fix floating point bug
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765dea9ddf
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efd2615844
@ -169,8 +169,12 @@ struct CascadeIntrinsics
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static float getFor(int channel, float scaling)
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{
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CV_Assert(channel < 10);
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#if defined WITH_DEBUG_OUT
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printf("QQQQQQQQQQQQQQQq: %f %f\n", scaling, fabs(scaling - 1.f));
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#endif
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if ((scaling - 1.f) < FLT_EPSILON)
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if (fabs(scaling - 1.f) < FLT_EPSILON)
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// if (scaling == 1.f)
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return 1.f;
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// according to R. Benenson, M. Mathias, R. Timofte and L. Van Gool's and Dallal's papers
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@ -190,7 +194,7 @@ struct CascadeIntrinsics
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float b = B[(int)(scaling >= 1)][(int)(channel > 6)];
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#if defined WITH_DEBUG_OUT
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printf("scaling: %f %f %f %f\n", scaling, a, b, a * pow(scaling, b));
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printf("!!! scaling: %f %f %f %f\n", scaling, a, b, a * pow(scaling, b));
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#endif
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return a * pow(scaling, b);
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}
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@ -344,6 +348,47 @@ void calcHistBins(const cv::Mat& grey, cv::Mat& magIntegral, std::vector<cv::Mat
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histInts.push_back(magIntegral);
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}
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template< typename T>
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struct Decimate {
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int shrinkage;
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Decimate(const int sr) : shrinkage(sr) {}
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void operator()(const cv::Mat& in, cv::Mat& out) const
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{
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int cols = in.cols / shrinkage;
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int rows = in.rows / shrinkage;
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out.create(rows, cols, in.type());
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CV_Assert(cols * shrinkage == in.cols);
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CV_Assert(rows * shrinkage == in.rows);
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std::cout << "type: " << out.type() << std::endl;
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for (int outIdx_y = 0; outIdx_y < rows; ++outIdx_y)
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{
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T* outPtr = out.ptr<T>(outIdx_y);
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for (int outIdx_x = 0; outIdx_x < cols; ++outIdx_x)
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{
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// do desimate
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int inIdx_y = outIdx_y * shrinkage;
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int inIdx_x = outIdx_x * shrinkage;
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int sum = 0;
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for (int y = inIdx_y; y < inIdx_y + shrinkage; ++y)
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for (int x = inIdx_x; x < inIdx_x + shrinkage; ++x)
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sum += in.at<T>(y, x);
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sum /= shrinkage * shrinkage;
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outPtr[outIdx_x] = cv::saturate_cast<T>(sum);
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}
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}
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}
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};
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//#define USE_REFERENCE_VALUES
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struct ChannelStorage
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{
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std::vector<cv::Mat> hog;
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@ -358,24 +403,65 @@ struct ChannelStorage
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ChannelStorage(cv::Mat& colored, int shr) : shrinkage(shr)
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{
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hog.clear();
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cv::FileStorage fs("/home/kellan/testInts.xml", cv::FileStorage::READ);
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char buff[33];
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float scale = 1.f / shrinkage;
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for(int i = 0; i < 10; ++i)
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{
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cv::Mat channel;
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fs[std::string("channel") + itoa(i, buff, 10)] >> channel;
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Decimate<uchar> decimate(shr);
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cv::Mat shrunk, sum;
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// cv::resize(channel, shrunk, cv::Size(), scale, scale, cv::INTER_AREA);
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// cv::imshow(std::string("channel") + itoa(i, buff, 10), shrunk);
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// cv::waitKey(0);
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// cv::integral(channel, sum);
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// if (i == 1)
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// std::cout << channel << std::endl;
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hog.push_back(channel);
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#if defined USE_REFERENCE_VALUES
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cv::FileStorage imgs("/home/kellan/testInts.xml", cv::FileStorage::READ);
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#else
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// add gauss
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cv::Mat gauss;
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cv::GaussianBlur(colored, gauss, cv::Size(3,3), 0 ,0);
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// convert to luv
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cv::Mat luv;
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cv::cvtColor(colored, luv, CV_RGB2Luv);
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// split to 3 one channel matrix
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std::vector<cv::Mat> splited, luvs;
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split(luv, splited);
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// shrink and integrate
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for (int i = 0; i < (int)splited.size(); i++)
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{
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cv::Mat shrunk, sum;
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decimate(splited[i], shrunk);
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cv::integral(shrunk, sum, cv::noArray(), CV_32S);
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luvs.push_back(sum);
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}
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// exit(1);
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// calculate magnitude
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static const float magnitudeScaling = 1.f / sqrt(2);
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cv::Mat grey;
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cv::cvtColor(colored, grey, CV_RGB2GRAY);
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// channels
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cv::FileStorage imgs("/home/kellan/testImgs.xml", cv::FileStorage::READ);
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#endif
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char buff[33];
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for(int i = 0; i < 7; ++i)
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{
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cv::Mat channel, shrunk, sum;
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imgs[std::string("channel") + itoa(i, buff, 10)] >> channel;
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#if defined USE_REFERENCE_VALUES
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hog.push_back(channel);
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#else
