remove input frame size constraints

modules/objdetect/perf/perf_cascadeclassifier.cpp

@@ -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);
 }

modules/objdetect/src/isf.cpp

@@ -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);
     }

modules/objdetect/src/softcascade.cpp

@@ -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);
 

modules/objdetect/test/test_softcascade.cpp

@@ -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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