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Python wrapper around C++ utility to compute local geometric features of a point cloud

License: MIT License

Python 9.81% C++ 87.76% CMake 2.43%

3d python numpy machine-learning geometric-features point-cloud cpu fast features nanoflann

point_geometric_features's Introduction

Deep Learning researcher working on
point clouds ☁️ | images 🖼️ | satellites 🛰️ | environment 🌲

Personal webpage

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charlesgaydon loicland rjanvier qingxia1994 3dfin

point_geometric_features's Issues

Installation failed due to "Failed building wheel for pgeof"

I am running into trouble installing the library using pip. It looks like an issue with the nanobind library. The last time I installed pgeof it went fine (a couple of months ago). The installation ends with:

Failed to build pgeof
ERROR: Could not build wheels for pgeof, which is required to install pyproject.toml-based projects

Full log trace

python -m pip install pgeof Collecting pgeof Downloading pgeof-0.2.0.tar.gz (69.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 69.0/69.0 MB 7.0 MB/s eta 0:00:00 Installing build dependencies ... done Getting requirements to build wheel ... done Installing backend dependencies ... done Preparing metadata (pyproject.toml) ... done Collecting numpy<2,>=1.7 (from pgeof) Using cached numpy-1.24.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.6 kB) Using cached numpy-1.24.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.3 MB) Building wheels for collected packages: pgeof Building wheel for pgeof (pyproject.toml) ... error error: subprocess-exited-with-error

× Building wheel for pgeof (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> [110 lines of output]
*** scikit-build-core 0.9.4 using CMake 3.27.7 (wheel)
*** Configuring CMake...
2024-05-31 11:06:57,601 - scikit_build_core - WARNING - Can't find a Python library, got libdir=/home/matic/anaconda3/envs/test-env/lib, ldlibrary=libpython3.8.a, multiarch=x86_64-linux-gnu, masd=None
loading initial cache file build/cp38-cp38-linux_x86_64/CMakeInit.txt
-- The C compiler identification is GNU 9.4.0
-- The CXX compiler identification is GNU 9.4.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /usr/bin/cc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Found Python: /home/matic/anaconda3/envs/test-env/bin/python (found suitable version "3.8.19", minimum required is "3.8") found components: Interpreter Development.Module
-- Configuring done (0.4s)
-- Generating done (0.0s)
-- Build files have been written to: /tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/build/cp38-cp38-linux_x86_64
*** Building project with Ninja...
[1/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/nb_static_property.cpp.o
[2/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/implicit.cpp.o
[3/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/trampoline.cpp.o
[4/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/nb_internals.cpp.o
[5/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/error.cpp.o
[6/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/nb_ndarray.cpp.o
[7/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/common.cpp.o
[8/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/nb_enum.cpp.o
[9/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/nb_func.cpp.o
[10/13] Building CXX object CMakeFiles/nanobind-static.dir/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/src/nb_type.cpp.o
[11/13] Linking CXX static library libnanobind-static.a
[12/13] Building CXX object CMakeFiles/pgeof_ext.dir/src/pgeof_ext.cpp.o
FAILED: CMakeFiles/pgeof_ext.dir/src/pgeof_ext.cpp.o
/usr/bin/c++ -Dpgeof_ext_EXPORTS -I/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include -I/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/third_party/eigen -I/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/third_party/nanoflann/include -I/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/third_party/taskflow -I/home/matic/anaconda3/envs/test-env/include/python3.8 -I/tmp/pip-build-env-34w23q9k/overlay/lib/python3.8/site-packages/nanobind/include -O3 -DNDEBUG -std=gnu++17 -flto -fno-fat-lto-objects -fPIC -fvisibility=hidden -fno-stack-protector -ffunction-sections -fdata-sections -MD -MT CMakeFiles/pgeof_ext.dir/src/pgeof_ext.cpp.o -MF CMakeFiles/pgeof_ext.dir/src/pgeof_ext.cpp.o.d -o CMakeFiles/pgeof_ext.dir/src/pgeof_ext.cpp.o -c /tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/src/pgeof_ext.cpp
In file included from /tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/src/pgeof_ext.cpp:8:
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:76:58: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
76 | static nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, feature_count>> compute_geometric_features(
| ^~~~~~~~~~~~~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:76:58: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:76:71: error: template argument 3 is invalid
76 | static nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, feature_count>> compute_geometric_features(
| ^~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp: In function ‘int pgeof::compute_geometric_features(pgeof::RefCloud<real_t>, nanobind::ndarray<const unsigned int, nanobind::shape<-1> >, nanobind::ndarray<const unsigned int, nanobind::shape<-1> >, size_t, bool)’:
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:114:62: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
114 | return nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, feature_count>>(features, 2, shape, owner_features);
| ^~~~~~~~~~~~~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:114:62: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:114:75: error: template argument 3 is invalid
114 | return nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, feature_count>>(features, 2, shape, owner_features);
| ^~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp: At global scope:
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:158:67: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
158 | static nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, nb::any, feature_count>> compute_geometric_features_multiscale(
| ^~~~~~~~~~~~~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:158:67: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:158:67: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:158:67: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:158:80: error: template argument 3 is invalid
158 | static nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, nb::any, feature_count>> compute_geometric_features_multiscale(
| ^~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp: In function ‘int pgeof::compute_geometric_features_multiscale(pgeof::RefCloud<real_t>, nanobind::ndarray<const unsigned int, nanobind::shape<-1> >, nanobind::ndarray<const unsigned int, nanobind::shape<-1> >, const std::vector&, bool)’:
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:206:71: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
206 | return nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, nb::any, feature_count>>(
| ^~~~~~~~~~~~~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:206:71: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:206:71: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:206:71: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:206:84: error: template argument 3 is invalid
206 | return nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, nb::any, feature_count>>(
| ^~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp: At global scope:
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:241:58: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
241 | static nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, feature_count>> compute_geometric_features_optimal(
| ^~~~~~~~~~~~~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:241:58: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:241:71: error: template argument 3 is invalid
241 | static nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, feature_count>> compute_geometric_features_optimal(
| ^~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp: In function ‘int pgeof::compute_geometric_features_optimal(pgeof::RefCloud<real_t>, nanobind::ndarray<const unsigned int, nanobind::shape<-1> >, nanobind::ndarray<const unsigned int, nanobind::shape<-1> >, uint32_t, uint32_t, uint32_t, bool)’:
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:303:62: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
303 | return nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, feature_count>>(features, 2, shape, owner_features);
| ^~~~~~~~~~~~~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:303:62: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:303:75: error: template argument 3 is invalid
303 | return nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, feature_count>>(features, 2, shape, owner_features);
| ^~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp: At global scope:
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:320:62: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
320 | static nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, nb::any>> compute_geometric_features_selected(
| ^~~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:320:62: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:320:62: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:320:62: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:320:65: error: template argument 3 is invalid
320 | static nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, nb::any>> compute_geometric_features_selected(
| ^~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp: In function ‘int pgeof::compute_geometric_features_selected(pgeof::RefCloud<real_t>, real_t, uint32_t, const std::vectorpgeof::EFeatureID&)’:
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:367:66: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
367 | return nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, nb::any>>(features, {static_cast<size_t>(n_points), feature_count}, owner_features);
| ^~~
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:367:66: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:367:66: error: type/value mismatch at argument 1 in template parameter list for ‘template<long int ...Is> struct nanobind::shape’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:367:66: note: expected a constant of type ‘long int’, got ‘nanobind::any’
/tmp/pip-install-i_isslon/pgeof_16416ab81e6a4431b1b2dc0f09770a72/include/pgeof.hpp:367:69: error: template argument 3 is invalid
367 | return nb::ndarray<nb::numpy, real_t, nb::shape<nb::any, nb::any>>(features, {static_cast<size_t>(n_points), feature_count}, owner_features);
| ^~
ninja: build stopped: subcommand failed.

