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Compatibility issues with open3d #61

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22 changes: 11 additions & 11 deletions compute_gt_poses.py
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Original file line number Diff line number Diff line change
Expand Up @@ -149,9 +149,9 @@ def full_registration(path,max_correspondence_distance_coarse,
max_correspondence_distance_fine):

global N_Neighbours, LABEL_INTERVAL, n_pcds
pose_graph = registration.PoseGraph()
pose_graph = pipelines.registration.PoseGraph()
odometry = np.identity(4)
pose_graph.nodes.append(registration.PoseGraphNode(odometry))
pose_graph.nodes.append(pipelines.registration.PoseGraphNode(odometry))

pcds = [[] for i in range(n_pcds)]
for source_id in trange(n_pcds):
Expand Down Expand Up @@ -183,19 +183,19 @@ def full_registration(path,max_correspondence_distance_coarse,

else:
transformation_icp = res
information_icp = registration.get_information_matrix_from_point_clouds(
information_icp = pipelines.registration.get_information_matrix_from_point_clouds(
pcds[source_id], pcds[target_id], max_correspondence_distance_fine,
transformation_icp)

if target_id == source_id + 1:
# odometry
odometry = np.dot(transformation_icp, odometry)
pose_graph.nodes.append(registration.PoseGraphNode(np.linalg.inv(odometry)))
pose_graph.edges.append(registration.PoseGraphEdge(source_id, target_id,
pose_graph.nodes.append(pipelines.registration.PoseGraphNode(np.linalg.inv(odometry)))
pose_graph.edges.append(pipelines.registration.PoseGraphEdge(source_id, target_id,
transformation_icp, information_icp, uncertain = False))
else:
# loop closure
pose_graph.edges.append(registration.PoseGraphEdge(source_id, target_id,
pose_graph.edges.append(pipelines.registration.PoseGraphEdge(source_id, target_id,
transformation_icp, information_icp, uncertain = True))

return pose_graph
Expand Down Expand Up @@ -233,7 +233,7 @@ def load_pcds(path, downsample = True, interval = 1):
global voxel_size, camera_intrinsics
pcds= []

for Filename in xrange(len(glob.glob1(path+"JPEGImages","*.jpg"))/interval):
for Filename in range(len(glob.glob1(path+"JPEGImages","*.jpg"))/interval):
img_file = path + 'JPEGImages/%s.jpg' % (Filename*interval)

cad = cv2.imread(img_file)
Expand Down Expand Up @@ -352,13 +352,13 @@ def print_usage():
max_correspondence_distance_fine)

print("Optimizing PoseGraph ...")
option =registration.GlobalOptimizationOption(
option =pipelines.registration.GlobalOptimizationOption(
max_correspondence_distance = max_correspondence_distance_fine,
edge_prune_threshold = 0.25,
reference_node = 0)
registration.global_optimization(pose_graph,
registration.GlobalOptimizationLevenbergMarquardt(),
registration.GlobalOptimizationConvergenceCriteria(), option)
pipelines.registration.global_optimization(pose_graph,
pipelines.registration.GlobalOptimizationLevenbergMarquardt(),
pipelines.registration.GlobalOptimizationConvergenceCriteria(), option)



Expand Down
2 changes: 1 addition & 1 deletion get_BBs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@
mask = cv2.imread(mask_dir,0)
thresh = cv2.threshold(mask.copy(), 30, 255, cv2.THRESH_BINARY)[1]

_, contours, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
contours, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cnt = max(contours, key=cv2.contourArea)
x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(img_original,(x,y),(x+w,y+h),(0,255,0),2)
Expand Down
14 changes: 7 additions & 7 deletions registration.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,25 +46,25 @@ def icp(source,target,voxel_size,max_correspondence_distance_coarse,max_correspo

assert method in ["point-to-plane","colored-icp"],"point-to-plane or colored-icp"
if method == "point-to-plane":
icp_coarse = registration.registration_icp(source, target,
icp_coarse = pipelines.registration.registration_icp(source, target,
max_correspondence_distance_coarse, np.identity(4),
registration.TransformationEstimationPointToPlane())
icp_fine = registration.registration_icp(source, target,
pipelines.registration.TransformationEstimationPointToPlane())
icp_fine = pipelines.registration.registration_icp(source, target,
max_correspondence_distance_fine, icp_coarse.transformation,
registration.TransformationEstimationPointToPlane())
pipelines.registration.TransformationEstimationPointToPlane())

transformation_icp = icp_fine.transformation


if method == "colored-icp":
result_icp = registration.registration_colored_icp(source,target,voxel_size, np.identity(4),
registration.ICPConvergenceCriteria(relative_fitness = 1e-8,
result_icp = pipelines.registration.registration_colored_icp(source,target,voxel_size, np.identity(4),
pipelines.registration.ICPConvergenceCriteria(relative_fitness = 1e-8,
relative_rmse = 1e-8, max_iteration = 50))

transformation_icp = result_icp.transformation


information_icp = registration.get_information_matrix_from_point_clouds(
information_icp = pipelines.registration.get_information_matrix_from_point_clouds(
source, target, max_correspondence_distance_fine,
transformation_icp)

Expand Down