Kitti

class torchvision.datasets.Kitti(root: Union[str, Path], train: bool = True, transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, transforms: Optional[Callable] = None, download: bool = False)

KITTI Dataset.

It corresponds to the “left color images of object” dataset, for object detection.

Parameters:

• root (str or pathlib.Path) –

  Root directory where images are downloaded to. Expects the following folder structure if download=False:

  <root>
      └── Kitti
          └─ raw
              ├── training
              |   ├── image_2
              |   └── label_2
              └── testing
                  └── image_2
  

• train (bool, optional) – Use train split if true, else test split. Defaults to train.

• transform (callable, optional) – A function/transform that takes in a PIL image and returns a transformed version. E.g, transforms.PILToTensor

• target_transform (callable, optional) – A function/transform that takes in the target and transforms it.

• transforms (callable, optional) – A function/transform that takes input sample and its target as entry and returns a transformed version.

• download (bool, optional) – If true, downloads the dataset from the internet and puts it in root directory. If dataset is already downloaded, it is not downloaded again.

Special-members:

__getitem__(index: int) → tuple[Any, Any]

Get item at a given index.

Parameters:

index (int) – Index

Returns:

(image, target), where target is a list of dictionaries with the following keys:

• type: str

• truncated: float

• occluded: int

• alpha: float

• bbox: float[4]

• dimensions: float[3]

• locations: float[3]

• rotation_y: float

Return type:

tuple