open3d.ml.torch.datasets.NuScenes#
- class open3d.ml.torch.datasets.NuScenes(dataset_path, info_path=None, name='NuScenes', cache_dir='./logs/cache', use_cache=False, **kwargs)#
This class is used to create a dataset based on the NuScenes 3D dataset, and used in object detection, visualizer, training, or testing.
The NuScenes 3D dataset is best suited for autonomous driving applications.
- __init__(dataset_path, info_path=None, name='NuScenes', 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.
info_path – The path to the file that includes information about the dataset. This is default to dataset path if nothing is provided.
name – The name of the dataset (NuScenes 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:
dataset – The current dataset to which the datum belongs to. attr: The attribute that needs to be checked.
- Returns:
- If the dataum attribute is tested, then return the path where the
attribute is stored; else, returns false.
- read_cams(cam_dict)#
Reads image data from the cam dict provided.
- Parameters:
cam_dict (Dict) – Mapping from camera names to dict with image information (‘data_path’, ‘sensor2lidar_translation’, ‘sensor2lidar_rotation’, ‘cam_intrinsic’).
- Returns:
A dict with keys as camera names and value as images.
- static read_label(info, calib)#
Reads labels of bound boxes.
- Returns:
The data objects with bound boxes information.
- static read_lidar(path)#
Reads lidar data from the path provided.
- Returns:
A data object with lidar information.
- save_test_result()#
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.