Visual Servoing Platform  version 3.4.1 under development (2021-10-20)
vpKeyPoint.h
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29  * WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
30  *
31  * Description:
32  * Key point functionalities.
33  *
34  * Authors:
35  * Souriya Trinh
36  *
37  *****************************************************************************/
38 #ifndef _vpKeyPoint_h_
39 #define _vpKeyPoint_h_
40 
41 #include <algorithm> // std::transform
42 #include <float.h> // DBL_MAX
43 #include <fstream> // std::ofstream
44 #include <limits>
45 #include <map> // std::map
46 #include <numeric> // std::accumulate
47 #include <stdlib.h> // srand, rand
48 #include <time.h> // time
49 #include <vector> // std::vector
50 
51 #include <visp3/core/vpConfig.h>
52 #include <visp3/core/vpDisplay.h>
53 #include <visp3/core/vpImageConvert.h>
54 #include <visp3/core/vpPixelMeterConversion.h>
55 #include <visp3/core/vpPlane.h>
56 #include <visp3/core/vpPoint.h>
57 #include <visp3/vision/vpBasicKeyPoint.h>
58 #include <visp3/vision/vpPose.h>
59 #ifdef VISP_HAVE_MODULE_IO
60 # include <visp3/io/vpImageIo.h>
61 #endif
62 #include <visp3/core/vpConvert.h>
63 #include <visp3/core/vpCylinder.h>
64 #include <visp3/core/vpMeterPixelConversion.h>
65 #include <visp3/core/vpPolygon.h>
66 #include <visp3/vision/vpXmlConfigParserKeyPoint.h>
67 
68 // Require at least OpenCV >= 2.1.1
69 #if (VISP_HAVE_OPENCV_VERSION >= 0x020101)
70 
71 # include <opencv2/calib3d/calib3d.hpp>
72 # include <opencv2/features2d/features2d.hpp>
73 # include <opencv2/imgproc/imgproc.hpp>
74 
75 # if (VISP_HAVE_OPENCV_VERSION >= 0x040000) // Require opencv >= 4.0.0
76 # include <opencv2/imgproc/imgproc_c.h>
77 # include <opencv2/imgproc.hpp>
78 # endif
79 
80 # if defined(VISP_HAVE_OPENCV_XFEATURES2D) // OpenCV >= 3.0.0
81 # include <opencv2/xfeatures2d.hpp>
82 # elif defined(VISP_HAVE_OPENCV_NONFREE) && (VISP_HAVE_OPENCV_VERSION >= 0x020400) && \
83  (VISP_HAVE_OPENCV_VERSION < 0x030000)
84 # include <opencv2/nonfree/nonfree.hpp>
85 # endif
86 
222 class VISP_EXPORT vpKeyPoint : public vpBasicKeyPoint
223 {
224 
225 public:
228  constantFactorDistanceThreshold,
230  stdDistanceThreshold,
232  ratioDistanceThreshold,
235  stdAndRatioDistanceThreshold,
237  noFilterMatching
238  };
239 
242  detectionThreshold,
244  detectionScore
247  };
248 
250  typedef enum {
254  pgmImageFormat
256 
259 #if (VISP_HAVE_OPENCV_VERSION >= 0x020403)
266 #if (VISP_HAVE_OPENCV_VERSION < 0x030000) || (defined(VISP_HAVE_OPENCV_XFEATURES2D))
267  DETECTOR_STAR,
268 #endif
269 #if defined(VISP_HAVE_OPENCV_NONFREE) || defined(VISP_HAVE_OPENCV_XFEATURES2D) || \
270  (VISP_HAVE_OPENCV_VERSION >= 0x030411 && CV_MAJOR_VERSION < 4) || (VISP_HAVE_OPENCV_VERSION >= 0x040400)
272 #endif
273 #if defined(VISP_HAVE_OPENCV_NONFREE) || defined(VISP_HAVE_OPENCV_XFEATURES2D)
275 #endif
276 #if (VISP_HAVE_OPENCV_VERSION >= 0x030000)
280 #endif
281 #if (VISP_HAVE_OPENCV_VERSION >= 0x030100) && defined(VISP_HAVE_OPENCV_XFEATURES2D)
282  DETECTOR_MSD,
283 #endif
284 #endif
285  DETECTOR_TYPE_SIZE
286  };
287 
290 #if (VISP_HAVE_OPENCV_VERSION >= 0x020403)
293 #if (VISP_HAVE_OPENCV_VERSION < 0x030000) || (defined(VISP_HAVE_OPENCV_XFEATURES2D))
294  DESCRIPTOR_FREAK,
295  DESCRIPTOR_BRIEF,
296 #endif
297 #if defined(VISP_HAVE_OPENCV_NONFREE) || defined(VISP_HAVE_OPENCV_XFEATURES2D) || \
298  (VISP_HAVE_OPENCV_VERSION >= 0x030411 && CV_MAJOR_VERSION < 4) || (VISP_HAVE_OPENCV_VERSION >= 0x040400)
300 #endif
301 #if defined(VISP_HAVE_OPENCV_NONFREE) || defined(VISP_HAVE_OPENCV_XFEATURES2D)
303 #endif
304 #if (VISP_HAVE_OPENCV_VERSION >= 0x030000)
307 #if defined(VISP_HAVE_OPENCV_XFEATURES2D)
308  DESCRIPTOR_DAISY,
309  DESCRIPTOR_LATCH,
310 #endif
311 #endif
