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path: root/Software/Visual_Studio/Tango.CodeGeneration/Tango.CodeGeneration.csproj
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generated by cgit v1.3.1 (git 2.54.0) at 2026-08-02 01:04:04 +0000
span class="cm"> // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "precomp.hpp" namespace cv { namespace saliency { /** * Fine Grained Saliency */ StaticSaliencyFineGrained::StaticSaliencyFineGrained() { className = "FINE_GRAINED"; } StaticSaliencyFineGrained::~StaticSaliencyFineGrained() { } bool StaticSaliencyFineGrained::computeSaliencyImpl(InputArray image, OutputArray saliencyMap ) { Mat dst(Size(image.getMat().cols, image.getMat().rows), CV_8UC1); calcIntensityChannel(image.getMat(), dst); dst.copyTo(saliencyMap); #ifdef SALIENCY_DEBUG // visualize saliency map imshow( "Saliency Map Interna", saliencyMap ); #endif return true; } void StaticSaliencyFineGrained::copyImage(Mat srcArg, Mat dstArg) { srcArg.copyTo(dstArg); } void StaticSaliencyFineGrained::calcIntensityChannel(Mat srcArg, Mat dstArg) { if(dstArg.channels() > 1) { //("Error: Destiny image must have only one channel.\n"); return; } const int numScales = 6; Mat intensityScaledOn[numScales]; Mat intensityScaledOff[numScales]; Mat gray = Mat::zeros(Size(srcArg.cols, srcArg.rows), CV_8UC1); Mat integralImage(Size(srcArg.cols + 1, srcArg.rows + 1), CV_32FC1); Mat intensity(Size(srcArg.cols, srcArg.rows), CV_8UC1); Mat intensityOn(Size(srcArg.cols, srcArg.rows), CV_8UC1); Mat intensityOff(Size(srcArg.cols, srcArg.rows), CV_8UC1); int i; int neighborhood; int neighborhoods[] = {3*4, 3*4*2, 3*4*2*2, 7*4, 7*4*2, 7*4*2*2}; for(i=0; i<numScales; i++) { intensityScaledOn[i] = Mat(Size(srcArg.cols, srcArg.rows), CV_8UC1); intensityScaledOff[i] = Mat(Size(srcArg.cols, srcArg.rows), CV_8UC1); } // Prepare the input image: put it into a grayscale image. if(srcArg.channels()==3) { cvtColor(srcArg, gray, COLOR_BGR2GRAY); } else { srcArg.copyTo(gray); } // smooth pixels at least twice, as done by Frintrop and Itti GaussianBlur( gray, gray, Size( 3, 3 ), 0, 0 ); GaussianBlur( gray, gray, Size( 3, 3 ), 0, 0 ); // Calculate integral image, only once. integral(gray, integralImage, CV_32F); for(i=0; i< numScales; i++) { neighborhood = neighborhoods[i] ; getIntensityScaled(integralImage, gray, intensityScaledOn[i], intensityScaledOff[i], neighborhood); } mixScales(intensityScaledOn, intensityOn, intensityScaledOff, intensityOff, numScales); mixOnOff(intensityOn, intensityOff, intensity); intensity.copyTo(dstArg); } void StaticSaliencyFineGrained::getIntensityScaled(Mat integralImage, Mat gray, Mat intensityScaledOn, Mat intensityScaledOff, int neighborhood) { float value, meanOn, meanOff; Point2i point; int x,y; intensityScaledOn.setTo(Scalar::all(0)); intensityScaledOff.setTo(Scalar::all(0)); for(y = 0; y < gray.rows; y++) { for(x = 0; x < gray.cols; x++) { point.x = x; point.y = y; value = getMean(integralImage, point, neighborhood, gray.at<uchar>(y, x)); meanOn = gray.at<uchar>(y, x) - value; meanOff = value - gray.at<uchar>(y, x); if(meanOn > 0) intensityScaledOn.at<uchar>(y, x) = (uchar)meanOn; else intensityScaledOn.at<uchar>(y, x) = 0; if(meanOff > 0) intensityScaledOff.at<uchar>(y, x) = (uchar)meanOff; else intensityScaledOff.at<uchar>(y, x) = 