Semantic camera¶
A smart camera allowing to retrieve objects in its field of view
This sensor emulates a high level abstract camera that outputs the
name and 6D pose of visible objects (i.e. objects in the field of
view of the camera). It also outputs the type of the object if the Type
property is set (my_object.properties(Type="Bottle")
for
instance).
General usage¶
You need to tag the objects you want your camera to track by either
adding a boolean property Object
to your object:
my_object.properties(Object=True)
, or by setting a type and
using this type as the value of the tag
property of the camera:
object_to_track = PassiveObject(...)
object_to_track.properties(Type="Bottle")
...
semcam = SemanticCamera()
semcam.properties(tag="Bottle")
...
See the Examples section below for a complete working example.
If the Label
property is defined, it is used as exported
name. Otherwise, the Blender object name is used.
By default, the pose of the objects is provided in the world frame.
When setting the relative
property to True
(semcam.properties(relative=True)
), the pose is computed in the
camera frame instead.
Details of implementation¶
A test is made to identify which of these objects are inside of
the view frustum of the camera. Finally, a single visibility test is
performed by casting a ray from the center of the camera to the
center of the object. If anything other than the test object is
found first by the ray, the object is considered to be occluded by
something else, even if it is only the center that is being blocked.
This occulsion check can be deactivated (for slightly improved
performances) by setting the sensor property noocclusion
to True
.
See also Generic Camera for generic informations about MORSE cameras.
. note:
As any other MORSE camera, the semantic camera *only* works if the
rendering mode is set to `GLSL` (default). In particular, it does
not work in `fastmode` (ie, wireframe mode).
Configuration parameters for Semantic camera¶
You can set these properties in your scripts with <component>.properties(<property1>=..., <property2>=...)
.
cam_width
(default:256
)- (no documentation available yet)
cam_height
(default:256
)- (no documentation available yet)
cam_focal
(default:25.0
)- (no documentation available yet)
cam_fov
(default:None
)- (no documentation available yet)
cam_near
(default:0.1
)- (no documentation available yet)
cam_far
(default:100.0
)- (no documentation available yet)
Vertical_Flip
(default:True
)- (no documentation available yet)
retrieve_depth
(default:False
)- (no documentation available yet)
retrieve_zbuffer
(default:False
)- (no documentation available yet)
relative
(bool, default:False
)- Return object position relatively to the sensor frame.
noocclusion
(bool, default:False
)- Do not check for objects possibly hiding each others (faster but less realistic behaviour)
tag
(string, default:"Object"
)- The type of detected objects. This type is looked for as a game property of scene objects or as their ‘Type’ property. You must then add fix this property to the objects you want to be detected by the semantic camera.
Data fields¶
This sensor exports these datafields at each simulation step:
timestamp
(float, initial value:0.0
)- number of seconds in simulated time
visible_objects
(list<objects>, initial value:[]
)- A list containing the different objects visible by the camera. Each object is represented by a dictionary composed of:
- name (String): the name of the object
- type (String): the type of the object
- position (vec3<float>): the position of the object, in meter, in the blender frame
- orientation (quaternion): the orientation of the object, in the blender frame
Interface support:
ros
as std_msgs/String (morse.middleware.ros.semantic_camera.SemanticCameraPublisher
) or as std_msgs/String (morse.middleware.ros.semantic_camera.SemanticCameraPublisherLisp
)socket
as straight JSON serialization (morse.middleware.socket_datastream.SocketPublisher
)yarp
as YarpPublisher (morse.middleware.yarp_datastream.YarpPublisher
)pocolibs
as VimanObjectPublicArray (morse.middleware.pocolibs.sensors.viman.VimanPoster
)
Services for Semantic camera¶
get_configurations()
(blocking)Returns the configurations of a component (parsed from the properties).
Return value
a dictionary of the current component’s configurations
get_local_data()
(blocking)Returns the current data stored in the sensor.
Return value
a dictionary of the current sensor’s data
get_properties()
(blocking)Returns the properties of a component.
Return value
a dictionary of the current component’s properties
set_property(prop_name, prop_val)
(blocking)Modify one property on a component
Parameters
prop_name
: the name of the property to modify (as shown the documentation)prop_val
: the new value of the property. Note that there is no checking about the type of the value so be careful
Return value
nothing
Examples¶
The following examples show how to use this component in a Builder script:
# add a 'passive' object visible to the semantic cameras
table = PassiveObject('props/objects','SmallTable')
table.translate(x=3.5, y=-3, z=0)
table.rotate(z=0.2)
# by setting the 'Object' property to true, this object becomes
# visible to the semantic cameras present in the simulation.
# Note that you can set this property on any object (other robots, humans,...).
table.properties(Type = "table", Label = "MY_FAVORITE_TABLE")
# then, create a robot
robot = Morsy()
# creates a new instance of the sensor, that tracks all tables.
# If you do not specify a particular 'tag', the camera tracks by default
# all object with the properties 'type="Object"' or 'Object=True'.
semcam = SemanticCamera()
semcam.properties(tag = "table")
# place the camera at the correct location
semcam.translate(<x>, <y>, <z>)
semcam.rotate(<rx>, <ry>, <rz>)
robot.append(semcam)
# define one or several communication interface, like 'socket'
semcam.add_interface(<interface>)
env = Environment('empty')
Other sources of examples¶
(This page has been auto-generated from MORSE module morse.sensors.semantic_camera.)