312 #if (VISP_HAVE_OPENCV_VERSION >= 0x030200) && defined(VISP_HAVE_OPENCV_XFEATURES2D)
313  DESCRIPTOR_VGG,
314  DESCRIPTOR_BoostDesc,
315 #endif
316 #endif
317  DESCRIPTOR_TYPE_SIZE
318  };
319 
320  vpKeyPoint(const vpFeatureDetectorType &detectorType, const vpFeatureDescriptorType &descriptorType,
321  const std::string &matcherName, const vpFilterMatchingType &filterType = ratioDistanceThreshold);
322  vpKeyPoint(const std::string &detectorName = "ORB", const std::string &extractorName = "ORB",
323  const std::string &matcherName = "BruteForce-Hamming",
324  const vpFilterMatchingType &filterType = ratioDistanceThreshold);
325  vpKeyPoint(const std::vector<std::string> &detectorNames, const std::vector<std::string> &extractorNames,
326  const std::string &matcherName = "BruteForce",
327  const vpFilterMatchingType &filterType = ratioDistanceThreshold);
328 
329  unsigned int buildReference(const vpImage<unsigned char> &I);
330  unsigned int buildReference(const vpImage<unsigned char> &I, const vpImagePoint &iP, unsigned int height,
331  unsigned int width);
332  unsigned int buildReference(const vpImage<unsigned char> &I, const vpRect &rectangle);
333 
334  unsigned int buildReference(const vpImage<unsigned char> &I, std::vector<cv::KeyPoint> &trainKeyPoints,
335  std::vector<cv::Point3f> &points3f, bool append = false, int class_id = -1);
336  unsigned int buildReference(const vpImage<unsigned char> &I, const std::vector<cv::KeyPoint> &trainKeyPoints,
337  const cv::Mat &trainDescriptors, const std::vector<cv::Point3f> &points3f,
338  bool append = false, int class_id = -1);
339 
340  unsigned int buildReference(const vpImage<vpRGBa> &I_color);
341  unsigned int buildReference(const vpImage<vpRGBa> &I_color, const vpImagePoint &iP, unsigned int height,
342  unsigned int width);
343  unsigned int buildReference(const vpImage<vpRGBa> &I_color, const vpRect &rectangle);
344 
345  unsigned int buildReference(const vpImage<vpRGBa> &I_color, std::vector<cv::KeyPoint> &trainKeyPoints,
346  std::vector<cv::Point3f> &points3f, bool append = false, int class_id = -1);
347  unsigned int buildReference(const vpImage<vpRGBa> &I, const std::vector<cv::KeyPoint> &trainKeyPoints,
348  const cv::Mat &trainDescriptors, const std::vector<cv::Point3f> &points3f,
349  bool append = false, int class_id = -1);
350 
351  static void compute3D(const cv::KeyPoint &candidate, const std::vector<vpPoint> &roi, const vpCameraParameters &cam,
352  const vpHomogeneousMatrix &cMo, cv::Point3f &point);
353 
354  static void compute3D(const vpImagePoint &candidate, const std::vector<vpPoint> &roi, const vpCameraParameters &cam,
355  const vpHomogeneousMatrix &cMo, vpPoint &point);
356 
357  static void compute3DForPointsInPolygons(const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam,
358  std::vector<cv::KeyPoint> &candidates,
359  const std::vector<vpPolygon> &polygons,
360  const std::vector<std::vector<vpPoint> > &roisPt,
361  std::vector<cv::Point3f> &points, cv::Mat *descriptors = NULL);
362 
363  static void compute3DForPointsInPolygons(const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam,
364  std::vector<vpImagePoint> &candidates,
365  const std::vector<vpPolygon> &polygons,
366  const std::vector<std::vector<vpPoint> > &roisPt,
367  std::vector<vpPoint> &points, cv::Mat *descriptors = NULL);
368 
369  static void
370  compute3DForPointsOnCylinders(const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam,
371  std::vector<cv::KeyPoint> &candidates, const std::vector<vpCylinder> &cylinders,
372  const std::vector<std::vector<std::vector<vpImagePoint> > > &vectorOfCylinderRois,
373  std::vector<cv::Point3f> &points, cv::Mat *descriptors = NULL);
374 
375  static void
