def main_display_cloud():
global received_ros_cloud
# Set viewer
open3d_cloud = open3d.PointCloud()
vis = open3d.Visualizer()
vis.create_window()
vis.add_geometry(open3d_cloud)
# Loop
rate = rospy.Rate(100)
cnt = 0
while not rospy.is_shutdown():
if received_ros_cloud is not None:
cnt += 1
idx_method = 1
if idx_method == 1:
tmp = convertCloudFromRosToOpen3d(received_ros_cloud)
copyOpen3dCloud(tmp, open3d_cloud)
vis.add_geometry(open3d_cloud)
if idx_method == 2: # this is not working!!!
open3d_cloud = convertCloudFromRosToOpen3d(received_ros_cloud)
if idx_method == 3: # this is keep adding clouds to viewer
open3d_cloud = convertCloudFromRosToOpen3d(received_ros_cloud)
vis.add_geometry(open3d_cloud)
vis.update_geometry()
print("Updating geometry for the {}th time".format(cnt))
received_ros_cloud = None # clear
vis.poll_events()
vis.update_renderer()
rate.sleep()
# print("Updating viewer")
# Return
vis.destroy_window()
def get_cloud(self):
''' Get the next cloud subscribed from ROS topic.
Convert it to open3d format and then return. '''
if not self.has_cloud():
return None
ros_cloud = self._clouds_queue.get(timeout=0.05)
open3d_cloud = convertCloudFromRosToOpen3d(ros_cloud)
return open3d_cloud
def sub_callback(self, ros_cloud):
if 1:
rospy.sleep(2.0)
filename = file_folder + file_name_cloud_segmented + "{:02d}".format(
cnt + 1) + ".pcd"
open3d_cloud = open3d.read_point_cloud(filename)
else: # Here has a bug. The received cloud is very sparse when running the ROS server on Baxter.
# The bug disapears when running the ROS server on my laptop (by using my fake node1 to debug).
# So the conclusion is that I still don't know what the bug is.
open3d_cloud = convertCloudFromRosToOpen3d(ros_cloud)
# open3d.write_point_cloud(file_folder+"n3_subed_cloud_"+str(cnt)+".pcd", open3d_cloud)
# self.rotateCloudForBetterViewing(open3d_cloud)
self.cloud_buff.append(open3d_cloud)
def get_objects_clouds_from_RGBD(self, color, depth):
obj_clouds = list()
# Generate cloud data from color and depth images
cloud_src = rgbd2cloud(color,
depth,
self.camera_intrinsic,
output_img_format="cv2")
cloud_src = self.filtCloud(cloud_src, self.xmin, self.xmax, self.ymin,
self.ymax, self.zmin, self.zmax,
self.voxel_size)
# Send cloud to .cpp node for detect object
self.sub_objects.reset()
self.pub_cloud.publish(cloud_src, cloud_format="open3d")
while (self.sub_objects.num_objects is None
and (not rospy.is_shutdown())):
# wait until receives the result from .cpp node
rospy.sleep(0.001)
# Receive detection results, which are a list of clouds
cnt_processed = 0
start = time.time()
while (
((not self.sub_objects.flag_receive_all)) and
(not rospy.is_shutdown())): # wait until processed all obj clouds
if len(self.sub_objects.clouds_buff
) > 0: # A new cloud has been received
cnt_processed += 1
cloud_ros_format = self.sub_objects.pop_cloud(
) # pop cloud from buff
obj_clouds.append(
convertCloudFromRosToOpen3d(
(cloud_ros_format))) # save to results
# Deal with error: Set up max waiting time
rospy.sleep(0.001)
if time.time() - start > self.max_wait_time:
break
# Check error
num_unreceived = self.sub_objects.num_objects - cnt_processed
if num_unreceived != 0:
print "my Warning: might miss a number of {:02d} objects".format(
num_unreceived)
# Return
return obj_clouds, cloud_src
def main_save_cloud():
global received_ros_cloud
rate = rospy.Rate(100)
cnt = 0
file_folder = "/home/feiyu/baxterws/src/winter_prj/mask_objects_from_rgbd/data/"
file_name = "pcd_"
while not rospy.is_shutdown():
if received_ros_cloud is not None:
cnt += 1
open3d_cloud = convertCloudFromRosToOpen3d(received_ros_cloud)
