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rename markDetection to addDetection
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@ -135,12 +135,9 @@ struct CascadeIntrinsics
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{
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static const float lambda = 1.099f, a = 0.89f;
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static float getFor(int channel, float scaling)
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static float getFor(bool isUp, float scaling)
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{
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CV_Assert(channel < 10);
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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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@ -156,8 +153,8 @@ struct CascadeIntrinsics
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{ 0.f, 2.f} // up
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};
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float a = A[(int)(scaling >= 1)][(int)(channel > 6)];
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float b = B[(int)(scaling >= 1)][(int)(channel > 6)];
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float a = A[(int)(scaling >= 1)][(int)(isUp)];
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float b = B[(int)(scaling >= 1)][(int)(isUp)];
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dprintf("scaling: %f %f %f %f\n", scaling, a, b, a * pow(scaling, b));
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return a * pow(scaling, b);
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@ -170,7 +167,6 @@ struct Level
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float origScale;
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float relScale;
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float shrScale; // used for marking detection
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int scaleshift;
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cv::Size workRect;
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@ -182,16 +178,16 @@ struct Level
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typedef cv::SoftCascade::Detection detection_t;
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Level(const Octave& oct, const float scale, const int shrinkage, const int w, const int h)
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: octave(&oct), origScale(scale), relScale(scale / oct.scale), shrScale (relScale / (float)shrinkage),
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: octave(&oct), origScale(scale), relScale(scale / oct.scale),
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workRect(cv::Size(cvRound(w / (float)shrinkage),cvRound(h / (float)shrinkage))),
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objSize(cv::Size(cvRound(oct.size.width * relScale), cvRound(oct.size.height * relScale)))
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{
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scaling[0] = CascadeIntrinsics::getFor(0, relScale) / (relScale * relScale);
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scaling[1] = CascadeIntrinsics::getFor(9, relScale) / (relScale * relScale);
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scaling[0] = CascadeIntrinsics::getFor(false, relScale) / (relScale * relScale);
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scaling[1] = CascadeIntrinsics::getFor(true, relScale) / (relScale * relScale);
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scaleshift = relScale * (1 << 16);
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}
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void markDetection(const int x, const int y, float confidence, std::vector<detection_t>& detections) const
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void addDetection(const int x, const int y, float confidence, std::vector<detection_t>& detections) const
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{
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int shrinkage = (*octave).shrinkage;
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cv::Rect rect(cvRound(x * shrinkage), cvRound(y * shrinkage), objSize.width, objSize.height);
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@ -345,7 +341,7 @@ struct cv::SoftCascade::Filds
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dprintf("x %d y %d: %d\n", dx, dy, st - stBegin);
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dprintf(" got %d\n", st);
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level.markDetection(dx, dy, detectionScore, detections);
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level.addDetection(dx, dy, detectionScore, detections);
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}
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octIt_t fitOctave(const float& logFactor)
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@ -400,7 +396,6 @@ struct cv::SoftCascade::Filds
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<< levels[sc].octave->scale
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<< " "
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<< levels[sc].relScale
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<< " " << levels[sc].shrScale
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<< " [" << levels[sc].objSize.width
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<< " " << levels[sc].objSize.height << "] ["
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<< levels[sc].workRect.width << " " << levels[sc].workRect.height << "]" << std::endl;
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@ -533,8 +528,6 @@ bool cv::SoftCascade::load( const string& filename, const float minScale, const
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void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::Rect>& /*rois*/,
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std::vector<Detection>& objects, const int /*rejectfactor*/) const
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{
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typedef std::vector<cv::Rect>::const_iterator RIter_t;
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// only color images are supperted
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CV_Assert(image.type() == CV_8UC3);
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@ -549,7 +542,6 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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ChannelStorage storage(image, fld.shrinkage);
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typedef std::vector<Level>::const_iterator lIt;
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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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@ -563,5 +555,4 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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}
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}
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}
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}
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