felja633 / dare Goto Github PK
View Code? Open in Web Editor NEWDensity Adaptive Point Set Registration
License: MIT License
Density Adaptive Point Set Registration
License: MIT License
Please note that the installations were carried out by executing the shell script , in a conda environment.
traceback (most recent call last):
File "reg_demo.py", line 6, in
from src import psreg
File "/home/dl/DARE/src/psreg.py", line 11, in
from .math_utils.build import math_utils
ImportError: cannot import name 'math_utils' from 'src.math_utils.build' (unknown location)
Thank you!
hello
I want to use your code on my point cloud processing. but I have problem to use pcl and I cant build it. when I want to bui this with cmake it returns error:
CMake Error at CMakeLists.txt:9 (find_package):
By not providing "Findpybind11.cmake" in CMAKE_MODULE_PATH this project has
asked CMake to find a package configuration file provided by "pybind11",
but CMake did not find one.
Could not find a package configuration file provided by "pybind11" with any
of the following names:
pybind11Config.cmake
pybind11-config.cmake
Add the installation prefix of "pybind11" to CMAKE_PREFIX_PATH or set
"pybind11_DIR" to a directory containing one of the above files. If
"pybind11" provides a separate development package or SDK, be sure it has
been installed.
can you help me?
Thanks
The patten on the point cloud data is
X Y Z R G B
????
the cppsr code is ok, but the code of FPPSR still doesn't work.
i have compile the pcl_utils.cpp file successfully. the file can get the shape features
Errors occur in common code of :
ValueError: shapes (10000,300) and (10000,300) not aligned: 300 (dim 1) != 10000 (dim 0)
i find cppsr's featrues's shape is[0],[1],[3],each of them is[10000,64]
but the fppsr's feature's shape is[0],[1],[3],each of them is[10000,]
the reason for the error is that the features get from shape_feature_extraction.py is different from the color_feature_extraction.py
Although I know the reason, I don't know how to modify it. Can you help me
No offense, the work is interesting, but the article and code are hard to read...
Sorry, but if there are more comments on code, things will be better.
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