Q&A
あのさー...こんなに長いコードなら、せめてそのエラーがどの行で出たかくらいは突き止めてから質問してよー
閲覧有難うございます。
前回の質問から、少しずつですが開発をしています。
リアルタイム笑顔検出は、できるようになりました。
現在行おうとしていることが、リアルタイムで得た動画にエッジ検出を適応することです。
新しく加えた箇所は、以下のとおりです。
//////////////////////////////////////////////////// capture >> frame; // (2)calculate the first image derivatives using an Sobel operator Mat tmp_img, sobel_img, laplacian_img, canny_img; Sobel(frame, tmp_img, CV_32F, 1, 1); convertScaleAbs(tmp_img, sobel_img, 1, 0); // (3)calculate the Laplacian of an image Laplacian(frame, tmp_img, CV_32F, 3); convertScaleAbs(tmp_img, laplacian_img, 1, 0); // (4)implement the Canny algorithm for edge detection Canny(frame, canny_img, 50, 200); // (5)show original gray and their edge images respectively, // and quit when any key pressed imshow("Canny", canny_img); waitKey(0); //////////////////////////////////////////
下記が全体のコード文です。コード文の下に、実行した際のエラーを載せておきます。
よろしくお願いします。
C++
1#include "opencv2/objdetect.hpp" 2#include "opencv2/highgui.hpp" 3#include "opencv2/imgproc.hpp" 4#include "opencv2/opencv.hpp" 5#include "opencv2/highgui/highgui.hpp" 6#include <iostream> 7using namespace std; 8using namespace cv; 9static void help() 10{ 11cout<<"Program build!!!! "<<CV_VERSION<< "\n"<<endl; 12} 13void detectAndDraw( Mat& img, CascadeClassifier& cascade, 14 CascadeClassifier& nestedCascade, 15 double scale, bool tryflip ); 16string cascadeName; 17string nestedCascadeName; 18int main(int argc, const char** argv) 19{ 20 VideoCapture capture; 21 22 Mat frame, image; 23 string inputName; 24 bool tryflip; 25 help(); 26 CascadeClassifier cascade, nestedCascade; 27 double scale; 28 29 //////////////////////////////////////////////////// 30 上記のコードの場所 31 ////////////////////////////////////////// 32 33 cv::CommandLineParser parser(argc, argv, 34 "{help h||}{scale|1|}" 35 "{cascade|../../data/haarcascades/haarcascade_frontalface_alt.xml|}" 36 "{smile-cascade|../../data/haarcascades/haarcascade_smile.xml|}" 37 "{try-flip||}{@input||}"); 38 if (parser.has("help")) 39 { 40 help(); 41 return 0; 42 } 43 44 cascadeName = parser.get<string>("cascade"); 45 nestedCascadeName = parser.get<string>("smile-cascade"); 46 tryflip = parser.has("try-flip"); 47 inputName = parser.get<string>("@input"); 48 scale = parser.get<int>("scale"); 49 if (!parser.check()) 50 { 51 help(); 52 return 1; 53 } 54 if (scale < 1) 55 scale = 1; 56 if( !cascade.load( cascadeName ) ) 57 { 58 cerr << "ERROR: Could not load face cascade" << endl; 59 help(); 60 return -1; 61 } 62 if( !nestedCascade.load( nestedCascadeName ) ) 63 { 64 cerr << "ERROR: Could not load smile cascade" << endl; 65 help(); 66 return -1; 67 } 68 if( inputName.empty() || (isdigit(inputName[0]) && inputName.size() == 1) ) 69 { 70 int c = inputName.empty() ? 0 : inputName[0] - '0' ; 71 if(!capture.open(c)) 72 cout << "Capture from camera #" << c << " didn't work" << endl; 73 } 74 else if( inputName.size() ) 75 { 76 if(!capture.open( inputName )) 77 cout << "Could not read " << inputName << endl; 78 } 79 if( capture.isOpened() ) 80 { 81 cout << "Video capturing has been started ..." << endl; 82 cout << endl << "NOTE: Smile intensity will only be valid after a first smile has been detected" << endl; 83 while(1) 84 { 85 capture >> frame; 86 if( frame.empty() ) 87 break; 88 Mat frame1 = frame.clone(); 89 detectAndDraw( frame1, cascade, nestedCascade, scale, tryflip ); 90 char c = (char)waitKey(10); 91 if( c == 27 || c == 'q' || c == 'Q' ) 92 { 93 break; 94 } 95 } 96 } 97 else 98 { 99 cerr << "ERROR: Could not initiate capture" << endl; 100 help(); 101 return -1; 102 } 103 return 0; 104} 105void detectAndDraw( Mat& img, CascadeClassifier& cascade, 106 CascadeClassifier& nestedCascade, 107 double scale, bool tryflip) 108{ 109 vector<Rect> faces, faces2; 110 const static Scalar colors[] = 111 { 112 Scalar(255,0,0), 113 Scalar(255,128,0), 114 Scalar(255,255,0), 115 Scalar(0,255,0), 116 Scalar(0,128,255), 117 Scalar(0,255,255), 118 Scalar(0,0,255), 119 Scalar(255,0,255) 120 }; 121 Mat gray, smallImg; 122 cvtColor( img, gray, COLOR_BGR2GRAY ); 123 double fx = 1 / scale; 124 resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR ); 125 equalizeHist( smallImg, smallImg ); 126 cascade.detectMultiScale( smallImg, faces, 127 1.1, 2, 0 128 //|CASCADE_FIND_BIGGEST_OBJECT 129 //|CASCADE_DO_ROUGH_SEARCH 130 |CASCADE_SCALE_IMAGE, 131 Size(30, 30) ); 132 if( tryflip ) 133 { 134 flip(smallImg, smallImg, 1); 135 cascade.detectMultiScale( smallImg, faces2, 136 1.5, 2, 0 137 //|CASCADE_FIND_BIGGEST_OBJECT 138 //|CASCADE_DO_ROUGH_SEARCH 139 |CASCADE_SCALE_IMAGE, 140 Size(30, 30) ); 141 for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); ++r ) 142 { 143 faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height)); 144 } 145 } 146 for ( size_t i = 0; i < faces.size(); i++ ) 147 { 148 Rect r = faces[i]; 149 Mat smallImgROI; 150 vector<Rect> nestedObjects; 151 Point center; 152 Scalar color = colors[i%8]; 153 int radius; 154 int face[] = {cv::FONT_HERSHEY_SIMPLEX, cv::FONT_HERSHEY_PLAIN, cv::FONT_HERSHEY_DUPLEX, cv::FONT_HERSHEY_COMPLEX, 155 cv::FONT_HERSHEY_TRIPLEX, cv::FONT_HERSHEY_COMPLEX_SMALL, cv::FONT_HERSHEY_SCRIPT_SIMPLEX, 156 cv::FONT_HERSHEY_SCRIPT_COMPLEX, cv::FONT_ITALIC}; 157 double aspect_ratio = (double)r.width/r.height; 158 if( 0.75 < aspect_ratio && aspect_ratio < 1.3 ) 159 { 160 center.x = cvRound((r.x + r.width*0.5)*scale); 161 center.y = cvRound((r.y + r.height*0.5)*scale); 162 radius = cvRound((r.width + r.height)*0.25*scale); 163 circle( img, center, radius, color, 3, 8, 0 ); 164 165 } 166 else 167 rectangle( img, cvPoint(cvRound(r.x*scale), cvRound(r.y*scale)), 168 cvPoint(cvRound((r.x + r.width-1)*scale), cvRound((r.y + r.height-1)*scale)),color, 3, 8, 0); 169 const int half_height=cvRound((float)r.height/2); 170 r.y=r.y + half_height; 171 r.height = half_height-1; 172 smallImgROI = smallImg( r ); 173 nestedCascade.detectMultiScale( smallImgROI, nestedObjects, 174 1.1, 0, 0 175 //|CASCADE_FIND_BIGGEST_OBJECT 176 //|CASCADE_DO_ROUGH_SEARCH 177 //|CASCADE_DO_CANNY_PRUNING 178 |CASCADE_SCALE_IMAGE, 179 Size(30, 30) ); 180 // The number of detected neighbors depends on image size (and also illumination, etc.). The 181 // following steps use a floating minimum and maximum of neighbors. Intensity thus estimated will be 182 //accurate only after a first smile has been displayed by the user. 183 const int smile_neighbors = (int)nestedObjects.size(); 184 static int max_neighbors=-1; 185 static int min_neighbors=-1; 186 if (min_neighbors == -1) 187 min_neighbors = smile_neighbors; 188 max_neighbors = MAX(max_neighbors, smile_neighbors); 189 // Draw rectangle on the left side of the image reflecting smile intensity 190 float