code review fixes

apps/sft/include/sft/common.hpp

@@ -46,8 +46,10 @@
 #include <opencv2/core/core.hpp>
 #include <opencv2/softcascade/softcascade.hpp>
 
+namespace cv {using namespace scascade;}
 namespace sft
 {
+
     using cv::Mat;
     struct ICF;
 

modules/python/src2/cv2.cpp

@@ -97,6 +97,7 @@ catch (const cv::Exception &e) \
 }
 
 using namespace cv;
+typedef cv::scascade::ChannelFeatureBuilder scascade_ChannelFeatureBuilder;
 
 typedef vector<uchar> vector_uchar;
 typedef vector<int> vector_int;
@@ -125,7 +126,7 @@ typedef Ptr<DescriptorExtractor> Ptr_DescriptorExtractor;
 typedef Ptr<Feature2D> Ptr_Feature2D;
 typedef Ptr<DescriptorMatcher> Ptr_DescriptorMatcher;
 
-typedef Ptr<ChannelFeatureBuilder> Ptr_ChannelFeatureBuilder;
+typedef Ptr<cv::scascade::ChannelFeatureBuilder> Ptr_ChannelFeatureBuilder;
 
 typedef SimpleBlobDetector::Params SimpleBlobDetector_Params;
 

modules/softcascade/include/opencv2/softcascade/softcascade.hpp

@@ -45,7 +45,7 @@
 
 #include "opencv2/core/core.hpp"
 
-namespace cv {
+namespace cv { namespace scascade {
 
 // Representation of detectors result.
 struct CV_EXPORTS Detection
@@ -122,7 +122,7 @@ std::ostream& operator<<(std::ostream& out, const ChannelFeature& m);
 //             Public Interface for Integral Channel Feature.
 // ========================================================================== //
 
-class CV_EXPORTS_W ChannelFeatureBuilder : public Algorithm
+class CV_EXPORTS_W ChannelFeatureBuilder : public cv::Algorithm
 {
 public:
     virtual ~ChannelFeatureBuilder();
@@ -136,7 +136,7 @@ public:
 // ========================================================================== //
 //             Implementation of soft (stageless) cascaded detector.
 // ========================================================================== //
-class CV_EXPORTS_W SoftCascadeDetector : public Algorithm
+class CV_EXPORTS_W SoftCascadeDetector : public cv::Algorithm
 {
 public:
 
@@ -186,7 +186,7 @@ private:
 // ========================================================================== //
 //     Public Interface for singe soft (stageless) cascade octave training.
 // ========================================================================== //
-class CV_EXPORTS SoftCascadeOctave : public Algorithm
+class CV_EXPORTS SoftCascadeOctave : public cv::Algorithm
 {
 public:
     enum
@@ -211,6 +211,6 @@ public:
 
 CV_EXPORTS bool initModule_softcascade(void);
 
-}
+} }
 
 #endif
\ No newline at end of file

modules/softcascade/misc/sft.py

@@ -24,7 +24,7 @@ def convert2detections(rects, confs, crop_factor = 0.125):
 """ Create new instance of soft cascade."""
 def cascade(min_scale, max_scale, nscales, f):
     # where we use nms cv::SoftCascadeDetector::DOLLAR == 2
-    c = cv2.SoftCascadeDetector(min_scale, max_scale, nscales, 2)
+    c = cv2.scascade_SoftCascadeDetector(min_scale, max_scale, nscales, 2)
     xml = cv2.FileStorage(f, 0)
     dom = xml.getFirstTopLevelNode()
     assert c.load(dom)

modules/softcascade/perf/perf_softcascade.cpp

@@ -10,7 +10,7 @@ typedef perf::TestBaseWithParam<fixture> detect;
 
 namespace {
 
-void extractRacts(std::vector<cv::Detection> objectBoxes, std::vector<Rect>& rects)
+void extractRacts(std::vector<cv::scascade::Detection> objectBoxes, std::vector<Rect>& rects)
 {
     rects.clear();
     for (int i = 0; i < (int)objectBoxes.size(); ++i)
@@ -26,12 +26,12 @@ PERF_TEST_P(detect, SoftCascadeDetector,
     cv::Mat colored = cv::imread(getDataPath(get<1>(GetParam())));
     ASSERT_FALSE(colored.empty());
 