  *** CMake build failed
  [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for pgeof
Failed to build pgeof
ERROR: Could not build wheels for pgeof, which is required to install pyproject.toml-based projects

I tried installing inside a fresh conda environment using python3.8 and 3.9, both unsuccessful. Installation using install.sh inside the SPT repo also failed with the same error. Googling I found it could also be an issue with non-upgraded pip, wheel, but trying that didn't fix my issue.

I am using Ubuntu 20.04.4 LTS, CUDA Version 12.4

Conda list of the fresh python3.9 conda environment

Name Version Build Channel

_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_gnu conda-forge
bzip2 1.0.8 hd590300_5 conda-forge
ca-certificates 2024.2.2 hbcca054_0 conda-forge
ld_impl_linux-64 2.40 hf3520f5_1 conda-forge
libffi 3.4.2 h7f98852_5 conda-forge
libgcc-ng 13.2.0 h77fa898_7 conda-forge
libgomp 13.2.0 h77fa898_7 conda-forge
libnsl 2.0.1 hd590300_0 conda-forge
libsqlite 3.45.3 h2797004_0 conda-forge
libuuid 2.38.1 h0b41bf4_0 conda-forge
libxcrypt 4.4.36 hd590300_1 conda-forge
libzlib 1.2.13 h4ab18f5_6 conda-forge
ncurses 6.5 h59595ed_0 conda-forge
openssl 3.3.0 h4ab18f5_3 conda-forge
pip 24.0 pyhd8ed1ab_0 conda-forge
python 3.9.19 h0755675_0_cpython conda-forge
readline 8.2 h8228510_1 conda-forge
setuptools 70.0.0 pyhd8ed1ab_0 conda-forge
tk 8.6.13 noxft_h4845f30_101 conda-forge
tzdata 2024a h0c530f3_0 conda-forge
wheel 0.43.0 pyhd8ed1ab_1 conda-forge
xz 5.2.6 h166bdaf_0 conda-forge

Any help is appreciated!

