vector<VisionRecognitionResult> KITECH_ERSPViPRObjectRecognitionComp::Recognize(vector<unsigned char> image,int width,int height,int pixelBytes)
{
//PrintMessage("SUCCESS:KITECH_ERSPViPRObjectRecognitionComp::Recognize()\n");
vector<VisionRecognitionResult> _recognitionResult(0);
IplImage *cvImage = cvCreateImageHeader( cvSize(width, height), 8, pixelBytes );
cvImage->imageData = (char *)&image[0];
Evolution::Matrix<int> e_img;
Evolution::Image capture_img;
if (ImageConversion (&e_img, (BYTE *)cvImage->imageData, width, height, pixelBytes) < 0) {
return _recognitionResult;
}
capture_img.copy_matrix(e_img); //이미지를 얻음.
//특징점 추출
Evolution::ObjRecKeypointList* capture_features = new Evolution::ObjRecKeypointList ();
if (capture_features->extract (&capture_img) != Evolution::RESULT_SUCCESS) {
capture_features->remove_ref ();
return _recognitionResult;
}
//특징점들을 비교하여 사물 인식
Evolution::ObjRecQuery* query = new Evolution::ObjRecQuery ();
query->recognize (_vipr->objrecDB, capture_features);
// The image features are not needed after recognition is performed
// so we should release the resource.
capture_features->remove_ref ();
int n = query->get_num_matches ();
_recognitionResult.resize(n);
for( int i = 0 ; i < n ; i++ )
{
Evolution::ObjRecQuery::MatchInfo info[1];
query->get_match_info (i, info);
_recognitionResult[i].name = info->label;
_recognitionResult[i].point1X = (long)info->rectangle[0][0];
_recognitionResult[i].point1Y = height-(long)info->rectangle[0][1];
_recognitionResult[i].point2X = (long)info->rectangle[1][0];
_recognitionResult[i].point2Y = height-(long)info->rectangle[1][1];
_recognitionResult[i].point3X = (long)info->rectangle[2][0];
_recognitionResult[i].point3Y = height-(long)info->rectangle[2][1];
_recognitionResult[i].point4X = (long)info->rectangle[3][0];
_recognitionResult[i].point4Y = height-(long)info->rectangle[3][1];
}
query->remove_ref (); // clean-up the query object
cvReleaseImageHeader(&cvImage);
return _recognitionResult;
}
vector<VisionRecognitionResult> KITECH_HSVColorRecognitionComp::Recognize(vector<unsigned char> image,int width,int height,int pixelBytes)
{
//PrintMessage("SUCCESS:KITECH_HSVColorRecognitionComp::Recognize()");
vector<VisionRecognitionResult> _recognitionResult(0);
VisionRecognitionResult tmpResult;
IplImage *cvImage = cvCreateImageHeader( cvSize(width, height), 8, pixelBytes );
cvImage->imageData = (char *)&image[0];
IplImage *hsvImage = cvCreateImage( cvGetSize(cvImage), 8, pixelBytes );
cvCvtColor(cvImage, hsvImage, CV_BGR2HSV);
IplImage *cvMask= cvCreateImage( cvSize(width, height), IPL_DEPTH_8U, 1 );
for( unsigned int p = 0 ; p < _colorRange.size() ; p++ ) {
cvInRangeS( hsvImage,
cvScalar(_colorRange[p].min1,_colorRange[p].min2,_colorRange[p].min3,0),
cvScalar(_colorRange[p].max1,_colorRange[p].max2,_colorRange[p].max3,255),
cvMask );
CBlobLabeling blob;
blob.SetParam( cvMask, width*height/1000 );
blob.DoLabeling();
// _recognitionResult.resize(blob.m_nBlobs);
for( int i = 0 ; i < blob.m_nBlobs ; i++ ) {
tmpResult.name = _colorRange[p].name;
tmpResult.point1X = blob.m_recBlobs[i].x;
tmpResult.point1Y = blob.m_recBlobs[i].y;
tmpResult.point2X = blob.m_recBlobs[i].x + blob.m_recBlobs[i].width;
tmpResult.point2Y = blob.m_recBlobs[i].y;
tmpResult.point3X = blob.m_recBlobs[i].x + blob.m_recBlobs[i].width;
tmpResult.point3Y = blob.m_recBlobs[i].y + blob.m_recBlobs[i].height;
tmpResult.point4X = blob.m_recBlobs[i].x;
tmpResult.point4Y = blob.m_recBlobs[i].y + blob.m_recBlobs[i].height;
_recognitionResult.push_back(tmpResult);
//PrintMessage("SUCCESS:KITECH_HSVColorRecognitionComp::Recognize() -> I found %d data.(%d=%s)\n", blob.m_nBlobs, i, tmpResult.name.c_str());
}
}
//cvSaveImage("KITECH_HSVColorRecognitionComp.jpg", cvImage);
cvReleaseImage(&cvMask);
cvReleaseImage(&hsvImage);
cvReleaseImageHeader(&cvImage);
return _recognitionResult;
}