-    cv::SoftCascadeDetector cascade;
+    cv::scascade::SoftCascadeDetector cascade;
     cv::FileStorage fs(getDataPath(get<0>(GetParam())), cv::FileStorage::READ);
     ASSERT_TRUE(fs.isOpened());
     ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 
-    std::vector<cv::Detection> objectBoxes;
+    std::vector<cv::scascade::Detection> objectBoxes;
     cascade.detect(colored, cv::noArray(), objectBoxes);
 
     TEST_CYCLE()

modules/softcascade/src/integral_channel_builder.cpp

@@ -44,7 +44,7 @@
 
 namespace {
 
-class ICFBuilder : public cv::ChannelFeatureBuilder
+class ICFBuilder : public ChannelFeatureBuilder
 {
     virtual ~ICFBuilder() {}
     virtual cv::AlgorithmInfo* info() const;
@@ -109,29 +109,29 @@ class ICFBuilder : public cv::ChannelFeatureBuilder
 
 CV_INIT_ALGORITHM(ICFBuilder, "ChannelFeatureBuilder.ICFBuilder", );
 
-cv::ChannelFeatureBuilder::~ChannelFeatureBuilder() {}
+cv::scascade::ChannelFeatureBuilder::~ChannelFeatureBuilder() {}
 
-cv::Ptr<cv::ChannelFeatureBuilder> cv::ChannelFeatureBuilder::create()
+cv::Ptr<ChannelFeatureBuilder> ChannelFeatureBuilder::create()
 {
-    cv::Ptr<cv::ChannelFeatureBuilder> builder(new ICFBuilder());
+    cv::Ptr<ChannelFeatureBuilder> builder(new ICFBuilder());
     return builder;
 }
 
-cv::ChannelFeature::ChannelFeature(int x, int y, int w, int h, int ch)
+cv::scascade::ChannelFeature::ChannelFeature(int x, int y, int w, int h, int ch)
 : bb(cv::Rect(x, y, w, h)), channel(ch) {}
 
-bool cv::ChannelFeature::operator ==(cv::ChannelFeature b)
+bool ChannelFeature::operator ==(ChannelFeature b)
 {
     return bb == b.bb && channel == b.channel;
 }
 
-bool cv::ChannelFeature::operator !=(cv::ChannelFeature b)
+bool ChannelFeature::operator !=(ChannelFeature b)
 {
     return bb != b.bb || channel != b.channel;
 }
 
 
-float cv::ChannelFeature::operator() (const cv::Mat& integrals, const cv::Size& model) const
+float cv::scascade::ChannelFeature::operator() (const cv::Mat& integrals, const cv::Size& model) const
 {
     int step = model.width + 1;
 
@@ -148,22 +148,22 @@ float cv::ChannelFeature::operator() (const cv::Mat& integrals, const cv::Size&
     return (float)(a - b + c - d);
 }
 
-void cv::write(cv::FileStorage& fs, const string&, const cv::ChannelFeature& f)
+void cv::scascade::write(cv::FileStorage& fs, const string&, const ChannelFeature& f)
 {
     fs << "{" << "channel" << f.channel << "rect" << f.bb << "}";
 }
 
-std::ostream& cv::operator<<(std::ostream& out, const cv::ChannelFeature& m)
+std::ostream& cv::scascade::operator<<(std::ostream& out, const ChannelFeature& m)
 {
     out << m.channel << " " << m.bb;
     return out;
 }
 
-cv::ChannelFeature::~ChannelFeature(){}
+cv::scascade::ChannelFeature::~ChannelFeature(){}
 
 namespace {
 
-class ChannelFeaturePool : public cv::FeaturePool
+class ChannelFeaturePool : public FeaturePool
 {
 public:
     ChannelFeaturePool(cv::Size m, int n) : FeaturePool(), model(m)
@@ -183,7 +183,7 @@ private:
     void fill(int desired);
 
     cv::Size model;
-    std::vector<cv::ChannelFeature> pool;
+    std::vector<ChannelFeature> pool;
     enum { N_CHANNELS = 10 };
 };
 
