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# Kitti

class torchvision.datasets.Kitti(root: str, 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 (string) –

      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

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