open3d.ml.torch.datasets.Waymo#

class open3d.ml.torch.datasets.Waymo(dataset_path, name='Waymo', cache_dir='./logs/cache', use_cache=False, **kwargs)#

This class is used to create a dataset based on the Waymo 3D dataset, and used in object detection, visualizer, training, or testing.

The Waymo 3D dataset is best suited for autonomous driving applications.

__init__(dataset_path, name='Waymo', cache_dir='./logs/cache', use_cache=False, **kwargs)#

Initialize the function by passing the dataset and other details.

Parameters:

  • dataset_path – The path to the dataset to use.

  • name – The name of the dataset (Waymo in this case).

  • cache_dir – The directory where the cache is stored.

  • use_cache – Indicates if the dataset should be cached.

Returns:

The corresponding class.

Return type:

class

static get_label_to_names()#

Returns a label to names dictionary object.

Returns:

A dict where keys are label numbers and values are the corresponding names.

get_split(split)#

Returns a dataset split.

Parameters:

  • split – A string identifying the dataset split that is usually one of

  • 'training' –

  • 'test' –

  • 'validation' –

  • 'all'. (or) –

Returns:

A dataset split object providing the requested subset of the data.

get_split_list(split)#

Returns the list of data splits available.

Parameters:

  • split – A string identifying the dataset split that is usually one of

  • 'training' –

  • 'test' –

  • 'validation' –

  • 'all'. (or) –

Returns:

A dataset split object providing the requested subset of the data.

Raises:

  • ValueError – Indicates that the split name passed is incorrect. The

  • split name should be one of 'training', 'test', 'validation', or –

  • 'all'. –

is_tested()#

Checks if a datum in the dataset has been tested.

Parameters:

attr – The attribute that needs to be checked.

Returns:

If the datum attribute is tested, then return the path where the

attribute is stored; else, returns false.

static read_calib(path)#

Reads calibiration for the dataset. You can use them to compare modeled results to observed results.

Returns:

The camera and the camera image used in calibration.

static read_label(path, calib)#

Reads labels of bounding boxes.

Parameters:

  • path – The path to the label file.

  • calib – Calibration as returned by read_calib().

Returns:

The data objects with bounding boxes information.

static read_lidar(path)#

Reads lidar data from the path provided.

Returns:

pointcloud data with shape [N, 6], where

the format is xyzRGB.

Return type:

pc

save_test_result(attr)#

Saves the output of a model.

Parameters:

  • results – The output of a model for the datum associated with the attribute passed.

  • attr – The attributes that correspond to the outputs passed in results.