vector<VisionRecognitionResult> KitechSkinColorFaceRecognitionComp::Recognize(vector<unsigned char> image,int width,int height,int pixelBytes)
{
vector<VisionRecognitionResult> _recognitionResult(0);
IplImage *cvImage = cvCreateImageHeader( cvSize(width, height), 8, pixelBytes );
cvImage->imageData = (char *)&(image)[0];
IplImage *ycrcbImage = cvCreateImage( cvGetSize(cvImage), 8, pixelBytes );
cvCvtColor(cvImage, ycrcbImage, CV_BGR2YCrCb);
IplImage *cvMask= cvCreateImage( cvSize(width, height), IPL_DEPTH_8U, 1 );
cvInRangeS( ycrcbImage, cvScalar(0,133,77), cvScalar(255,173,127), cvMask );
CBlobLabeling blob;
blob.SetParam( cvMask, width*height/100 );
blob.DoLabeling();
_recognitionResult.resize(blob.m_nBlobs);
for( int i = 0 ; i < blob.m_nBlobs ; i++ ) {
_recognitionResult[i].name = "Face";
_recognitionResult[i].point1X = blob.m_recBlobs[i].x;
_recognitionResult[i].point1Y = blob.m_recBlobs[i].y;
_recognitionResult[i].point2X = blob.m_recBlobs[i].x + blob.m_recBlobs[i].width;
_recognitionResult[i].point2Y = blob.m_recBlobs[i].y;
_recognitionResult[i].point3X = blob.m_recBlobs[i].x + blob.m_recBlobs[i].width;
_recognitionResult[i].point3Y = blob.m_recBlobs[i].y + blob.m_recBlobs[i].height;
_recognitionResult[i].point4X = blob.m_recBlobs[i].x;
_recognitionResult[i].point4Y = blob.m_recBlobs[i].y + blob.m_recBlobs[i].height;
//PrintMessage("SUCCESS:KitechSkinColorFaceRecognitionComp::recognize() -> I found %d data.(%d=%s)\n", blob.m_nBlobs, i, _recognitionResult[i].name.c_str());
}
//cvSaveImage("KitechSkinColorFaceRecognitionComp.jpg", cvImage);
cvReleaseImage(&cvMask);
cvReleaseImage(&ycrcbImage);
cvReleaseImageHeader(&cvImage);
return _recognitionResult;
}
vector<VisionRecognitionResult> KitechSurfObjectRecognitionComp::Recognize(vector<unsigned char> image,int width,int height,int pixelBytes)
{
vector<VisionRecognitionResult> _recognitionResult(0);
IplImage *cvImage = cvCreateImageHeader( cvSize(width, height), 8, pixelBytes );
cvImage->imageData = (char *)&image[0];
IplImage *grayImage = cvCreateImage( cvGetSize(cvImage), 8, 1 );
cvCvtColor( cvImage, grayImage, CV_BGR2GRAY );
CvMemStorage *imageStorage = cvCreateMemStorage(0);
CvSeq *imageKeypoints, *imageDescriptors;
cvExtractSURF( grayImage, 0, &imageKeypoints, &imageDescriptors, imageStorage, cvSURFParams(500,1) );
CvPoint src_corners[4] = {{0,0}, {_orgWidth,0}, {_orgWidth, _orgHeight}, {0, _orgHeight}};
CvPoint dst_corners[4];
if( LocatePlanarObject( _objectKeypoints, _objectDescriptors, imageKeypoints, imageDescriptors, src_corners, dst_corners ) ) {
_recognitionResult.resize(1);
_recognitionResult[0].name = _objName;
_recognitionResult[0].point1X = dst_corners[0].x;
_recognitionResult[0].point1Y = dst_corners[0].y;
_recognitionResult[0].point2X = dst_corners[1].x;
_recognitionResult[0].point2Y = dst_corners[1].y;
_recognitionResult[0].point3X = dst_corners[2].x;
_recognitionResult[0].point3Y = dst_corners[2].y;
_recognitionResult[0].point4X = dst_corners[3].x;
_recognitionResult[0].point4Y = dst_corners[3].y;
//PrintMessage("KitechSurfObjectRecognitionComp::recognize() -> I found data.(%s)\n", _recognitionResult[0].name.c_str());
}
cvReleaseMemStorage( &imageStorage );
cvReleaseImage( &grayImage );
cvReleaseImageHeader( &cvImage );
return _recognitionResult;
}
vector<VisionRecognitionResult> IPEL_Haar2FaceEyeDetectionComp::Recognize(vector<unsigned char> image,int width,int height,int pixelBytes)
{
//PrintMessage("SUCCESS:IPEL_Haar2FaceEyeDetectionComp::Recognize()\n");
vector<VisionRecognitionResult> _recognitionResult(0);
IplImage *cvImage = cvCreateImageHeader( cvSize(width, height), 8, pixelBytes );
cvImage->imageData = (char *)&image[0];
if( _storage ) cvClearMemStorage( _storage );
if( _cascade_f ) {
/* detect faces */
CvSeq *faces = cvHaarDetectObjects(cvImage, _cascade_f, _storage,
1.1, 3, CV_HAAR_DO_CANNY_PRUNING, cvSize( 30, 30 ) );
if( faces && faces->total>0) {
/* Get region of face */
int nfaces = faces->total; // faces->total값이 변한다.
