Node Opencv Addon

摘要：安装使用下载安装包解压进入目录编译需要为系统生成，是基于的。

下载Opencv安装包: http://opencv.org/releases.html

解压进入Opencv目录

编译Opencv(需要cmake)

mkdir release
cd release
cmake -G "Unix Makefiles" .. (为Unix 系统生成Makefile，Mac OSX是基于Unix的。未安装cmake 可以通过Homebrew安装，未安装Homebrew需安装Homebrew）
make

安装Opencv

make install

安装完成的目录

/usr/local/lib (Opencv库文件)
/usr/local/include (Opencv头文件）
/usr/local/share/ (Opencv xml配置文件)

使用Opencv(C++ Version)

编写CMakeLists.txt文件

project( ORBFeatureAndCompare ) // 项目的名称
cmake_minimum_required(VERSION 2.8) // cmake的版本要求
find_package( OpenCV REQUIRED ) // 查找对应的Opencv依赖库
find_package(Boost COMPONENTS log log_setup thread filesystem system) // 查找对应的Boost依赖库(下文出现Boost的安装方法)
add_executable( ORBFeatureAndCompare ORBFeatureAndCompare )  // 指定可运行的文件
// 引入对应的依赖库文件的位置
target_link_libraries(ORBFeatureAndCompare
    ${OpenCV_LIBS}
    ${Boost_LOG_SETUP_LIBRARY}
    ${Boost_LOG_LIBRARY}
    ${Boost_FILESYSTEM_LIBRARY}
    ${Boost_THREAD_LIBRARY}
    ${Boost_SYSTEM_LIBRARY}
)

编写Opencv的cpp文件

//必要的头文件
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 

using namespace boost::filesystem;  
namespace newfs = boost::filesystem;
using namespace cv;
using namespace std;

int main () {
  ....
  return 0;
}

创建一个images(其他命名都可以)的资源文件夹

cd images
cmake ..
make
./ORBFeatureAndCompare //编译出的可执行程序

下载Boost安装包: https://dl.bintray.com/boosto...

解压进入Boost目录

编译安装Boost

./bootstrap.sh
./b2

引入Boost库进行数据序列化,同样是在CmakeList中引入文件路径, 在cpp文件中使用

依赖安装

全局安装node-gyp

本地安装nan

编写binding.gyp

{
  "targets": [
  {
    "target_name": "feature",
    "sources": [ "./src/feature.cc" ],
    "include_dirs": [
      "

编写node c++ 插件


#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 

using namespace boost::filesystem;
namespace newfs = boost::filesystem;
using namespace v8;
using namespace std;

vector matToString(cv::Mat descriptorMat) {
  vector buf;
  imencode(".png", descriptorMat, buf);
  return buf;
}

vector descriptorMat(cv::Mat image) {
  vector keyPoint;
  cv::Ptr orb = cv::ORB::create(4000, 1.2f, 8, 31, 0, 2,             cv::ORB::HARRIS_SCORE, 31, 20);
  orb->detect(image, keyPoint);
  cv::Mat descriptorMat;
  orb->compute(image, keyPoint, descriptorMat);
  return matToString(descriptorMat);
}

void imageFeature(const FunctionCallbackInfo& args) {
  Isolate* isolate = args.GetIsolate();
  if (args.Length() < 1) {
    isolate->ThrowException(Exception::TypeError(String::NewFromUtf8(isolate, "Wrong number of arguments")));
    return;
  }
  if (!args[0]->IsString()) {
    isolate->ThrowException(Exception::TypeError(String::NewFromUtf8(isolate, "Wrong arguments")));
    return;
  }
  String::Utf8Value pathValue(Local::Cast(args[0]));
  string path = string(*pathValue);
  cv::Mat image = cv::imread(path, 1);
  if (image.empty()) {
    isolate->ThrowException(Exception::TypeError(String::NewFromUtf8(isolate, "Input image error")));
    return;
  }
  vector descriptorString = descriptorMat(image);
  Local