376  compute3DForPointsOnCylinders(const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam,
377  std::vector<vpImagePoint> &candidates, const std::vector<vpCylinder> &cylinders,
378  const std::vector<std::vector<std::vector<vpImagePoint> > > &vectorOfCylinderRois,
379  std::vector<vpPoint> &points, cv::Mat *descriptors = NULL);
380 
381  bool computePose(const std::vector<cv::Point2f> &imagePoints, const std::vector<cv::Point3f> &objectPoints,
382  const vpCameraParameters &cam, vpHomogeneousMatrix &cMo, std::vector<int> &inlierIndex,
383  double &elapsedTime, bool (*func)(const vpHomogeneousMatrix &) = NULL);
384 
385  bool computePose(const std::vector<vpPoint> &objectVpPoints, vpHomogeneousMatrix &cMo, std::vector<vpPoint> &inliers,
386  double &elapsedTime, bool (*func)(const vpHomogeneousMatrix &) = NULL);
387 
388  bool computePose(const std::vector<vpPoint> &objectVpPoints, vpHomogeneousMatrix &cMo, std::vector<vpPoint> &inliers,
389  std::vector<unsigned int> &inlierIndex, double &elapsedTime,
390  bool (*func)(const vpHomogeneousMatrix &) = NULL);
391 
392  void createImageMatching(vpImage<unsigned char> &IRef, vpImage<unsigned char> &ICurrent,
393  vpImage<unsigned char> &IMatching);
394  void createImageMatching(vpImage<unsigned char> &ICurrent, vpImage<unsigned char> &IMatching);
395 
396  void createImageMatching(vpImage<unsigned char> &IRef, vpImage<vpRGBa> &ICurrent,
397  vpImage<vpRGBa> &IMatching);
398  void createImageMatching(vpImage<vpRGBa> &ICurrent, vpImage<vpRGBa> &IMatching);
399 
400  void detect(const vpImage<unsigned char> &I, std::vector<cv::KeyPoint> &keyPoints,
401  const vpRect &rectangle = vpRect());
402  void detect(const vpImage<vpRGBa> &I_color, std::vector<cv::KeyPoint> &keyPoints,
403  const vpRect &rectangle = vpRect());
404  void detect(const cv::Mat &matImg, std::vector<cv::KeyPoint> &keyPoints, const cv::Mat &mask = cv::Mat());
405  void detect(const vpImage<unsigned char> &I, std::vector<cv::KeyPoint> &keyPoints, double &elapsedTime,
406  const vpRect &rectangle = vpRect());
407  void detect(const vpImage<vpRGBa> &I_color, std::vector<cv::KeyPoint> &keyPoints, double &elapsedTime,
408  const vpRect &rectangle = vpRect());
409  void detect(const cv::Mat &matImg, std::vector<cv::KeyPoint> &keyPoints, double &elapsedTime,
410  const cv::Mat &mask = cv::Mat());
411 
412  void detectExtractAffine(const vpImage<unsigned char> &I, std::vector<std::vector<cv::KeyPoint> > &listOfKeypoints,
413  std::vector<cv::Mat> &listOfDescriptors,
414  std::vector<vpImage<unsigned char> > *listOfAffineI = NULL);
415 
416  void display(const vpImage<unsigned char> &IRef, const vpImage<unsigned char> &ICurrent, unsigned int size = 3);
417  void display(const vpImage<unsigned char> &ICurrent, unsigned int size = 3, const vpColor &color = vpColor::green);
418  void display(const vpImage<vpRGBa> &IRef, const vpImage<vpRGBa> &ICurrent, unsigned int size = 3);
419  void display(const vpImage<vpRGBa> &ICurrent, unsigned int size = 3, const vpColor &color = vpColor::green);
420 
421  void displayMatching(const vpImage<unsigned char> &IRef, vpImage<unsigned char> &IMatching, unsigned int crossSize,
422  unsigned int lineThickness = 1, const vpColor &color = vpColor::green);
423  void displayMatching(const vpImage<unsigned char> &ICurrent, vpImage<unsigned char> &IMatching,
424  const std::vector<vpImagePoint> &ransacInliers = std::vector<vpImagePoint>(),
425  unsigned int crossSize = 3, unsigned int lineThickness = 1);
426  void displayMatching(const vpImage<unsigned char> &IRef, vpImage<vpRGBa> &IMatching, unsigned int crossSize,
427  unsigned int lineThickness = 1, const vpColor &color = vpColor::green);
428  void displayMatching(const vpImage<vpRGBa> &IRef, vpImage<vpRGBa> &IMatching, unsigned int crossSize,
