/v1.2 (default config)

• Config description: Waymo Open Dataset v1.2

• Dataset size: 336.62 GiB

• Splits:

Split	Examples
'train'	158,081
'validation'	39,987

• Examples (tfds.as_dataframe):

waymo_open_dataset/v1.1

• Config description: Waymo Open Dataset v1.1

• Dataset size: 336.62 GiB

• Splits:

Split	Examples
'train'	158,081
'validation'	39,987

• Examples (tfds.as_dataframe):

waymo_open_dataset/v1.0

• Config description: Waymo Open Dataset v1.0 This dataset is also available in pre-processed format, making it faster to load, if you select the correct data_dir:

tfds.load('waymo_open_dataset/v1.0', data_dir='gs://waymo_open_dataset_v_1_0_0_individual_files/tensorflow_datasets')

• Dataset size: 34.73 GiB

• Splits:

Split	Examples
'train'	14,884
'validation'	4,954

• Examples (tfds.as_dataframe):