Hi!
Thanks for your interesting work.When I run "python -m apps.align_point_cloud samples/000.ply samples/002.ply --logdir logs/LCD-D256/", I got the error: TypeError: registration_ransac_based_on_feature_matching(): incompatible function arguments. The following argument types are supported.
log:
python -m apps.align_point_cloud samples/000.ply samples/002.ply --logdir logs/LCD-D256/
Loading model from logs/LCD-D256/model.pth
Extracted 1469 features from source
Extracted 1432 features from target
Traceback (most recent call last):
File "/home/houyongkuo/miniconda3/envs/lmpr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/houyongkuo/miniconda3/envs/lmpr/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/houyongkuo/Documents/lcd/apps/align_point_cloud.py", line 94, in
result = open3d.pipelines.registration.registration_ransac_based_on_feature_matching(
TypeError: registration_ransac_based_on_feature_matching(): incompatible function arguments. The following argument types are supported:
1. (source: open3d.cpu.pybind.geometry.PointCloud, target: open3d.cpu.pybind.geometry.PointCloud, source_feature: open3d::pipelines::registration::Feature, target_feature: open3d::pipelines::registration::Feature, mutual_filter: bool, max_correspondence_distance: float, estimation_method: open3d.cpu.pybind.pipelines.registration.TransformationEstimation = TransformationEstimationPointToPoint without scaling., ransac_n: int = 3, checkers: List[open3d.cpu.pybind.pipelines.registration.CorrespondenceChecker] = [], criteria: open3d.cpu.pybind.pipelines.registration.RANSACConvergenceCriteria = RANSACConvergenceCriteria class with max_iteration=100000, and confidence=9.990000e-01) -> open3d.cpu.pybind.pipelines.registration.RegistrationResult
Invoked with: PointCloud with 1469 points., PointCloud with 1432 points., Feature class with dimension = 256 and num = 1469
Access its data via data member., Feature class with dimension = 256 and num = 1432
Access its data via data member., 0.075, TransformationEstimationPointToPoint without scaling., 4, [CorrespondenceCheckerBasedOnDistance with distance_threshold=0.075000], RANSACConvergenceCriteria class with max_iteration=4000000, and confidence=5.000000e+02
Thanks!
Hi!
Thanks for your interesting work.When I run "python -m apps.align_point_cloud samples/000.ply samples/002.ply --logdir logs/LCD-D256/", I got the error: TypeError: registration_ransac_based_on_feature_matching(): incompatible function arguments. The following argument types are supported.
log:
python -m apps.align_point_cloud samples/000.ply samples/002.ply --logdir logs/LCD-D256/
Invoked with: PointCloud with 1469 points., PointCloud with 1432 points., Feature class with dimension = 256 and num = 1469
Access its data via data member., Feature class with dimension = 256 and num = 1432
Access its data via data member., 0.075, TransformationEstimationPointToPoint without scaling., 4, [CorrespondenceCheckerBasedOnDistance with distance_threshold=0.075000], RANSACConvergenceCriteria class with max_iteration=4000000, and confidence=5.000000e+02
Thanks!