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add ROI support

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This commit is contained in:
marina.kolpakova 2012-11-06 01:30:20 +04:00
parent 6a3a723938
commit 157ab66ab9
4 changed files with 135 additions and 36 deletions
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4
modules/objdetect/include/opencv2/objdetect/objdetect.hpp
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@ -556,9 +556,11 @@ public:
// Param image is a frame on which detector will be applied. // Param image is a frame on which detector will be applied.
// Param rois is a vector of regions of interest. Only the objects that fall into one of the regions will be returned. // Param rois is a vector of regions of interest. Only the objects that fall into one of the regions will be returned.
// Param objects is an output array of Detections // Param objects is an output array of Detections
virtual void detect(const Mat& image, const std::vector<cv::Rect>& rois, std::vector<Detection>& objects) const; virtual void detect(InputArray image, InputArray rois, std::vector<Detection>& objects) const;
private: private:
void detectNoRoi(const Mat& image, std::vector<Detection>& objects) const;
struct Filds; struct Filds;
Filds* filds; Filds* filds;

5
modules/objdetect/perf/perf_cascadeclassifier.cpp
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@ -81,13 +81,12 @@ PERF_TEST_P(detect, SCascade,
ASSERT_TRUE(fs.isOpened()); ASSERT_TRUE(fs.isOpened());
ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
std::vector<cv::Rect> rois;
std::vector<detection_t> objectBoxes; std::vector<detection_t> objectBoxes;
cascade.detect(colored, rois, objectBoxes); cascade.detect(colored, cv::noArray(), objectBoxes);
TEST_CYCLE() TEST_CYCLE()
{ {
cascade.detect(colored, rois, objectBoxes); cascade.detect(colored, cv::noArray(), objectBoxes);
} }
vector<Rect> rects; vector<Rect> rects;

54
modules/objdetect/src/softcascade.cpp
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@ -510,16 +510,9 @@ bool cv::SCascade::load(const FileNode& fn)
return filds->fill(fn, minScale, maxScale); return filds->fill(fn, minScale, maxScale);
} }
void cv::SCascade::detect(const Mat& image, const std::vector<cv::Rect>& /*rois*/, std::vector<Detection>& objects) const void cv::SCascade::detectNoRoi(const cv::Mat& image, std::vector<Detection>& objects) const
{ {
// only color images are supperted
CV_Assert(image.type() == CV_8UC3);
Filds& fld = *filds; Filds& fld = *filds;
fld.calcLevels(image.size(), scales);
objects.clear();
// create integrals // create integrals
ChannelStorage storage(image, fld.shrinkage); ChannelStorage storage(image, fld.shrinkage);
@ -537,4 +530,49 @@ void cv::SCascade::detect(const Mat& image, const std::vector<cv::Rect>& /*rois*
} }
} }
} }
}
void cv::SCascade::detect(cv::InputArray _image, cv::InputArray _rois, std::vector<Detection>& objects) const
{
// only color images are supperted
cv::Mat image = _image.getMat();
CV_Assert(image.type() == CV_8UC3);
Filds& fld = *filds;
fld.calcLevels(image.size(), scales);
objects.clear();
if (_rois.kind() == cv::_InputArray::NONE)
return detectNoRoi(image, objects);
cv::Mat roi = _rois.getMat();
cv::Mat mask(image.rows / fld.shrinkage, image.cols / fld.shrinkage, CV_8UC1);
mask.setTo(cv::Scalar::all(0));
cv::Rect* r = roi.ptr<cv::Rect>(0);
for (int i = 0; i < (int)roi.cols; ++i)
cv::Mat(mask, cv::Rect(r[i].x / fld.shrinkage, r[i].y / fld.shrinkage, r[i].width / fld.shrinkage , r[i].height / fld.shrinkage)).setTo(cv::Scalar::all(1));
// create integrals
ChannelStorage storage(image, fld.shrinkage);
typedef std::vector<Level>::const_iterator lIt;
for (lIt it = fld.levels.begin(); it != fld.levels.end(); ++it)
{
const Level& level = *it;
for (int dy = 0; dy < level.workRect.height; ++dy)
{
uchar* m = mask.ptr<uchar>(dy);
for (int dx = 0; dx < level.workRect.width; ++dx)
{
if (m[dx])
{
storage.offset = dy * storage.step + dx;
fld.detectAt(dx, dy, level, storage, objects);
}
}
}
}
} }