_recognitionResult.resize (nfaces);
CvRect *fr = new CvRect[nfaces];
for( int i = 0; i < (faces ? nfaces : 0); i++ ) {
/* draw a rectangle */
CvRect *r = (CvRect*)cvGetSeqElem(faces, i);
memcpy(&fr[i],r,sizeof(CvRect));
//rec.type = 1;
_recognitionResult[i].name = "Face";
/*- Get Upper left rectangle corner coordinate -*/
_recognitionResult[i].point1X = (int)((r->x) + 0.5);
_recognitionResult[i].point1Y = (int)((r->y) + 0.5);
/*- Get Upper right rectangle corner coordinate -*/
_recognitionResult[i].point2X = (int)((r->x + r->width) + 0.5);
_recognitionResult[i].point2Y = (int)((r->y) + 0.5);
/*- Get Lower right rectangle corner coordinate -*/
_recognitionResult[i].point3X = (int)((r->x + r->width) + 0.5);
_recognitionResult[i].point3Y = (int)((r->y + r->height) + 0.5);
/*- Get Lower left rectangle corner coordinate -*/
_recognitionResult[i].point4X = (int)((r->x) + 0.5);
_recognitionResult[i].point4Y = (int)((r->y + r->height) + 0.5);
}
// Haar함수를 두번 수행할때 결과가 다를수 있다.
for( int i = 0; i < (faces ? nfaces : 0); i++ ) {
/* reset buffer for the next object detection */
cvClearMemStorage(_storage);
/* Set the Region of Interest: estimate the eyes' position */
cvSetImageROI(cvImage, cvRect(fr[i].x, fr[i].y + (int)(fr[i].height/5.5), fr[i].width, (int)(fr[i].height/3.0) ) );
/* detect eyes */
CvSeq* eyes = cvHaarDetectObjects(cvImage, _cascade_e, _storage,
1.15, 3, CV_HAAR_DO_CANNY_PRUNING, cvSize(25, 15));
/* draw a rectangle for each eye found */
for(int j = 0; j < (eyes ? eyes->total : 0); j++ ) {
if(j>1) break;
CvRect *er = (CvRect*) cvGetSeqElem( eyes, j );
cvRectangle(cvImage,
cvPoint(er->x, er->y),
cvPoint(er->x + er->width, er->y + er->height),
CV_RGB(255, 0, 0), 1, 8, 0);
}
cvResetImageROI(cvImage);
}
delete fr;
}
}
#if 0
if( _recognitionResult.size() ) {
for( std::vector<VisionRecognitionResult>::iterator it = _recognitionResult.begin() ; it != _recognitionResult.end() ; it++ ) {
cvLine(cvImage,
cvPoint(it->point1X,it->point1Y),
cvPoint(it->point2X,it->point2Y),
CV_RGB(0, 255, 0));
cvLine(cvImage,
cvPoint(it->point2X,it->point2Y),
cvPoint(it->point3X,it->point3Y),
CV_RGB(0, 255, 0));
cvLine(cvImage,
cvPoint(it->point3X,it->point3Y),
cvPoint(it->point4X,it->point4Y),
CV_RGB(0, 255, 0));
cvLine(cvImage,
cvPoint(it->point4X,it->point4Y),
cvPoint(it->point1X,it->point1Y),
CV_RGB(0, 255, 0));
}
}
#endif
cvReleaseImageHeader( &cvImage );
return _recognitionResult;
}