@@ -235,7 +235,7 @@ void ChannelFeaturePool::fill(int desired)
 
         int ch = chRand(eng_ch);
 
-        cv::ChannelFeature f(x, y, w, h, ch);
+        ChannelFeature f(x, y, w, h, ch);
 
         if (std::find(pool.begin(), pool.end(),f) == pool.end())
         {
@@ -246,8 +246,8 @@ void ChannelFeaturePool::fill(int desired)
 
 }
 
-cv::Ptr<cv::FeaturePool> cv::FeaturePool::create(const cv::Size& model, int nfeatures)
+cv::Ptr<FeaturePool> cv::scascade::FeaturePool::create(const cv::Size& model, int nfeatures)
 {
-    cv::Ptr<cv::FeaturePool> pool(new ChannelFeaturePool(model, nfeatures));
+    cv::Ptr<FeaturePool> pool(new ChannelFeaturePool(model, nfeatures));
     return pool;
 }

modules/softcascade/src/precomp.hpp

@@ -55,4 +55,6 @@
 #include "opencv2/ml/ml.hpp"
 #include "_random.hpp"
 
+using namespace cv::scascade;
+
 #endif

modules/softcascade/src/soft_cascade_octave.cpp

@@ -44,19 +44,17 @@
 #include <queue>
 #include <string>
 
-using cv::Dataset;
-using cv::FeaturePool;
 using cv::InputArray;
 using cv::OutputArray;
 using cv::Mat;
 
-cv::FeaturePool::~FeaturePool(){}
-cv::Dataset::~Dataset(){}
+cv::scascade::FeaturePool::~FeaturePool(){}
+cv::scascade::Dataset::~Dataset(){}
 
 namespace {
 
 
-class BoostedSoftCascadeOctave : public cv::Boost, public cv::SoftCascadeOctave
+class BoostedSoftCascadeOctave : public cv::Boost, public SoftCascadeOctave
 {
 public:
 
@@ -96,7 +94,7 @@ private:
 
     Mat trainData;
 
-    cv::Ptr<cv::ChannelFeatureBuilder> builder;
+    cv::Ptr<ChannelFeatureBuilder> builder;
 };
 
 BoostedSoftCascadeOctave::BoostedSoftCascadeOctave(cv::Rect bb, int np, int nn, int ls, int shr, int poolSize)
@@ -128,7 +126,7 @@ BoostedSoftCascadeOctave::BoostedSoftCascadeOctave(cv::Rect bb, int np, int nn,
 
     params = _params;
 
-    builder = cv::ChannelFeatureBuilder::create();
+    builder = ChannelFeatureBuilder::create();
 
     int w = boundingBox.width;
     int h = boundingBox.height;
@@ -195,7 +193,7 @@ void BoostedSoftCascadeOctave::processPositives(const Dataset* dataset)
 {
     int h = boundingBox.height;
 
-    cv::ChannelFeatureBuilder& _builder = *builder;
+    ChannelFeatureBuilder& _builder = *builder;
 
     int total = 0;
     for (int curr = 0; curr < dataset->available( Dataset::POSITIVE); ++curr)
@@ -228,7 +226,7 @@ void BoostedSoftCascadeOctave::generateNegatives(const Dataset* dataset)
     int total = 0;
     Mat sum;
 
-    cv::ChannelFeatureBuilder& _builder = *builder;
+    ChannelFeatureBuilder& _builder = *builder;
     for (int i = npositives; i < nnegatives + npositives; ++total)
     {
         int curr = iRand(idxEng);
@@ -441,12 +439,12 @@ void BoostedSoftCascadeOctave::write( CvFileStorage* fs, std::string _name) cons
 
 CV_INIT_ALGORITHM(BoostedSoftCascadeOctave, "SoftCascadeOctave.BoostedSoftCascadeOctave", );
 
-cv::SoftCascadeOctave::~SoftCascadeOctave(){}
+cv::scascade::SoftCascadeOctave::~SoftCascadeOctave(){}
 