filename_to_save = file_folder + file_name + "{:03d}".format(
cnt) + ".pcd"
open3d.write_point_cloud(filename_to_save, open3d_cloud)
print("Saving" + filename_to_save)
received_ros_cloud = None # clear
rate.sleep()
def callback(data):
assert isinstance(data, PointCloud2)
# gen = pc2.read_points(data,field_names=("x","y","z","rgb"),skip_nans=True)
# print gen.Header
# time.sleep(1)
# print msg1.data
# print "3"
rate = rospy.Rate(10.0)
# try:
fname = str(time.time())
# transform1 = tf_buffer.lookup_transform("workspace_link", "camera3_depth_optical_frame", rospy.Time()) #3B
# print transform1
# transform = tf_buffer.lookup_transform("hand_link", "camera3_depth_optical_frame", rospy.Time()) #3B
transform_h3 = tf_buffer.lookup_transform("hand_link",
"camera3_depth_optical_frame",
rospy.Time()) # 3B
transform_wh = tf_buffer.lookup_transform("workspace_link", "hand_link",
rospy.Time()) # 3B
p, q = transform_to_pq(transform_h3)
Th3 = convertRostfTotransform(p, q)
print "trans h 3 call", transform_h3
print "Th3", Th3
pcd_transformed_h3 = do_transform_cloud(
data, transform_h3) #cam3 to hand crop this
temppcd = convertCloudFromRosToOpen3d(pcd_transformed_h3)
# o3d.io.write_point_cloud("rostrans.ply",temppcd)
temppcd = convertCloudFromRosToOpen3d(data)
temppcd.transform(Th3)
# o3d.io.write_point_cloud("o3dtrans.ply",temppcd)
p, q = transform_to_pq(transform_h3)
T = convertRostfTotransform(p, q)
print T
data_o3d = convertCloudFromRosToOpen3d(data)
# o3d.io.write_point_cloud("cam3raw.ply",data_o3d) # can delete
pcd_o3d_3h = convertCloudFromRosToOpen3d(pcd_transformed_h3)
# o3d.io.write_point_cloud("3h_test.ply",pcd_o3d_3h) #delete
cropped = vol.crop_point_cloud(pcd_o3d_3h)
T3h = np.linalg.inv(Th3)
cropped_h3 = copy.deepcopy(cropped).transform(T3h)
# o3d.io.write_point_cloud("crop_back.ply",cropped_h3)
# o3d.draw_geometries([cropped_h3])
pwh, qwh = transform_to_pq(transform_wh)
Twh = convertRostfTotransform(pwh, qwh)
threshold = 0.02
trans_init = T3h
source = pcd_stl
target = cropped_h3
# estimate_normals(cloud=source,search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))
# estimate_normals(cloud=target,search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))
draw_registration_result(source, target, trans_init)
print("Initial alignment")
print trans_init
evaluation = o3d.registration.evaluate_registration(
source, target, threshold, trans_init)
print("Init evaluation :", evaluation)
print("Apply point-to-point ICP")
reg_p2p = o3d.registration.registration_icp(
source, target, threshold, trans_init,
o3d.registration.TransformationEstimationPointToPoint())
print(reg_p2p)
print("Transformation is:")
print(reg_p2p.transformation)
T3ph = reg_p2p.transformation
Tw3p = np.dot(Twh, np.linalg.inv(T3ph))
transform = tf_buffer.lookup_transform("camera3_depth_optical_frame",
"camera3_link", rospy.Time()) # 3B
p, q = transform_to_pq(transform)
To3l = convertRostfTotransform(p, q)
Tw3l = np.dot(Tw3p, To3l)
print("")
draw_registration_result(source, target, reg_p2p.transformation)
resT = Tw3l
camera = "camera3"
Q = Quaternion(matrix=resT)
print dir
with open(dir + "/{}_transform.yaml".format(camera), 'w') as f:
f.write("eye_on_hand: false\n")
f.write("robot_base_frame: workspace_link\n")
f.write("tracking_base_frame: {}_link\n".format(camera))
f.write("transformation: {")
f.write("x: {}, ".format(resT[0, 3]))
f.write("y: {}, ".format(resT[1, 3]))
f.write("z: {}, ".format(resT[2, 3]))
f.write("qx: {}, ".format(Q[1]))
f.write("qy: {}, ".format(Q[2]))
f.write("qz: {}, ".format(Q[3]))
f.write("qw: {} }}\n".format(Q[0]))