108
modules/objdetect/test/test_softcascade.cpp
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@ -63,36 +63,96 @@ TEST(SCascade, detect)
cv::Mat colored = cv::imread(cvtest::TS::ptr()->get_data_path() + "cascadeandhog/bahnhof/image_00000000_0.png"); cv::Mat colored = cv::imread(cvtest::TS::ptr()->get_data_path() + "cascadeandhog/bahnhof/image_00000000_0.png");
ASSERT_FALSE(colored.empty()); ASSERT_FALSE(colored.empty());
std::vector<Detection> objects;
cascade.detect(colored, cv::noArray(), objects);
// cv::Mat out = colored.clone();
// int level = 0, total = 0;
// int levelWidth = objects[0].bb.width;
// for(int i = 0 ; i < (int)objects.size(); ++i)
// {
// if (objects[i].bb.width != levelWidth)
// {
// std::cout << "Level: " << level << " total " << total << std::endl;
// cv::imshow("out", out);
// cv::waitKey(0);
// out = colored.clone();
// levelWidth = objects[i].bb.width;
// total = 0;
// level++;
// }
// cv::rectangle(out, objects[i].bb, cv::Scalar(255, 0, 0, 255), 1);
// std::cout << "detection: " << objects[i].bb.x
// << " " << objects[i].bb.y
// << " " << objects[i].bb.width
// << " " << objects[i].bb.height << std::endl;
// total++;
// }
// std::cout << "detected: " << (int)objects.size() << std::endl;
ASSERT_EQ((int)objects.size(), 3498);
}
TEST(SCascade, detectRoi)
{
typedef cv::SCascade::Detection Detection;
std::string xml = cvtest::TS::ptr()->get_data_path() + "cascadeandhog/sc_cvpr_2012_to_opencv.xml";
cv::SCascade cascade;
cv::FileStorage fs(xml, cv::FileStorage::READ);
ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
cv::Mat colored = cv::imread(cvtest::TS::ptr()->get_data_path() + "cascadeandhog/bahnhof/image_00000000_0.png");
ASSERT_FALSE(colored.empty());
std::vector<Detection> objects; std::vector<Detection> objects;
std::vector<cv::Rect> rois; std::vector<cv::Rect> rois;
rois.push_back(cv::Rect(0, 0, 640, 480)); rois.push_back(cv::Rect(0, 0, 640, 480));
cascade.detect(colored, rois, objects); cascade.detect(colored, rois, objects);
// cv::Mat out = colored.clone();
// int level = 0, total = 0;
// int levelWidth = objects[0].bb.width;
cv::Mat out = colored.clone(); // for(int i = 0 ; i < (int)objects.size(); ++i)
int level = 0, total = 0; // {
int levelWidth = objects[0].bb.width; // if (objects[i].bb.width != levelWidth)
// {
for(int i = 0 ; i < (int)objects.size(); ++i) // std::cout << "Level: " << level << " total " << total << std::endl;
{ // cv::imshow("out", out);
if (objects[i].bb.width != levelWidth) // cv::waitKey(0);
{ // out = colored.clone();
std::cout << "Level: " << level << " total " << total << std::endl; // levelWidth = objects[i].bb.width;
cv::imshow("out", out); // total = 0;
cv::waitKey(0); // level++;
out = colored.clone(); // }
levelWidth = objects[i].bb.width; // cv::rectangle(out, objects[i].bb, cv::Scalar(255, 0, 0, 255), 1);
total = 0; // std::cout << "detection: " << objects[i].bb.x
level++; // << " " << objects[i].bb.y
} // << " " << objects[i].bb.width
cv::rectangle(out, objects[i].bb, cv::Scalar(255, 0, 0, 255), 1); // << " " << objects[i].bb.height << std::endl;
std::cout << "detection: " << objects[i].bb.x // total++;
<< " " << objects[i].bb.y // }
<< " " << objects[i].bb.width // std::cout << "detected: " << (int)objects.size() << std::endl;
<< " " << objects[i].bb.height << std::endl;
total++;
}
std::cout << "detected: " << (int)objects.size() << std::endl;
ASSERT_EQ((int)objects.size(), 3498); ASSERT_EQ((int)objects.size(), 3498);
}
TEST(SCascade, detectNoRoi)
{
typedef cv::SCascade::Detection Detection;
std::string xml = cvtest::TS::ptr()->get_data_path() + "cascadeandhog/sc_cvpr_2012_to_opencv.xml";
cv::SCascade cascade;
cv::FileStorage fs(xml, cv::FileStorage::READ);
ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
cv::Mat colored = cv::imread(cvtest::TS::ptr()->get_data_path() + "cascadeandhog/bahnhof/image_00000000_0.png");
ASSERT_FALSE(colored.empty());
std::vector<Detection> objects;
std::vector<cv::Rect> rois;
cascade.detect(colored, rois, objects);
ASSERT_EQ((int)objects.size(), 0);
} }