求助：请问在android中如何用代码检测是不是ping通指定的IP地址？

Posted 2023-04-08

根据网友共享的函数，调用系统命令“ping server_ip -n -1 -w 3000"方式在Windows系统上测试可以监测到是否能ping 通指定IP，但是在android手机上始终ping不同，但是网页却可以访问

public boolean isIpReachable(String ip)

    try
    
        InetAddress addr = InetAddress.getByName(ip);
        if (addr.isReachable(3000))
        
            return true;
        
        return false;
    
    catch (UnknownHostException e)
    
    
    catch (IOException e)
    
    

参考技术A 使用http协议访问ip地址..成功返回字符串,失败为ping不通 参考技术B 手机访问网页的ip地址是随机的吧，不是固定的，好像是用不好那个的追问

没明白你的意思，手机浏览器直接输入IP+port 可以访问，但是手机上用java调用ping命令走不通，同样的代码，在电脑上运行正常。难道是Linux中不能这样调用ping?或是接收信号的接口不一样

android中如何用opencv处理倾斜校正的问题，求源代码

参考技术A #include "cv.h"
#include "highgui.h"
#include "cxcore.h"
#include "cvcam.h"
//图像的像素直接提取
#define _I(img,x,y) ((unsigned char*)((img)->imageData + (img)->widthStep*(y)))[(x)]
//亚像素级灰度值
#define _IF(image,x,y) ( ((int)(x+1)-(x))*((int)(y+1)-(y))*_I((image),(int)(x),(int)(y)) + ((int)(x+1)-(x))*((y)-(int)(y))*_I((image),(int)(x),(int)(y+1)) + ((x)-(int)(x))*((int)(y+1)-(y))*_I((image),(int)(x+1),(int)(y)) + ((x)-(int)(x))*((y)-(int)(y))*_I((image),(int)(x+1),(int)(y+1)) )//插值后的像素值(IN表示interpolation),x、y可以为小数

void callback(IplImage* image);
void main()

int ncams = cvcamGetCamerasCount( );//返回可以访问的摄像头数目
HWND mywin;
cvcamSetProperty(0, CVCAM_PROP_ENABLE, CVCAMTRUE);
cvcamSetProperty(0, CVCAM_PROP_RENDER, CVCAMTRUE);
mywin = (HWND)cvGetWindowHandle("cvcam window");
cvcamSetProperty(0, CVCAM_PROP_WINDOW, &mywin);
cvcamSetProperty(0, CVCAM_PROP_CALLBACK, callback);
//cvcamGetProperty(0, CVCAM_VIDEOFORMAT,NULL);
cvNamedWindow( "径向矫正1", 1 );//创建窗口
cvNamedWindow( "径向矫正2", 1 );//创建窗口
cvcamInit( );
cvcamStart( );
cvWaitKey(0);
cvcamStop( );
cvcamExit( );
cvDestroyWindow( "径向矫正1" );//销毁窗口
cvDestroyWindow( "径向矫正2" );//销毁窗口

void callback(IplImage* image)

IplImage* Show1 = cvCreateImage( cvSize(320,240), IPL_DEPTH_8U, 1);
IplImage* Show2 = cvCreateImage( cvSize(420,340), IPL_DEPTH_8U, 1);
IplImage* ImageC1 = cvCreateImage( cvSize(320,240), IPL_DEPTH_8U, 1);
//转换为灰度图
cvCvtColor( image, ImageC1, CV_RGB2GRAY);
cvFlip( ImageC1, NULL, 0);

double *mi;
double *md;
mi = new double[3*3];
md = new double[4];
CvMat intrinsic_matrix,distortion_coeffs;
//摄像机内参数
cvInitMatHeader(&intrinsic_matrix,3,3,CV_64FC1,mi);

