add ROI support

modules/objdetect/include/opencv2/objdetect/objdetect.hpp

@@ -556,9 +556,11 @@ public:
     // 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 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:
+    void detectNoRoi(const Mat& image, std::vector<Detection>& objects) const;
+
     struct Filds;
     Filds* filds;
 

modules/objdetect/perf/perf_cascadeclassifier.cpp

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

modules/objdetect/src/softcascade.cpp

@@ -510,16 +510,9 @@ bool cv::SCascade::load(const FileNode& fn)
     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;
-    fld.calcLevels(image.size(), scales);
-
-    objects.clear();
-
     // create integrals
     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);
+                 }
+             }
+         }
+    }
 }
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modules/objdetect/test/test_softcascade.cpp

@@ -63,36 +63,96 @@ TEST(SCascade, detect)
     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;
+
+    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<cv::Rect> rois;
     rois.push_back(cv::Rect(0, 0, 640, 480));
 
     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();
-    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;
+    // 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, 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);
 }
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