0; } } } float StaticSaliencyFineGrained::getMean(Mat srcArg, Point2i PixArg, int neighbourhood, int centerVal) { Point2i P1, P2; float value; P1.x = PixArg.x - neighbourhood + 1; P1.y = PixArg.y - neighbourhood + 1; P2.x = PixArg.x + neighbourhood + 1; P2.y = PixArg.y + neighbourhood + 1; if(P1.x < 0) P1.x = 0; else if(P1.x > srcArg.cols - 1) P1.x = srcArg.cols - 1; if(P2.x < 0) P2.x = 0; else if(P2.x > srcArg.cols - 1) P2.x = srcArg.cols - 1; if(P1.y < 0) P1.y = 0; else if(P1.y > srcArg.rows - 1) P1.y = srcArg.rows - 1; if(P2.y < 0) P2.y = 0; else if(P2.y > srcArg.rows - 1) P2.y = srcArg.rows - 1; // we use the integral image to compute fast features value = (float) ( (srcArg.at<float>(P2.y, P2.x)) + (srcArg.at<float>(P1.y, P1.x)) - (srcArg.at<float>(P2.y, P1.x)) - (srcArg.at<float>(P1.y, P2.x)) ); value = (value - centerVal)/ (( (P2.x - P1.x) * (P2.y - P1.y))-1) ; return value; } void StaticSaliencyFineGrained::mixScales(Mat *intensityScaledOn, Mat intensityOn, Mat *intensityScaledOff, Mat intensityOff, const int numScales) { int i=0, x, y; int width = intensityScaledOn[0].cols; int height = intensityScaledOn[0].rows; short int maxValOn = 0, currValOn=0; short int maxValOff = 0, currValOff=0; int maxValSumOff = 0, maxValSumOn=0; Mat mixedValuesOn(Size(width, height), CV_16UC1); Mat mixedValuesOff(Size(width, height), CV_16UC1); mixedValuesOn.setTo(Scalar::all(0)); mixedValuesOff.setTo(Scalar::all(0)); for(i=0;i<numScales;i++) { for(y=0;y<height;y++) for(x=0;x<width;x++) { currValOn = intensityScaledOn[i].at<uchar>(y, x); if(currValOn > maxValOn) maxValOn = currValOn; currValOff = intensityScaledOff[i].at<uchar>(y, x); if(currValOff > maxValOff) maxValOff = currValOff; mixedValuesOn.at<unsigned short>(y, x) += currValOn; mixedValuesOff.at<unsigned short>(y, x) += currValOff; } } for(y=0;y<height;y++) for(x=0;x<width;x++) { currValOn = mixedValuesOn.at<unsigned short>(y, x); currValOff = mixedValuesOff.at<unsigned short>(y, x); if(currValOff > maxValSumOff) maxValSumOff = currValOff; if(currValOn > maxValSumOn) maxValSumOn = currValOn; } for(y=0;y<height;y++) for(x=0;x<width;x++) { intensityOn.at<uchar>(y, x) = (uchar)(255.*((float)(mixedValuesOn.at<unsigned short>(y, x) / (float)maxValSumOn))); intensityOff.at<uchar>(y, x) = (uchar)(255.*((float)(mixedValuesOff.at<unsigned short>(y, x) / (float)maxValSumOff))); } } void StaticSaliencyFineGrained::mixOnOff(Mat intensityOn, Mat intensityOff, Mat intensityArg) { int x,y; int width = intensityOn.cols; int height= intensityOn.rows; int maxVal=0; int currValOn, currValOff, maxValSumOff, maxValSumOn; Mat intensity(Size(width, height), CV_8UC1); maxValSumOff = 0; maxValSumOn = 0; for(y=0;y<height;y++) for(x=0;x<width;x++) { currValOn = intensityOn.at<uchar>(y, x); currValOff = intensityOff.at<uchar>(y, x); if(currValOff > maxValSumOff) maxValSumOff = currValOff; if(currValOn > maxValSumOn) maxValSumOn = currValOn; } if(maxValSumOn > maxValSumOff) maxVal = maxValSumOn; else maxVal = maxValSumOff; for(y=0;y<height;y++) for(x=0;x<width;x++) { intensity.at<uchar>(y, x) = (uchar) (255. * (float) (intensityOn.at<uchar>(y, x) + intensityOff.at<uchar>(y, x)) / (float)maxVal); } intensity.copyTo(intensityArg); } } /* namespace saliency */ }/* namespace cv */
generated by cgit v1.3.1 (git 2.54.0) at 2026-08-02 01:04:04 +0000