openCV doc

HoughLine

Gallery

src 元画像

dst 処理画像 (grayscale, Canny, HoughLine)

what process?

CUDAを使ったHough変換(直線抽出)。グレースケールとCanny変換にした後で処理をかけています。データセットは、"The PASCAL Visual Object Classes Challenge 2007"(VOC2007)で使われている訓練データとテストデータを合わせた9963枚の画像とした。実行環境PCは下記の通りです。(そこまで新しくない) ・CPU AMD Ryzan 5 1400 ・GPU NVIDIA GeForce GTX960 (CUDAコア数:1024、GPUメモリ:2GB) ・マザーボード MSI B450 GAMING PLUS MAX B450 ・メモリ DDR4 8G * 4枚 CPU と GPU でそれぞれ処理させて時間を計測してみた。・CPU 224.100992[sec] ・GPU 51.030191[sec] GPUの方がCPUより3,4倍はやいです。

cook code C++

//STANDARD
#include <iostream>
#include <algorithm>

//OPENCV
#include <opencv2/core.hpp>
#include <opencv2/core/utility.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/core/cuda.hpp>
#include <opencv2/cudawarping.hpp>
#include <opencv2/cudaimgproc.hpp>

//BOOST
#include <boost/timer/timer.hpp>
#include <boost/filesystem.hpp>
#include <boost/foreach.hpp>

namespace fs = boost::filesystem;
const int __MAG__ = 4;

cv::Mat cpu_process(std::string path){
	cv::Mat mat = cv::imread(path);
	cv::Mat bigMat;
	cv::Mat gray;
	cv::Mat canny;
	cv::Mat dst;

dst = mat.clone();
	cv::cvtColor(mat, gray, cv::COLOR_BGR2GRAY);
	cv::Canny(gray, canny, 50, 200, 3);

std::vector<cv::Vec2f> lines;

cv::HoughLines(canny, lines, 1, CV_PI/180, 200, 0, 0);

std::cout << lines.size() << std::endl;
	for(int i = 0; i < lines.size()  ;i++){
	    cv::Point pt1, pt2;

float rho = lines[i][0], theta = lines[i][1];
      double a = cos(theta), b = sin(theta);
      double x0 = a*rho, y0 = b*rho;
      pt1.x = cv::saturate_cast<int>(x0 + 1000*(-b));
      pt1.y = cv::saturate_cast<int>(y0 + 1000*(a));
      pt2.x = cv::saturate_cast<int>(x0 - 1000*(-b));
      pt2.y = cv::saturate_cast<int>(y0 - 1000*(a));

cv::line(dst, pt1, pt2, cv::Scalar(0,0,255), 3, cv::LINE_AA);
	}

mat.release();
	bigMat.release();
  gray.release();
  canny.release();

return dst;
}

cv::Mat gpu_process(std::string path){

cv::Mat mat = cv::imread(path), dst;
    std::vector<cv::Vec2f> lines;
    cv::cuda::GpuMat gpu_src, gpu_bigmat, gpu_gray, gpu_dst, d_lines;

dst = mat.clone();
    gpu_src.upload(mat);

cv::cuda::cvtColor(gpu_src, gpu_gray, cv::COLOR_BGR2GRAY);
    cv::Ptr<cv::cuda::CannyEdgeDetector> obj = 
	    cv::cuda::createCannyEdgeDetector(50, 200);

cv::Ptr<cv::cuda::HoughLinesDetector> houghObj =
      cv::cuda::createHoughLinesDetector(1, CV_PI/180, 200);

obj->detect(gpu_gray, gpu_dst);
    houghObj->detect(gpu_dst, d_lines);
    houghObj->downloadResults(d_lines, lines);

for(int i = 0; i < lines.size() ;i++){
      float rho = lines[i][0], theta = lines[i][1];
      cv::Point pt1, pt2;
      double a = cos(theta), b = sin(theta);
      double x0 = a*rho, y0 = b*rho;
      pt1.x = cv::saturate_cast<int>(x0 + 1000*(-b));
      pt1.y = cv::saturate_cast<int>(y0 + 1000*(a));
      pt2.x = cv::saturate_cast<int>(x0 - 1000*(-b));
      pt2.y = cv::saturate_cast<int>(y0 - 1000*(a));
 	    cv::line(dst, pt1, pt2, cv::Scalar(0,0,255), 3, cv::LINE_AA);
    }

gpu_dst.release();
    gpu_src.release();
    mat.release();

return dst;
}

int main(int argc, const char* argv[]){

cv::String keys = "{gpu||}";
    cv::CommandLineParser parser(argc, argv, keys);
    bool is_gpu = parser.get<bool>("gpu");

boost::timer::cpu_timer timer; // 時間計測を開始
    
	fs::path dir("../dataset/VOCdevkit/VOC2007/JPEGImages");
	cv::Mat outMat, dstMat;

int i = 0;
	BOOST_FOREACH(const fs::path& p, std::make_pair(fs::directory_iterator(dir),
                                                    fs::directory_iterator())) {
        if (!fs::is_directory(p)){
        	std::string parent_path = p.parent_path().c_str();  
        	std::string slash = "/";
        	std::string filename = p.filename().c_str();
        	std::string full_path = parent_path + slash + filename;
        	std::cout << full_path << std::endl;

if(is_gpu){
	        	    outMat = gpu_process(full_path);
			}else{
	        	    outMat = cpu_process(full_path);
			}
        }
        i++;
    }

std::cout << "[file count]:" << i << std::endl;
	std::string result = timer.format(); // 結果文字列を取得する
    std::cout << result << std::endl;

cv::imwrite("output.png", dstMat);
    return 0;
}

openCV doc

HoughLine

Gallery

what process?

cook code C++

cook code Python

Reference