429  unsigned int lineThickness = 1, const vpColor &color = vpColor::green);
430  void displayMatching(const vpImage<vpRGBa> &ICurrent, vpImage<vpRGBa> &IMatching,
431  const std::vector<vpImagePoint> &ransacInliers = std::vector<vpImagePoint>(),
432  unsigned int crossSize = 3, unsigned int lineThickness = 1);
433 
434  void extract(const vpImage<unsigned char> &I, std::vector<cv::KeyPoint> &keyPoints, cv::Mat &descriptors,
435  std::vector<cv::Point3f> *trainPoints = NULL);
436  void extract(const vpImage<vpRGBa> &I_color, std::vector<cv::KeyPoint> &keyPoints, cv::Mat &descriptors,
437  std::vector<cv::Point3f> *trainPoints = NULL);
438  void extract(const cv::Mat &matImg, std::vector<cv::KeyPoint> &keyPoints, cv::Mat &descriptors,
439  std::vector<cv::Point3f> *trainPoints = NULL);
440  void extract(const vpImage<unsigned char> &I, std::vector<cv::KeyPoint> &keyPoints, cv::Mat &descriptors,
441  double &elapsedTime, std::vector<cv::Point3f> *trainPoints = NULL);
442  void extract(const vpImage<vpRGBa> &I_color, std::vector<cv::KeyPoint> &keyPoints, cv::Mat &descriptors,
443  double &elapsedTime, std::vector<cv::Point3f> *trainPoints = NULL);
444  void extract(const cv::Mat &matImg, std::vector<cv::KeyPoint> &keyPoints, cv::Mat &descriptors, double &elapsedTime,
445  std::vector<cv::Point3f> *trainPoints = NULL);
446 
457  {
458  if (!m_computeCovariance) {
459  std::cout << "Warning : The covariance matrix has not been computed. "
460  "See setCovarianceComputation() to do it."
461  << std::endl;
462  return vpMatrix();
463  }
464 
465  if (m_computeCovariance && !m_useRansacVVS) {
466  std::cout << "Warning : The covariance matrix can only be computed "
467  "with a Virtual Visual Servoing approach."
468  << std::endl
469  << "Use setUseRansacVVS(true) to choose to use a pose "
470  "estimation method based on a Virtual Visual Servoing "
471  "approach."
472  << std::endl;
473  return vpMatrix();
474  }
475 
476  return m_covarianceMatrix;
477  }
478 
484  inline double getDetectionTime() const { return m_detectionTime; }
485 
493  inline cv::Ptr<cv::FeatureDetector> getDetector(const vpFeatureDetectorType &type) const
494  {
495  std::map<vpFeatureDetectorType, std::string>::const_iterator it_name = m_mapOfDetectorNames.find(type);
496  if (it_name == m_mapOfDetectorNames.end()) {
497  std::cerr << "Internal problem with the feature type and the "
498  "corresponding name!"
499  << std::endl;
500  }
501 
502  std::map<std::string, cv::Ptr<cv::FeatureDetector> >::const_iterator findDetector =
503  m_detectors.find(it_name->second);
504  if (findDetector != m_detectors.end()) {
505  return findDetector->second;
506  }
507 
508  std::cerr << "Cannot find: " << it_name->second << std::endl;
509  return cv::Ptr<cv::FeatureDetector>();
510  }
511 
519  inline cv::Ptr<cv::FeatureDetector> getDetector(const std::string &name) const
520  {
521  std::map<std::string, cv::Ptr<cv::FeatureDetector> >::const_iterator findDetector = m_detectors.find(name);
522  if (findDetector != m_detectors.end()) {
523  return findDetector->second;
524  }
525 
526  std::cerr << "Cannot find: " << name << std::endl;
527  return cv::Ptr<cv::FeatureDetector>();
528  }
529 
533  inline std::map<vpFeatureDetectorType, std::string> getDetectorNames() const { return m_mapOfDetectorNames; }
534 
540  inline double getExtractionTime() const { return m_extractionTime; }
541 
549  inline cv::Ptr<cv::DescriptorExtractor> getExtractor(const vpFeatureDescriptorType &type) const
550  {
551  std::map<vpFeatureDescriptorType, std::string>::const_iterator it_name = m_mapOfDescriptorNames.find(type);
552  if (it_name == m_mapOfDescriptorNames.end()) {
553  std::cerr << "Internal problem with the feature type and the "
554  "corresponding name!"