-cv::Ptr<cv::SoftCascadeOctave> cv::SoftCascadeOctave::create(cv::Rect boundingBox, int npositives, int nnegatives,
+cv::Ptr<SoftCascadeOctave> cv::scascade::SoftCascadeOctave::create(cv::Rect boundingBox, int npositives, int nnegatives,
         int logScale, int shrinkage, int poolSize)
 {
-    cv::Ptr<cv::SoftCascadeOctave> octave(
+    cv::Ptr<SoftCascadeOctave> octave(
         new BoostedSoftCascadeOctave(boundingBox, npositives, nnegatives, logScale, shrinkage, poolSize));
     return octave;
 }

modules/softcascade/src/softcascade.cpp

@@ -145,13 +145,13 @@ struct Level
         scaleshift = static_cast<int>(relScale * (1 << 16));
     }
 
-    void addDetection(const int x, const int y, float confidence, std::vector<cv::Detection>& detections) const
+    void addDetection(const int x, const int y, float confidence, std::vector<Detection>& detections) const
     {
         // fix me
         int shrinkage = 4;//(*octave).shrinkage;
         cv::Rect rect(cvRound(x * shrinkage), cvRound(y * shrinkage), objSize.width, objSize.height);
 
-        detections.push_back(cv::Detection(rect, confidence));
+        detections.push_back(Detection(rect, confidence));
     }
 
     float rescale(cv::Rect& scaledRect, const float threshold, int idx) const
@@ -177,13 +177,13 @@ struct ChannelStorage
     int step;
     int model_height;
 
-    cv::Ptr<cv::ChannelFeatureBuilder> builder;
+    cv::Ptr<ChannelFeatureBuilder> builder;
 
     enum {HOG_BINS = 6, HOG_LUV_BINS = 10};
 
     ChannelStorage(const cv::Mat& colored, int shr) : shrinkage(shr)
     {
-        builder = cv::ChannelFeatureBuilder::create();
+        builder = ChannelFeatureBuilder::create();
         (*builder)(colored, hog);
 
         step = hog.step1();
@@ -205,7 +205,7 @@ struct ChannelStorage
 
 }
 
-struct cv::SoftCascadeDetector::Fields
+struct SoftCascadeDetector::Fields
 {
     float minScale;
     float maxScale;
@@ -409,17 +409,17 @@ struct cv::SoftCascadeDetector::Fields
     }
 };
 
-cv::SoftCascadeDetector::SoftCascadeDetector(const double mins, const double maxs, const int nsc, const int rej)
+SoftCascadeDetector::SoftCascadeDetector(const double mins, const double maxs, const int nsc, const int rej)
 : fields(0), minScale(mins), maxScale(maxs), scales(nsc), rejCriteria(rej) {}
 
-cv::SoftCascadeDetector::~SoftCascadeDetector() { delete fields;}
+SoftCascadeDetector::~SoftCascadeDetector() { delete fields;}
 
-void cv::SoftCascadeDetector::read(const FileNode& fn)
+void SoftCascadeDetector::read(const FileNode& fn)
 {
     Algorithm::read(fn);
 }
 
-bool cv::SoftCascadeDetector::load(const FileNode& fn)
+bool SoftCascadeDetector::load(const FileNode& fn)
 {
     if (fields) delete fields;
 
@@ -429,12 +429,12 @@ bool cv::SoftCascadeDetector::load(const FileNode& fn)
 
 namespace {
 
-typedef std::vector<cv::Detection>  dvector;
+typedef std::vector<Detection>  dvector;
 
 
 struct ConfidenceGt
 {
-    bool operator()(const cv::Detection& a, const cv::Detection& b) const
+    bool operator()(const Detection& a, const Detection& b) const
     {
         return a.confidence > b.confidence;
     }
@@ -455,10 +455,10 @@ void DollarNMS(dvector& objects)
 
     for (dvector::iterator dIt = objects.begin(); dIt != objects.end(); ++dIt)
     {
-        const cv::Detection &a = *dIt;
+        const Detection &a = *dIt;
         for (dvector::iterator next = dIt + 1; next != objects.end(); )
         {
-            const cv::Detection &b = *next;
+            const Detection &b = *next;
 
             const float ovl =  overlap(a.bb, b.bb) / std::min(a.bb.area(), b.bb.area());
 
