refactor logs
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marina.kolpakova
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26af7d7389
@ -47,8 +47,8 @@
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#include <vector>
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#include <string>
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#include <iostream>
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#include <string>
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#include <cstdio>
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#include <stdarg.h>
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namespace {
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@ -61,6 +61,13 @@ char *itoa(long i, char* s, int /*dummy_radix*/)
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// used for noisy printfs
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// #define WITH_DEBUG_OUT
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#if defined WITH_DEBUG_OUT
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# define dprintf(format, ...) \
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do { printf(format, __VA_ARGS__); } while (0)
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#else
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# define dprintf(format, ...)
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#endif
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struct Octave
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{
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int index;
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@ -169,9 +176,6 @@ 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 (fabs(scaling - 1.f) < FLT_EPSILON)
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// if (scaling == 1.f)
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@ -193,9 +197,7 @@ struct CascadeIntrinsics
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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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#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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#endif
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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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}
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};
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@ -269,6 +271,7 @@ struct Decimate {
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};
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// use previous stored integrals for regression testing
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// #define USE_REFERENCE_VALUES
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struct ChannelStorage
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@ -279,14 +282,14 @@ struct ChannelStorage
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enum {HOG_BINS = 6, HOG_LUV_BINS = 10};
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ChannelStorage() {}
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ChannelStorage(cv::Mat& colored, int shr) : shrinkage(shr)
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ChannelStorage(const cv::Mat& colored, int shr) : shrinkage(shr)
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{
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hog.clear();
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Decimate<uchar> decimate(shr);
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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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char buff[33];
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cv::FileStorage imgs("/home/kellan/testInts.xml", cv::FileStorage::READ);
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for(int i = 0; i < HOG_LUV_BINS; ++i)
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{
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@ -310,10 +313,10 @@ struct ChannelStorage
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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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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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// convert to grey
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@ -353,12 +356,12 @@ struct ChannelStorage
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cv::integral(shrMag, mag, cv::noArray(), CV_32S);
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// create hog channels
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angle /= 60;
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angle /= 60.f;
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std::vector<cv::Mat> hist;
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for (int bin = 0; bin < 6; ++bin)
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for (int bin = 0; bin < HOG_BINS; ++bin)
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{
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hist.push_back(cv::Mat(colored.rows, colored.cols, CV_8UC1));
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hist.push_back(cv::Mat::zeros(saturatedMag.rows, saturatedMag.cols, CV_8UC1));
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}
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for (int y = 0; y < saturatedMag.rows; ++y)
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@ -375,7 +378,6 @@ struct ChannelStorage
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for(int i = 0; i < HOG_BINS; ++i)
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{
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cv::Mat shrunk, sum;
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decimate(hist[i], shrunk);
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cv::integral(shrunk, sum, cv::noArray(), CV_32S);
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hog.push_back(sum);
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@ -385,7 +387,6 @@ struct ChannelStorage
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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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float get(const int x, const int y, const int channel, const cv::Rect& area) const
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@ -393,26 +394,23 @@ struct ChannelStorage
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CV_Assert(channel < HOG_LUV_BINS);
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const cv::Mat m = hog[channel];
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#if defined WITH_DEBUG_OUT
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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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dprintf("feature box %d %d %d %d ", area.x, area.y, area.width, area.height);
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dprintf("get for channel %d\n", channel);
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dprintf("!! %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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dprintf("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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dprintf("at point %d %d with offset %d\n", x, y, 0);
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int a = m.ptr<int>(y + area.y)[x + area.x];
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int b = m.ptr<int>(y + area.y)[x + area.width];
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int c = m.ptr<int>(y + area.height)[x + area.width];
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int d = m.ptr<int>(y + area.height)[x + area.x];
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#if defined WITH_DEBUG_OUT
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printf(" retruved integral values: %d %d %d %d\n", a, b, c, d);
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#endif
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dprintf(" retruved integral values: %d %d %d %d\n", a, b, c, d);
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return (a - b + c - d);
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}
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};
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@ -444,12 +442,10 @@ struct cv::SoftCascade::Filds
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float scaling = CascadeIntrinsics::getFor(feature.channel, relScale);
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scaledRect = feature.rect;
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#if defined WITH_DEBUG_OUT
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printf("feature %d box %d %d %d %d\n", feature.channel, scaledRect.x, scaledRect.y,
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dprintf("feature %d box %d %d %d %d\n", feature.channel, scaledRect.x, scaledRect.y,
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scaledRect.width, scaledRect.height);
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std::cout << "rescale: " << feature.channel << " " << relScale << " " << scaling << std::endl;
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#endif
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dprintf("rescale: %d %f %f\n",feature.channel, relScale, scaling);
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float farea = (scaledRect.width - scaledRect.x) * (scaledRect.height - scaledRect.y);
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// rescale
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@ -458,14 +454,9 @@ struct cv::SoftCascade::Filds
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scaledRect.width = cvRound(relScale * scaledRect.width);
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scaledRect.height = cvRound(relScale * scaledRect.height);
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#if defined WITH_DEBUG_OUT
