Opencv Node Addon

Opencv 安装使用

• 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 <opencv2/core/core.hpp>
    #include <opencv2/highgui/highgui.hpp>
    #include <opencv2/imgproc/imgproc.hpp>
    #include <opencv2/features2d/features2d.hpp>
    #include <boost/filesystem.hpp>
    #include <boost/filesystem/fstream.hpp>
    #include <iostream>
    #include <fstream>
    #include <cstring>
    #include <iterator>
    #include <vector>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

安装使用Boost进行数据序列化

• 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

封装cpp程序为Node Addon

• 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": ["<!(node -e \"require('nan')\")","/usr/local/include/boost","/usr/local/include/opencv2"],"conditions": [[ "OS==\"linux\" or OS==\"freebsd\" or OS==\"openbsd\" or OS==\"solaris\" or OS==\"aix\"", {}],["OS==\"mac\"", {"libraries": ["/usr/local/lib/libboost_log_setup-mt.dylib","/usr/local/lib/libboost_log-mt.dylib","/usr/local/lib/libboost_filesystem-mt.dylib","/usr/local/lib/libboost_thread-mt.dylib","/usr/local/lib/libboost_system-mt.dylib","/usr/local/lib/libopencv_core.3.2.0.dylib","/usr/local/lib/libopencv_highgui.3.2.0.dylib","/usr/local/lib/libopencv_imgproc.3.2.0.dylib","/usr/local/lib/libopencv_features2d.3.2.0.dylib"]}]]}]
  }

• 编写node c++ 插件

#include <node.h>
#include <nan.h>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <boost/filesystem.hpp>
#include <boost/filesystem/fstream.hpp>
#include <iostream>
#include <fstream>
#include <string>
#include <iterator>
#include <vector>using namespace boost::filesystem;
namespace newfs = boost::filesystem;
using namespace v8;
using namespace std;vector<uchar> matToString(cv::Mat descriptorMat) {vector<uchar> buf;imencode(".png", descriptorMat, buf);return buf;
}vector<uchar> descriptorMat(cv::Mat image) {vector<cv::KeyPoint> keyPoint;cv::Ptr<cv::ORB> 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<Value>& 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<String>::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<uchar> descriptorString = descriptorMat(image);Local<Object> buf = Nan::NewBuffer(descriptorString.size()).ToLocalChecked();uchar* data = (uchar*) node::Buffer::Data(buf);memcpy(data, &descriptorString[0], descriptorString.size());v8::Local<v8::Object> globalObj = Nan::GetCurrentContext()->Global();v8::Local<v8::Function> bufferConstructor = v8::Local<v8::Function>::Cast(globalObj->Get(Nan::New<String>("Buffer").ToLocalChecked()));v8::Local<v8::Value> constructorArgs[3] = {buf, Nan::New<v8::Integer>((unsigned)descriptorString.size()), Nan::New<v8::Integer>(0)};v8::Local<v8::Object> actualBuffer = bufferConstructor->NewInstance(3, constructorArgs);args.GetReturnValue().Set(actualBuffer);
}int bfMatcherCompare (cv::Mat &descriptors1, cv::Mat &descriptors2) {cv::BFMatcher matcher(cv::NORM_HAMMING);vector<cv::DMatch> matches;matcher.match(descriptors1, descriptors2, matches);double max_dist = 0;double min_dist = 100;/*for (int i = 0; i < descriptors1.rows; i++){double dist = matches[i].distance;if (dist < min_dist)min_dist = dist;if (dist > max_dist)max_dist = dist;}vector<cv::DMatch> good_matches;for (int i = 0; i < descriptors1.rows; i++){if (matches[i].distance < 3 * min_dist)good_matches.push_back(matches[i]);}return good_matches.size();*/for (int i = 0; i < descriptors1.rows; i++) {double dist = matches[i].distance;if (dist < min_dist) {min_dist = dist;}if (dist > max_dist) {max_dist = dist;}}std::vector<cv::DMatch> good_matches;double good_matches_sum = 0.0;for (int i = 0; i < descriptors1.rows; i++) {double distance = matches[i].distance;if (distance <= std::max(2 * min_dist, 0.02)) {good_matches.push_back(matches[i]);good_matches_sum += distance;}}return (double) good_matches_sum / (double) good_matches.size();
}void similarity(const FunctionCallbackInfo<Value>& args) {Isolate* isolate = args.GetIsolate();Local<Object> arg1 = args[0]->ToObject();int size1 = args[1]->NumberValue();Local<Object> arg2 = args[2]->ToObject();int size2 = args[3]->NumberValue();if (args.Length() < 4) {isolate->ThrowException(Exception::TypeError(String::NewFromUtf8(isolate, "Wrong number of arguments")));return;}uchar*buffer1 = (uchar*) node::Buffer::Data(arg1);std::vector<uchar> vec1(buffer1, buffer1 +  (unsigned int) size1);cv::Mat img_decode1;img_decode1 = cv::imdecode(vec1, CV_8U);uchar*buffer2 = (uchar*) node::Buffer::Data(arg2);std::vector<uchar> vec2(buffer2, buffer2 +  (unsigned int) size2);cv::Mat img_decode2;img_decode2 = cv::imdecode(vec2, CV_8U);int similarity = bfMatcherCompare(img_decode1, img_decode2);args.GetReturnValue().Set(similarity);
}void init(Local<Object> exports, Local<Object> module) {NODE_SET_METHOD(exports, "imageFeature", imageFeature);NODE_SET_METHOD(exports, "similarity", similarity);
}NODE_MODULE(addon, init)

• 编写Js文件

const feature = require('./build/Release/feature');exports.getImageFeature = (filePath) => {return feature.imageFeature(filePath).toString('utf8');
};exports.getImageSimilarity = (descriptor1, descriptor2) => {let matBuffer1 = Buffer.from(descriptor1);let matBuffer2 = Buffer.from(descriptor2);return feature.similarity(matBuffer1, matBuffer1.length, matBuffer2, matBuffer2.length);
};

• 编译运行

node-gyp configure build
node test.js