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error in preprocessing #28

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MARS-J opened this issue Dec 5, 2023 · 10 comments
Open

error in preprocessing #28

MARS-J opened this issue Dec 5, 2023 · 10 comments

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@MARS-J
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MARS-J commented Dec 5, 2023

你好，我在运行python utils/preprocessing.py datasets/mvtec3d/ 这行代码的时候，出现了一个报错，(m3dm1) PS D:\M3DM-main\M3DM-main> python utils/preprocessing.py datasets/mvtec3d/
Found 4147 tiff files in datasets/mvtec3d/
ransac: 50
[Open3D Error] (class std::tuple<class Eigen::Matrix<double,4,1,0,4,1>,class std::vector<unsigned __int64,class std::allocator > > __cdecl open3d::geometry::PointCloud::SegmentPlane(const double,const int,const int,const double) const) D:\a\Open3D\Open3D\cpp\open3d\geometry\PointCloudSegmentation.cpp:172: There must be at least 'ransac_n' points.

Traceback (most recent call last):
File "utils/preprocessing.py", line 142, in
preprocess_pc(path)
File "utils/preprocessing.py", line 113, in preprocess_pc
planeless_organized_pc, planeless_organized_rgb = remove_plane(organized_pc, organized_rgb)
File "utils/preprocessing.py", line 34, in remove_plane
plane_model = get_plane_eq(get_edges_of_pc(organized_pc_clean))
File "utils/preprocessing.py", line 23, in get_plane_eq
plane_model, inliers = o3d_pc.segment_plane(distance_threshold=0.004, ransac_n=ransac_n_pts, num_iterations=1000)
RuntimeError: [Open3D Error] (class std::tuple<class Eigen::Matrix<double,4,1,0,4,1>,class std::vector<unsigned __int64,class std::allocator > > __cdecl open3d::geometry::PointCloud::SegmentPlane(const double,const int,const int,const double) const) D:\a\Open3D\Open3D\cpp\open3d\geometry\PointCloudSegmentation.cpp:172: There must be at least 'ransac_n' points.

请问您知道报错的原因吗，求教
@MARS-J
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MARS-J commented Dec 5, 2023

换过很多个open3d的版本都报错

@OneRilard
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你好，我在运行python utils/preprocessing.py datasets/mvtec3d/ 这行代码的时候，出现了一个报错，(m3dm1) PS D:\M3DM-main\M3DM-main> python utils/preprocessing.py datasets/mvtec3d/ Found 4147 tiff files in datasets/mvtec3d/ ransac: 50 [Open3D Error] (class std::tuple<class Eigen::Matrix<double,4,1,0,4,1>,class std::vector<unsigned __int64,class std::allocator > > __cdecl open3d::geometry::PointCloud::SegmentPlane(const double,const int,const int,const double) const) D:\a\Open3D\Open3D\cpp\open3d\geometry\PointCloudSegmentation.cpp:172: There must be at least 'ransac_n' points.

Traceback (most recent call last): File "utils/preprocessing.py", line 142, in preprocess_pc(path) File "utils/preprocessing.py", line 113, in preprocess_pc planeless_organized_pc, planeless_organized_rgb = remove_plane(organized_pc, organized_rgb) File "utils/preprocessing.py", line 34, in remove_plane plane_model = get_plane_eq(get_edges_of_pc(organized_pc_clean)) File "utils/preprocessing.py", line 23, in get_plane_eq plane_model, inliers = o3d_pc.segment_plane(distance_threshold=0.004, ransac_n=ransac_n_pts, num_iterations=1000) RuntimeError: [Open3D Error] (class std::tuple<class Eigen::Matrix<double,4,1,0,4,1>,class std::vector<unsigned __int64,class std::allocator > > __cdecl open3d::geometry::PointCloud::SegmentPlane(const double,const int,const int,const double) const) D:\a\Open3D\Open3D\cpp\open3d\geometry\PointCloudSegmentation.cpp:172: There must be at least 'ransac_n' points.

