text: #!/usr/bin/env python
  
  # Copyright (c) 2015, Carnegie Mellon University
  # All rights reserved.
  # Authors: Jennifer King <jeking@cs.cmu.edu>
  #
  # Redistribution and use in source and binary forms, with or without
  # modification, are permitted provided that the following conditions are met:
  #
  # - Redistributions of source code must retain the above copyright notice, this
  #   list of conditions and the following disclaimer.
  # - Redistributions in binary form must reproduce the above copyright notice,
  #   this list of conditions and the following disclaimer in the documentation
  #   and/or other materials provided with the distribution.
  # - Neither the name of Carnegie Mellon University nor the names of its
  #   contributors may be used to endorse or promote products derived from this
  #   software without specific prior written permission.
  #
  # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
  # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
  # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
  # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
  # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
  # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
  # SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
  # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
  # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
  # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
  # POSSIBILITY OF SUCH DAMAGE.
  
  import logging
  from base import PerceptionModule, PerceptionMethod
  
  logger = logging.getLogger(__name__)
  logger.setLevel(logging.INFO)
  
  class ApriltagsModule(PerceptionModule):
      
      def __init__(self, marker_topic, marker_data_path, kinbody_path,
                   detection_frame, destination_frame,reference_link,):
          """
          This initializes an April Tags detector.
          
          @param marker_topic The ROS topic to read markers from. Typically the output topic for April Tags
          @param marker_data_path The json file where the association between tag and object is stored
          @param kinbody_path The path to the folder where kinbodies are stored
          @param detection_frame The TF frame of the camera
          @param destination_frame The desired world TF frame
          """
  
          super(ApriltagsModule, self).__init__()
          
          self.marker_topic = marker_topic
          self.marker_data_path = marker_data_path
          self.kinbody_path = kinbody_path
          self.detection_frame = detection_frame
          self.destination_frame = destination_frame
          self.reference_link = reference_link
          
          
      def __str__(self):
          return self.__class__.__name__
      
  
      def _DetectObjects(self, env, marker_topic=None, marker_data_path=None, 
                         kinbody_path=None, detection_frame=None, 
                         destination_frame=None, reference_link=None,**kw_args):
          """
          Use the apriltags service to detect objects and add them to the
          environment. Params are as in __init__.
  
          @param env: The current OpenRAVE environment
          @param marker_topic The ROS topic to read markers from. Typically the output topic for April Tags
          @param marker_data_path The json file where the association between tag and object is stored
          @param kinbody_path The path to the folder where kinbodies are stored
          @param detection_frame The TF frame of the camera
          @param destination_frame The desired world TF frame
  
          @return The list of kinbodies associated with the detected apriltags
          """
          try:
              # Allow caller to override any of the initial parameters
              # loaded into the module
              if marker_topic is None:
                  marker_topic = self.marker_topic
              
              if marker_data_path is None:
                  marker_data_path = self.marker_data_path
  
              if kinbody_path is None:
                  kinbody_path = self.kinbody_path
  
              if detection_frame is None:
                  detection_frame = self.detection_frame
  
              if destination_frame is None:
                  destination_frame = self.destination_frame
  
              if reference_link is None:
                  reference_link = self.reference_link
  
              # TODO: Creating detector is not instant...might want
              #  to just do this once in the constructor
              import kinbody_detector.kinbody_detector as kd
              detector = kd.KinBodyDetector(env,
                                            marker_data_path,
                                            kinbody_path,
                                            marker_topic,
                                            detection_frame,
                                            destination_frame,
                                            reference_link)
  
              logger.warn('Waiting to detect objects...')
              return detector.Update(**kw_args)
          except Exception, e:
              logger.error('Detecton failed update: %s' % str(e))
              raise
  
      @PerceptionMethod
      def DetectObjects(self, robot, **kw_args):
          """
          Overriden method for detection_frame
          """
  
          added_kinbodies, updated_kinbodies = self._DetectObjects(robot.GetEnv(), **kw_args)
          return added_kinbodies + updated_kinbodies
                                            
      @PerceptionMethod
      def DetectObject(self, robot, object_name, **kw_args):
          """
          Detects a single named object.
          """
          added_bodies, updated_bodies = self._DetectObjects(robot.GetEnv(), **kw_args)
  
          return_obj = None
          for obj in added_bodies:
              if obj.GetName() != object_name:
                  env = robot.GetEnv()
                  env.Remove(obj)
              else:
                  return_obj = obj
          for obj in updated_bodies:
              if obj.GetName() == object_name:
                  return_obj = obj
              # TODO: Otherwise we need to put it back
  
          if return_obj is not None:
              return return_obj
  
          from prpy.perception.base import PerceptionException
          raise PerceptionException('Failed to detect object %s', object_name)
  