555  << std::endl;
556  }
557 
558  std::map<std::string, cv::Ptr<cv::DescriptorExtractor> >::const_iterator findExtractor =
559  m_extractors.find(it_name->second);
560  if (findExtractor != m_extractors.end()) {
561  return findExtractor->second;
562  }
563 
564  std::cerr << "Cannot find: " << it_name->second << std::endl;
565  return cv::Ptr<cv::DescriptorExtractor>();
566  }
567 
575  inline cv::Ptr<cv::DescriptorExtractor> getExtractor(const std::string &name) const
576  {
577  std::map<std::string, cv::Ptr<cv::DescriptorExtractor> >::const_iterator findExtractor = m_extractors.find(name);
578  if (findExtractor != m_extractors.end()) {
579  return findExtractor->second;
580  }
581 
582  std::cerr << "Cannot find: " << name << std::endl;
583  return cv::Ptr<cv::DescriptorExtractor>();
584  }
585 
589  inline std::map<vpFeatureDescriptorType, std::string> getExtractorNames() const { return m_mapOfDescriptorNames; }
590 
596  inline vpImageFormatType getImageFormat() const { return m_imageFormat; }
597 
603  inline double getMatchingTime() const { return m_matchingTime; }
604 
610  inline cv::Ptr<cv::DescriptorMatcher> getMatcher() const { return m_matcher; }
611 
618  inline std::vector<cv::DMatch> getMatches() const { return m_filteredMatches; }
619 
627  inline std::vector<std::pair<cv::KeyPoint, cv::KeyPoint> > getMatchQueryToTrainKeyPoints() const
628  {
629  std::vector<std::pair<cv::KeyPoint, cv::KeyPoint> > matchQueryToTrainKeyPoints(m_filteredMatches.size());
630  for (size_t i = 0; i < m_filteredMatches.size(); i++) {
631  matchQueryToTrainKeyPoints.push_back(
632  std::pair<cv::KeyPoint, cv::KeyPoint>(m_queryFilteredKeyPoints[(size_t)m_filteredMatches[i].queryIdx],
633  m_trainKeyPoints[(size_t)m_filteredMatches[i].trainIdx]));
634  }
635  return matchQueryToTrainKeyPoints;
636  }
637 
643  inline unsigned int getNbImages() const {
644  return static_cast<unsigned int>(m_mapOfImages.size());
645  }
646 
647  void getObjectPoints(std::vector<cv::Point3f> &objectPoints) const;
648  void getObjectPoints(std::vector<vpPoint> &objectPoints) const;
649 
655  inline double getPoseTime() const { return m_poseTime; }
656 
663  inline cv::Mat getQueryDescriptors() const { return m_queryDescriptors; }
664 
665  void getQueryKeyPoints(std::vector<cv::KeyPoint> &keyPoints, bool matches = true) const;
666  void getQueryKeyPoints(std::vector<vpImagePoint> &keyPoints, bool matches = true) const;
667 
673  inline std::vector<vpImagePoint> getRansacInliers() const { return m_ransacInliers; }
674 
680  inline std::vector<vpImagePoint> getRansacOutliers() const { return m_ransacOutliers; }
681 
688  inline cv::Mat getTrainDescriptors() const { return m_trainDescriptors; }
689 
690  void getTrainKeyPoints(std::vector<cv::KeyPoint> &keyPoints) const;
691  void getTrainKeyPoints(std::vector<vpImagePoint> &keyPoints) const;
692 
693  void getTrainPoints(std::vector<cv::Point3f> &points) const;
694  void getTrainPoints(std::vector<vpPoint> &points) const;
695 
696  void initMatcher(const std::string &matcherName);
697 
698  void insertImageMatching(const vpImage<unsigned char> &IRef, const vpImage<unsigned char> &ICurrent,
699  vpImage<unsigned char> &IMatching);
700  void insertImageMatching(const vpImage<unsigned char> &ICurrent, vpImage<unsigned char> &IMatching);
701 
702  void insertImageMatching(const vpImage<vpRGBa> &IRef, const vpImage<vpRGBa> &ICurrent,
703  vpImage<vpRGBa> &IMatching);
704  void insertImageMatching(const vpImage<vpRGBa> &ICurrent, vpImage<vpRGBa> &IMatching);
705 
706  void loadConfigFile(const std::string &configFile);
707 
708  void loadLearningData(const std::string &filename, bool binaryMode = false, bool append = false);
709 
710  void match(const cv::Mat &trainDescriptors, const cv::Mat &queryDescriptors, std::vector<cv::DMatch> &matches,
711  double &elapsedTime);
712 
713  unsigned int matchPoint(const vpImage<unsigned char> &I);
714  unsigned int matchPoint(const vpImage<unsigned char> &I, const vpImagePoint &iP, unsigned int height,