print "------------written in yaml------------"
# print Tw3
print Tw3l
#
# print("Apply point-to-plane ICP")
# reg_p2l = o3d.registration.registration_icp(
# source, target, threshold, trans_init,
# o3d.registration.TransformationEstimationPointToPlane())
# print(reg_p2l)
# print("Transformation is:")
# print(reg_p2l.transformation)
# dict=t2q(reg_p2l.transformation)
print("")
# draw_registration_result(source, target, reg_p2l.transformation)
# o3d.write_point_cloud("cam3_raw.ply",pcd_o3d_cam3)
# o3d.write_point_cloud("cam3_3h_raw.ply",pcd_o3d_cam3_3h)
print "written"
def callback(msg1, msg2):
# print msg1.data
try:
fname = str(time.time())
print "a"
transform_w3 = tf_buffer.lookup_transform(
"workspace_link", "camera3_depth_optical_frame", rospy.Time()) #3B
transform_w4 = tf_buffer.lookup_transform(
"workspace_link", "camera4_depth_optical_frame", rospy.Time()) #4B
transform_43 = tf_buffer.lookup_transform(
"camera4_depth_optical_frame", "camera3_depth_optical_frame",
rospy.Time()) # 4B
transform_o4 = tf_buffer.lookup_transform(
"camera4_depth_optical_frame", "camera4_link", rospy.Time()) # 4B
transform_wo4 = tf_buffer.lookup_transform("workspace_link",
"camera4_link",
rospy.Time()) #4B
print "trans_wo4", transform_wo4
p, q = transform_to_pq(transform_wo4)
Two4 = convertRostfTotransform(p, q)
print "init two4", Two4
# trans=tf_buffer.lookup_transform("hand_link","base_link",rospy.Time())
#
# print trans
pcd1_transformed = do_transform_cloud(msg1, transform_w3)
# temp=convertCloudFromRosToOpen3d(msg1)
q1, p1 = transform_to_pq(transform_w3)
Tw3 = convertRostfTotransform(q1, p1)
# temp2=copy.deepcopy(temp).transform(Tw3)
# o3d.io.write_point_cloud("cam3Tw3.ply",temp2)
# o3d.io.write_point_cloud("cam3raw.ply",temp)
# temp=convertCloudFromRosToOpen3d(pcd1_transformed)
# o3d.io.write_point_cloud("cam3trans1.ply",temp)
#convert pcd from camera 3,4 to work_link
pcd2_transformed = do_transform_cloud(msg2, transform_w4)
pcd1_o3d = convertCloudFromRosToOpen3d(
pcd1_transformed
) #conver pcd from Pointcloud2 to open3d Pointcloud
pcd2_o3d = convertCloudFromRosToOpen3d(pcd2_transformed)
center1 = vol.crop_point_cloud(pcd1_o3d) #crop
center2 = vol.crop_point_cloud(pcd2_o3d)
# #--------------------
#
trans_init = np.asarray([
[1, 0.0, -0.0, 0.], # 変換無し
[-0.0, 1, -0.0, 0.0],
[0.0, 0.0, 1.0, 0],
[0.0, 0.0, 0.0, 1.0]
])
"center 1 2 単位I"
# draw_registration_result(center1, center2, trans_init)
#
# #--------------------
p1, q1 = transform_to_pq(
transform_w3
) #use homogeneous Matrix to conver back to camera coordination
# print("trans2",p1,q1)
Tw3 = convertRostfTotransform(p1, q1) # T3B
T3w = np.linalg.inv(Tw3)
p2, q2 = transform_to_pq(transform_w4) # T4b
Tw4 = convertRostfTotransform(p2, q2)
T4w = np.linalg.inv(Tw4)
p12, q12 = transform_to_pq(transform_43) # T4b
T43 = convertRostfTotransform(p12, q12)
source = center1.transform(
T3w
) # cam3 #convert pcd back to camera frame
target = center2.transform(T4w) # cam4
o3d.io.write_point_cloud("source.ply", source)
o3d.io.write_point_cloud("target.ply", target)
# #--------------------
#
# trans_init = np.asarray([[1, 0.0, -0.0, 0.], # 変換無し
# [-0.0, 1, -0.0, 0.0],
# [0.0, 0.0, 1.0, 0],
# [0.0, 0.0, 0.0, 1.0]])
#
#
# #--------------------
trans_init = T43 #init Matrix
evaluation = o3d.registration.evaluate_registration(
source,
target, #init result
threshold,
trans_init)
"back to 3,4, with initT=T43 should match"
draw_registration_result(source, target, trans_init)
# print("Trans 34",transform_43.transform)
# print("tf T43")
# print("T3b inv Tw3")
# print(Tw3)
print("Tf published T43")
print(T43)
print("Init evaluation :", evaluation)
