Module ouster.sdk.examples

Copyright (c) 2021, Ouster, Inc. All rights reserved.

Code examples for using the Ouster SDK.

These modules are provided for documentation and testing purposes only, and should not be considered a stable public API.

Client Examples ouster.sdk.examples.client

Copyright (c) 2021, Ouster, Inc. All rights reserved.

Executable examples for using the sensor client APIs.

This module has a rudimentary command line interface. For usage, run:

$ python -m ouster.sdk.examples.client -h
configure_dual_returns(hostname)[source]

Configure sensor to use dual returns profile given hostname

Parameters:

hostname (str) – hostname of the sensor

Return type:

None

configure_sensor_params(hostname)[source]

Configure sensor params given hostname

Parameters:

hostname (str) – hostname of the sensor

Return type:

None

fetch_metadata(hostname)[source]

Fetch metadata from a sensor and write it to disk.

Accurately reconstructing point clouds from a sensor data stream requires access to sensor calibration and per-run configuration like the operating mode and azimuth window.

The client API makes it easy to read metadata and write it to disk for use with recorded data streams.

Parameters:

hostname (str) – hostname of the sensor

Return type:

None

filter_3d_by_range_and_azimuth(hostname, lidar_port=7502, range_min=2)[source]

Easily filter 3D Point Cloud by Range and Azimuth Using the 2D Representation

Parameters:

  • hostname (str) – hostname of sensor

  • lidar_port (int) – UDP port to listen on for lidar data

  • range_min (int) – range minimum in meters

Return type:

None

live_plot_reflectivity(hostname, lidar_port=7502)[source]

Display reflectivity from live sensor

Parameters:

  • hostname (str) – hostname of the sensor

  • lidar_port (int) – UDP port to listen on for lidar data

Return type:

None

plot_xyz_points(hostname, lidar_port=7502)[source]

Display range from a single scan as 3D points

Parameters:

  • hostname (str) – hostname of the sensor

  • lidar_port (int) – UDP port to listen on for lidar data

Return type:

None

record_pcap(hostname, lidar_port=7502, imu_port=7503, n_seconds=10)[source]

Record data from live sensor to pcap file.

Note that pcap files recorded this way only preserve the UDP data stream and not networking information, unlike capturing packets directly from a network interface with tools like tcpdump or wireshark.

See the API docs of pcap.record() for additional options for writing pcap files.

Parameters:

  • hostname (str) – hostname of the sensor

  • lidar_port (int) – UDP port to listen on for lidar data

  • imu_port (int) – UDP port to listen on for imu data

  • n_seconds (int) – max seconds of time to record. (Ctrl-Z correctly closes streams)

Return type:

None

PCAP Examples ouster.sdk.examples.pcap

Copyright (c) 2021, Ouster, Inc. All rights reserved.

Executable examples for using the pcap APIs.

This module has a rudimentary command line interface. For usage, run:

$ python -m ouster.sdk.examples.pcap -h
pcap_3d_one_scan(source_file, num=0)[source]

Render one scan from a pcap file in the Open3D viewer.

Parameters:

  • source – path to pcap

  • num (int) – scan number in a given pcap file (satrs from 0)

Return type:

None

pcap_display_xyz_points(source_file, num=0)[source]

Plot point cloud using matplotlib.

Return type:

None

pcap_to_las(source_file, num=0, las_dir='.', las_base='las_out', las_ext='las')[source]

Write scans from a pcap to las files (one per lidar scan).

Return type:

None

pcap_to_pcd(source_file, num=0, pcd_dir='.', pcd_base='pcd_out', pcd_ext='pcd')[source]

Write scans from a pcap to pcd files (one per lidar scan).

Return type:

None

pcap_to_ply(source_file, num=0, ply_dir='.', ply_base='ply_out', ply_ext='ply')[source]

Write scans from a pcap to ply files (one per lidar scan).

Return type:

None

pcap_query_scan(source_file, num=0)[source]

Example: Query available fields in LidarScan

Parameters:

  • source_file (str) – Path to pcap file

  • num (int) – scan number in a given pcap file (satrs from 0)

Return type:

None

pcap_read_packets(source_file, num=0)[source]

Basic read packets example from pcap file.

Return type:

None

main()[source]

Pcap examples runner.

Open3D Examples ouster.sdk.examples.open3d

Examples PointViz ouster.sdk.examples.viz

Copyright (c) 2021, Ouster, Inc. All rights reserved.

Example of custom visualizer use.

Intended to run with python -m ouster.sdk.examples.viz

make_checker_board(square_size, reps)[source]

Makes a test checker board image.

main()[source]

PointViz visualizer examples.

Reference Code ouster.sdk.examples.reference

Copyright (c) 2021, Ouster, Inc. All rights reserved.

Reference implementations of common operations.

xyz_proj_beam_to_sensor_transform(metadata, scan)[source]

Computes a point cloud from a scan as numpy array.

This is a reference implementation that follows the calculations from Section X of the Software User Manual exactly. Output is a point cloud in the sensor frame with points arranged in column-major order, with coordinates in meters.

Parameters:

  • metadata (SensorInfo) – Sensor metadata associated with the scan

  • scan (LidarScan) – A frame of lidar data

Return type:

ndarray

Returns:

A H x W x 3 array of point coordinates

xyz_proj_origin_to_origin_mm(metadata, scan)[source]

Computes a point cloud from a scan as numpy array

This is the old reference implementation that follows the calculations from Section 3.1.2 of the FW 2.0 Software User Manual exactly for OS-0, OS-1, and OS-2 sensors. The output is a point cloud in the sensor frame with points arranged in column-major order, with coordinates in meters.

Parameters:

  • metadata (SensorInfo) – Sensor metadata associated with the scan

  • scan (LidarScan) – A frame of lidar data

Return type:

ndarray

Returns:

A H x W x 3 array of point coordinates

destagger(pixel_shift_by_row, field)[source]

Reference implementation for destaggering a field of data.

In the default staggered representation, each column corresponds to a single timestamp. In the destaggered representation, each column corresponds to a single azimuth angle, compensating for the azimuth offset of each beam.

Destaggering is used for visualizing lidar data as an image or for algorithms that exploit the structure of the lidar data, such as beam_uniformity in ouster_viz, or computer vision algorithms.

Parameters:

  • pixel_shift_by_row (List[int]) – List of pixel shifts by row from sensor metadata

  • field (ndarray) – Staggered data as a H x W numpy array

Return type:

ndarray

Returns:

Destaggered data as a H x W numpy array