Multi scale features computation

Hi Damien,
I have a little window to try to implement multi scale feature computation we talked about (see #4).
I would like to know how do you see the thing? would you want to rely on an aggregation scheme (I don't think a mean makes sense for all features) or output the whole multi scale feature map?
Thank in advance,
Romain

pgeof as a pip package

Packaging pgeof as a pip package, free from the conda dependency of eigen3 would be great.

@rjanvier I think you were thinking of working on this at some point. Is this still something you are considering ?

Memory leak of pgeof

Hello,
as mentionned in this issue I think pgeof has a memory leaks too:
If we take the demo.py script with a slightly faster knn :

from pgeof import pgeof
import numpy as np
import tracemalloc
tracemalloc.start()
num_iter=200
marqueur=0
snapshot=tracemalloc.take_snapshot()
import gc 
from scipy.spatial import cKDTree
def get_x(n_points=4000000):
    import torch
    x_min=[-15,46]
    y_min=[-45,30]
    z_min=[0,7]
    num_class=9
    x=torch.rand((n_points,3))
    x[:,0]=x[:,0]*(x_min[1]-x_min[0])+x_min[0]
    x[:,1]=x[:,1]*(y_min[1]-y_min[0])+y_min[0]
    x[:,2]=x[:,2]*(z_min[1]-z_min[0])+z_min[0]


    return x


def Query_CPU(
        xyz_query, xyz_search, K,r):

    kdtree=cKDTree(xyz_search)
    distances, neighbors = kdtree.query(xyz_query, k=K, distance_upper_bound=r,workers=-1)
    neighbors[distances==float('inf')]=-1
    return distances, neighbors 

for j in range(num_iter):
    # Generate a random synthetic point cloud
    num_points = int(1e5)
    xyz=get_x(num_points).numpy()

    # Manually generating random neighbors in CSR format
    nn_ptr = np.r_[0, np.random.randint(low=0, high=30, size=num_points).cumsum()]
    nn = np.random.randint(low=0, high=num_points, size=nn_ptr[-1])

    # Converting k-nearest neighbors to CSR format
    from sklearn.neighbors import NearestNeighbors
    k = 20
    kneigh = Query_CPU(xyz, xyz, k,20)
    nn_ptr = np.arange(num_points + 1) * k
    nn = kneigh[1].flatten()

    # Converting radius neighbors to CSR format
    # from sklearn.neighbors import NearestNeighbors
    # radius = 0.1
    # rneigh = NearestNeighbors(radius=radius).fit(xyz).radius_neighbors(xyz)
    # nn_ptr = np.r_[0, np.array([x.shape[0] for x in rneigh[1]]).cumsum()]
    # nn = np.concatenate(rneigh[1])

    # Make sure xyz are float32 and nn and nn_ptr are uint32
    xyz = xyz.astype('float32')
    nn_ptr = nn_ptr.astype('uint32')
    nn = nn.astype('uint32')

    # Make sure arrays are contiguous (C-order) and not Fortran-order
    xyz = np.ascontiguousarray(xyz)
    nn_ptr = np.ascontiguousarray(nn_ptr)
    nn = np.ascontiguousarray(nn)


    geof = pgeof(
    xyz, nn, nn_ptr, k_min=10, k_step=1, k_min_search=15,
        verbose=True)  
    marqueur+=1
    gc.collect()

    if marqueur>1e1:
        snapshot2=tracemalloc.take_snapshot()
        marqueur=0
        Top_stats=snapshot2.compare_to(snapshot,'lineno')
        print("TOP 10 differneces")
        for stat in Top_stats[:10]:
            print(stat)
        current,peak=tracemalloc.get_traced_memory()
        print(f"Current memory usage is {current/10**6}MB; Peak was {peak/10**6}MB")
        top_stats=snapshot2.statistics('traceback')
        stat=top_stats[0]
        print("%s memory blocks: %.1f in MiB: " % (stat.count,stat.size/1024**2))
        for line in stat.traceback.format():
            print(line)

the memory is slightly increasing each iteration and I tried to run the script with valgrind and I indeed go some memory definitely lsot

Migrate from distutils to setuptools

Hi Damien,

For a bit of context, I currently use @drprojects/superpoint_transformer to make some forest segmentation for the @3DFin project. It works pretty well but we want to lower the technical cost of using it (in an inference context) for scientist interested in the field of Forest management.

I started to review compiled dependency and evaluate if we can offer pre build wheels (via https://github.com/pypa/cibuildwheel). I first noticed that all your C++ based python module/dependencies use distutils as a build system. distutils is deprecated and I think it did not even work anymore with python 3.12. So future users could have hard time to install your dependencies. Would you agree if I try to port pgeof to setuptools build system (which is the "drop in" replacement for distutils)?

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