agents.components.vision
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Module Contents#
Classes#
This component performs object detection and tracking on input images and outputs a list of detected objects, along with their bounding boxes and confidence scores. |
API#
- class agents.components.vision.Vision(*, inputs: List[Union[agents.ros.Topic, agents.ros.FixedInput]], outputs: List[agents.ros.Topic], model_client: agents.clients.model_base.ModelClient, config: Optional[agents.config.VisionConfig] = None, trigger: Union[agents.ros.Topic, List[agents.ros.Topic], float] = 1.0, callback_group=None, component_name: str = 'vision_component', **kwargs)#
Bases:
agents.components.model_component.ModelComponent
This component performs object detection and tracking on input images and outputs a list of detected objects, along with their bounding boxes and confidence scores.
- Parameters:
inputs (list[Union[Topic, FixedInput]]) – The input topics for the object detection. This should be a list of Topic objects or FixedInput objects, limited to Image type.
outputs (list[Topic]) – The output topics for the object detection. This should be a list of Topic objects, Detection and Tracking types are handled automatically.
model_client (ModelClient) – The model client for the vision component. This should be an instance of ModelClient.
config (VisionConfig) – The configuration for the vision component. This should be an instance of VisionConfig. If not provided, defaults to VisionConfig().
trigger (Union[Topic, list[Topic], float]) – The trigger value or topic for the vision component. This can be a single Topic object, a list of Topic objects, or a float value for timed components.
callback_group (str) – An optional callback group for the vision component. If provided, this should be a string. Otherwise, it defaults to None.
component_name (str) – The name of the vision component. This should be a string and defaults to “vision_component”.
Example usage:
image_topic = Topic(name="image", msg_type="Image") detections_topic = Topic(name="detections", msg_type="Detections") config = VisionConfig() model_client = ModelClient(model=DetectionModel(name='yolov5')) vision_component = Vision( inputs=[image_topic], outputs=[detections_topic], model_client=model_client config=config, )