Linux   发布时间:2022-03-31  发布网站:大佬教程  code.js-code.com
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概述

主要的步骤其他人已经写过,请参这篇:https://www.cnblogs.com/hrlnw/p/4720977.html 操作的细节请参附件的pdf:  https://files.cnblogs.com/files/ahfuzhang/opencvwithopencl4androidndk-141129030940-conversion-gate02.pdf.zip 用于测试的代码如下:

主要的步骤其他人已经写过,请参这篇:https://www.cnblogs.com/hrlnw/p/4720977.html

操作的细节请参附件的pdf:  https://files.cnblogs.com/files/ahfuzhang/opencvwithopencl4androidndk-141129030940-conversion-gate02.pdf.zip

用于测试的代码如下:

//jpg2gary.cpp
#include <inttypes.h>
#include <stdio.h>
#include <stdlib.h>
#include <String.h>
#include <sys/time.h>
#include <opencv2/core.hpp>
#include <opencv2/opencv.hpp>
#include <opencv2/core/ocl.hpp>
#include <fstream>

#ifndef P
#define P(format,...)                                                        do {                                                                          printf("%s %s %d " format "\n",__FILE__,__FUNCTION__,__LINE__,##__VA_ARGS__);                                                    fflush(stdout);                                                       } while (0);
#endif

void cpu(const char* img,int times) {
    cv::Mat image = cv::imread(img,cv::IMREAD_UNCHANGED);
    cv::Mat out;
    struct timeval start,end;
    gettimeofday(&start,null);
    for (int i = 0; i < times; i++) {
        cv::cvtColor(image,out,cv::COLOR_BGR2GRAY);
    }
    gettimeofday(&end,null);
    P("run times:%d,spend:%d ms",times,(end.tv_sec - start.tv_seC) * 1000 +
                                       (end.tv_usec - start.tv_useC) / 1000);
}

void opencl(const char* img,cv::IMREAD_UNCHANGED);
    //cv::UMat u_img = image.getUMat(cv::ACCESS_READ);
    cv::UMat u_img;
    image.copyTo(u_img);
    cv::UMat out;
    struct timeval start,null);
    for (int i = 0; i < times; i++) {
        cv::cvtColor(u_img,(end.tv_sec - start.tv_seC) * 1000 +
                                       (end.tv_usec - start.tv_useC) / 1000);
}

int init_col(){
    cv::ocl::setUSEOpenCL(true);
  if (!cv::ocl::haveOpenCL()) {
    P("OpenCL is not available...");
    return -1;
  }
  cv::ocl::Context context;
  if (!context.create(cv::ocl::Device::TYPE_GPU)) {
    P("Failed creaTing the context...");
    return -1;
  }
  std::vector<cv::ocl::PlatformInfo> platform_info;
  cv::ocl::getPlatfomsInfo(platform_info);
  for (int i = 0; i < platform_info.size(); i++) {
    cv::ocl::PlatformInfo sdk = platform_info.at(i);
    for (int j = 0; j < sdk.devicenumber(); j++) {
      cv::ocl::Device device;
      sdk.getDevice(device,j);

      std::cout << "\n\n*********************\n Device " << i + 1 << std::endl;
      std::cout << "Vendor ID: " << device.vendorID() << std::endl;
      std::cout << "Vendor name: " << device.vendorName() << std::endl;
      std::cout << "Name: " << device.name() << std::endl;
      std::cout << "Driver version: " << device.driverVersion() << std::endl;
      std::cout << "available: " << device.available() << std::endl;

      if (device.isAMD()) std::cout << "Is an AMD device" << std::endl;
      if (device.isIntel()) std::cout << "Is a Intel device" << std::endl;

      std::cout << "Global Memory size: " << device.globalMemSize()
                << std::endl;
      std::cout << "Memory cache size: " << device.globalMemCacheSize()
                << std::endl;
      std::cout << "Memory cache type: " << device.globalMemCacheType()
                << std::endl;
      std::cout << "Local Memory size: " << device.localMemSize() << std::endl;
      std::cout << "Local Memory type: " << device.localMemType() << std::endl;
      std::cout << "Max Clock frequency: " << device.maxClockFrequency()
                << std::endl;
    }
  }
  if (!cv::ocl::haveOpenCL()) {
    P("OpenCL is not available,again...");
    return -1;
  }  
  cv::ocl::Device(context.device(0));   
  return 0; 
}

int main(int argc,char* argv[]) {
    if (argc < 3) {
        printf("usage:%s <from> <cpu/opencl> [times=1]\n",argv[0]);
        return 0;
    }
    int times = 1;
    if (argc >= 4) {
        times = atoi(argv[3]);
    }
    if (strcmp(argv[2],"cpu") == 0) {
        cpu(argv[1],times);
    } else if (strcmp(argv[2],"opencl") == 0) {
        if (0!=init_col()){
            return 1;
        }
        opencl(argv[1],times);
    } else {
        P("unkNow cpu/opencl");
        return 0;
    }

    return 1;
}

  

使用Xiaomi mix 2s,高通骁龙 845, GPU Adreno 630,对一张1080*1443尺寸的@L_673_14@使用cvtColor转换RGB到灰度。
连续执行1000次:
   cpu  595ms
   OpenCL  96ms

加速6.2倍!

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