Reconocimiento de patrones en Android con OpenCV. Rubén Serrano

Transcripción

1 Reconocimiento de patrones en Android con OpenCV Rubén Serrano

2 1.Introducción 2.Herramientas de desarrollo 3.Proyecto 1.Código Android SDK 2.Código Android NDK 3.Código OpenCV

3 Introducción Formas de trabajar con OpenCV Java API Librerías nativas (C/C++)

4 Herramientas que vamos a utilizar hoy Eclipse Android SDK Android NDK OpenCV

5 Herramientas Compilación de OpenCV para Android Linux i Windows el Unix de la manzana El enlace anterior, y whichlight.com/blog

6 Proyecto App en el Android Market Buscar: Demo Reconocimiento Patrones Proyecto base para Eclipse Estas transparencias

7 Código Android SDK Añadir llamadas a código nativo En la clase SampleView public native long ObtainPattern(int width, int height, byte yuv[], int[] rgba); public native void FindPattern(long processor, int width, int height, byte yuv[], int[] rgba); static { System.loadLibrary("pattern_recognition"); En processframe, en el switch case MainActivity.PATTERN_RECORD: mprocessor = ObtainPattern(getFrameWidth(), getframeheight(), data, rgba); MainActivity.mProcessMode = MainActivity.VIDEO_MODE; break; case MainActivity.INSPECTION_MODE: FindPattern(mProcessor, getframewidth(), getframeheight(), data, rgba); break;

8 Código JNI / OpenCV Método ObtainPattern jbyte* _yuv = env->getbytearrayelements(yuv, 0); jint* _bgra = env->getintarrayelements(bgra, 0); Mat matgray(height, width, CV_8UC1, (unsigned char *)_yuv); Mat myuv(height + height/2, width, CV_8UC1, (unsigned char *)_yuv); Mat mbgra(height, width, CV_8UC4, (unsigned char *)_bgra); Processor* processor = new Processor(); processor->obtainpattern(matgray); drawtext(mbgra, "Patron adquirido"); return (long)processor; env->releaseintarrayelements(bgra, _bgra, 0); env->releasebytearrayelements(yuv, _yuv, 0);

9 Código OpenCV (Patrón) Constructor de Processor storage = cvcreatememstorage(0); params = cvsurfparams(500, 1); Función obtainpattern() objectkeypoints = 0; objectdescriptors = 0; cvextractsurf( &(static_cast<iplimage>(imgmat)), 0, &objectkeypoints, &objectdescriptors, storage, params );

10 Código JNI / OpenCV Método FindPattern jbyte* _yuv = env->getbytearrayelements(yuv, 0); jint* _bgra = env->getintarrayelements(bgra, 0); Mat matgray(height, width, CV_8UC1, (unsigned char *)_yuv); Mat myuv(height + height/2, width, CV_8UC1, (unsigned char *)_yuv); Mat mbgra(height, width, CV_8UC4, (unsigned char *)_bgra); //Please make attention about BGRA byte order //ARGB stored in java as int array becomes BGRA at native level cvtcolor(myuv, mbgra, CV_YUV420sp2BGR, 4); Processor* processor = (Processor*) pprocessor; processor->detectanddrawfeatures(mbgra, matgray); env->releaseintarrayelements(bgra, _bgra, 0); env->releasebytearrayelements(yuv, _yuv, 0);

11 Código OpenCV Función detectanddrawfeatures() IplImage img = greymat; int i; imagekeypoints = 0; imagedescriptors = 0; cvextractsurf( &img, 0, &imagekeypoints, &imagedescriptors, storage, params ); CvPoint src_corners[4] = {{0,0, {img.width,0, {img.width, img.height, {0, img.height; CvPoint dst_corners[4]; if( locateplanarobject( objectkeypoints, objectdescriptors, imagekeypoints, imagedescriptors, src_corners, dst_corners )) { for( i = 0; i < 4; i++ ) { CvPoint r1 = dst_corners[i%4]; CvPoint r2 = dst_corners[(i+1)%4]; line(imgmat, cvpoint(r1.x, r1.y), cvpoint(r2.x, r2.y), CV_RGB(0, 0, 0), 6, CV_AA); drawtext(imgmat, "Found ya!");

12 Código OpenCV Función locateplanarobject() double h[9]; CvMat _h = cvmat(3, 3, CV_64F, h); vector<int> ptpairs; vector<cvpoint2d32f> pt1, pt2; CvMat _pt1, _pt2; int i, n; flannfindpairs(objectdescriptors, imagedescriptors, ptpairs ); n = (int)(ptpairs.size()/2); if( n < 4 ) return 0; pt1.resize(n); pt2.resize(n); for( i = 0; i < n; i++ ) { pt1[i] = ((CvSURFPoint*)cvGetSeqElem(objectKeypoints,ptpairs[i*2]))->pt; pt2[i] = ((CvSURFPoint*)cvGetSeqElem(imageKeypoints,ptpairs[i*2+1]))->pt;

13 Código OpenCV _pt1 = cvmat(1, n, CV_32FC2, &pt1[0] ); _pt2 = cvmat(1, n, CV_32FC2, &pt2[0] ); if(!cvfindhomography( &_pt1, &_pt2, &_h, CV_RANSAC, 5 )) return 0; for( i = 0; i < 4; i++ ) { double x = src_corners[i].x, y = src_corners[i].y; double Z = 1./(h[6]*x + h[7]*y + h[8]); double X = (h[0]*x + h[1]*y + h[2])*z; double Y = (h[3]*x + h[4]*y + h[5])*z; dst_corners[i] = cvpoint(cvround(x), cvround(y)); return 1;

14 Código OpenCV Función flannfindpairs() int length = (int)(objectdescriptors->elem_size/sizeof(float)); Mat m_object(objectdescriptors->total, length, CV_32F); Mat m_image(imagedescriptors->total, length, CV_32F); // copy descriptors CvSeqReader obj_reader; float* obj_ptr = m_object.ptr<float>(0); cvstartreadseq( objectdescriptors, &obj_reader ); for(int i = 0; i < objectdescriptors->total; i++ ) { const float* descriptor = (const float*)obj_reader.ptr; CV_NEXT_SEQ_ELEM( obj_reader.seq->elem_size, obj_reader ); memcpy(obj_ptr, descriptor, length*sizeof(float)); obj_ptr += length; CvSeqReader img_reader; float* img_ptr = m_image.ptr<float>(0); cvstartreadseq( imagedescriptors, &img_reader ); for(int i = 0; i < imagedescriptors->total; i++ ) { const float* descriptor = (const float*)img_reader.ptr; CV_NEXT_SEQ_ELEM( img_reader.seq->elem_size, img_reader ); memcpy(img_ptr, descriptor, length*sizeof(float)); img_ptr += length;

15 Código OpenCV // find nearest neighbors using FLANN Mat m_indices(objectdescriptors->total, 2, CV_32S); Mat m_dists(objectdescriptors->total, 2, CV_32F); flann::index flann_index(m_image, flann::kdtreeindexparams(4)); // using 4 randomized kdtrees flann_index.knnsearch(m_object, m_indices, m_dists, 2, flann::searchparams(64) ); // maximum number of leafs checked int* indices_ptr = m_indices.ptr<int>(0); float* dists_ptr = m_dists.ptr<float>(0); for (int i=0;i<m_indices.rows;++i) { if (dists_ptr[2*i]<0.6*dists_ptr[2*i+1]) { ptpairs.push_back(i); ptpairs.push_back(indices_ptr[2*i]);

16 APM? Muchas gracias por vuestra atención!