intensityZeroOne = ((float)smile_neighbors - min_neighbors) / (max_neighbors - min_neighbors + 1); 191 //(現在の笑顔-笑顔の最小値)/(笑顔の最大値 - 笑顔の最小値 + 1) 192 double rect_height = cvRound((float)img.rows* intensityZeroOne)/2; 193 char rectchar[256]; 194 char maxsmile[256]; 195 char minsmile[256]; 196 Scalar col = Scalar((float)255 * intensityZeroOne, 0, 0); 197 sprintf(rectchar, "%f", rect_height);//対応しているのはdouble型 198 sprintf(maxsmile, "%d", max_neighbors);//対応しているのはint型 199 sprintf(minsmile, "%d", min_neighbors);//対応しているのはint型 200 201 //greenline 202 line(img,Point(0,240), Point(70,240), Scalar(0,200,0), 5, CV_AA); 203 204 //上から笑顔度、笑顔度の最大値、笑顔度の最小値、現在の笑顔度 205 putText(img, "smile", cvPoint(488,30), face[2], 0.5, cvScalar(0,0,200), 1, CV_AA); 206 putText(img, "degree", cvPoint(478,50), face[2], 0.5, cvScalar(0,0,200), 1, CV_AA); 207 putText(img, "MAX", cvPoint(488,75), face[3], 0.8, cvScalar(0,0,200), 1, CV_AA); 208 putText(img, maxsmile, cvPoint(540,75), face[3], 0.8, cvScalar(0,0,200), 1, CV_AA); 209 putText(img, "MIN", cvPoint(488,95), face[3], 0.8, cvScalar(0,0,200), 1, CV_AA); 210 putText(img, minsmile, cvPoint(540,95), face[3], 0.8, cvScalar(0,0,200), 1, CV_AA); 211 //putText(img, imgrow, cvPoint(540,115), face[3], 0.8, cvScalar(0,0,200), 1, CV_AA); 212 213 if(rect_height>0) 214 { 215 rectangle(img, cvPoint(0, 235), cvPoint(img.cols/10, 240-rect_height), CV_RGB(200,0,0), CV_FILLED); 216 putText(img, "GOOD", cvPoint(535,50), face[0], 1.2, cv::Scalar(0,0,200), 2, CV_AA); 217 } 218 else 219 { 220 rectangle(img, cvPoint(0,245), cvPoint(img.cols/10,240-rect_height), CV_RGB(0,0,200), CV_FILLED); 221 putText(img, "BAD", cvPoint(535,50), face[0], 1.2, cv::Scalar(0,0,200), 2, CV_AA); 222 } 223 } 224 imshow( "result", img ); 225} 226
コンパイルは、通ります。
しかし、実行した際に以下のようなエラーを吐いてしまいます。
- OpenCV Error: Assertion failed (dims <= 2 && step[0] > 0) in locateROI, file /home/ユーザー名/Install-OpenCV/Ubuntu/OpenCV/opencv-3.3.1/modules/core/src/matrix.cpp, line 991
- terminate called after throwing an instance of 'cv::Exception'
- what(): /home/ユーザー名/Install-OpenCV/Ubuntu/OpenCV/opencv-3.3.1/modules/core/src/matrix.cpp:991: error: (-215) dims <= 2 && step[0] > 0 in function locateROI
回答2件
0
自己解決
フレーム開放をしないといけない処理なのに、フレーム開放せずに実行していた。
加えた箇所としては、以下のとおりである。
if( capture.isOpened() )
{
cout << "Video capturing has been started ..." << endl;
cout << endl << "NOTE: Smile intensity will only be valid after a first smile has been detected" << endl;
while(1)
{
capture >> frame;
if( frame.empty() )
break;
Mat frame1 = frame.clone();
detectAndDraw( frame1, cascade, nestedCascade, scale, tryflip );
// (2)calculate the first image derivatives using an Sobel operator
Mat tmp_img, sobel_img, laplacian_img, canny_img;
Sobel(frame1, tmp_img, CV_32F, 1, 1);
convertScaleAbs(tmp_img, sobel_img, 1, 0);
// (3)calculate the Laplacian of an image
Laplacian(frame1, tmp_img, CV_32F, 3);
convertScaleAbs(tmp_img, laplacian_img, 1, 0);
// (4)implement the Canny algorithm for edge detection
Canny(frame1, canny_img, 50, 200);
// (5)show original gray and their edge images respectively,
// and quit when any key pressed
imshow("Canny", canny_img);
char c = (char)waitKey(10);
if( c == 27 || c == 'q' || c == 'Q' )
{
break;
}
}
}
今回から、学んだことはカメラを使うなどUSB接続機器を使って何か処理したい場合は、フレーム開放、カメラなどの機器を開放？しているisOpened()の所に処理を書くことですね。
投稿2018/02/12 06:10
総合スコア34
あなたの回答
tips
プレビュー
