Merge remote-tracking branch 'upstream/3.4' into merge-3.4

Author: alalek

modules/face/src/mace.cpp

@@ -204,52 +204,18 @@ struct MACEImpl CV_FINAL : MACE {
         minMaxLoc(re, &m1, &M1, 0, 0);
         double peakCorrPlaneEnergy = M1 / sqrt(sum(re)[0]);
         re -= m1;
-        double value=0;
-        double num=0;
-        int rad_1=int(floor((double)(45.0/64.0)*(double)IMGSIZE));
-        int rad_2=int(floor((double)(27.0/64.0)*(double)IMGSIZE));
-        // cache a few pow's and sqrts
-        std::vector<double> r2(IMGSIZE_2X);
-        Mat_<double> radtab(IMGSIZE_2X,IMGSIZE_2X);
-        for (int l=0; l<IMGSIZE_2X; l++) {
-            r2[l] = (l-IMGSIZE) * (l-IMGSIZE);
-        }
-        for (int l=0; l<IMGSIZE_2X; l++) {
-            for (int m=l+1; m<IMGSIZE_2X; m++) {
-                double rad = sqrt(r2[m] + r2[l]);
-                radtab(l,m) = radtab(m,l) = rad;
-            }
-        }
-        // mean of the sidelobe area:
-        for (int l=0; l<IMGSIZE_2X; l++) {
-            for (int m=0; m<IMGSIZE_2X; m++) {
-                double rad = radtab(l,m);
-                if (rad < rad_1) {
-                    if (rad > rad_2) {
-                        value += re(l,m);
-                        num++;
-                    }
-                }
-            }
-        }
-        value /= num;
-        // normalize it
-        double std2=0;
-        for (int l=0; l<IMGSIZE_2X; l++) {
-            for (int m=0; m<IMGSIZE_2X; m++) {
-                double rad = radtab(l,m);
-                if (rad < rad_1) {
-                    if (rad > rad_2) {
-                        double d = (value - re(l,m));
-                        std2 += d * d;
-                    }
-                }
-            }
-        }
-        std2 /= num;
-        std2 = sqrt(std2);
-        double sca = re(IMGSIZE, IMGSIZE);
-        double peakToSideLobeRatio = (sca - value) / std2;
+
+        // circle mask for the sidelobe area
+        Mat mask(IMGSIZE_2X, IMGSIZE_2X, CV_8U, Scalar(0));
+        int rad_1 = int(floor((double)(45.0/64.0)*(double)IMGSIZE));
+        int rad_2 = int(floor((double)(27.0/64.0)*(double)IMGSIZE));
+        circle(mask, Point(IMGSIZE,IMGSIZE), rad_1, Scalar(255), -1);
+        circle(mask, Point(IMGSIZE,IMGSIZE), rad_2, Scalar(0), -1);
+
+        Scalar mean, dev;
+        meanStdDev(re, mean, dev, mask);
+        double peak = re(IMGSIZE, IMGSIZE);
+        double peakToSideLobeRatio = (peak - mean[0]) / dev[0];
 
         return 100.0 * peakToSideLobeRatio * peakCorrPlaneEnergy;
     }

modules/face/test/test_mace.cpp

@@ -7,134 +7,62 @@
 
 namespace opencv_test { namespace {
 
-//
-// train on one person, and test against the other
-//
-#define TESTSET_NAMES testing::Values("david","dudek")
-
-const string TRACKING_DIR = "tracking";
-const string FOLDER_IMG = "data";
-
+const string FACE_DIR = "face";
+const int WINDOW_SIZE = 64;
 
 class MaceTest
 {
 public:
 
-    MaceTest(string _video, bool salt);
+    MaceTest(bool salt);
     void run();
 
 protected:
-    vector<Rect> boxes(const string &fn);
-    vector<Mat> samples(const string &name, int N,int off=0);
-    int found(const string &vid);
-
     Ptr<MACE> mace;
-
-    string video; // train
-    string vidA; // test
-
-    int nSampsTest;
-    int nSampsTrain;
-    int nStep;
     bool salt;
 };
 
-MaceTest::MaceTest(string _video, bool use_salt)
+MaceTest::MaceTest(bool use_salt)
 {
-    int Z = 64; // window size
-    mace = MACE::create(Z);
-
-    video = _video;
-    if (video=="david") { vidA="dudek"; }
-    if (video=="dudek") { vidA="david"; }
-
-    nStep = 2;
-    nSampsTest = 5;
-    nSampsTrain = 35;
+    mace = MACE::create(WINDOW_SIZE);
     salt = use_salt;
 }
 
