merged regression tests for FeatureDetector, DescriptorExtractor from branch .features2d;

renamed createDetector to createFeatureDetector

modules/features2d/include/opencv2/features2d/features2d.hpp

@@ -1354,7 +1354,7 @@ protected:
     SURF surf;
 };
 
-CV_EXPORTS Ptr<FeatureDetector> createDetector( const string& detectorType );
+CV_EXPORTS Ptr<FeatureDetector> createFeatureDetector( const string& detectorType );
 
 /*
  * Adapts a detector to partition the source image into a grid and detect

modules/features2d/src/detectors.cpp

@@ -316,7 +316,7 @@ void SurfFeatureDetector::detectImpl( const Mat& image, const Mat& mask,
     surf(image, mask, keypoints);
 }
 
-Ptr<FeatureDetector> createDetector( const string& detectorType )
+Ptr<FeatureDetector> createFeatureDetector( const string& detectorType )
 {
     FeatureDetector* fd = 0;
     if( !detectorType.compare( "FAST" ) )

samples/cpp/build3dmodel.cpp

@@ -651,7 +651,7 @@ int main(int argc, char** argv)
     Size calibratedImageSize;
     readCameraMatrix(intrinsicsFilename, cameraMatrix, distCoeffs, calibratedImageSize);
     
-    Ptr<FeatureDetector> detector = createDetector(detectorName);
+    Ptr<FeatureDetector> detector = createFeatureDetector(detectorName);
     Ptr<DescriptorExtractor> descriptorExtractor = createDescriptorExtractor(descriptorExtractorName);
     
     string modelIndexFilename = format("%s_segm/frame_index.yml", modelName);

samples/cpp/descriptor_extractor_matcher.cpp

@@ -143,7 +143,7 @@ int main(int argc, char** argv)
         ransacReprojThreshold = atof(argv[5]);
 
     cout << "< Creating detector, descriptor extractor and descriptor matcher ..." << endl;
-    Ptr<FeatureDetector> detector = createDetector( argv[1] );
+    Ptr<FeatureDetector> detector = createFeatureDetector( argv[1] );
     Ptr<DescriptorExtractor> descriptorExtractor = createDescriptorExtractor( argv[2] );
     Ptr<DescriptorMatcher> descriptorMatcher = createDescriptorMatcher( "BruteForce" );
     cout << ">" << endl;

tests/cv/src/adetectordescriptor_evaluation.cpp

@@ -686,8 +686,8 @@ inline void readKeypoints( FileStorage& fs, vector<KeyPoint>& keypoints, int img
 
 void DetectorQualityTest::readAlgorithm ()
 {
-    defaultDetector = createDetector( algName );
-    specificDetector = createDetector( algName );
+    defaultDetector = createFeatureDetector( algName );
+    specificDetector = createFeatureDetector( algName );
     if( defaultDetector == 0 )
     {
         ts->printf(CvTS::LOG, "Algorithm can not be read\n");