print("Init workspace_link to camera4_depth_optical_frame is :")
# print("tf tb4")
# print("init calc tb4")
# print(np.dot(Tw3,T43))
# print("init tf Tb4")
print(T4w)
print("Apply point-to-point ICP")
reg_p2p = o3d.registration.registration_icp( #P2P ICP result
source, target, threshold, trans_init,
o3d.registration.TransformationEstimationPointToPoint())
print("ICP T43")
print(reg_p2p)
print("point-to-point ICP Transformation is:")
print(reg_p2p.transformation)
resultTw4 = np.dot(Tw3,
np.linalg.inv(np.array(reg_p2p.transformation)))
print("result Tw4", resultTw4)
p, q = transform_to_pq(transform_o4)
To4 = convertRostfTotransform(p, q)
print "To4", To4
resultTwo4 = np.dot(resultTw4, To4)
print "result Two4", resultTwo4
print(resultTwo4)
"ICP caulced should match"
draw_registration_result(source, target, reg_p2p.transformation)
#-----------------------------------
# try:
# (trans1, rot1) = tf_listener.lookupTransform('camera3_link', 'workspace_link', rospy.Time(0))
# except (tf.LookupException, tf.ConnectivityException, tf.ExtrapolationException):
# print("err")
#
#
# pcd1_base = convertCloudFromOpen3dToRos(center1, frame_id="workspace_link")
# pcd2_base = convertCloudFromOpen3dToRos(center2, frame_id="workspace_link")
#
# transform1_ = tf_buffer.lookup_transform("camera3_depth_optical_frame","workspace_link", rospy.Time())
# transform2_ = tf_buffer.lookup_transform("camera4_depth_optical_frame","workspace_link", rospy.Time())
#
# pcd1_returned = do_transform_cloud(pcd1_base, transform1_)
# pcd2_returned = do_transform_cloud(pcd2_base, transform2_)
#
# pcd1_returned_o3d=convertCloudFromRosToOpen3d(pcd1_returned)
# pcd2_returned_o3d=convertCloudFromRosToOpen3d(pcd2_returned)
#
# o3d.io.write_point_cloud("/home/finibo/ws1/libs/test/Open3D/examples/TestData/pcd1_returned_ros2o3d.ply", pcd1_returned_o3d)
# o3d.io.write_point_cloud("/home/finibo/ws1/libs/test/Open3D/examples/TestData/pcd2_returned_ros2o3d.ply", pcd2_returned_o3d)
# estimate_normals(cloud=center1, search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))
# estimate_normals(cloud=center2, search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))
#
# print("Apply point-to-plane ICP")
# reg_p2p = o3d.registration.registration_icp(
# pcd1_returned_o3d, pcd2_returned_o3d, threshold, trans_init,
# o3d.registration.TransformationEstimationPointToPoint())
# print(reg_p2p)
# print("Transformation is:")
# print(reg_p2p.transformation)
camera = "camera4"
Q = Quaternion(matrix=resultTwo4)
print directory
print "w"
with open(directory + "/{}_transform.yaml".format(camera), 'w') as f:
f.write("eye_on_hand: false\n")
f.write("robot_base_frame: workspace_link\n")
f.write("tracking_base_frame: {}_link\n".format(camera))
f.write("transformation: {")
f.write("x: {}, ".format(resultTwo4[0, 3]))
f.write("y: {}, ".format(resultTwo4[1, 3]))
f.write("z: {}, ".format(resultTwo4[2, 3]))
f.write("qx: {}, ".format(Q[1]))
f.write("qy: {}, ".format(Q[2]))
f.write("qz: {}, ".format(Q[3]))
f.write("qw: {} }}\n".format(Q[0]))
print "------------written in yaml------------"
except:
pass
def callback(msg1,msg2):
# print msg1.data
try:
fname=str(time.time())
tf_buffer = tf2_ros.Buffer()
tf_listener = tf2_ros.TransformListener(tf_buffer)
transform1 = tf_buffer.lookup_transform("workspace_link", "camera3_depth_optical_frame", rospy.Time()) #3B
transform2 = tf_buffer.lookup_transform("workspace_link", "camera4_depth_optical_frame", rospy.Time()) #4B
transform12 = tf_buffer.lookup_transform("camera4_depth_optical_frame", "camera3_depth_optical_frame", rospy.Time()) # 4B