-vector<Rect> MaceTest::boxes(const string &fn)
-{
-    std::ifstream in(fn.c_str());
-    int x,y,w,h;
-    char sep;
-    vector<Rect> _boxes;
-    while (in.good() && (in >> x >> sep >> y >> sep >> w >> sep >> h))
-    {
-        _boxes.push_back( Rect(x,y,w,h) );
-    }
-    return _boxes;
-}
-
 void MaceTest::run()
 {
-    vector<Mat> sam_train = samples(video, nSampsTrain, 0);
-    if (salt) mace->salt(video); // "owner's" salt with "two factor"
+    Rect david1 (125,66,58,56);
+    Rect david2 (132,69,73,74);
+    Rect detect (199,124,256,274);
+    string folder = cvtest::TS::ptr()->get_data_path() + FACE_DIR;
+    Mat train = imread(folder + "/david2.jpg", 0);
+    Mat tst_p = imread(folder + "/david1.jpg", 0);
+    Mat tst_n = imread(folder + "/detect.jpg", 0);
+    vector<Mat> sam_train;
+    sam_train.push_back( train(Rect(132,69,73,74)) );
+    sam_train.push_back( train(Rect(130,69,73,72)) );
+    sam_train.push_back( train(Rect(134,67,73,74)) );
+    sam_train.push_back( tst_p(Rect(125,66,58,56)) );
+    sam_train.push_back( tst_p(Rect(123,67,55,58)) );
+    sam_train.push_back( tst_p(Rect(125,65,58,60)) );
+
+    if (salt) mace->salt("it's david"); // "owner's" salt
     mace->train(sam_train);
-    int self_ok = found(video);
-    if (salt) mace->salt(vidA); // "other's" salt
-    int false_A = found(vidA);
-    ASSERT_GE(self_ok, nSampsTest/2);  // it may miss positives
-    ASSERT_EQ(false_A, 0);  // but *absolutely* no false positives allowed.
+    bool self_ok = mace->same(train(david2));
+    if (salt) mace->salt("this is a test"); // "other's" salt
+    bool false_A = mace->same(tst_n(detect));
+    ASSERT_TRUE(self_ok);
+    ASSERT_FALSE(false_A);
 }
 
-int MaceTest::found(const string &vid)
-{
-    vector<Mat> sam_test = samples(vid, nSampsTest, (1+nStep*nSampsTrain));
-    int hits = 0;
-    for (size_t i=0; i<sam_test.size(); i++)
-    {
-        hits += mace->same(sam_test[i]);
-    }
-    return hits;
-}
-
-vector<Mat> MaceTest::samples(const string &name, int N, int off)
-{
-    string folder = cvtest::TS::ptr()->get_data_path() + TRACKING_DIR + "/" + name;
-    string vid  = folder + "/" + FOLDER_IMG + "/" + name + ".webm";
-    string anno = folder + "/gt.txt";
-    vector<Rect> bb = boxes(anno);
-    int startFrame = (name=="david") ? 300 : 0;
-    VideoCapture c;
-    EXPECT_TRUE(c.open(vid));
-    vector<Mat> samps;
-    while (samps.size() < size_t(N))
-    {
-        int frameNo = startFrame + off;
-        c.set(CAP_PROP_POS_FRAMES, frameNo);
-        Mat frame;
-        c >> frame;
-        Rect r = bb[off];
-        off += nStep;
-        samps.push_back(frame(r));
-    }
-    c.release();
-    return samps;
-}
 
-//[TESTDATA]
-PARAM_TEST_CASE(MACE_, string)
+TEST(MACE_, unsalted)
 {
-    string dataset;
-    virtual void SetUp()
-    {
-        dataset = GET_PARAM(0);
-    }
-};
-
-
-TEST_P(MACE_, unsalted)
-{
-    MaceTest test(dataset, false); test.run();
+    MaceTest test(false); test.run();
 }
-TEST_P(MACE_, salted)
+TEST(MACE_, salted)
 {
-    MaceTest test(dataset, true); test.run();
+    MaceTest test(true); test.run();
 }
 
 
-INSTANTIATE_TEST_CASE_P(Face, MACE_, TESTSET_NAMES);
-
 }} // namespace

modules/ximgproc/src/l0_smooth.cpp

@@ -252,6 +252,8 @@ namespace cv
             CV_Assert(!S.empty());
             CV_Assert(S.depth() == CV_8U || S.depth() == CV_16U
             || S.depth() == CV_32F || S.depth() == CV_64F);
+            CV_Assert(lambda > 0.0);
+            CV_Assert(kappa > 1.0);
 
             dst.create(src.size(), src.type());
 

modules/xobjdetect/src/waldboost.cpp

@@ -333,7 +333,14 @@ void WaldBoost::fit(Mat& data_pos, Mat& data_neg)
 
 
         if (loss < 1e-50 || min_err > 0.5) {
-            std::cerr << "Stopping early" << std::endl;
+            std::cerr << "Stopping early. loss=" << loss << " min_err=" << min_err << std::endl;
+            weak_count_ = i + 1;
+            break;
+        }
+
+        // Avoid crashing on next Mat creation
+        if (pos <= 1) {
+            std::cerr << "Stopping early. pos=" << pos << std::endl;
             weak_count_ = i + 1;
             break;
         }