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printf("feature %d box %d %d %d %d\n", feature.channel, scaledRect.x, scaledRect.y,
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dprintf("feature %d box %d %d %d %d\n", feature.channel, scaledRect.x, scaledRect.y,
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scaledRect.width, scaledRect.height);
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std::cout << " new rect: " << scaledRect.x << " " << scaledRect.y
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<< " " << scaledRect.width << " " << scaledRect.height << " ";
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#endif
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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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@ -474,20 +465,14 @@ struct cv::SoftCascade::Filds
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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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#if defined WITH_DEBUG_OUT
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std::cout << " rel areas " << expected_new_area << " " << sarea << std::endl;
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#endif
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dprintf(" rel areas %f %f\n", expected_new_area, sarea);
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}
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// compensation areas rounding
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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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std::cout << "approximation " << approx << " " << threshold << " -> " << rootThreshold
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<< " " << scaling << std::endl;
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#endif
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dprintf("approximation %f %f -> %f %f\n", approx, threshold, rootThreshold, scaling);
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return rootThreshold;
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}
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@ -495,26 +480,21 @@ struct cv::SoftCascade::Filds
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void detectAt(const Level& level, const int dx, const int dy, const ChannelStorage& storage,
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std::vector<Object>& detections) const
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{
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#if defined WITH_DEBUG_OUT
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std::cout << "detect at: " << dx << " " << dy << std::endl;
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#endif
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dprintf("detect at: %d %d\n", dx, dy);
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float detectionScore = 0.f;
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const Octave& octave = *(level.octave);
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int stBegin = octave.index * octave.stages, stEnd = stBegin + octave.stages;
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#if defined WITH_DEBUG_OUT
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std::cout << " octave stages: " << stBegin << " to " << stEnd << " index " << octave.index << " "
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<< octave.scale << " level " << level.origScale << std::endl;
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#endif
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dprintf(" octave stages: %d to %d index %d %f level %f\n",
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stBegin, stEnd, octave.index, octave.scale, level.origScale);
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int st = stBegin;
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for(; st < stEnd; ++st)
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{
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#if defined WITH_DEBUG_OUT
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printf("index: %d\n", st);
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#endif
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dprintf("index: %d\n", st);
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const Stage& stage = stages[st];
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{
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@ -529,15 +509,11 @@ struct cv::SoftCascade::Filds
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float sum = storage.get(dx, dy, feature.channel, scaledRect);
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#if defined WITH_DEBUG_OUT
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printf("root feature %d %f\n",feature.channel, sum);
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#endif
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dprintf("root feature %d %f\n",feature.channel, sum);
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int next = (sum >= threshold)? 2 : 1;
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#if defined WITH_DEBUG_OUT
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printf("go: %d (%f >= %f)\n\n" ,next, sum, threshold);
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#endif
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dprintf("go: %d (%f >= %f)\n\n" ,next, sum, threshold);
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// leaves
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const Node& leaf = nodes[nId + next];
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@ -549,23 +525,24 @@ struct cv::SoftCascade::Filds
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int lShift = (next - 1) * 2 + ((sum >= threshold) ? 1 : 0);
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float impact = leaves[(st * 4) + lShift];
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#if defined WITH_DEBUG_OUT
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printf("decided: %d (%f >= %f) %d %f\n\n" ,next, sum, threshold, lShift, impact);
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#endif
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dprintf("decided: %d (%f >= %f) %d %f\n\n" ,next, sum, threshold, lShift, impact);
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detectionScore += impact;
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}
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dprintf("extracted stage:\n");
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dprintf("ct %f\n", stage.threshold);
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dprintf("computed score %f\n\n", detectionScore);
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#if defined WITH_DEBUG_OUT
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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 > 50 ) break;
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#endif
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if (detectionScore <= stage.threshold) break;
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}
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printf("x %d y %d: %d\n", dx, dy, st - stBegin);
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dprintf("x %d y %d: %d\n", dx, dy, st - stBegin);
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if (st == stEnd)
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{
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@ -793,7 +770,7 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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const Filds& fld = *filds;
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cv::Mat image1;
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cv::cvtColor(image, image1, CV_RGB2RGBA);
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cv::cvtColor(image, image1, CV_BGR2RGB);
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#if defined DEBUG_STORE_IMAGES
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cv::FileStorage fs("/home/kellan/opencvInputImage.xml", cv::FileStorage::WRITE);
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@ -812,8 +789,11 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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#endif
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cv::imshow("!!", image1);
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cv::waitKey(0);
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// create integrals
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ChannelStorage storage(image1, fld.shrinkage);
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ChannelStorage storage(image, fld.shrinkage);
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// object candidates
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std::vector<Object> detections;
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@ -826,6 +806,8 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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#if defined WITH_DEBUG_OUT
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std::cout << "================================ " << l++ << std::endl;
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#else
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(void)l;
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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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@ -834,9 +816,7 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
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{
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fld.detectAt(level, dx, dy, storage, detections);
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total++;
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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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