@@ -470,15 +470,15 @@ void DollarNMS(dvector& objects)
     }
 }
 
-static void suppress(int type, std::vector<cv::Detection>& objects)
+static void suppress(int type, std::vector<Detection>& objects)
 {
-    CV_Assert(type == cv::SoftCascadeDetector::DOLLAR);
+    CV_Assert(type == SoftCascadeDetector::DOLLAR);
     DollarNMS(objects);
 }
 
 }
 
-void cv::SoftCascadeDetector::detectNoRoi(const cv::Mat& image, std::vector<Detection>& objects) const
+void SoftCascadeDetector::detectNoRoi(const cv::Mat& image, std::vector<Detection>& objects) const
 {
     Fields& fld = *fields;
     // create integrals
@@ -505,7 +505,7 @@ void cv::SoftCascadeDetector::detectNoRoi(const cv::Mat& image, std::vector<Dete
     // if (rejCriteria != NO_REJECT) suppress(rejCriteria, objects);
 }
 
-void cv::SoftCascadeDetector::detect(cv::InputArray _image, cv::InputArray _rois, std::vector<Detection>& objects) const
+void SoftCascadeDetector::detect(cv::InputArray _image, cv::InputArray _rois, std::vector<Detection>& objects) const
 {
     // only color images are suppered
     cv::Mat image = _image.getMat();
@@ -557,7 +557,7 @@ void cv::SoftCascadeDetector::detect(cv::InputArray _image, cv::InputArray _rois
     if (rejCriteria != NO_REJECT) suppress(rejCriteria, objects);
 }
 
-void cv::SoftCascadeDetector::detect(InputArray _image, InputArray _rois,  OutputArray _rects, OutputArray _confs) const
+void SoftCascadeDetector::detect(InputArray _image, InputArray _rois,  OutputArray _rects, OutputArray _confs) const
 {
     std::vector<Detection> objects;
     detect( _image, _rois, objects);

modules/softcascade/src/softcascade_init.cpp

@@ -42,7 +42,7 @@
 
 #include "precomp.hpp"
 
-namespace cv
+namespace cv { namespace scascade
 {
 
 CV_INIT_ALGORITHM(SoftCascadeDetector, "SoftCascade.SoftCascadeDetector",
@@ -58,4 +58,4 @@ bool initModule_softcascade(void)
     return (sc1->info() != 0);
 }
 
-}
+} }
\ No newline at end of file

modules/softcascade/test/test_channel_features.cpp

@@ -44,13 +44,13 @@
 
 TEST(ChannelFeatureBuilderTest, info)
 {
-    cv::Ptr<cv::ChannelFeatureBuilder> builder = cv::ChannelFeatureBuilder::create();
+    cv::Ptr<cv::scascade::ChannelFeatureBuilder> builder = cv::scascade::ChannelFeatureBuilder::create();
     ASSERT_TRUE(builder->info() != 0);
 }
 
 TEST(ChannelFeatureBuilderTest, compute)
 {
-    cv::Ptr<cv::ChannelFeatureBuilder> builder = cv::ChannelFeatureBuilder::create();
+    cv::Ptr<cv::scascade::ChannelFeatureBuilder> builder = cv::scascade::ChannelFeatureBuilder::create();
 
     cv::Mat colored = cv::imread(cvtest::TS::ptr()->get_data_path()  + "cascadeandhog/images/image_00000000_0.png");
     cv::Mat ints;

modules/softcascade/test/test_softcascade.cpp

@@ -44,11 +44,12 @@
 #include <fstream>
 
 #include "test_precomp.hpp"
+    typedef cv::scascade::Detection Detection;
 
 TEST(SoftCascadeDetector, readCascade)
 {
     std::string xml = cvtest::TS::ptr()->get_data_path() + "cascadeandhog/cascades/inria_caltech-17.01.2013.xml";
-    cv::SoftCascadeDetector cascade;
+    cv::scascade::SoftCascadeDetector cascade;
     cv::FileStorage fs(xml, cv::FileStorage::READ);
     ASSERT_TRUE(fs.isOpened());
     ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
@@ -56,9 +57,8 @@ TEST(SoftCascadeDetector, readCascade)
 
