ubuntu安装colmap

为防止安装colmap时，在编译过程中存在路径冲突，因此将anaconda文件名暂时更改为其他名称

安装Ceres

官网链接官方链接是这个我下载失败了

git clone https://ceres-solver.googlesource.com/ceres-solver

找了一个非官方的，自行下载，我下载的是2.2.0版本

Index of /ceres-solverhttps://distfiles.macports.org/ceres-solver/

tar -zxvf ceres-solver-2.0.0.tar.gz  
cd ceres-solver-2.0.0/
mkdir build 
cd build
cmake .. 
make -j$(nproc)
sudo make install

此时文件夹是3d/ceres-solver-2.0.0/build，重新打开3d文件夹环境

安装colmap 

安装 — COLMAP 3.12.0.dev0 文档官方链接

-DCMAKE_CUDA_ARCHITECTURES=61 是GPU型号确定的，详见https://blog.csdn.net/Stay_Foo_lish/article/details/134318450

git clone https://github.com/colmap/colmap.git



cd colmap
mkdir build
cd build
# 指定gpu的架构，这个61是我显卡的架构，具体需要根据自己的显卡来确定。
cmake -DCMAKE_CUDA_ARCHITECTURES=61 ..
make -j$(nproc)
sudo make install

在camake这一步一直出现

CMake Error at /home/amx/.local/lib/python3.9/site-packages/cmake/data/share/cmake-3.27/Modules/CMakeDetermineCompilerId.cmake:753 (message):
  Compiling the CUDA compiler identification source file
  "CMakeCUDACompilerId.cu" failed.

  Compiler: /usr/bin/nvcc

  Build flags:

  Id flags: --keep;--keep-dir;tmp -v

  The output was:

  255

  #$ _SPACE_=

  #$ _CUDART_=cudart

  #$ _HERE_=/usr/lib/nvidia-cuda-toolkit/bin

  #$ _THERE_=/usr/lib/nvidia-cuda-toolkit/bin

  #$ _TARGET_SIZE_=

  #$ _TARGET_DIR_=

  #$ _TARGET_SIZE_=64

  #$ NVVMIR_LIBRARY_DIR=/usr/lib/nvidia-cuda-toolkit/libdevice

  #$
  PATH=/usr/lib/nvidia-cuda-toolkit/bin:/home/amx/anaconda3/bin:/usr/local/cuda-11.3/bin:/home/amx/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/home/amx/anaconda3/envs

  #$ LIBRARIES= -L/usr/lib/x86_64-linux-gnu/stubs -L/usr/lib/x86_64-linux-gnu

  #$ rm tmp/a_dlink.reg.c

  #$ gcc -D__CUDA_ARCH__=300 -E -x c++ -DCUDA_DOUBLE_MATH_FUNCTIONS
  -D__CUDACC__ -D__NVCC__ -D__CUDACC_VER_MAJOR__=10 -D__CUDACC_VER_MINOR__=1
  -D__CUDACC_VER_BUILD__=243 -include "cuda_runtime.h" -m64
  "CMakeCUDACompilerId.cu" > "tmp/CMakeCUDACompilerId.cpp1.ii"

  #$ cicc --c++14 --gnu_version=90400 --allow_managed -arch compute_30 -m64
  -ftz=0 -prec_div=1 -prec_sqrt=1 -fmad=1 --include_file_name
  "CMakeCUDACompilerId.fatbin.c" -tused -nvvmir-library
  "/usr/lib/nvidia-cuda-toolkit/libdevice/libdevice.10.bc"
  --gen_module_id_file --module_id_file_name
  "tmp/CMakeCUDACompilerId.module_id" --orig_src_file_name
  "CMakeCUDACompilerId.cu" --gen_c_file_name
  "tmp/CMakeCUDACompilerId.cudafe1.c" --stub_file_name
  "tmp/CMakeCUDACompilerId.cudafe1.stub.c" --gen_device_file_name
  "tmp/CMakeCUDACompilerId.cudafe1.gpu" "tmp/CMakeCUDACompilerId.cpp1.ii" -o
  "tmp/CMakeCUDACompilerId.ptx"

  #$ ptxas -arch=sm_30 -m64 "tmp/CMakeCUDACompilerId.ptx" -o
  "tmp/CMakeCUDACompilerId.sm_30.cubin"

  ptxas fatal : Value 'sm_30' is not defined for option 'gpu-name'

  # --error 0xff --

Call Stack (most recent call first):
  /home/amx/.local/lib/python3.9/site-packages/cmake/data/share/cmake-3.27/Modules/CMakeDetermineCompilerId.cmake:8 (CMAKE_DETERMINE_COMPILER_ID_BUILD)
  /home/amx/.local/lib/python3.9/site-packages/cmake/data/share/cmake-3.27/Modules/CMakeDetermineCompilerId.cmake:53 (__determine_compiler_id_test)
  /home/amx/.local/lib/python3.9/site-packages/cmake/data/share/cmake-3.27/Modules/CMakeDetermineCUDACompiler.cmake:307 (CMAKE_DETERMINE_COMPILER_ID)
  cmake/FindDependencies.cmake:167 (enable_language)
  CMakeLists.txt:116 (include)

 先删除colmap下的build文件夹，依次运行

apt-cache policy nvidia-cuda-toolkit
sudo apt remove nvidia-cuda-toolkit

重新运行

cd colmap
mkdir build
cd build
# 指定gpu的架构，这个61是我显卡的架构，具体需要根据自己的显卡来确定。
cmake -DCMAKE_CUDA_ARCHITECTURES=61 ..
make -j$(nproc)
sudo make install

一直到100%，成功

启动

colmap gui

别忘了anaconda文件名改回去