tests/cv/src/afeatures2d.cpp

@@ -0,0 +1,334 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                        Intel License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000, Intel Corporation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of Intel Corporation may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+#include "cvtest.h"
+#include "opencv2/core/core.hpp"
+
+using namespace std;
+using namespace cv;
+
+const string FEATURES2D_DIR = "features2d";
+const string DETECTOR_DIR = FEATURES2D_DIR + "/feature_detectors";
+const string DESCRIPTOR_DIR = FEATURES2D_DIR + "/descriptor_extractors";
+const string IMAGE_FILENAME = "tsukuba.png";
+
+/****************************************************************************************\
+*            Regression tests for feature detectors comparing keypoints.                 *
+\****************************************************************************************/
+
+class CV_FeatureDetectorTest : public CvTest
+{
+public:
+    CV_FeatureDetectorTest( const char* testName, const Ptr<FeatureDetector>& _fdetector ) :
+        CvTest( testName, "cv::FeatureDetector::detect"), fdetector(_fdetector) {}
+
+protected:
+    virtual void run( int start_from )
+    {
+        const float maxPtDif = 1.f;
+        const float maxSizeDif = 1.f;
+        const float maxAngleDif = 2.f;
+        const float maxResponseDif = 0.1f;
+
+        string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
+        string resFilename = string(ts->get_data_path()) + DETECTOR_DIR + "/" + string(name) + "_res.xml.gz";
+
+        if( fdetector.empty() )
+        {
+            ts->printf( CvTS::LOG, "Feature detector is empty" );
+            ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+            return;
+        }
+
+        Mat image = imread( imgFilename, 0 );
+        if( image.empty() )
+        {
+            ts->printf( CvTS::LOG, "image %s can not be read \n", imgFilename.c_str() );
+            ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+            return;
+        }
+
+        FileStorage fs( resFilename, FileStorage::READ );
+
+        vector<KeyPoint> calcKeypoints;
+        fdetector->detect( image, calcKeypoints );
+
+        if( fs.isOpened() ) // compare computed and valid keypoints
+        {
+            // TODO compare saved feature detector params with current ones
+            vector<KeyPoint> validKeypoints;
+            read( fs["keypoints"], validKeypoints );
+            if( validKeypoints.empty() )
+            {
+                ts->printf( CvTS::LOG, "Keypoints can nod be read\n" );
+                ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+                return;
+            }
+
+            int progress = 0, progressCount = validKeypoints.size() * calcKeypoints.size();
+            int badPointCount = 0, commonPointCount = max(validKeypoints.size(), calcKeypoints.size());
+            for( size_t v = 0; v < validKeypoints.size(); v++ )
+            {
+                int nearestIdx = -1;
+                float minDist = std::numeric_limits<float>::max();
+
+                for( size_t c = 0; c < calcKeypoints.size(); c++ )
+                {
+                    progress = update_progress( progress, v*calcKeypoints.size() + c, progressCount, 0 );
+                    float curDist = norm( calcKeypoints[c].pt - validKeypoints[v].pt );
+                    if( curDist < minDist )
+                    {
+                        minDist = curDist;
+                        nearestIdx = c;
+                    }
+                }
+
+                if( minDist > maxPtDif ||
+                    fabs(calcKeypoints[nearestIdx].size - validKeypoints[v].size) > maxSizeDif ||
+                    abs(calcKeypoints[nearestIdx].angle - validKeypoints[v].angle) > maxAngleDif ||
+                    abs(calcKeypoints[nearestIdx].response - validKeypoints[v].response) > maxResponseDif ||
+                    calcKeypoints[nearestIdx].octave != validKeypoints[v].octave
+
+                    // TODO !!!!!!!
+                    /*||
+                    calcKeypoints[nearestIdx].class_id != validKeypoints[v].class_id*/ )
+                {
+                    badPointCount++;
+                }
+            }
+            ts->printf( CvTS::LOG, "badPointCount = %d; validPointCount = %d; calcPointCount = %d\n",
+                        badPointCount, validKeypoints.size(), calcKeypoints.size() );
+            if( badPointCount > 0.9 * commonPointCount )
+            {
+                ts->printf( CvTS::LOG, "Bad accuracy!\n" );
+                ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
+                return;
+            }
+        }
+        else // write
+        {
+            fs.open( resFilename, FileStorage::WRITE );
+            if( !fs.isOpened() )
+            {
+                ts->printf( CvTS::LOG, "file %s can not be opened to write\n", resFilename.c_str() );
+                ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+                return;
+            }
+            else
+            {
+                fs << "detector_params" << "{";
+                fdetector->write( fs );
+                fs << "}";
+
+                write( fs, "keypoints", calcKeypoints );
+            }
+        }
+        ts->set_failed_test_info( CvTS::OK );
+    }
+
+    Ptr<FeatureDetector> fdetector;
+};
+
+CV_FeatureDetectorTest fastTest( "detector_fast", createFeatureDetector("FAST") );
+CV_FeatureDetectorTest gfttTest( "detector_gftt", createFeatureDetector("GFTT") );
+CV_FeatureDetectorTest harrisTest( "detector_harris", createFeatureDetector("HARRIS") );
+CV_FeatureDetectorTest mserTest( "detector_mser", createFeatureDetector("MSER") );
+CV_FeatureDetectorTest siftTest( "detector_sift", createFeatureDetector("SIFT") );
+CV_FeatureDetectorTest starTest( "detector_star", createFeatureDetector("STAR") );
+CV_FeatureDetectorTest surfTest( "detector_surf", createFeatureDetector("SURF") );
+
+/****************************************************************************************\
+*                     Regression tests for descriptor extractors.                        *
