viam.services.vision.client

Module Contents

Classes

VisionClient

Connect to the Vision service, which allows you to access various computer vision algorithms
class viam.services.vision.client.VisionClient(name: str, channel: grpclib.client.Channel)[source]

Bases: viam.services.vision.vision.Vision, viam.resource.rpc_client_base.ReconfigurableResourceRPCClientBase

Connect to the Vision service, which allows you to access various computer vision algorithms (like detection, segmentation, tracking, etc) that usually only require a camera or image input.

client: viam.proto.service.vision.VisionServiceStub
async get_detections_from_camera(camera_name: str, *, extra: Optional[Mapping[str, Any]] = None, timeout: Optional[float] = None) → List[viam.proto.service.vision.Detection][source]

Get a list of detections in the next image given a camera and a detector

Parameters:

camera_name (str) – The name of the camera to use for detection

Returns:

A list of 2D bounding boxes, their labels, and the confidence score of the labels, around the found objects in the next 2D image from the given camera, with the given detector applied to it.

Return type:

List[viam.proto.service.vision.Detection]

async get_detections(image: Union[viam.media.viam_rgba_plugin.Image.Image, viam.media.video.RawImage], *, extra: Optional[Mapping[str, Any]] = None, timeout: Optional[float] = None) → List[viam.proto.service.vision.Detection][source]

Get a list of detections in the given image using the specified detector

Parameters:

image (Image) – The image to get detections from

Returns:

A list of 2D bounding boxes, their labels, and the confidence score of the labels, around the found objects in the next 2D image from the given camera, with the given detector applied to it.

Return type:

List[viam.proto.service.vision.Detection]

async get_classifications_from_camera(camera_name: str, count: int, *, extra: Optional[Mapping[str, Any]] = None, timeout: Optional[float] = None) → List[viam.proto.service.vision.Classification][source]

Get a list of classifications in the next image given a camera and a classifier

Parameters:

  • camera_name (str) – The name of the camera to use for detection

  • count (int) – The number of classifications desired

Returns:

The list of Classifications

Return type:

List[viam.proto.service.vision.Classification]

async get_classifications(image: Union[viam.media.viam_rgba_plugin.Image.Image, viam.media.video.RawImage], count: int, *, extra: Optional[Mapping[str, Any]] = None, timeout: Optional[float] = None) → List[viam.proto.service.vision.Classification][source]

Get a list of classifications in the given image using the specified classifier

Parameters:

  • image (Image) – The image to get detections from

  • count (int) – The number of classifications desired

Returns:

The list of Classifications

Return type:

List[viam.proto.service.vision.Classification]

async get_object_point_clouds(camera_name: str, *, extra: Optional[Mapping[str, Any]] = None, timeout: Optional[float] = None) → List[viam.proto.common.PointCloudObject][source]

Returns a list of the 3D point cloud objects and associated metadata in the latest picture obtained from the specified 3D camera (using the specified segmenter).

To deserialize the returned information into a numpy array, use the Open3D library.

import numpy as np
import open3d as o3d

object_point_clouds = await vision.get_object_point_clouds(camera_name, segmenter_name)

# write the first object point cloud into a temporary file
with open("/tmp/pointcloud_data.pcd", "wb") as f:
    f.write(object_point_clouds[0].point_cloud)
pcd = o3d.io.read_point_cloud("/tmp/pointcloud_data.pcd")
points = np.asarray(pcd.points)
Parameters:

camera_name (str) – The name of the camera

Returns:

The pointcloud objects with metadata

Return type:

List[viam.proto.common.PointCloudObject]

async do_command(command: Mapping[str, viam.utils.ValueTypes], *, timeout: Optional[float] = None) → Mapping[str, viam.utils.ValueTypes][source]

Send/receive arbitrary commands

Parameters:

command (Dict[str, ValueTypes]) – The command to execute

Returns:

Result of the executed command

Return type:

Dict[str, ValueTypes]

classmethod from_robot(robot: viam.robot.client.RobotClient, name: str) → typing_extensions.Self

Get the service named name from the provided robot.

Parameters:

  • robot (RobotClient) – The robot

  • name (str) – The name of the service

Returns:

The service, if it exists on the robot

Return type:

Self

classmethod get_resource_name(name: str) → viam.proto.common.ResourceName

Get the ResourceName for this Resource with the given name

Parameters:

name (str) – The name of the Resource

get_operation(kwargs: Mapping[str, Any]) → viam.operations.Operation

Get the Operation associated with the currently running function.

When writing custom resources, you should get the Operation by calling this function and check to see if it’s cancelled. If the Operation is cancelled, then you can perform any necessary (terminating long running tasks, cleaning up connections, etc. ).

Parameters:

kwargs (Mapping[str, Any]) – The kwargs object containing the operation

Returns:

The operation associated with this function

Return type:

viam.operations.Operation