ORB_SLAM3安装和本地视频
1、找ORB_SLAM3的github链接：
UZ-SLAMLab/ORB_SLAM3: ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM (github.com)
https://github.com/UZ-SLAMLab/ORB_SLAM3
2、根据Prerequisites中的说明，安装相关库
—— C++11 or C++0x Compiler
——Pangolin
安装依赖项：
sudo apt-get install libglew-dev
sudo apt-get install cmake
sudo apt-get install ffmpeg libavcodec-dev libavutil-dev libavformat-dev libswscale-dev libavdevice-dev
sudo apt-get install libdc1394-22-dev libraw1394-dev
sudo apt-get install libjpeg-dev libpng-dev libtiff5-dev libopenexr-dev下载并安装Pangolin，安装有权限错误记得加sudo
git clone https://github.com/stevenlovegrove/Pangolin.git
cd Pangolin
mkdir build
cd build
cmake ..
cmake --build .
sudo make install
——OpenCV
参考该博主的链接：https://blog.csdn.net/s15810751918/article/details/107705387
网上有很多相关教程，记录我安装时主要的几个error
(1)安装opencv时会卡在ippicv的安装，无法继续
解决方案：下载ippicv的文件，进行本地安装
进入"/home/ubuntu/cxj/opencv/3rdparty/ippicv/ippicv.cmake"，vim打开ippicv.cmake，将原来的下载连接改成自己的ippicv文件的地址，下图为我的示例。
(2)cmake配置opencv命令： cmake -D CMAKE_BUILD_TYPE=Release ..
(3)没有/uer/local/lib/下没有pkgconfig和opencv.pc文件
解决方案：自己写一个，搜一下，有相关教程
——Eigen3(建议安装在Pangolin之前）
sudo apt-get install libeigen3-dev——DBoW2 and g2o (Included in Thirdparty folder)(ORB_SLAM3文件中自带)
进入Thirdparity编译一下就好了
——Python
sudo apt install libpython2.7-dev3、ORB_SLAM3
安装方法按照github上的来 
安装过程中可能会有error，往上翻日志，相关error会有记录
4、运行本地视频
首先上传myvideo.mp4到ORB_SLAM3/Examples/Monocular/（参考了其他博客的，放在其它文件夹应该也可以，由于时间关系没有试）
(1)在ORB_SLAM3/Examples/Monocular/新建两个文件：myvideo.cpp myvideo.yaml
myvideo.yaml为以下内容：
%YAML:1.0
#--------------------------------------------------------------------------------------------
# Camera Parameters. Adjust them!
#--------------------------------------------------------------------------------------------
Camera.type: "PinHole"
# Camera calibration and distortion parameters (OpenCV)
Camera.fx: 614.3472290039062
Camera.fy: 613.3615112304688
Camera.cx: 314.36767578125
Camera.cy: 239.8182830810547
Camera.k1: 0.0
Camera.k2: 0.0
Camera.p1: 0.0
Camera.p2: 0.0
Camera.k3: 0.0
# Camera frames per second
Camera.fps: 30.0
# Color order of the images (0: BGR, 1: RGB. It is ignored if images are grayscale)
Camera.RGB: 1
# Camera resolution
Camera.width: 1920
Camera.height: 1080
#--------------------------------------------------------------------------------------------
# ORB Parameters
#--------------------------------------------------------------------------------------------
# ORB Extractor: Number of features per image
ORBextractor.nFeatures: 1000
# ORB Extractor: Scale factor between levels in the scale pyramid
ORBextractor.scaleFactor: 1.2
# ORB Extractor: Number of levels in the scale pyramid
ORBextractor.nLevels: 8
# ORB Extractor: Fast threshold
# Image is divided in a grid. At each cell FAST are extracted imposing a minimum response.
# Firstly we impose iniThFAST. If no corners are detected we impose a lower value minThFAST
# You can lower these values if your images have low contrast
ORBextractor.iniThFAST: 20
ORBextractor.minThFAST: 7
#--------------------------------------------------------------------------------------------
# Viewer Parameters
#--------------------------------------------------------------------------------------------
Viewer.KeyFrameSize: 0.05
Viewer.KeyFrameLineWidth: 5
Viewer.GraphLineWidth: 0.9
Viewer.PointSize:2
Viewer.CameraSize: 0.08
Viewer.CameraLineWidth: 3
Viewer.ViewpointX: 0
Viewer.ViewpointY: -0.7
Viewer.ViewpointZ: -1.8
Viewer.ViewpointF: 500
myvideo.cpp为以下内容：
//需要opencv库
#include
//ORB_SLAM的系统接口
#include "System.h"
#include
//计算时间
#include
#include
using namespace std;
//
string parameterFile = "./myvideo.yaml";
string vocFile = "/home/ubuntu/cxj/ORB_SLAM3/Vocabulary/ORBvoc.bin";
//视频文件，该示例中视频文件存放在/Workspace/src/ORB_SLAM3/Examples/Monocular下
string videoFile = "./myvideo.mp4";
int main(int argc, char **argv){
//声明ORB_SLAM3系统
ORB_SLAM3::System SLAM(vocFile, parameterFile, ORB_SLAM3::System::MONOCULAR, true);
//获取视频图像
cv::VideoCapture cap(videoFile); //如果使用的是USB相机，将该参数修改成接口名称，如：0，1
//记录系统时间
auto start = chrono::system_clock::now();
while(1){
cv::Mat frame;
cap >> frame; //读取相机数据
if(frame.data == nullptr)
break;
cv::Mat frame_resized;
cv::resize(frame, frame_resized, cv::Size(960,540));//运行时显示的视频的尺寸
auto now = chrono::system_clock::now();
auto timestamp = chrono::duration_cast(now - start);
SLAM.TrackMonocular(frame_resized, double(timestamp.count())/1000.0);
cv::waitKey(30);
}
SLAM.Shutdown();
return 0;
}
注意：我的myvideo.yaml和myvideo.mp4为相对路径，vocFile为绝对路径ORBvoc.bin(参考该链接：https://github.com/darlwen/ORB_SLAM3/blob/master/Examples/Monocular/myVideo.cpp)
string parameterFile = "./myvideo.yaml";
string vocFile = "/home/ubuntu/cxj/ORB_SLAM3/Vocabulary/ORBvoc.bin";
//视频文件，该示例中视频文件存放在/Workspace/src/ORB_SLAM3/Examples/Monocular下
string videoFile = "./myvideo.mp4";(2)打开ORB_SLAM3/CMakeLists.txt文件，把下面的代码
add_executable(myvideo ./Examples/Monocular/myvideo.cpp)
target_link_libraries(myvideo ${PROJECT_NAME})
加入到Monocular examples这一段。（权限问题记得加sudo, 这段代码对应的是Exampls和Examples old文件夹里面的文件夹，放在哪个后面，最后编译生成的myvideo就在哪个文件夹下面）
(3)运行build
./build.sh
然后在Monocular文件夹下找到myvideo, 运行./myvideo
说明：博客内容只记录了当前的安装方式，可能会随着相关库的版本更新，会有error产生，因此建议读者多个参考。