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decimate(channel, shrunk);
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// cv::resize(channel, shrunk, cv::Size(), 1.f / shr, 1.f / shr, cv::INTER_AREA);
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cv::integral(shrunk, sum, cv::noArray(), CV_32S);
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hog.push_back(sum);
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#endif
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}
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#if !defined USE_REFERENCE_VALUES
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hog.insert(hog.end(), luvs.begin(), luvs.end());
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CV_Assert(hog.size() == 10);
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#endif
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// exit(10);
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}
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// {
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// // add gauss
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@ -427,6 +513,12 @@ struct ChannelStorage
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printf("feature box %d %d %d %d ", area.x, area.y, area.width, area.height);
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printf("get for channel %d\n", channel);
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printf("!! %d\n", m.depth());
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printf("extract feature for: [%d %d] [%d %d] [%d %d] [%d %d]\n",
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x + area.x, y + area.y, x + area.width,y + area.y, x + area.width,y + area.height,
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x + area.x, y + area.height);
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printf("at point %d %d with offset %d\n", x, y, 0);
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#endif
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int a = m.ptr<int>(y + area.y)[x + area.x];
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@ -493,7 +585,7 @@ struct cv::SoftCascade::Filds
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float sarea = (scaledRect.width - scaledRect.x) * (scaledRect.height - scaledRect.y);
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float approx = 1.f;
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if ((farea - 0.f) > FLT_EPSILON && (farea - 0.f) > FLT_EPSILON)
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if (fabs(farea - 0.f) > FLT_EPSILON && fabs(farea - 0.f) > FLT_EPSILON)
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{
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const float expected_new_area = farea * relScale * relScale;
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approx = expected_new_area / sarea;
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@ -505,7 +597,7 @@ struct cv::SoftCascade::Filds
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}
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// compensation areas rounding
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float rootThreshold = threshold / approx;/
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float rootThreshold = threshold / approx;
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rootThreshold *= scaling;
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#if defined WITH_DEBUG_OUT
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@ -583,7 +675,7 @@ struct cv::SoftCascade::Filds
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printf("extracted stage:\n");
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printf("ct %f\n", stage.threshold);
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printf("computed score %f\n\n", detectionScore);
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// if (st - stBegin > 100) break;
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if (st - stBegin > 50 ) break;
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#endif
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if (detectionScore <= stage.threshold) break;
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@ -681,7 +773,7 @@ struct cv::SoftCascade::Filds
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static const char *const SC_LEAF = "leafValues";
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// only boost supported
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// only Ada Boost supported
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std::string stageTypeStr = (string)root[SC_STAGE_TYPE];
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CV_Assert(stageTypeStr == SC_BOOST);
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@ -799,7 +891,7 @@ bool cv::SoftCascade::load( const string& filename, const float minScale, const
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return true;
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}
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#define DEBUG_STORE_IMAGES
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// #define DEBUG_STORE_IMAGES
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#define DEBUG_SHOW_RESULT
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void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::Rect>& /*rois*/,
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@ -833,7 +925,8 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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fs << "absdiff" << diff;
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fs.release();
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#if defined DEBUG_STORE_IMAGES
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#endif
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// create integrals
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ChannelStorage storage(image1, fld.shrinkage);
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@ -843,13 +936,14 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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typedef std::vector<Level>::const_iterator lIt;
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int total = 0, l = 0;
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for (lIt it = fld.levels.begin() + 26; it != fld.levels.end(); ++it)
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for (lIt it = fld.levels.begin(); it != fld.levels.end(); ++it)
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{
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const Level& level = *it;
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#if defined WITH_DEBUG_OUT
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std::cout << "================================ " << l++ << std::endl;
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#endif
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// int dx = 79; int dy = 76;
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for (int dy = 0; dy < level.workRect.height; ++dy)
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{
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for (int dx = 0; dx < level.workRect.width; ++dx)
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@ -860,22 +954,24 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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}
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// break;
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}
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break;
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}
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cv::Mat out = image.clone();
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#if defined DEBUG_SHOW_RESULT
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printf("TOTAL: %d from %d\n", (int)detections.size(),total) ;
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printf("TOTAL: %d from %d\n", (int)detections.size(),total) ;
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for(int i = 0; i < (int)detections.size(); ++i)
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{
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cv::rectangle(out, detections[i].rect, cv::Scalar(255, 0, 0, 255), 2);
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for(int i = 0; i < (int)detections.size(); ++i)
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{
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cv::rectangle(out, detections[i].rect, cv::Scalar(255, 0, 0, 255), 1);
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}
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cv::imshow("out", out);
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cv::waitKey(0);
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#endif
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std::cout << "work rect: " << level.workRect.width << " " << level.workRect.height << std::endl;
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detections.clear();
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}
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cv::imshow("out", out);
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cv::waitKey(0);
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#endif
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// std::swap(detections, objects);
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}
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