pcd1_transformed = do_transform_cloud(msg1, transform1) #convert pcd from camera 3,4 to work_link
pcd2_transformed = do_transform_cloud(msg2, transform2)
pcd1_o3d=convertCloudFromRosToOpen3d(pcd1_transformed) #conver pcd from Pointcloud2 to open3d Pointcloud
pcd2_o3d=convertCloudFromRosToOpen3d(pcd2_transformed)
center1 = vol.crop_point_cloud(pcd1_o3d) #crop
center2 = vol.crop_point_cloud(pcd2_o3d)
p1, q1 = transform_to_pq(transform1) #use homogeneous Matrix to conver back to camera coordination
# print("trans2",p1,q1)
T3b=convertRostfTotransform(p1,q1)
print("T3b")# T3B
print(T3b)
Tb3=np.linalg.inv(T3b)
print("inv calc Tb3")
print(Tb3)
transform02 = tf_buffer.lookup_transform( "camera3_depth_optical_frame","workspace_link", rospy.Time()) # 4B
p1, q1 = transform_to_pq(transform02)
Tb30=convertRostfTotransform(p1,q1)
print("tf Tb3")
print(Tb30)
p2, q2 = transform_to_pq(transform2) # T4b
T4b=convertRostfTotransform(p2,q2)
Tb4=np.linalg.inv(T4b)
p12, q12 = transform_to_pq(transform12) # T4b
T34=convertRostfTotransform(p12,q12)
source = center1.transform(Tb3) #convert pcd back to camera frame
target = center2.transform(Tb4)
trans_init=T34 #init Matrix
evaluation = o3d.registration.evaluate_registration(source, target, #init result
threshold, trans_init)
# print("Trans 34",transform12.transform)
print("tf T34")
transform340 = tf_buffer.lookup_transform("camera4_depth_optical_frame", "camera3_depth_optical_frame", rospy.Time()) # 4B
p120, q120 = transform_to_pq(transform340) # T4b
T340=convertRostfTotransform(p120,q120)
print(T340)
print("calc b4")
print(np.dot(Tb3,T34))
print("tf b4")
print(Tb4)
print("T3b inv Tb3")
print(Tb3)
print(T34)
print("Init evaluation :",evaluation)
print("Init workspace_link to camera4_depth_optical_frame is :")
print("tf tb4")
print("init calc tb4")
print(np.dot(Tb3,T34))
print("init tf Tb4")
print(Tb4)
print("Apply point-to-point ICP")
reg_p2p = o3d.registration.registration_icp( #P2P ICP result
source, target, threshold, trans_init,
o3d.registration.TransformationEstimationPointToPoint())
print("ICP T34")
print(reg_p2p)
print("point-to-point ICP Transformation is:")
print(reg_p2p.transformation)
print("result Tb4")
print(np.dot(Tb3,np.array(reg_p2p.transformation)))
#-----------------------------------
# try:
# (trans1, rot1) = tf_listener.lookupTransform('camera3_link', 'workspace_link', rospy.Time(0))
# except (tf.LookupException, tf.ConnectivityException, tf.ExtrapolationException):
# print("err")
#
#
#
# pcd1_base = convertCloudFromOpen3dToRos(center1, frame_id="workspace_link")
# pcd2_base = convertCloudFromOpen3dToRos(center2, frame_id="workspace_link")
#
# transform1_ = tf_buffer.lookup_transform("camera3_depth_optical_frame","workspace_link", rospy.Time())
# transform2_ = tf_buffer.lookup_transform("camera4_depth_optical_frame","workspace_link", rospy.Time())
#
# pcd1_returned = do_transform_cloud(pcd1_base, transform1_)
# pcd2_returned = do_transform_cloud(pcd2_base, transform2_)
#
# pcd1_returned_o3d=convertCloudFromRosToOpen3d(pcd1_returned)
# pcd2_returned_o3d=convertCloudFromRosToOpen3d(pcd2_returned)
#
# o3d.io.write_point_cloud("/home/finibo/ws1/libs/test/Open3D/examples/TestData/pcd1_returned_ros2o3d.ply", pcd1_returned_o3d)
# o3d.io.write_point_cloud("/home/finibo/ws1/libs/test/Open3D/examples/TestData/pcd2_returned_ros2o3d.ply", pcd2_returned_o3d)
# estimate_normals(cloud=center1, search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))
# estimate_normals(cloud=center2, search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))
#
# print("Apply point-to-plane ICP")
# reg_p2p = o3d.registration.registration_icp(
# pcd1_returned_o3d, pcd2_returned_o3d, threshold, trans_init,
# o3d.registration.TransformationEstimationPointToPoint())
# print(reg_p2p)
# print("Transformation is:")
# print(reg_p2p.transformation)
print "------------written in yaml------------"
