Open
Description
Trying to run the demo.py but I get Floating point exception (core dumped).
I traced it back when calling __getitem__() for demo_dataset
transform_points_to_voxels() calls the VoxelGeneratorWrapper with its generate() function:
def generate(self, points):
if self.spconv_ver == 1:
voxel_output = self._voxel_generator.generate(points)
if isinstance(voxel_output, dict):
voxels, coordinates, num_points = \
voxel_output['voxels'], voxel_output['coordinates'], voxel_output['num_points_per_voxel']
else:
voxels, coordinates, num_points = voxel_output
else:
assert tv is not None, f"Unexpected error, library: 'cumm' wasn't imported properly."
voxel_output = self._voxel_generator.point_to_voxel(tv.from_numpy(points))
tv_voxels, tv_coordinates, tv_num_points = voxel_output
# make copy with numpy(), since numpy_view() will disappear as soon as the generator is deleted
voxels = tv_voxels.numpy()
coordinates = tv_coordinates.numpy()
num_points = tv_num_points.numpy()
return voxels, coordinates, num_pointsand the core dump happens inside tv.from_numpy(points) in the else branch.
I am running the demo.py with the command:
demo.py --cfg_file cfgs/kitti_models/pointpillar.yaml --ckpt ../models/pointpillar_7728.pth --data_path ../dataset_pointcloud/
where I put only the 000000.bin from kitti dataset in that dataset_pointcloud address.
I am running on a linux server with Tesla V100 gpu. Driver Version: 545.23.08 CUDA Version: 12.3
Package Version Editable project location
------------------------- ------------- ---------------------------------------------
addict 2.4.0
argcomplete 3.6.2
asttokens 3.0.0
attrs 25.3.0
av 14.4.0
av2 0.2.0
blinker 1.9.0
ccimport 0.4.4
certifi 2025.4.26
charset-normalizer 3.4.2
click 8.2.1
colorlog 6.9.0
comm 0.2.2
ConfigArgParse 1.7.1
contourpy 1.3.2
cumm 0.7.11
cumm-cu120 0.4.11
cycler 0.12.1
dash 3.0.4
decorator 5.2.1
dependency-groups 1.3.1
distlib 0.3.9
easydict 1.13
exceptiongroup 1.3.0
executing 2.2.0
fastjsonschema 2.21.1
filelock 3.13.1
fire 0.7.0
Flask 3.0.3
fonttools 4.58.0
fsspec 2024.6.1
idna 3.10
imageio 2.37.0
importlib_metadata 8.7.0
ipython 8.36.0
ipywidgets 8.1.7
itsdangerous 2.2.0
jedi 0.19.2
Jinja2 3.1.6
joblib 1.5.1
jsonschema 4.24.0
jsonschema-specifications 2025.4.1
jupyter_core 5.8.0
jupyterlab_widgets 3.0.15
kiwisolver 1.4.8
kornia 0.6.8
kornia_rs 0.1.9
lark 1.2.2
lazy_loader 0.4
llvmlite 0.44.0
markdown-it-py 3.0.0
MarkupSafe 3.0.2
matplotlib 3.10.3
matplotlib-inline 0.1.7
mdurl 0.1.2
mpmath 1.3.0
narwhals 1.41.0
nbformat 5.10.4
nest-asyncio 1.6.0
networkx 3.3
ninja 1.11.1.4
nox 2025.5.1
numba 0.61.2
numpy 2.2.6
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu12 9.1.0.70
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu12 12.1.0.106
nvidia-nccl-cu12 2.21.5
nvidia-nvjitlink-cu12 12.1.105
nvidia-nvtx-cu12 12.1.105
open3d 0.19.0
opencv-python 4.11.0.86
packaging 25.0
pandas 2.2.3
parso 0.8.4
pccm 0.4.16
pcdet 0.6.0+8caccce /path to/OpenPCDet
pexpect 4.9.0
pillow 11.2.1
pip 25.1.1
platformdirs 4.3.8
plotly 6.1.1
portalocker 3.1.1
prompt_toolkit 3.0.51
protobuf 6.31.0
ptyprocess 0.7.0
pure_eval 0.2.3
pyarrow 20.0.0
pybind11 2.13.6
Pygments 2.19.1
pyparsing 3.2.3
pyproj 3.7.1
pyquaternion 0.9.9
python-dateutil 2.9.0.post0
pytz 2025.2
PyYAML 6.0.2
referencing 0.36.2
requests 2.32.3
retrying 1.3.4
rich 14.0.0
rpds-py 0.25.1
scikit-image 0.25.2
scikit-learn 1.6.1
scipy 1.15.3
setuptools 65.5.0
SharedArray 3.2.4
six 1.17.0
spconv-cu120 2.3.6
stack-data 0.6.3
sympy 1.13.1
tensorboardX 2.6.2.2
tensorvision 0.1.dev2
termcolor 3.1.0
threadpoolctl 3.6.0
tifffile 2025.5.10
tomli 2.2.1
torch 2.5.1+cu121
torchaudio 2.5.1+cu121
torchvision 0.20.1+cu121
tqdm 4.67.1
traitlets 5.14.3
triton 3.1.0
typing_extensions 4.13.2
tzdata 2025.2
urllib3 2.4.0
virtualenv 20.31.2
wcwidth 0.2.13
Werkzeug 3.0.6
widgetsnbextension 4.0.14
zipp 3.22.0