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remove input frame size constraints

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pull/137/head
marina.kolpakova 12 years ago
parent 3cb9afb4e7
commit ff8417db00
4 changed files with 45 additions and 87 deletions
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  1. 18
      modules/objdetect/perf/perf_cascadeclassifier.cpp
  2. 48
      modules/objdetect/src/isf.cpp
  3. 18
      modules/objdetect/src/softcascade.cpp
  4. 48
      modules/objdetect/test/test_softcascade.cpp

18
modules/objdetect/perf/perf_cascadeclassifier.cpp
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@ -56,6 +56,18 @@ PERF_TEST_P(ImageName_MinSize, CascadeClassifierLBPFrontalFace,
typedef std::tr1::tuple<std::string, std::string> fixture;
typedef perf::TestBaseWithParam<fixture> detect;
namespace {
typedef cv::SoftCascade::Detection detection_t;
void extractRacts(std::vector<detection_t> objectBoxes, vector<Rect> rects)
{
rects.clear();
for (int i = 0; i < (int)objectBoxes.size(); ++i)
rects.push_back(objectBoxes[i].rect);
}
}
PERF_TEST_P(detect, SoftCascade,
testing::Combine(testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png"))))
@ -76,5 +88,9 @@ PERF_TEST_P(detect, SoftCascade,
{
cascade.detectMultiScale(colored, rois, objectBoxes);
}
SANITY_CHECK(objectBoxes);
vector<Rect> rects;
extractRacts(objectBoxes, rects);
std::sort(rects.begin(), rects.end(), comparators::RectLess());
SANITY_CHECK(rects);
}

48
modules/objdetect/src/isf.cpp
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@ -44,44 +44,6 @@
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/core/core.hpp>
template<typename T>
struct Decimate {
int shrinkage;
Decimate(const int sr) : shrinkage(sr) {}
void operator()(const cv::Mat& in, cv::Mat& out) const
{
int cols = in.cols / shrinkage;
int rows = in.rows / shrinkage;
out.create(rows, cols, in.type());
CV_Assert(cols * shrinkage == in.cols);
CV_Assert(rows * shrinkage == in.rows);
for (int outIdx_y = 0; outIdx_y < rows; ++outIdx_y)
{
T* outPtr = out.ptr<T>(outIdx_y);
for (int outIdx_x = 0; outIdx_x < cols; ++outIdx_x)
{
// do desimate
int inIdx_y = outIdx_y * shrinkage;
int inIdx_x = outIdx_x * shrinkage;
int sum = 0;
for (int y = inIdx_y; y < inIdx_y + shrinkage; ++y)
for (int x = inIdx_x; x < inIdx_x + shrinkage; ++x)
sum += in.at<T>(y, x);
sum /= shrinkage * shrinkage;
outPtr[outIdx_x] = cv::saturate_cast<T>(sum);
}
}
}
};
void cv::IntegralChannels::createHogBins(const cv::Mat gray, std::vector<cv::Mat>& integrals, int bins) const
{
CV_Assert(gray.type() == CV_8UC1);
@ -89,8 +51,6 @@ void cv::IntegralChannels::createHogBins(const cv::Mat gray, std::vector<cv::Mat
int w = gray.cols;
CV_Assert(!(w % shrinkage) && !(h % shrinkage));
Decimate<uchar> decimate(shrinkage);
cv::Mat df_dx, df_dy, mag, angle;
cv::Sobel(gray, df_dx, CV_32F, 1, 0, 3, 0.125);
cv::Sobel(gray, df_dy, CV_32F, 0, 1, 3, 0.125);
@ -121,13 +81,13 @@ void cv::IntegralChannels::createHogBins(const cv::Mat gray, std::vector<cv::Mat
for(int i = 0; i < bins; ++i)
{
cv::Mat shrunk, sum;
decimate(hist[i], shrunk);
cv::resize(hist[i], shrunk, cv::Size(), 1.0 / shrinkage, 1.0 / shrinkage, CV_INTER_AREA);
cv::integral(shrunk, sum, cv::noArray(), CV_32S);
integrals.push_back(sum);
}
cv::Mat shrMag;
decimate(nmag, shrMag);
cv::resize(nmag, shrMag, cv::Size(), 1.0 / shrinkage, 1.0 / shrinkage, CV_INTER_AREA);
cv::integral(shrMag, mag, cv::noArray(), CV_32S);
integrals.push_back(mag);
}
@ -137,8 +97,6 @@ void cv::IntegralChannels::createLuvBins(const cv::Mat frame, std::vector<cv::Ma
CV_Assert(frame.type() == CV_8UC3);
CV_Assert(!(frame.cols % shrinkage) && !(frame.rows % shrinkage));
Decimate<uchar> decimate(shrinkage);
cv::Mat luv;
cv::cvtColor(frame, luv, CV_BGR2Luv);
@ -148,7 +106,7 @@ void cv::IntegralChannels::createLuvBins(const cv::Mat frame, std::vector<cv::Ma
for (size_t i = 0; i < splited.size(); ++i)
{
cv::Mat shrunk, sum;
decimate(splited[i], shrunk);
cv::resize(splited[i], shrunk, cv::Size(), 1.0 / shrinkage, 1.0 / shrinkage, CV_INTER_AREA);
cv::integral(shrunk, sum, cv::noArray(), CV_32S);
integrals.push_back(sum);
}