except :pass
def callback(msg1, msg2):
# print msg1.data
# print "3"
try:
fname = str(time.time())
tf_buffer = tf2_ros.Buffer()
tf_listener = tf2_ros.TransformListener(tf_buffer)
transform1 = tf_buffer.lookup_transform("hand_link",
"camera3_depth_optical_frame",
rospy.Time()) #3B
transform2 = tf_buffer.lookup_transform("workspace_link",
"camera4_depth_optical_frame",
rospy.Time()) #4B
transform12 = tf_buffer.lookup_transform("camera4_depth_optical_frame",
"camera3_depth_optical_frame",
rospy.Time()) # 4B
pcd1_transformed = do_transform_cloud(
msg1, transform1) #convert pcd from camera 3,4 to work_link
pcd2_transformed = do_transform_cloud(msg2, transform2)
pcd1_o3d = convertCloudFromRosToOpen3d(
pcd1_transformed
) #conver pcd from Pointcloud2 to open3d Pointcloud
pcd2_o3d = convertCloudFromRosToOpen3d(pcd2_transformed)
o3d.io.write_point_cloud("cam3_hand_link.ply", pcd1_o3d)
#-----------------------------------
# try:
# (trans1, rot1) = tf_listener.lookupTransform('camera3_link', 'workspace_link', rospy.Time(0))
# except (tf.LookupException, tf.ConnectivityException, tf.ExtrapolationException):
# print("err")
#
#
# pcd1_base = convertCloudFromOpen3dToRos(center1, frame_id="workspace_link")
# pcd2_base = convertCloudFromOpen3dToRos(center2, frame_id="workspace_link")
#
# transform1_ = tf_buffer.lookup_transform("camera3_depth_optical_frame","workspace_link", rospy.Time())
# transform2_ = tf_buffer.lookup_transform("camera4_depth_optical_frame","workspace_link", rospy.Time())
#
# pcd1_returned = do_transform_cloud(pcd1_base, transform1_)
# pcd2_returned = do_transform_cloud(pcd2_base, transform2_)
#
# pcd1_returned_o3d=convertCloudFromRosToOpen3d(pcd1_returned)
# pcd2_returned_o3d=convertCloudFromRosToOpen3d(pcd2_returned)
#
# o3d.io.write_point_cloud("/home/finibo/ws1/libs/test/Open3D/examples/TestData/pcd1_returned_ros2o3d.ply", pcd1_returned_o3d)
# o3d.io.write_point_cloud("/home/finibo/ws1/libs/test/Open3D/examples/TestData/pcd2_returned_ros2o3d.ply", pcd2_returned_o3d)
# estimate_normals(cloud=center1, search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))
# estimate_normals(cloud=center2, search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))
#
# print("Apply point-to-plane ICP")
# reg_p2p = o3d.registration.registration_icp(
# pcd1_returned_o3d, pcd2_returned_o3d, threshold, trans_init,
# o3d.registration.TransformationEstimationPointToPoint())
# print(reg_p2p)
# print("Transformation is:")
# print(reg_p2p.transformation)
except:
pass
# Set viewer
open3d_cloud = open3d.PointCloud()
vis = open3d.Visualizer()
vis.create_window()
vis.add_geometry(open3d_cloud)
# Loop
rate = rospy.Rate(100)
cnt = 0
while not rospy.is_shutdown():
if received_ros_cloud is not None:
cnt += 1
idx_method = 1
if idx_method == 1:
tmp = convertCloudFromRosToOpen3d(received_ros_cloud)
copyOpen3dCloud(tmp, open3d_cloud)
vis.add_geometry(open3d_cloud)
if idx_method == 2: # this is not working!!!
open3d_cloud = convertCloudFromRosToOpen3d(received_ros_cloud)
if idx_method == 3: # this is keep adding clouds to viewer
open3d_cloud = convertCloudFromRosToOpen3d(received_ros_cloud)
vis.add_geometry(open3d_cloud)
vis.update_geometry()
print("Updating geometry for the {}th time".format(cnt))
received_ros_cloud = None # clear
vis.poll_events()
vis.update_renderer()
rate.sleep()
# print("Updating viewer")