Object Detection#
About#
This feature lets you generate object detection using existing cameras in Colosseum, similar to detection DNN.
Using the API you can control which object to detect by name and radius from camera.
One can control these settings for each camera, image type and vehicle combination separately.
API#
-
Set mesh name to detect in wildcard format
simAddDetectionFilterMeshName(camera_name, image_type, mesh_name, vehicle_name = '')
-
Clear all mesh names previously added
simClearDetectionMeshNames(camera_name, image_type, vehicle_name = '')
-
Set detection radius in cm
simSetDetectionFilterRadius(camera_name, image_type, radius_cm, vehicle_name = '')
-
Get detections
simGetDetections(camera_name, image_type, vehicle_name = '')
The return value of simGetDetections
is a DetectionInfo
array:
DetectionInfo
name = ''
geo_point = GeoPoint()
box2D = Box2D()
box3D = Box3D()
relative_pose = Pose()
Usage example#
Python script detection.py shows how to set detection parameters and shows the result in OpenCV capture.
A minimal example using API with Blocks environment to detect Cylinder objects:
camera_name = "0"
image_type = airsim.ImageType.Scene
client = airsim.MultirotorClient()
client.confirmConnection()
client.simSetDetectionFilterRadius(camera_name, image_type, 80 * 100) # in [cm]
client.simAddDetectionFilterMeshName(camera_name, image_type, "Cylinder_*")
client.simGetDetections(camera_name, image_type)
detections = client.simClearDetectionMeshNames(camera_name, image_type)
Output result:
Cylinder: <DetectionInfo> { 'box2D': <Box2D> { 'max': <Vector2r> { 'x_val': 617.025634765625,
'y_val': 583.5487060546875},
'min': <Vector2r> { 'x_val': 485.74359130859375,
'y_val': 438.33465576171875}},
'box3D': <Box3D> { 'max': <Vector3r> { 'x_val': 4.900000095367432,
'y_val': 0.7999999523162842,
'z_val': 0.5199999809265137},
'min': <Vector3r> { 'x_val': 3.8999998569488525,
'y_val': -0.19999998807907104,
'z_val': 1.5199999809265137}},
'geo_point': <GeoPoint> { 'altitude': 16.979999542236328,
'latitude': 32.28772183970703,
'longitude': 34.864785008379876},
'name': 'Cylinder9_2',
'relative_pose': <Pose> { 'orientation': <Quaternionr> { 'w_val': 0.9929741621017456,
'x_val': 0.0038591264747083187,
'y_val': -0.11333247274160385,
'z_val': 0.03381215035915375},
'position': <Vector3r> { 'x_val': 4.400000095367432,
'y_val': 0.29999998211860657,
'z_val': 1.0199999809265137}}}