ubuntu下安裝運行colmap

從源碼安裝

colmap可以在主流的系統windows,mac,linux安裝

從github上獲取colmap的最新源碼

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

安裝教程如下

Linux

Recommended dependencies: CUDA.

1. 安裝依賴包

$ 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

其中openjdk是必須的，不然在之后配置文件的時候會報錯。

2. 安裝CUDA和cuDNN

這兩個是NVIDIA開發的專門用於機器學習的底層計算框架，通過軟硬件的加成達到深度學習吊打I卡的神功。
安裝的CUDA和cuDNN版本以來所選用的顯卡，可以在這里查詢。這里我們用的是GeForce 1080ti，所以對應的版本為CUDA8.0(.run版本)（這里下載）和cuDNN6.0(這里下載)。

# 安裝cuda $ wget https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run $ sudo sh cuda_8.0.61_375.26_linux.run --override --silent --toolkit # 安裝的cuda在/usr/local/cuda下面 # 安裝cdDNN $ cd /usr/local/cuda # cuDNN放在這個目錄下解壓 $ tar -xzvf cudnn-8.0-linux-x64-v6.0.tgz $ sudo cp cuda/include/cudnn.h /usr/local/cuda/include $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 $ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*

然后將將一下路徑加入環境變量：

export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64" export CUDA_HOME=/usr/local/cuda

即將上述代碼放入~/.bashrc文件保存后source ~/.bashrc

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

Install Ceres Solver:

sudo apt-get install libatlas-base-dev libsuitesparse-dev
git clone https://ceres-solver.googlesource.com/ceres-solver
cd ceres-solver
mkdir build
cd build
cmake .. -DBUILD_TESTING=OFF -DBUILD_EXAMPLES=OFF
make
sudo make install

Configure and compile COLMAP:

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

Run COLMAP:

colmap -h
colmap gui

運行colmap

數據集下載：

A number of different datasets are available for download at: https://demuc.de/colmap/datasets/