请问您知道报错的原因吗，求教

我想问下，你解决这个问题了吗，大佬，求教会

@MARS-J
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MARS-J commented Mar 2, 2024 via email

@OneRilard
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我记得好像是open3d的版本不对，又或者是是前面点云数据处理得有问题，导致没有正常读取到点云数据，我有点忘记，不好意思
…
---Original--- From: @.> Date: Sat, Mar 2, 2024 20:29 PM To: @.>; Cc: "Lin @.@.>; Subject: Re: [nomewang/M3DM] error in preprocessing (Issue #28) 你好，我在运行python utils/preprocessing.py datasets/mvtec3d/ 这行代码的时候，出现了一个报错，(m3dm1) PS D:\M3DM-main\M3DM-main> python utils/preprocessing.py datasets/mvtec3d/ Found 4147 tiff files in datasets/mvtec3d/ ransac: 50 [Open3D Error] (class std::tuple<class Eigen::Matrix<double,4,1,0,4,1>,class std::vector<unsigned __int64,class std::allocator > > __cdecl open3d::geometry::PointCloud::SegmentPlane(const double,const int,const int,const double) const) D:\a\Open3D\Open3D\cpp\open3d\geometry\PointCloudSegmentation.cpp:172: There must be at least 'ransac_n' points. Traceback (most recent call last): File "utils/preprocessing.py", line 142, in preprocess_pc(path) File "utils/preprocessing.py", line 113, in preprocess_pc planeless_organized_pc, planeless_organized_rgb = remove_plane(organized_pc, organized_rgb) File "utils/preprocessing.py", line 34, in remove_plane plane_model = get_plane_eq(get_edges_of_pc(organized_pc_clean)) File "utils/preprocessing.py", line 23, in get_plane_eq plane_model, inliers = o3d_pc.segment_plane(distance_threshold=0.004, ransac_n=ransac_n_pts, num_iterations=1000) RuntimeError: [Open3D Error] (class std::tuple<class Eigen::Matrix<double,4,1,0,4,1>,class std::vector<unsigned __int64,class std::allocator > > __cdecl open3d::geometry::PointCloud::SegmentPlane(const double,const int,const int,const double) const) D:\a\Open3D\Open3D\cpp\open3d\geometry\PointCloudSegmentation.cpp:172: There must be at least 'ransac_n' points. 请问您知道报错的原因吗，求教 我想问下，你解决这个问题了吗，大佬，求教会 — Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you authored the thread.Message ID: @.***>

您这个项目还保留有虚拟环境吗，我遇到了和你相同的问题，我刚刚重新安装了open3d和opencv-python的版本，还是显示提取的点云数量不足

@cshunxin
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cshunxin commented Mar 6, 2024

题主可以分享一下跑出来的最终结果吗？QQ2701484292重谢

@XHD5656123
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I have the error too...And I don't know how to figure it out.Anyone success,please help me!

@lprintf
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lprintf commented Apr 10, 2024 

