detection.tabletop_fetch.ros.ork

source1:
  type: RosKinect
  module: 'object_recognition_ros.io'
  parameters:
    rgb_frame_id: '/head_camera_rgb_optical_frame'
    rgb_image_topic: '/head_camera/rgb/image_raw'
    rgb_camera_info: '/head_camera/rgb/camera_info'
    depth_image_topic: '/head_camera/depth_registered/image_raw'
    depth_camera_info: '/head_camera/depth_registered/camera_info'
    #
    #crop_enabled: True
    #x_min: -0.4
    #x_max: 0.4
    #y_min: -1.0
    #y_max: 0.2
    #z_min: 0.3
    #z_max: 1.5

sink1:
  type: TablePublisher
  module: 'object_recognition_tabletop'
  inputs: [source1]

pipeline1:
  type: TabletopTableDetector
  module: 'object_recognition_tabletop'
  inputs: [source1]
  outputs: [sink1]
  parameters:
    table_detector:
      min_table_size: 4000
      plane_threshold: 0.01
    #zclusterer:
    #  table_z_filter_max: 0.35
    #  table_z_filter_min: 0.025

init_table_top.launch

<launch>
    
    <arg name="tabletop_ork_file" value="$(find my_object_recognition_pkg)/conf/detection.tabletop_fetch.ros.ork"/>
    
    <node pkg="object_recognition_core"
    type="detection"
    name="tabletop_server_node"
    args="-c $(arg tabletop_ork_file)"
    output="screen">
    </node>

</launch>