kitti

• Visualization: Explore in Know Your Data north_east

• Description:

Kitti contains a suite of vision tasks built using an autonomous driving platform. The full benchmark contains many tasks such as stereo, optical flow, visual odometry, etc. This dataset contains the object detection dataset, including the monocular images and bounding boxes. The dataset contains 7481 training images annotated with 3D bounding boxes. A full description of the annotations can be found in the readme of the object development kit readme on the Kitti homepage.

• Homepage: http://www.cvlibs.net/datasets/kitti/

• Source code: tfds.object_detection.Kitti

• Versions:

  • 3.1.0: No release notes.
  • 3.2.0 (default): Devkit updated.

• Download size: 11.71 GiB

• Dataset size: 5.27 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'test'	711
'train'	6,347
'validation'	423

• Feature structure:

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'image/file_name': Text(shape=(), dtype=tf.string),
    'objects': Sequence({
        'alpha': tf.float32,
        'bbox': BBoxFeature(shape=(4,), dtype=tf.float32),
        'dimensions': Tensor(shape=(3,), dtype=tf.float32),
        'location': Tensor(shape=(3,), dtype=tf.float32),
        'occluded': ClassLabel(shape=(), dtype=tf.int64, num_classes=4),
        'rotation_y': tf.float32,
        'truncated': tf.float32,
        'type': ClassLabel(shape=(), dtype=tf.int64, num_classes=8),
    }),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(None, None, 3)	tf.uint8
image/file_name	Text		tf.string
objects	Sequence
objects/alpha	Tensor		tf.float32
objects/bbox	BBoxFeature	(4,)	tf.float32
objects/dimensions	Tensor	(3,)	tf.float32
objects/location	Tensor	(3,)	tf.float32
objects/occluded	ClassLabel		tf.int64
objects/rotation_y	Tensor		tf.float32
objects/truncated	Tensor		tf.float32
objects/type	ClassLabel		tf.int64

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

• Citation:

@inproceedings{Geiger2012CVPR,
  author = {Andreas Geiger and Philip Lenz and Raquel Urtasun},
  title = {Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2012}
}