715  unsigned int width);
716  unsigned int matchPoint(const vpImage<unsigned char> &I, const vpRect &rectangle);
717 
718  unsigned int matchPoint(const std::vector<cv::KeyPoint> &queryKeyPoints, const cv::Mat &queryDescriptors);
720  bool (*func)(const vpHomogeneousMatrix &) = NULL, const vpRect &rectangle = vpRect());
722  double &error, double &elapsedTime, bool (*func)(const vpHomogeneousMatrix &) = NULL,
723  const vpRect &rectangle = vpRect());
724 
725  bool matchPointAndDetect(const vpImage<unsigned char> &I, vpRect &boundingBox, vpImagePoint &centerOfGravity,
726  const bool isPlanarObject = true, std::vector<vpImagePoint> *imPts1 = NULL,
727  std::vector<vpImagePoint> *imPts2 = NULL, double *meanDescriptorDistance = NULL,
728  double *detectionScore = NULL, const vpRect &rectangle = vpRect());
729 
730  bool matchPointAndDetect(const vpImage<unsigned char> &I, const vpCameraParameters &cam, vpHomogeneousMatrix &cMo,
731  double &error, double &elapsedTime, vpRect &boundingBox, vpImagePoint &centerOfGravity,
732  bool (*func)(const vpHomogeneousMatrix &) = NULL, const vpRect &rectangle = vpRect());
733 
734  unsigned int matchPoint(const vpImage<vpRGBa> &I_color);
735  unsigned int matchPoint(const vpImage<vpRGBa> &I_color, const vpImagePoint &iP, unsigned int height,
736  unsigned int width);
737  unsigned int matchPoint(const vpImage<vpRGBa> &I_color, const vpRect &rectangle);
738 
739  bool matchPoint(const vpImage<vpRGBa> &I_color, const vpCameraParameters &cam, vpHomogeneousMatrix &cMo,
740  bool (*func)(const vpHomogeneousMatrix &) = NULL, const vpRect &rectangle = vpRect());
741  bool matchPoint(const vpImage<vpRGBa> &I_color, const vpCameraParameters &cam, vpHomogeneousMatrix &cMo,
742  double &error, double &elapsedTime, bool (*func)(const vpHomogeneousMatrix &) = NULL,
743  const vpRect &rectangle = vpRect());
744 
745  void reset();
746 
747  void saveLearningData(const std::string &filename, bool binaryMode = false,
748  bool saveTrainingImages = true);
749 
756  inline void setCovarianceComputation(const bool &flag)
757  {
758  m_computeCovariance = flag;
759  if (!m_useRansacVVS) {
760  std::cout << "Warning : The covariance matrix can only be computed "
761  "with a Virtual Visual Servoing approach."
762  << std::endl
763  << "Use setUseRansacVVS(true) to choose to use a pose "
764  "estimation method based on a Virtual "
765  "Visual Servoing approach."
766  << std::endl;
767  }
768  }
769 
775  inline void setDetectionMethod(const vpDetectionMethodType &method) { m_detectionMethod = method; }
776 
782  inline void setDetector(const vpFeatureDetectorType &detectorType)
783  {
784  m_detectorNames.clear();
785  m_detectorNames.push_back(m_mapOfDetectorNames[detectorType]);
786  m_detectors.clear();
787  initDetector(m_mapOfDetectorNames[detectorType]);
788  }
789 
795  inline void setDetector(const std::string &detectorName)
796  {
797  m_detectorNames.clear();
798  m_detectorNames.push_back(detectorName);
799  m_detectors.clear();
800  initDetector(detectorName);
801  }
802 
803 #if (VISP_HAVE_OPENCV_VERSION >= 0x020400 && VISP_HAVE_OPENCV_VERSION < 0x030000)
804 
812  template <typename T1, typename T2, typename T3>
813  inline void setDetectorParameter(const T1 detectorName, const T2 parameterName, const T3 value)
814  {
815  if (m_detectors.find(detectorName) != m_detectors.end()) {
816  m_detectors[detectorName]->set(parameterName, value);
817  }
818  }
819 #endif
820 
827  inline void setDetectors(const std::vector<std::string> &detectorNames)
828  {
829  m_detectorNames.clear();
830  m_detectors.clear();
831  m_detectorNames = detectorNames;
832  initDetectors(m_detectorNames);
833  }
834 
840  inline void setExtractor(const vpFeatureDescriptorType &extractorType)
841  {
842  m_extractorNames.clear();
843  m_extractorNames.push_back(m_mapOfDescriptorNames[extractorType]);
844  m_extractors.clear();
845  initExtractor(m_mapOfDescriptorNames[extractorType]);
