火线1394相机与OpenCV

Question

我正在尝试使用火线1394相机从OpenCV运行人脸检测演示。在这样做的时候，我得到了以下错误。

Unable to stop the stream.: Bad file descriptor
In capture ...
VIDIOC_STREAMON: Inappropriate ioctl for device
Unable to stop the stream.: Inappropriate ioctl for device

这是来自OpenCV的人脸检测演示代码

#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <cctype>
#include <iostream>
#include <iterator>
#include <stdio.h>
using namespace std;
using namespace cv;
static void help()
{
    cout << "nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.n"
            "This classifier can recognize many kinds of rigid objects, once the appropriate classifier is trained.n"
            "It's most known use is for faces.n"
            "Usage:n"
            "./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]n"
               "   [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]n"
               "   [--scale=<image scale greater or equal to 1, try 1.3 for example>]n"
               "   [--try-flip]n"
               "   [filename|camera_index]nn"
            "see facedetect.cmd for one call:n"
            "./facedetect --cascade="../../data/haarcascades/haarcascade_frontalface_alt.xml" --nested-cascade="../../data/haarcascades/haarcascade_eye.xml" --scale=1.3nn"
            "During execution:ntHit any key to quit.n"
            "tUsing OpenCV version " << CV_VERSION << "n" << endl;
}
void detectAndDraw( Mat& img, CascadeClassifier& cascade,
                    CascadeClassifier& nestedCascade,
                    double scale, bool tryflip );
string cascadeName = "../../data/lbpcascades/lbpcascade_frontalface.xml";
string nestedCascadeName = "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";
int main( int argc, const char** argv )
{
    CvCapture* capture = 0;
    Mat frame, frameCopy, image;
    const string scaleOpt = "--scale=";
    size_t scaleOptLen = scaleOpt.length();
    const string cascadeOpt = "--cascade=";
    size_t cascadeOptLen = cascadeOpt.length();
    const string nestedCascadeOpt = "--nested-cascade";
    size_t nestedCascadeOptLen = nestedCascadeOpt.length();
    const string tryFlipOpt = "--try-flip";
    size_t tryFlipOptLen = tryFlipOpt.length();
    string inputName;
    bool tryflip = false;
    help();
    CascadeClassifier cascade, nestedCascade;
    double scale = 1;
    for( int i = 1; i < argc; i++ )
    {
        cout << "Processing " << i << " " <<  argv[i] << endl;
        if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 )
        {
            cascadeName.assign( argv[i] + cascadeOptLen );
            cout << "  from which we have cascadeName= " << cascadeName << endl;
        }
        else if( nestedCascadeOpt.compare( 0, nestedCascadeOptLen, argv[i], nestedCascadeOptLen ) == 0 )
        {
            if( argv[i][nestedCascadeOpt.length()] == '=' )
                nestedCascadeName.assign( argv[i] + nestedCascadeOpt.length() + 1 );
            if( !nestedCascade.load( nestedCascadeName ) )
                cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
        }
        else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
        {
            if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale < 1 )
                scale = 1;
            cout << " from which we read scale = " << scale << endl;
        }
        else if( tryFlipOpt.compare( 0, tryFlipOptLen, argv[i], tryFlipOptLen ) == 0 )
        {
            tryflip = true;
            cout << " will try to flip image horizontally to detect assymetric objectsn";
        }
        else if( argv[i][0] == '-' )
        {
            cerr << "WARNING: Unknown option %s" << argv[i] << endl;
        }
        else
            inputName.assign( argv[i] );
    }
    if( !cascade.load( cascadeName ) )
    {
        cerr << "ERROR: Could not load classifier cascade" << endl;
        help();
        return -1;
    }
    if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '') )
    {
        capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );
        int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
        if(!capture) cout << "Capture from CAM " <<  c << " didn't work" << endl;
    }
    else if( inputName.size() )
    {
        image = imread( inputName, 1 );
        if( image.empty() )
        {
            capture = cvCaptureFromAVI( inputName.c_str() );
            if(!capture) cout << "Capture from AVI didn't work" << endl;
        }
    }
    else
    {
        image = imread( "lena.jpg", 1 );
        if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
    }
    cvNamedWindow( "result", 1 );
    if( capture )
    {
        cout << "In capture ..." << endl;
        for(;;)
        {
            IplImage* iplImg = cvQueryFrame( capture );
            frame = iplImg;
            if( frame.empty() )
                break;
            if( iplImg->origin == IPL_ORIGIN_TL )
                frame.copyTo( frameCopy );
            else
                flip( frame, frameCopy, 0 );