 TEST(SoftCascadeDetector, detect)
 {
-    typedef cv::Detection Detection;
     std::string xml =  cvtest::TS::ptr()->get_data_path()+ "cascadeandhog/cascades/inria_caltech-17.01.2013.xml";
-    cv::SoftCascadeDetector cascade;
+    cv::scascade::SoftCascadeDetector cascade;
     cv::FileStorage fs(xml, cv::FileStorage::READ);
     ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 
@@ -73,9 +73,8 @@ TEST(SoftCascadeDetector, detect)
 
 TEST(SoftCascadeDetector, detectSeparate)
 {
-    typedef cv::Detection Detection;
     std::string xml =  cvtest::TS::ptr()->get_data_path() + "cascadeandhog/cascades/inria_caltech-17.01.2013.xml";
-    cv::SoftCascadeDetector cascade;
+    cv::scascade::SoftCascadeDetector cascade;
     cv::FileStorage fs(xml, cv::FileStorage::READ);
     ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 
@@ -90,9 +89,8 @@ TEST(SoftCascadeDetector, detectSeparate)
 
 TEST(SoftCascadeDetector, detectRoi)
 {
-    typedef cv::Detection Detection;
     std::string xml =  cvtest::TS::ptr()->get_data_path() + "cascadeandhog/cascades/inria_caltech-17.01.2013.xml";
-    cv::SoftCascadeDetector cascade;
+    cv::scascade::SoftCascadeDetector cascade;
     cv::FileStorage fs(xml, cv::FileStorage::READ);
     ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 
@@ -109,9 +107,8 @@ TEST(SoftCascadeDetector, detectRoi)
 
 TEST(SoftCascadeDetector, detectNoRoi)
 {
-    typedef cv::Detection Detection;
     std::string xml =  cvtest::TS::ptr()->get_data_path() + "cascadeandhog/cascades/inria_caltech-17.01.2013.xml";
-    cv::SoftCascadeDetector cascade;
+    cv::scascade::SoftCascadeDetector cascade;
     cv::FileStorage fs(xml, cv::FileStorage::READ);
     ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 
@@ -128,9 +125,8 @@ TEST(SoftCascadeDetector, detectNoRoi)
 
 TEST(SoftCascadeDetector, detectEmptyRoi)
 {
-    typedef cv::Detection Detection;
     std::string xml =  cvtest::TS::ptr()->get_data_path() + "cascadeandhog/cascades/inria_caltech-17.01.2013.xml";
-    cv::SoftCascadeDetector cascade;
+    cv::scascade::SoftCascadeDetector cascade;
     cv::FileStorage fs(xml, cv::FileStorage::READ);
     ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 

modules/softcascade/test/test_training.cpp

@@ -58,7 +58,7 @@ using namespace std;
 namespace {
 
 typedef vector<string> svector;
-class ScaledDataset : public cv::Dataset
+class ScaledDataset : public cv::scascade::Dataset
 {
 public:
     ScaledDataset(const string& path, const int octave);
@@ -210,7 +210,7 @@ TEST(DISABLED_SoftCascade, training)
         float octave = powf(2.f, (float)(*it));
         cv::Size model = cv::Size( cvRound(64 * octave) / shrinkage, cvRound(128 * octave) / shrinkage );
 
-        cv::Ptr<cv::FeaturePool> pool = cv::FeaturePool::create(model, nfeatures);
+        cv::Ptr<cv::scascade::FeaturePool> pool = cv::scascade::FeaturePool::create(model, nfeatures);
         nfeatures = pool->size();
         int npositives = 20;
         int nnegatives = 40;
@@ -218,7 +218,7 @@ TEST(DISABLED_SoftCascade, training)
         cv::Rect boundingBox = cv::Rect( cvRound(20 * octave), cvRound(20  * octave),
                                          cvRound(64 * octave), cvRound(128 * octave));
 
-        typedef cv::SoftCascadeOctave Octave;
+        typedef cv::scascade::SoftCascadeOctave Octave;
         cv::Ptr<Octave> boost = Octave::create(boundingBox, npositives, nnegatives, *it, shrinkage, nfeatures);
 
         std::string path = cvtest::TS::ptr()->get_data_path() + "softcascade/sample_training_set";