846  }
847 
854  inline void setExtractor(const std::string &extractorName)
855  {
856  m_extractorNames.clear();
857  m_extractorNames.push_back(extractorName);
858  m_extractors.clear();
859  initExtractor(extractorName);
860  }
861 
862 #if (VISP_HAVE_OPENCV_VERSION >= 0x020400 && VISP_HAVE_OPENCV_VERSION < 0x030000)
863 
871  template <typename T1, typename T2, typename T3>
872  inline void setExtractorParameter(const T1 extractorName, const T2 parameterName, const T3 value)
873  {
874  if (m_extractors.find(extractorName) != m_extractors.end()) {
875  m_extractors[extractorName]->set(parameterName, value);
876  }
877  }
878 #endif
879 
886  inline void setExtractors(const std::vector<std::string> &extractorNames)
887  {
888  m_extractorNames.clear();
889  m_extractorNames = extractorNames;
890  m_extractors.clear();
891  initExtractors(m_extractorNames);
892  }
893 
899  inline void setImageFormat(const vpImageFormatType &imageFormat) { m_imageFormat = imageFormat; }
900 
916  inline void setMatcher(const std::string &matcherName)
917  {
918  m_matcherName = matcherName;
919  initMatcher(m_matcherName);
920  }
921 
927  void setMaxFeatures(int maxFeatures)
928  {
929  m_maxFeatures = maxFeatures;
930  }
931 
947  inline void setFilterMatchingType(const vpFilterMatchingType &filterType)
948  {
949  m_filterType = filterType;
950 
951  // Use k-nearest neighbors (knn) to retrieve the two best matches for a
952  // keypoint So this is useful only for ratioDistanceThreshold method
953  if (filterType == ratioDistanceThreshold || filterType == stdAndRatioDistanceThreshold) {
954  m_useKnn = true;
955 
956 #if (VISP_HAVE_OPENCV_VERSION >= 0x020400 && VISP_HAVE_OPENCV_VERSION < 0x030000)
957  if (m_matcher != NULL && m_matcherName == "BruteForce") {
958  // if a matcher is already initialized, disable the crossCheck
959  // because it will not work with knnMatch
960  m_matcher->set("crossCheck", false);
961  }
962 #endif
963  } else {
964  m_useKnn = false;
965 
966 #if (VISP_HAVE_OPENCV_VERSION >= 0x020400 && VISP_HAVE_OPENCV_VERSION < 0x030000)
967  if (m_matcher != NULL && m_matcherName == "BruteForce") {
968  // if a matcher is already initialized, set the crossCheck mode if
969  // necessary
970  m_matcher->set("crossCheck", m_useBruteForceCrossCheck);
971  }
972 #endif
973  }
974  }
975 
982  inline void setMatchingFactorThreshold(const double factor)
983  {
984  if (factor > 0.0) {
985  m_matchingFactorThreshold = factor;
986  } else {
987  throw vpException(vpException::badValue, "The factor must be positive.");
988  }
989  }
990 
996  inline void setMatchingRatioThreshold(double ratio)
997  {
998  if (ratio > 0.0 && (ratio < 1.0 || std::fabs(ratio - 1.0) < std::numeric_limits<double>::epsilon())) {
999  m_matchingRatioThreshold = ratio;
1000  } else {
1001  throw vpException(vpException::badValue, "The ratio must be in the interval ]0 ; 1].");
1002  }
1003  }
1004 
1011  inline void setRansacConsensusPercentage(double percentage)
1012  {
1013  if (percentage > 0.0 &&
1014  (percentage < 100.0 || std::fabs(percentage - 100.0) < std::numeric_limits<double>::epsilon())) {
1015  m_ransacConsensusPercentage = percentage;
1016  } else {
1017  throw vpException(vpException::badValue, "The percentage must be in the interval ]0 ; 100].");
1018  }
1019  }
1020 
1025  {
1026  m_ransacFilterFlag = flag;
1027  }
1028 
1035  inline void setRansacIteration(int nbIter)
1036  {
1037  if (nbIter > 0) {
1038  m_nbRansacIterations = nbIter;
1039  } else {
1040  throw vpException(vpException::badValue, "The number of iterations must be greater than zero.");
1041  }
1042  }
1043 
1049  inline void setRansacParallel(bool parallel)
1050  {
1051  m_ransacParallel = parallel;
1052  }
1053 
1060  inline void setRansacParallelNbThreads(unsigned int nthreads)
1061  {
1062  m_ransacParallelNbThreads = nthreads;
1063  }
1064 
1072  inline void setRansacReprojectionError(double reprojectionError)
1073  {
