Ubuntu20.04安装Colmap

1. 安装CUDA 和CUDNN

一定要先安装CUDA和CUDNN，再安装COLMAP，否则在稠密建图时用不了CUDA。

2. 安装依赖

sudo apt-get install openjdk-8-jdk git python-dev python3-dev python-numpy python3-numpy python-six python3-six build-essential python-pip python3-pip python-virtualenv swig python-wheel python3-wheel libcurl3-dev libcupti-dev

3. github上获取colmap的最新源码

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

4. Dependencies from default Ubuntu repositories

sudo apt-get install \
    cmake \
    build-essential \
    libboost-all-dev \
    libeigen3-dev \
    libsuitesparse-dev \
    libfreeimage-dev \
    libgoogle-glog-dev \
    libgflags-dev \
    libglew-dev \
    qtbase5-dev \
    libqt5opengl5-dev

运行结果

5. 安装 Ceres Solver

5.1 安装依赖

# CMake
sudo apt-get install cmake
# google-glog + gflags
sudo apt-get install libgoogle-glog-dev libgflags-dev
# BLAS & LAPACK
sudo apt-get install libatlas-base-dev
# Eigen3
sudo apt-get install libeigen3-dev
# SuiteSparse and CXSparse (optional)
sudo apt-get install libsuitesparse-dev

在这里可能遇见无法定位libcxsparse3.1.2，解决办法见下：

//第一步，打开sources.list
sudo gedit /etc/apt/sources.list
//第二步，将下面的源粘贴到最上方sources.list
deb http://cz.archive.ubuntu.com/ubuntu trusty main universe
//第三步，更新源
sudo apt-get update
//第四步，重新输入依赖项安装命令安装依赖项
sudo apt-get install liblapack-dev libsuitesparse-dev libcxsparse3.1.2 libgflags-dev libgoogle-glog-dev libgtest-dev

5.2 然后解压ceres-solver-1.14.0.zip，进入解压后的文件，打开终端，编译安装

mkdir build
cd build
cmake ..
make -j16  //可用nproc这个命令查看cpu核心数，我的cpu核心数是8
sudo make install

运行结果图

6. 更改Anaconda3名字，记得安装colmap后改回来哈，这一步很重要不然会报错

运行结果

7. Configure and compile COLMAP

cd path/to/colmap
mkdir build
cd build
cmake ..
make
sudo make install

运行结果

8. Run COLMAP

colmap -h
colmap gui