name: m3dm
channels:
  - pytorch
  - nvidia
  - conda-forge
  - defaults
dependencies:
  - _libgcc_mutex=0.1=conda_forge
  - _openmp_mutex=4.5=2_gnu
  - blas=1.0=mkl
  - bottleneck=1.3.7=py38ha9d4c09_0
  - brotli=1.0.9=h5eee18b_7
  - brotli-bin=1.0.9=h5eee18b_7
  - brotli-python=1.0.9=py38h6a678d5_7
  - bzip2=1.0.8=hd590300_5
  - ca-certificates=2024.3.11=h06a4308_0
  - certifi=2024.2.2=py38h06a4308_0
  - chardet=4.0.0=py38h06a4308_1003
  - contourpy=1.0.5=py38hdb19cb5_0
  - cuda-cudart=11.7.99=0
  - cuda-cupti=11.7.101=0
  - cuda-libraries=11.7.1=0
  - cuda-nvrtc=11.7.99=0
  - cuda-nvtx=11.7.91=0
  - cuda-runtime=11.7.1=0
  - cudatoolkit=11.3.1=hb98b00a_13
  - cycler=0.11.0=pyhd3eb1b0_0
  - cyrus-sasl=2.1.28=h52b45da_1
  - dbus=1.13.18=hb2f20db_0
  - expat=2.5.0=h6a678d5_0
  - ffmpeg=4.3=hf484d3e_0
  - fontconfig=2.14.1=h4c34cd2_2
  - fonttools=4.25.0=pyhd3eb1b0_0
  - freetype=2.10.4=h0708190_1
  - giflib=5.2.1=h0b41bf4_3
  - glib=2.78.4=h6a678d5_0
  - glib-tools=2.78.4=h6a678d5_0
  - gmp=6.3.0=h59595ed_1
  - gmpy2=2.1.2=py38heeb90bb_0
  - gnutls=3.6.13=h85f3911_1
  - gst-plugins-base=1.14.1=h6a678d5_1
  - gstreamer=1.14.1=h5eee18b_1
  - icu=73.2=h59595ed_0
  - importlib_resources=6.1.1=py38h06a4308_1
  - intel-openmp=2023.1.0=hdb19cb5_46306
  - jinja2=3.1.3=py38h06a4308_0
  - jpeg=9e=h5eee18b_1
  - kiwisolver=1.4.4=py38h6a678d5_0
  - krb5=1.20.1=h143b758_1
  - lame=3.100=h166bdaf_1003
  - lcms2=2.12=h3be6417_0
  - ld_impl_linux-64=2.38=h1181459_1
  - lerc=3.0=h295c915_0
  - libblas=3.9.0=1_h86c2bf4_netlib
  - libbrotlicommon=1.0.9=h5eee18b_7
  - libbrotlidec=1.0.9=h5eee18b_7
  - libbrotlienc=1.0.9=h5eee18b_7
  - libcblas=3.9.0=5_h92ddd45_netlib
  - libclang=14.0.6=default_hc6dbbc7_1
  - libclang13=14.0.6=default_he11475f_1
  - libcublas=11.10.3.66=0
  - libcufft=10.7.2.124=h4fbf590_0
  - libcufile=1.9.1.3=0
  - libcups=2.4.2=h2d74bed_1
  - libcurand=10.3.5.147=0
  - libcusolver=11.4.0.1=0
  - libcusparse=11.7.4.91=0
  - libdeflate=1.17=h5eee18b_1
  - libedit=3.1.20230828=h5eee18b_0
  - libffi=3.4.4=h6a678d5_0
  - libgcc-ng=13.2.0=h807b86a_5
  - libgfortran-ng=13.2.0=h69a702a_5
  - libgfortran5=13.2.0=ha4646dd_5
  - libglib=2.78.4=hdc74915_0
  - libgomp=13.2.0=h807b86a_5
  - libhwloc=2.9.1=hd6dc26d_0
  - libiconv=1.17=hd590300_2
  - liblapack=3.9.0=5_h92ddd45_netlib
  - libllvm14=14.0.6=hdb19cb5_3
  - libnpp=11.7.4.75=0
  - libnvjpeg=11.8.0.2=0
  - libpng=1.6.39=h5eee18b_0
  - libpq=12.17=hdbd6064_0
  - libstdcxx-ng=13.2.0=h7e041cc_5
  - libtiff=4.5.1=h6a678d5_0
  - libuuid=1.41.5=h5eee18b_0
  - libuv=1.48.0=hd590300_0
  - libwebp=1.3.2=h11a3e52_0
  - libwebp-base=1.3.2=h5eee18b_0
  - libxcb=1.15=h7f8727e_0
  - libxkbcommon=1.0.1=h5eee18b_1
  - libxml2=2.10.4=hf1b16e4_1
  - lz4-c=1.9.4=h6a678d5_0
  - matplotlib=3.7.2=py38h06a4308_0
  - matplotlib-base=3.7.2=py38h1128e8f_0
  - mkl=2023.1.0=h213fc3f_46344
  - mkl-service=2.4.0=py38h5eee18b_1
  - mpc=1.1.0=h10f8cd9_1
  - mpfr=4.0.2=hb69a4c5_1
  - mpmath=1.3.0=py38h06a4308_0
  - munkres=1.1.4=py_0
  - mysql=5.7.24=h721c034_2
  - ncurses=6.4=h6a678d5_0
  - nettle=3.6=he412f7d_0
  - networkx=3.1=py38h06a4308_0
  - ninja=1.11.1=h924138e_0
  - numexpr=2.8.4=py38hc78ab66_1
  - numpy=1.24.4=py38h59b608b_0
  - openh264=2.1.1=h780b84a_0
  - openjpeg=2.4.0=h3ad879b_0
  - openssl=3.2.1=hd590300_1
  - pandas=2.0.3=py38h1128e8f_0
  - pcre2=10.42=hebb0a14_0
  - pillow=10.2.0=py38h5eee18b_0
  - pip=23.3.1=py38h06a4308_0
  - ply=3.11=py38_0
  - pyparsing=3.0.9=py38h06a4308_0
  - pyqt=5.15.10=py38h6a678d5_0
  - pyqt5-sip=12.13.0=py38h5eee18b_0
  - pysocks=1.7.1=py38h06a4308_0
  - python=3.8.19=h955ad1f_0
  - python-dateutil=2.8.2=pyhd3eb1b0_0
  - python-tzdata=2023.3=pyhd3eb1b0_0
  - python_abi=3.8=2_cp38
  - pytorch=2.0.1=py3.8_cuda11.7_cudnn8.5.0_0
  - pytorch-cuda=11.7=h778d358_5
  - pytorch-mutex=1.0=cuda
  - pytz=2023.3.post1=py38h06a4308_0
