Waymo¶
- class tri3d.datasets.Waymo(root, split='training')¶
Waymo Open dataset (parquet file format).
- cam_sensors: List[str] = ['CAM_FRONT', 'CAM_FRONT_LEFT', 'CAM_FRONT_RIGHT', 'CAM_SIDE_LEFT', 'CAM_SIDE_RIGHT', 'CAM_REAR_LEFT', 'CAM_REAR', 'CAM_REAR_RIGHT']¶
Camera names.
- img_sensors: List[str] = ['IMG_FRONT', 'IMG_FRONT_LEFT', 'IMG_FRONT_RIGHT', 'IMG_SIDE_LEFT', 'IMG_SIDE_RIGHT', 'IMG_REAR_LEFT', 'IMG_REAR', 'IMG_REAR_RIGHT']¶
Camera names (image plane coordinate).
- pcl_sensors: List[str] = ['LIDAR_TOP', 'LIDAR_FRONT', 'LIDAR_SIDE_LEFT', 'LIDAR_SIDE_RIGHT', 'LIDAR_REAR']¶
Point cloud sensor names.
- det_labels: List[str] = ['UNKNOWN', 'VEHICLE', 'PEDESTRIAN', 'SIGN', 'CYCLIST']¶
Detection labels.
- sem_labels: List[str] = ['UNDEFINED', 'CAR', 'TRUCK', 'BUS', 'OTHER_VEHICLE', 'MOTORCYCLIST', 'BICYCLIST', 'PEDESTRIAN', 'SIGN', 'TRAFFIC_LIGHT', 'POLE', 'CONSTRUCTION_CONE', 'BICYCLE', 'MOTORCYCLE', 'BUILDING', 'VEGETATION', 'TREE_TRUNK', 'CURB', 'ROAD', 'LANE_MARKER', 'OTHER_GROUND', 'WALKABLE', 'SIDEWALK']¶
Segmentation labels.
- sequences()¶
Return the list of sequences/recordings indices (0..num_sequences).
- timestamps(seq=None, sensor='LIDAR_TOP')¶
Return the frame timestamps for a given sensor .
- Parameters:
seq (int | None) – Sequence index.
sensor – Sensor name.
- Returns:
An array of timestamps.
Note
frames are guarenteed to be sorted.
- image(seq, frame, sensor='CAM_FRONT')¶
Return image from given camera at given frame.
A default sensor (for instance a front facing camera) should be provided for convenience.
- semantic(seq, frame, sensor='LIDAR_TOP')¶
Return pointwise class annotations.
- Parameters:
seq (int) – sequence
frame (int) – frame
- Returns:
array of pointwise class label
- instances(seq, frame, sensor='LIDAR_TOP')¶
Return pointwise instance annotations.
- Parameters:
seq (int) – sequence
frame (int) – frame
- Returns:
array of pointwise instance label
- frames(seq=None, sensor=None)¶
Return the frames in the dataset or a particular sequence.
- Parameters:
seq – Sequence index.
seq – Sequence index.
- Returns:
A list of (sequence, frame) index tuples sorted by sequence and frame.
- alignment(seq, frame, coords)¶
Return the transformation from one coordinate system and timestamp to another.
- Parameters:
seq (int) – The sequence index
frame (int | tuple[int, int]) – Either a single frame or a (src, dst) tuple. The frame is respective to the sensor timeline as specified by coords.
coords (str | tuple[str, str]) – Either a single sensor/coordinate system or a (src, dst) tuple. The transformation also accounts for mismatches in sensor timelines and movement of the ego-car.
- Returns:
A transformation that projects points from one coordinate system at one frame to another.
- boxes(seq, frame, coords=None)¶
Return the 3D box annotations.
This function will interpolate and transform annotations if necessary in order to match the requested coordinate system and timeline.
- Parameters:
seq (int) – Sequence index.
frame (int) – Frame index.
coords (str | None) – The coordinate system and timeline to use.
- Returns:
A list of box annotations.
- points(seq, frame, sensor=None, coords=None)¶
Return an array of 3D point coordinates from lidars.
The first three columns contains xyz coordinates, additional columns are dataset-specific.
- Parameters:
seq (int)
frame (int)
sensor (str | None)
coords (str | None)
- poses(seq, sensor, timeline=None)¶
Return all sensor to world transforms for a sensor.
World references an arbitrary coordinate system for a sequence, not all datasets provide an actual global coordinate system.
- Parameters:
seq (int) – sequence
sensor (str) – sensor name
timeline (str | None) – When specified, the sensor poses will be interpolated to the timestamps of that timeline if necessary.
- Returns:
Sensor poses as a batched transform.
- rectangles(seq, frame)¶
Return a list of 2D rectangle annotations.
Note
The default coordinate system should be documented.
- Parameters:
seq (int) – sequence
frame (int) – frame or None to request annotations for the whole sequence
- Returns:
A list of 2D annotations.