//镜头畸变参数
cvInitMatHeader(&distortion_coeffs,1,4,CV_64FC1,md);
/////////////////////////////////////////////////
////////////////////////////320*240 120度广角镜头
//参数由matlab获得
double fc1,fc2,cc1,cc2,kc1,kc2,kc3,kc4;
fc1 = 667.23923/2.5;
fc2 = 669.78156/2.5;
cc1 = 429.96933/2.5;
cc2 = 351.48350/2.5;
kc1 = -0.40100;
kc2 = 0.19463;
kc3 = 0.00508;
kc4 = -0.00051;
cvmSet(&intrinsic_matrix, 0, 0, fc1);
cvmSet(&intrinsic_matrix, 0, 1, 0);
cvmSet(&intrinsic_matrix, 0, 2, cc1);
cvmSet(&intrinsic_matrix, 1, 0, 0);
cvmSet(&intrinsic_matrix, 1, 1, fc2);
cvmSet(&intrinsic_matrix, 1, 2, cc2);
cvmSet(&intrinsic_matrix, 2, 0, 0);
cvmSet(&intrinsic_matrix, 2, 1, 0);
cvmSet(&intrinsic_matrix, 2, 2, 1);
cvmSet(&distortion_coeffs, 0, 0, kc1);
cvmSet(&distortion_coeffs, 0, 1, kc2);
cvmSet(&distortion_coeffs, 0, 2, kc3);
cvmSet(&distortion_coeffs, 0, 3, kc4);
////////////////////////////320*240 120度广角镜头
/////////////////////////////////////////////////
//矫正畸变(opencv)
cvUndistort2( ImageC1, Show1, &intrinsic_matrix, &distortion_coeffs);
//矫正畸变
for (int nx=0; nx<420; nx++)

for (int ny=0; ny<340; ny++)

double x=nx-50;
double y=ny-50;
double xx=(x-cc1)/fc1;
double yy=(y-cc2)/fc2;
double r2=pow(xx,2)+pow(yy,2);
double r4=pow(r2,2);
double xxx=xx*(1+kc1*r2+kc2*r4)+2*kc3*xx*yy+kc4*(r2+2*xx*xx);
double yyy=yy*(1+kc1*r2+kc2*r4)+2*kc4*xx*yy+kc3*(r2+2*yy*yy);
double xxxx = xxx*fc1+cc1;
double yyyy = yyy*fc2+cc2;
if (xxxx>0 && xxxx<320 && yyyy>0 && yyyy<240)

_I(Show2,nx,ny) = (int)_IF(ImageC1,xxxx,yyyy);

else

_I(Show2,nx,ny) = 0;




//画线
cvLine( Show1, cvPoint(0,10), cvPoint(320,10), cvScalar(255,255,255),3 );
cvLine( Show1, cvPoint(0,230), cvPoint(320,230), cvScalar(255,255,255),3 );
cvLine( Show1, cvPoint(10,0), cvPoint(10,240), cvScalar(255,255,255),3 );
cvLine( Show1, cvPoint(310,0), cvPoint(310,240), cvScalar(255,255,255),3 );
cvLine( Show1, cvPoint(0,0), cvPoint(320,240), cvScalar(255,255,255),3 );
cvLine( Show1, cvPoint(0,240), cvPoint(320,0), cvScalar(255,255,255),3 );
cvLine( Show1, cvPoint(0,10), cvPoint(320,10), cvScalar(0,0,0) );
cvLine( Show1, cvPoint(0,230), cvPoint(320,230), cvScalar(0,0,0) );
cvLine( Show1, cvPoint(10,0), cvPoint(10,240), cvScalar(0,0,0) );
cvLine( Show1, cvPoint(310,0), cvPoint(310,240), cvScalar(0,0,0) );
cvLine( Show1, cvPoint(0,0), cvPoint(320,240), cvScalar(0,0,0) );
cvLine( Show1, cvPoint(0,240), cvPoint(320,0), cvScalar(0,0,0) );
//显示
cvShowImage("径向矫正1", Show1);
cvShowImage("径向矫正2", Show2);
cvWaitKey(1);
cvReleaseImage( &Show1 );
cvReleaseImage( &Show2 );
cvReleaseImage( &ImageC1 );

来自: http://www.eyesourcecode.com/t/41983/1/1