  - qt-main=5.15.2=h53bd1ea_10
  - readline=8.2=h5eee18b_0
  - requests=2.31.0=py38h06a4308_1
  - sip=6.7.12=py38h6a678d5_0
  - six=1.16.0=pyhd3eb1b0_1
  - sqlite=3.41.2=h5eee18b_0
  - sympy=1.12=py38h06a4308_0
  - tabulate=0.9.0=py38h06a4308_0
  - tbb=2021.9.0=hf52228f_0
  - tk=8.6.12=h1ccaba5_0
  - tomli=2.0.1=py38h06a4308_0
  - torchaudio=2.0.2=py38_cu117
  - torchtriton=2.0.0=py38
  - torchvision=0.15.2=py38_cu117
  - tornado=6.3.3=py38h5eee18b_0
  - typing_extensions=4.11.0=pyha770c72_0
  - wheel=0.41.2=py38h06a4308_0
  - xz=5.4.6=h5eee18b_0
  - zlib=1.2.13=h5eee18b_0
  - zstd=1.5.5=hc292b87_0
  - pip:
      - absl-py==2.1.0
      - addict==2.4.0
      - asttokens==2.4.1
      - attrs==23.2.0
      - backcall==0.2.0
      - blinker==1.7.0
      - cachetools==5.3.3
      - charset-normalizer==3.3.2
      - click==8.1.7
      - comm==0.2.2
      - configargparse==1.7
      - dash==2.16.1
      - dash-core-components==2.0.0
      - dash-html-components==2.0.0
      - dash-table==5.0.0
      - decorator==5.1.1
      - executing==2.0.1
      - fastjsonschema==2.19.1
      - filelock==3.13.3
      - flask==3.0.2
      - fsspec==2024.3.1
      - google-auth==2.29.0
      - google-auth-oauthlib==1.0.0
      - grpcio==1.62.1
      - huggingface-hub==0.22.2
      - idna==3.6
      - imageio==2.34.0
      - importlib-metadata==7.1.0
      - ipython==8.12.3
      - ipywidgets==8.1.2
      - itsdangerous==2.1.2
      - jedi==0.19.1
      - joblib==1.3.2
      - jsonschema==4.21.1
      - jsonschema-specifications==2023.12.1
      - jupyter-core==5.7.2
      - jupyterlab-widgets==3.0.10
      - knn-cuda==0.2
      - kornia==0.7.2
      - kornia-rs==0.1.3
      - lazy-loader==0.4
      - markdown==3.6
      - markupsafe==2.1.5
      - matplotlib-inline==0.1.6
      - nbformat==5.10.4
      - nest-asyncio==1.6.0
      - 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==8.9.2.26
      - 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==2.19.3
      - nvidia-nvjitlink-cu12==12.4.127
      - nvidia-nvtx-cu12==12.1.105
      - oauthlib==3.2.2
      - open3d==0.18.0
      - opencv-python==4.9.0.80
      - packaging==24.0
      - parso==0.8.4
      - pexpect==4.9.0
      - pickleshare==0.7.5
      - pkgutil-resolve-name==1.3.10
      - platformdirs==4.2.0
      - plotly==5.20.0
      - pointnet2-ops==3.0.0
      - prompt-toolkit==3.0.43
      - protobuf==5.26.1
      - ptyprocess==0.7.0
      - pure-eval==0.2.2
      - pyasn1==0.6.0
      - pyasn1-modules==0.4.0
      - pygments==2.17.2
      - pyquaternion==0.9.9
      - pywavelets==1.4.1
      - pyyaml==6.0.1
      - referencing==0.34.0
      - requests-oauthlib==2.0.0
      - retrying==1.3.4
      - rpds-py==0.18.0
      - rsa==4.9
      - safetensors==0.4.2
      - scikit-image==0.21.0
      - scikit-learn==1.3.2
      - scipy==1.10.1
      - setuptools==59.5.0
      - stack-data==0.6.3
      - tenacity==8.2.3
      - tensorboard==2.14.0
      - tensorboard-data-server==0.7.2
      - threadpoolctl==3.4.0
      - tifffile==2023.7.10
      - timm==0.9.16
      - tqdm==4.66.2
      - traitlets==5.14.2
      - triton==2.2.0
      - urllib3==2.2.1
      - wcwidth==0.2.13
      - werkzeug==3.0.2
      - wget==3.2
      - widgetsnbextension==4.0.10
      - zipp==3.18.1

I have successfully run the project, and here is the corresponding conda environment configuration file. I hope it is helpful to you.

@OneRilard
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OneRilard commented Apr 10, 2024 via email

@MARS-J
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MARS-J commented Apr 11, 2024 via email

@MARS-J
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MARS-J commented Apr 11, 2024 via email

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@lprintf @MARS-J @XHD5656123 @OneRilard @cshunxin