+\****************************************************************************************/
+static void writeMatInBin( const Mat& mat, const string& filename )
+{
+    FILE* f = fopen( filename.c_str(), "wb");
+    if( f )
+    {
+        int type = mat.type();
+        fwrite( (void*)&mat.rows, sizeof(int), 1, f );
+        fwrite( (void*)&mat.cols, sizeof(int), 1, f );
+        fwrite( (void*)&type, sizeof(int), 1, f );
+        fwrite( (void*)&mat.step, sizeof(int), 1, f );
+        fwrite( (void*)mat.data, 1, mat.step*mat.rows, f );
+        fclose(f);
+    }
+}
+
+static Mat readMatFromBin( const string& filename )
+{
+    FILE* f = fopen( filename.c_str(), "rb" );
+    if( f )
+    {
+        int rows, cols, type, step;
+        fread( (void*)&rows, sizeof(int), 1, f );
+        fread( (void*)&cols, sizeof(int), 1, f );
+        fread( (void*)&type, sizeof(int), 1, f );
+        fread( (void*)&step, sizeof(int), 1, f );
+
+        uchar* data = (uchar*)cvAlloc(step*rows);
+        fread( (void*)data, 1, step*rows, f );
+        fclose(f);
+
+        return Mat( rows, cols, type, data );
+    }
+    return Mat();
+}
+
+class CV_DescriptorExtractorTest : public CvTest
+{
+public:
+    CV_DescriptorExtractorTest( const char* testName, float _normDif, const Ptr<DescriptorExtractor>& _dextractor, float _prevTime  ) :
+            CvTest( testName, "cv::DescriptorExtractor::compute" ), normDif(_normDif), prevTime(_prevTime), dextractor(_dextractor) {}
+protected:
+    virtual void createDescriptorExtractor() {}
+
+    void run(int)
+    {
+        createDescriptorExtractor();
+
+        if( dextractor.empty() )
+        {
+            ts->printf(CvTS::LOG, "Descriptor extractor is empty\n");
+            ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+            return;
+        }
+
+        string imgFilename =  string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
+        Mat img = imread( imgFilename, 0 );
+        if( img.empty() )
+        {
+            ts->printf( CvTS::LOG, "image %s can not be read\n", imgFilename.c_str() );
+            ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+            return;
+        }
+
+        vector<KeyPoint> keypoints;
+        FileStorage fs( string(ts->get_data_path()) + FEATURES2D_DIR + "/keypoints.xml.gz", FileStorage::READ );
+        if( fs.isOpened() )
+            read( fs.getFirstTopLevelNode(), keypoints );
+        else
+        {
+            ts->printf( CvTS::LOG, "Compute and write keypoints\n" );
+            fs.open( string(ts->get_data_path()) + FEATURES2D_DIR + "/keypoints.xml.gz", FileStorage::WRITE );
+            if( fs.isOpened() )
+            {
+                SurfFeatureDetector fd;
+                fd.detect(img, keypoints);
+                write( fs, "keypoints", keypoints );
+            }
+            else
+            {
+                ts->printf(CvTS::LOG, "File for writting keypoints can not be opened\n");
+                ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+                return;
+            }
+        }
+
+        Mat calcDescriptors;
+        double t = (double)getTickCount();
+        dextractor->compute( img, keypoints, calcDescriptors );
+        t = getTickCount() - t;
+        ts->printf(CvTS::LOG, "\nAverage time of computiting one descriptor = %g ms (previous time = %g ms)\n", t/((double)cvGetTickFrequency()*1000.)/calcDescriptors.rows, prevTime );
+
+        // TODO read and write descriptor extractor parameters and check them
+        Mat validDescriptors = readDescriptors();
+        if( !validDescriptors.empty() )
+        {
+            double normVal = norm( calcDescriptors, validDescriptors, NORM_INF );
+            ts->printf( CvTS::LOG, "nofm (inf) BTW valid and calculated float descriptors = %f\n", normVal );
+            if( normVal > normDif )
+                ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
+        }
+        else
+        {
+            if( !writeDescriptors( calcDescriptors ) )
+            {
+                ts->printf( CvTS::LOG, "Descriptors can not be written\n" );
+                ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+                return;
+            }
+        }
+    }
+
+    virtual Mat readDescriptors()
+    {
+        Mat res = readMatFromBin( string(ts->get_data_path()) + DESCRIPTOR_DIR + "/" + string(name) );
+        return res;
+    }
+
+    virtual bool writeDescriptors( Mat& descs )
+    {
+        writeMatInBin( descs,  string(ts->get_data_path()) + DESCRIPTOR_DIR + "/" + string(name) );
+        return true;
+    }
+
+    const float normDif;
+    const float prevTime;
+
+    Ptr<DescriptorExtractor> dextractor;
+};
+
+template<typename T>
+class CV_CalonderDescriptorExtractorTest : public CV_DescriptorExtractorTest
+{
+public:
+    CV_CalonderDescriptorExtractorTest( const char* testName, float _normDif, float _prevTime ) :
+            CV_DescriptorExtractorTest( testName, _normDif, Ptr<DescriptorExtractor>(), _prevTime )
+    {}
+
+    virtual void createDescriptorExtractor()
+    {
+        dextractor = new CalonderDescriptorExtractor<T>( string(ts->get_data_path()) + FEATURES2D_DIR + "/calonder_classifier.rtc");
+    }
+};
+
+CV_DescriptorExtractorTest siftDescriptorTest( "descriptor_sift", std::numeric_limits<float>::epsilon(),
+                                               createDescriptorExtractor("SIFT"), 8.06652f  );
+CV_DescriptorExtractorTest surfDescriptorTest( "descriptor_surf", std::numeric_limits<float>::epsilon(),
+                                               createDescriptorExtractor("SURF"), 0.147372f );
+#if CV_SSE2
+CV_CalonderDescriptorExtractorTest<uchar> ucharCalonderTest( "descriptor_calonder_uchar",
+                                                             std::numeric_limits<float>::epsilon() + 1,
+                                                             0.0132175f );
+CV_CalonderDescriptorExtractorTest<float> floatCalonderTest( "descriptor_calonder_float",
+                                                             std::numeric_limits<float>::epsilon(),
+                                                             0.0221308f );
+#endif // CV_SSE2