Kitti — Torchvision 0.22 documentation (original) (raw)

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)[source]¶

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: └── 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][source]¶

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