Python

get_sdk_version()

Get the SDK version number

Parameters: None

Return value:

version: str type, SDK version number

get_info(ip: str)

Get basic camera information, including serial number, IP address, model, and other device parameters. Returns None if retrieval fails.

Parameters:

ip: str type, IP address of the camera

Return value:

info: dict type, contains the following fields:

* sn: str type, camera serial number

* ip: str type, camera IP address

* model: str type, camera model

* alias: str type, camera name

* width: int type, image width

* height: int type, image height

get_header(ip: str, frame_id: str, timeout: int = 2000)

Get camera photo information, including width and height. Returns None if retrieval fails.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the camera

timeout: int type, timeout duration in milliseconds, default is 2000 ms

Return value:

header: dict type, camera photo information including width and height

get_config(ip: str, frame_id: str = "")

Get the current or specified frame configuration parameters of the camera. Returns None if retrieval fails.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the data to be retrieved. If an empty string is passed, the latest configuration will be returned.

Return value:

config: dict type, camera configuration parameters

set_config(ip: str, config: dict)

Update camera configuration parameters. Returns the current configuration if successful, or None if failed.

Parameters:

ip: str type, IP address of the camera

config: dict type, configuration parameters, defined the same as in get_config

Return value:

latest_config: dict type, the updated current configuration of the camera, defined the same as config

trigger_frame(ip: str, pointcloud: bool = True)

Trigger the capture of a frame, which may contain both 2D images and point cloud data. Uses frame ID for indexing. Returns None if failed.

Parameters:

ip: str type, IP address of the camera

pointcloud: bool type, whether to request point cloud data. If set to False, the triggered frame will contain only 2D image data.

Return value:

frame_id: str type, frame ID returned after triggering the capture

get_image(ip: str, frame_id: str)

Retrieve a 2D image based on the frame ID. Returns None if failed.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the data to be retrieved, which can be obtained from trigger_frame

Return value:

image: numpy.ndarray type, retrieved image data

get_point_cloud(ip: str, frame_id: str)

Retrieve the point cloud based on the frame ID. Returns None if failed.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the data to be retrieved, which can be obtained from trigger_frame

Return value:

point_map: numpy.ndarray type, point cloud data aligned pixel-wise with the 2D image

get_point_cloud_with_time_stats(ip: str, frame_id: str)

Retrieve the point cloud along with network transmission statistics based on the frame ID. Returns None if failed.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the data to be retrieved, which can be obtained from trigger_frame

Return value:

point_map: numpy.ndarray type, point cloud data aligned pixel-wise with the 2D image

network_transmit_time_ms: float type, network transmission time in milliseconds

network_speed_mbps: float type, network transmission speed in Mbps

get_image_and_point_cloud(ip: str, frame_id: str)

Retrieve both 2D image and point cloud data based on the frame ID. Returns None if failed.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the data to be retrieved, which can be obtained from trigger_frame

Return value:

image: numpy.ndarray type, retrieved image data

point_map: numpy.ndarray type, point cloud data aligned pixel-wise with the 2D image

get_image_and_point_cloud_with_time_stats(ip: str, frame_id: str)

Retrieve both 2D image and point cloud data along with network transmission statistics based on the frame ID. Returns None if failed.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the data to be retrieved, which can be obtained from trigger_frame

Return value:

image: numpy.ndarray type, retrieved image data

point_map: numpy.ndarray type, point cloud data aligned pixel-wise with the 2D image

network_transmit_time_ms: float type, network transmission time in milliseconds

network_speed_mbps: float type, network transmission speed in Mbps

get_depth(ip: str, frame_id: str)

Retrieve the depth map based on the frame ID. Returns None if failed.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the data to be retrieved, which can be obtained from trigger_frame

Return value:

depth: numpy.ndarray type, depth data aligned pixel-wise with the 2D image

get_camera_matrix(ip: str)

Retrieve the camera intrinsic matrix.

Parameters:

ip: str type, IP address of the camera

Return value:

camera_matrix: numpy.ndarray type, camera matrix stored row-wise, can be reshaped into a 3x3 matrix, compatible with OpenCV

get_distortion(ip: str)

Retrieve the camera distortion coefficients.

Parameters:

ip: str type, IP address of the camera

Return value:

distortion: numpy.ndarray type, distortion parameters, compatible with OpenCV

get_point_cloud_in_ply(ip: str, frame_id: str)

Retrieve point cloud data in PLY format. Returns None if failed.

Parameters:

ip: str type, IP address of the camera

frame_id: str type, frame ID of the data to be retrieved, which can be obtained from trigger_frame

Return value:

ply_data: bytes type, point cloud data in PLY format

search_camera()

Search for available camera devices on the network. Returns None if no cameras are found.

Parameters: None

Return value:

found_camera: list type, list of found camera information