def declare_cells(_p):
cells = {}
cells['convert2msg'] = CellInfo(ecto_rbo_pcl.PointCloud2Message, name='Converter')
cells['publisher'] = CellInfo(ecto_ros.ecto_sensor_msgs.Publisher_PointCloud2, name='Publisher')
return cells
def declare_cells(_p):
res = {
'camera_info_image': CellInfo(ecto_ros.CameraInfo2Cv),
'camera_info_depth': CellInfo(ecto_ros.CameraInfo2Cv),
'crop_box': CellInfo(CropBox)
}
if HAS_PCL:
res['cloud'] = CellInfo(MatToPointCloudXYZOrganized)
return res
def declare_cells(cls, p):
return {
'cluster_converter':
CellInfo(ClusterConverter),
'pc_publisher':
CellInfo(PointCloudPub, params={'latched': p.latched}),
'passthrough':
ecto.PassthroughN(
items=dict(image_message='The original imagemessage',
pose_results='The final results'))
}
def declare_cells(cls, _p):
# passthrough cells
cells = {'json_db': CellInfo(ecto.Constant),
'object_id': CellInfo(ecto.Constant)
}
# 'real cells'
cells.update({'model_filler': CellInfo(ecto_linemod.ModelFiller),
'model_writer': CellInfo(ModelWriter, params={'method':'LINEMOD'}),
'trainer': CellInfo(ecto_linemod.Trainer)})
return cells
def declare_cells(p):
cell_types = FeatureDescriptor._figure_out_cell_types(p)
cells = {}
if cell_types['feature_descriptor_cell'] is not None:
cells['feature_descriptor_cell'] = CellInfo(
cell_types['feature_descriptor_cell'])
else:
cells['image_passthrough'] = CellInfo(ecto.Passthrough)
cells['mask_passthrough'] = CellInfo(ecto.Passthrough)
cells['feature_cell'] = CellInfo(cell_types['feature_cell'])
cells['descriptor_cell'] = CellInfo(cell_types['descriptor_cell'])
return cells
def declare_cells(cls, p):
return {
'table_msg_assembler':
CellInfo(TableMsgAssembler),
'table_visualization_msg_assembler':
CellInfo(TableVisualizationMsgAssembler),
'marker_array_clusters':
CellInfo(MarkerArrayPub),
'table_array':
CellInfo(Publisher_TableArray),
'passthrough':
ecto.PassthroughN(
items=dict(image_message='The original imagemessage',
pose_results='The final results'))
}
def declare_cells(_p):
"""
Implement the virtual function from the base class
Only cells from which something is forwarded have to be declared
"""
cells = {}
# 'i2' has its start value exposed to the user so only a type is given
cells['i2'] = CellInfo(Increment, name='Inc 2')
# 'add' is always the same so we could define with a CellInfo(Add, name='Add') or
# just with an instance
cells['add'] = Add('Add')
return cells
def declare_cells(cls, _p):
return {
'passthrough':
ecto.PassthroughN(
items={
'K_image': 'The original calibration matrix',
'points3d': 'The 3d points as cv::Mat_<cv::Vec3f>.'
}),
'table_detector':
TableDetector(),
'table_pose':
CellInfo(TablePose),
'clusterer':
OnPlaneClusterer()
}
def declare_cells(_p):
res = {
'camera_info_image': CellInfo(ecto_ros.CameraInfo2Cv),
'camera_info_depth': CellInfo(ecto_ros.CameraInfo2Cv),
'crop_box': CellInfo(CropBox),
'depth_map': CellInfo(RescaledRegisteredDepth)
}
if HAS_PCL:
res['cloud'] = CellInfo(MatToPointCloudXYZOrganized)
if 'camera' in p['outputs_list']:
res['converter'] = CellInfo(CameraFromOpenNI)
return res
def declare_cells(_p):
from object_recognition_tabletop.ecto_cells import tabletop_object
return {'main': CellInfo(tabletop_object.ObjectRecognizer)}
def declare_cells(self, _p):
return {
'detector': CellInfo(Detector),
'mat_to_cloud': MatToPointCloudXYZOrganized()
}
def declare_cells(cls, p):
return {'msg_assembler': CellInfo(PointCloudMsgAssembler),
'passthrough': ecto.PassthroughN(items=dict(pose_results='The final results'))
}
def declare_cells(_p):
return {'trainer': CellInfo(transparent_objects_cells.Trainer)}
def declare_cells(cls, p):
return {
'gen': CellInfo(python_class=ecto_test.Generate),
'inc': CellInfo(python_class=ecto_test.Increment)
}
def declare_cells(cls, p):
return {
'gen': CellInfo(python_class=MyBlackBox, params={'start': 20}),
'inc': CellInfo(python_class=ecto_test.Increment)
}
def declare_cells(p):
return {
'cluster_drawer': CellInfo(ClusterDrawer),
'plane_drawer': CellInfo(PlaneDrawer)
}
