open3d.ml.tf.datasets

Classes

Argoverse(dataset_path[, info_path, name, ...])	This class is used to create a dataset based on the Agroverse dataset, and used in object detection, visualizer, training, or testing.
Custom3D(dataset_path[, name, cache_dir, ...])	A template for customized dataset that you can use with a dataloader to feed data when training a model.
InferenceDummySplit(inference_data)
KITTI(dataset_path[, name, cache_dir, ...])	This class is used to create a dataset based on the KITTI dataset, and used in object detection, visualizer, training, or testing.
Lyft(dataset_path[, info_path, name, ...])	This class is used to create a dataset based on the Lyft dataset, and used in object detection, visualizer, training, or testing.
MatterportObjects(dataset_path[, name, ...])	This class is used to create a dataset based on the Matterport-Chair dataset and other related datasets.
NuScenes(dataset_path[, info_path, name, ...])	This class is used to create a dataset based on the NuScenes 3D dataset, and used in object detection, visualizer, training, or testing.
ParisLille3D(dataset_path[, name, ...])	This class is used to create a dataset based on the ParisLille3D dataset, and used in visualizer, training, or testing.
S3DIS(dataset_path[, name, task, cache_dir, ...])	This class is used to create a dataset based on the S3DIS (Stanford Large-Scale 3D Indoor Spaces) dataset, and used in visualizer, training, or testing.
Scannet(dataset_path[, name, cache_dir, ...])	Scannet 3D dataset for Object Detection, used in visualizer, training, or test.
SemSegRandomSampler(dataset)	Random sampler for semantic segmentation datasets.
SemSegSpatiallyRegularSampler(dataset)	Spatially regularSampler sampler for semantic segmentation datasets.
Semantic3D(dataset_path[, name, cache_dir, ...])	This class is used to create a dataset based on the Semantic3D dataset, and used in visualizer, training, or testing.
SemanticKITTI(dataset_path[, name, ...])	This class is used to create a dataset based on the SemanticKitti dataset, and used in visualizer, training, or testing.
ShapeNet(dataset_path[, name, ...])	This class is used to create a dataset based on the ShapeNet dataset, and used in object detection, visualizer, training, or testing.
SunRGBD(dataset_path[, name, cache_dir, ...])	SunRGBD 3D dataset for Object Detection, used in visualizer, training, or test.
TUMFacade(dataset_path[, info_path, name, ...])
Toronto3D(dataset_path[, name, cache_dir, ...])	Toronto3D dataset, used in visualizer, training, or test.
Waymo(dataset_path[, name, cache_dir, use_cache])	This class is used to create a dataset based on the Waymo 3D dataset, and used in object detection, visualizer, training, or testing.

Functions

require_ml_extra()

Raise ImportError if Open3D-ML Python dependencies are not installed.

Modules

augment	Dataset augmentation classes with functions such as random rotation, translation, and scaling.
utils	Utilities for processing data, such as normalization and cropping.