def generate_pointclouds_in_object_space(dbs, session, args):
object_name = dbs[session.object_id]['object_name']
if not os.path.exists(object_name):
os.mkdir(object_name)
obs_ids = models.find_all_observations_for_session(dbs, session.id)
if len(obs_ids) == 0:
raise RuntimeError("There are no observations available.")
db_reader = capture.ObservationReader(
'Database Source', db_params=dbtools.args_to_db_params(args))
#observation dealer will deal out each observation id.
observation_dealer = ecto.Dealer(
tendril=db_reader.inputs.at('observation'), iterable=obs_ids)
depthTo3d = calib.DepthTo3d('Depth ~> 3D')
rescale_depth = capture.RescaledRegisteredDepth(
'Depth scaling') #this is for SXGA mode scale handling.
point_cloud_transform = reconstruction.PointCloudTransform(
'Object Space Transform', do_transform=False
) #keeps the points in camera coordinates, but populates the global sensor position and orientatino.
point_cloud_converter = conversion.MatToPointCloudXYZRGB('To Point Cloud')
to_ecto_pcl = ecto_pcl.PointCloudT2PointCloud('converter',
format=ecto_pcl.XYZRGB)
plasm = ecto.Plasm()
plasm.connect(observation_dealer[:] >> db_reader['observation'],
db_reader['K'] >> depthTo3d['K'],
db_reader['image'] >> rescale_depth['image'],
db_reader['depth'] >> rescale_depth['depth'],
rescale_depth[:] >> depthTo3d['depth'],
depthTo3d['points3d'] >> point_cloud_converter['points'],
db_reader['image'] >> point_cloud_converter['image'],
db_reader['mask'] >> point_cloud_converter['mask'],
db_reader['R', 'T'] >> point_cloud_transform['R', 'T'],
point_cloud_converter['point_cloud'] >> to_ecto_pcl[:],
to_ecto_pcl[:] >> point_cloud_transform['cloud'])
ply_writer = ecto_pcl.PLYWriter('PLY Saver',
filename_format='%s/cloud_%%05d.ply' %
(object_name))
pcd_writer = ecto_pcl.PCDWriter('PCD Saver',
filename_format='%s/cloud_%%05d.pcd' %
(object_name))
plasm.connect(point_cloud_transform['view'] >> (ply_writer['input'],
pcd_writer['input']))
if args.visualize:
global cloud_view
plasm.connect(
point_cloud_transform['view'] >> cloud_view,
db_reader['image'] >> imshows['image'],
db_reader['depth'] >> imshows['depth'],
db_reader['mask'] >> imshows['mask'],
)
from ecto.opts import run_plasm
run_plasm(args, plasm, locals=vars())
def generate_pointclouds_in_object_space(dbs, session, args):
object_name = dbs[session.object_id]['object_name']
if not os.path.exists(object_name):
os.mkdir(object_name)
obs_ids = models.find_all_observations_for_session(dbs, session.id)
if len(obs_ids) == 0:
raise RuntimeError("There are no observations available.")
db_reader = capture.ObservationReader('Database Source', db_params=dbtools.args_to_db_params(args))
#observation dealer will deal out each observation id.
observation_dealer = ecto.Dealer(tendril=db_reader.inputs.at('observation'), iterable=obs_ids)
depthTo3d = calib.DepthTo3d('Depth ~> 3D')
rescale_depth = capture.RescaledRegisteredDepth('Depth scaling') #this is for SXGA mode scale handling.
point_cloud_transform = reconstruction.PointCloudTransform('Object Space Transform',do_transform=False)#keeps the points in camera coordinates, but populates the global sensor position and orientatino.
point_cloud_converter = conversion.MatToPointCloudXYZRGB('To Point Cloud')
to_ecto_pcl = ecto_pcl.PointCloudT2PointCloud('converter', format=ecto_pcl.XYZRGB)
plasm = ecto.Plasm()
plasm.connect(
observation_dealer[:] >> db_reader['observation'],
db_reader['K'] >> depthTo3d['K'],
db_reader['image'] >> rescale_depth['image'],
db_reader['depth'] >> rescale_depth['depth'],
rescale_depth[:] >> depthTo3d['depth'],
depthTo3d['points3d'] >> point_cloud_converter['points'],
db_reader['image'] >> point_cloud_converter['image'],
db_reader['mask'] >> point_cloud_converter['mask'],
db_reader['R', 'T'] >> point_cloud_transform['R', 'T'],
point_cloud_converter['point_cloud'] >> to_ecto_pcl[:],
to_ecto_pcl[:] >> point_cloud_transform['cloud']
)
ply_writer = ecto_pcl.PLYWriter('PLY Saver',
filename_format='%s/cloud_%%05d.ply' % (object_name))
pcd_writer = ecto_pcl.PCDWriter('PCD Saver',
filename_format='%s/cloud_%%05d.pcd' % (object_name))
plasm.connect(point_cloud_transform['view'] >> (ply_writer['input'], pcd_writer['input'])
)
if args.visualize:
global cloud_view
plasm.connect(
point_cloud_transform['view'] >> cloud_view,
db_reader['image'] >> imshows['image'],
db_reader['depth'] >> imshows['depth'],
db_reader['mask'] >> imshows['mask'],
)
from ecto.opts import run_plasm
run_plasm(args, plasm, locals=vars())
from ecto_opencv import highgui
import object_recognition
from object_recognition import dbtools, models, capture
db_url = dbtools.DEFAULT_SERVER_URL
#database ritual
couch = couchdb.Server(db_url)
dbs = dbtools.init_object_databases(couch)
sessions = dbs['sessions']
observations = dbs['observations']
results = models.Session.all(sessions)
obs_ids = []
for session in results:
obs_ids += models.find_all_observations_for_session(observations, session.id)
if len(obs_ids) == 0:
raise RuntimeError("There are no observations available.")
db_reader = capture.ObservationReader('db_reader', db_params=ObjectDbParameters({'type':'CouchDB', 'root':db_url,
'collection':'observations'}))
#observation dealer will deal out each observation id.
observation_dealer = ecto.Dealer(tendril=db_reader.inputs.at('observation'), iterable=obs_ids)
fps = highgui.FPSDrawer('FPS drawer')
plasm = ecto.Plasm()
#View all of the observations.
plasm.connect(
observation_dealer[:] >> db_reader['observation'],
db_reader['image'] >> fps[:],
fps[:] >> highgui.imshow('image display', name='image')[:],
from ecto_opencv import highgui
import object_recognition
from object_recognition import dbtools, models, capture
db_url = dbtools.DEFAULT_SERVER_URL
#database ritual
couch = couchdb.Server(db_url)
dbs = dbtools.init_object_databases(couch)
sessions = dbs['sessions']
observations = dbs['observations']
results = models.Session.all(sessions)
obs_ids = []
for session in results:
obs_ids += models.find_all_observations_for_session(
observations, session.id)
if len(obs_ids) == 0:
raise RuntimeError("There are no observations available.")
db_reader = capture.ObservationReader('db_reader',
db_params=ObjectDbParameters({
'type':
'CouchDB',
'root':
db_url,
'collection':
'observations'
}))
#observation dealer will deal out each observation id.
observation_dealer = ecto.Dealer(tendril=db_reader.inputs.at('observation'),