            detectAndDraw( frameCopy, cascade, nestedCascade, scale, tryflip );
            if( waitKey( 10 ) >= 0 )
                goto _cleanup_;
        }
        waitKey(0);
_cleanup_:
        cvReleaseCapture( &capture );
    }
    else
    {
        cout << "In image read" << endl;
        if( !image.empty() )
        {
            detectAndDraw( image, cascade, nestedCascade, scale, tryflip );
            waitKey(0);
        }
        else if( !inputName.empty() )
        {
            /* assume it is a text file containing the
            list of the image filenames to be processed - one per line */
            FILE* f = fopen( inputName.c_str(), "rt" );
            if( f )
            {
                char buf[1000+1];
                while( fgets( buf, 1000, f ) )
                {
                    int len = (int)strlen(buf), c;
                    while( len > 0 && isspace(buf[len-1]) )
                        len--;
                    buf[len] = '';
                    cout << "file " << buf << endl;
                    image = imread( buf, 1 );
                    if( !image.empty() )
                    {
                        detectAndDraw( image, cascade, nestedCascade, scale, tryflip );
                        c = waitKey(0);
                        if( c == 27 || c == 'q' || c == 'Q' )
                            break;
                    }
                    else
                    {
                        cerr << "Aw snap, couldn't read image " << buf << endl;
                    }
                }
                fclose(f);
            }
        }
    }
    cvDestroyWindow("result");
    return 0;
}
void detectAndDraw( Mat& img, CascadeClassifier& cascade,
                    CascadeClassifier& nestedCascade,
                    double scale, bool tryflip )
{
    int i = 0;
    double t = 0;
    vector<Rect> faces, faces2;
    const static Scalar colors[] =  { CV_RGB(0,0,255),
        CV_RGB(0,128,255),
        CV_RGB(0,255,255),
        CV_RGB(0,255,0),
        CV_RGB(255,128,0),
        CV_RGB(255,255,0),
        CV_RGB(255,0,0),
        CV_RGB(255,0,255)} ;
    Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
    cvtColor( img, gray, CV_BGR2GRAY );
    resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
    equalizeHist( smallImg, smallImg );
    t = (double)cvGetTickCount();
    cascade.detectMultiScale( smallImg, faces,
        1.1, 2, 0
        //|CV_HAAR_FIND_BIGGEST_OBJECT
        //|CV_HAAR_DO_ROUGH_SEARCH
        |CV_HAAR_SCALE_IMAGE
        ,
        Size(30, 30) );
    if( tryflip )
    {
        flip(smallImg, smallImg, 1);
        cascade.detectMultiScale( smallImg, faces2,
                                 1.1, 2, 0
                                 //|CV_HAAR_FIND_BIGGEST_OBJECT
                                 //|CV_HAAR_DO_ROUGH_SEARCH
                                 |CV_HAAR_SCALE_IMAGE
                                 ,
                                 Size(30, 30) );
        for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
        {
            faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
        }
    }
    t = (double)cvGetTickCount() - t;
    printf( "detection time = %g msn", t/((double)cvGetTickFrequency()*1000.) );
    for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
    {
        Mat smallImgROI;
        vector<Rect> nestedObjects;
        Point center;
        Scalar color = colors[i%8];
        int radius;
        double aspect_ratio = (double)r->width/r->height;
        if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )
        {
            center.x = cvRound((r->x + r->width*0.5)*scale);
            center.y = cvRound((r->y + r->height*0.5)*scale);
            radius = cvRound((r->width + r->height)*0.25*scale);
            circle( img, center, radius, color, 3, 8, 0 );
        }
        else
            rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),
                       cvPoint(cvRound((r->x + r->width-1)*scale), cvRound((r->y + r->height-1)*scale)),
                       color, 3, 8, 0);
        if( nestedCascade.empty() )
            continue;
        smallImgROI = smallImg(*r);
        nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
            1.1, 2, 0
            //|CV_HAAR_FIND_BIGGEST_OBJECT
            //|CV_HAAR_DO_ROUGH_SEARCH
            //|CV_HAAR_DO_CANNY_PRUNING
            |CV_HAAR_SCALE_IMAGE
            ,
            Size(30, 30) );
        for( vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++ )
        {
            center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);
            center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
            radius = cvRound((nr->width + nr->height)*0.25*scale);
            circle( img, center, radius, color, 3, 8, 0 );
        }
    }
    cv::imshow( "result", img );
}

我使用预先构建的OpenCV用于Tegra。视频4 Linux设备工作正常。我可以用香菜看到火线1394摄像机的视频。我无法调试这个错误。我想可能是配置错误

Answer 1

代码没有问题。Jetson TK1为火线1394提供未经测试的支持。所以有时有效，有时无效。这里也可以勾选