18
modules/objdetect/src/softcascade.cpp
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@ -396,16 +396,6 @@ struct cv::SoftCascade::Filds
if (fabs(scale - maxScale) < FLT_EPSILON) break;
scale = std::min(maxScale, expf(log(scale) + logFactor));
std::cout << "level " << sc << " scale "
<< levels[sc].origScale
<< " octeve "
<< levels[sc].octave->scale
<< " "
<< levels[sc].relScale
<< " [" << levels[sc].objSize.width
<< " " << levels[sc].objSize.height << "] ["
<< levels[sc].workRect.width << " " << levels[sc].workRect.height << "]" << std::endl;
}
}
@ -523,10 +513,7 @@ bool cv::SoftCascade::read( const cv::FileStorage& fs)
filds = new Filds;
Filds& flds = *filds;
if (!flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale)) return false;
// flds.calcLevels(FRAME_WIDTH, FRAME_HEIGHT, scales);
return true;
return flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale);
}
void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::Rect>& /*rois*/,
@ -535,9 +522,6 @@ void cv::SoftCascade::detectMultiScale(const Mat& image, const std::vector<cv::R
// only color images are supperted
CV_Assert(image.type() == CV_8UC3);
// only this window size allowed
CV_Assert(image.cols == 640 && image.rows == 480);
Filds& fld = *filds;
fld.calcLevels(image.size(), scales);

48
modules/objdetect/test/test_softcascade.cpp
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@ -68,29 +68,29 @@ TEST(SoftCascade, detect)
cascade.detectMultiScale(colored, rois, objects);
cv::Mat out = colored.clone();
int level = 0, total = 0;
int levelWidth = objects[0].rect.width;
// cv::Mat out = colored.clone();
// int level = 0, total = 0;
// int levelWidth = objects[0].rect.width;
for(int i = 0 ; i < (int)objects.size(); ++i)
{
if (objects[i].rect.width != levelWidth)
{
std::cout << "Level: " << level << " total " << total << std::endl;
cv::imshow("out", out);
cv::waitKey(0);
out = colored.clone();
levelWidth = objects[i].rect.width;
total = 0;
level++;
}
cv::rectangle(out, objects[i].rect, cv::Scalar(255, 0, 0, 255), 1);
std::cout << "detection: " << objects[i].rect.x
<< " " << objects[i].rect.y
<< " " << objects[i].rect.width
<< " " << objects[i].rect.height << std::endl;
total++;
}
std::cout << "detected: " << (int)objects.size() << std::endl;
ASSERT_EQ((int)objects.size(), 1469);
// for(int i = 0 ; i < (int)objects.size(); ++i)
// {
// if (objects[i].rect.width != levelWidth)
// {
// std::cout << "Level: " << level << " total " << total << std::endl;
// cv::imshow("out", out);
// cv::waitKey(0);
// out = colored.clone();
// levelWidth = objects[i].rect.width;
// total = 0;
// level++;
// }
// cv::rectangle(out, objects[i].rect, cv::Scalar(255, 0, 0, 255), 1);
// std::cout << "detection: " << objects[i].rect.x
// << " " << objects[i].rect.y
// << " " << objects[i].rect.width
// << " " << objects[i].rect.height << std::endl;
// total++;
// }
// std::cout << "detected: " << (int)objects.size() << std::endl;
ASSERT_EQ((int)objects.size(), 3668);
}
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