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Lidars and Cameras Sequence

A LidarsAndCamerasSeq consists of a sequence of camera images and lidar point clouds, where each frame consists on 1-9 camera images as well as 1-20 point clouds. For more documentation on what each field corresponds to in the LidarsAndCamerasSeq object please check the section related to Scene Overview.

examples/lidars_and_cameras_seq.py
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Use dryrun to validate

Setting dryrun parameter to true in the method call, will validate the scene using the API but not create it.

reuse calibration

Note that you can, and should, reuse the same calibration for multiple s if possible.

Providing Ego Vehicle Motion Information​

Ego vehicle motion (i.e. the position and rotation of the ego vehicle) is optional information that can be provided when creating LidarsAndCamerasSeqs. This information can enable a massive reduction in the time it takes to annotate static objects. Ego vehicle motion information is provided by passing a EgoVehicleMotion object to each Frame in the scene.

examples/lidars_and_cameras_seq_full.py
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Coordinate Systems

Note that both position and rotation for ego vehicle pose are with respect to the local coordinate system.

Shutter timings​

Shutter timings are optional metadata that may be provided when creating an Image within a Frame. Timings are two values: shutter start and end timestamp in nanoseconds since unix epoch and are specified for each image in each frame.

examples/lidars_and_cameras_seq_with_imu_and_shutter_times.py
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