1074  if (reprojectionError > 0.0) {
1075  m_ransacReprojectionError = reprojectionError;
1076  } else {
1077  throw vpException(vpException::badValue, "The Ransac reprojection "
1078  "threshold must be positive "
1079  "as we deal with distance.");
1080  }
1081  }
1082 
1088  inline void setRansacMinInlierCount(int minCount)
1089  {
1090  if (minCount > 0) {
1091  m_nbRansacMinInlierCount = minCount;
1092  } else {
1093  throw vpException(vpException::badValue, "The minimum number of inliers must be greater than zero.");
1094  }
1095  }
1096 
1103  inline void setRansacThreshold(double threshold)
1104  {
1105  if (threshold > 0.0) {
1106  m_ransacThreshold = threshold;
1107  } else {
1108  throw vpException(vpException::badValue, "The Ransac threshold must be positive as we deal with distance.");
1109  }
1110  }
1111 
1119  inline void setUseAffineDetection(bool useAffine) { m_useAffineDetection = useAffine; }
1120 
1121 #if (VISP_HAVE_OPENCV_VERSION >= 0x020400 && VISP_HAVE_OPENCV_VERSION < 0x030000)
1122 
1128  inline void setUseBruteForceCrossCheck(bool useCrossCheck)
1129  {
1130  // Only available with BruteForce and with k=1 (i.e not used with a
1131  // ratioDistanceThreshold method)
1132  if (m_matcher != NULL && !m_useKnn && m_matcherName == "BruteForce") {
1133  m_matcher->set("crossCheck", useCrossCheck);
1134  } else if (m_matcher != NULL && m_useKnn && m_matcherName == "BruteForce") {
1135  std::cout << "Warning, you try to set the crossCheck parameter with a "
1136  "BruteForce matcher but knn is enabled";
1137  std::cout << " (the filtering method uses a ratio constraint)" << std::endl;
1138  }
1139  }
1140 #endif
1141 
1148  inline void setUseMatchTrainToQuery(bool useMatchTrainToQuery)
1149  {
1150  m_useMatchTrainToQuery = useMatchTrainToQuery;
1151  }
1152 
1160  inline void setUseRansacConsensusPercentage(bool usePercentage) { m_useConsensusPercentage = usePercentage; }
1161 
1169  inline void setUseRansacVVS(bool ransacVVS) { m_useRansacVVS = ransacVVS; }
1170 
1177  inline void setUseSingleMatchFilter(bool singleMatchFilter) { m_useSingleMatchFilter = singleMatchFilter; }
1178 
1179 private:
1182  bool m_computeCovariance;
1184  vpMatrix m_covarianceMatrix;
1186  int m_currentImageId;
1189  vpDetectionMethodType m_detectionMethod;
1191  double m_detectionScore;
1194  double m_detectionThreshold;
1196  double m_detectionTime;
1198  std::vector<std::string> m_detectorNames;
1201  // with a key based upon the detector name.
1202  std::map<std::string, cv::Ptr<cv::FeatureDetector> > m_detectors;
1204  double m_extractionTime;
1206  std::vector<std::string> m_extractorNames;
1209  // with a key based upon the extractor name.
1210  std::map<std::string, cv::Ptr<cv::DescriptorExtractor> > m_extractors;
1212  std::vector<cv::DMatch> m_filteredMatches;
1214  vpFilterMatchingType m_filterType;
1216  vpImageFormatType m_imageFormat;
1219  std::vector<std::vector<cv::DMatch> > m_knnMatches;
1221  std::map<vpFeatureDescriptorType, std::string> m_mapOfDescriptorNames;
1223  std::map<vpFeatureDetectorType, std::string> m_mapOfDetectorNames;
1226  std::map<int, int> m_mapOfImageId;
1229  std::map<int, vpImage<unsigned char> > m_mapOfImages;
1232  cv::Ptr<cv::DescriptorMatcher> m_matcher;
1234  std::string m_matcherName;
1236  std::vector<cv::DMatch> m_matches;
1238  double m_matchingFactorThreshold;
1240  double m_matchingRatioThreshold;
1242  double m_matchingTime;
1244  std::vector<std::pair<cv::KeyPoint, cv::Point3f> > m_matchRansacKeyPointsToPoints;
1246  int m_nbRansacIterations;
1248  int m_nbRansacMinInlierCount;
1251  std::vector<cv::Point3f> m_objectFilteredPoints;
1253  double m_poseTime;
1256  cv::Mat m_queryDescriptors;
1258  std::vector<cv::KeyPoint> m_queryFilteredKeyPoints;
1260  std::vector<cv::KeyPoint> m_queryKeyPoints;
1263  double m_ransacConsensusPercentage;
1265  vpPose::RANSAC_FILTER_FLAGS m_ransacFilterFlag;
1267  std::vector<vpImagePoint> m_ransacInliers;
1269  std::vector<vpImagePoint> m_ransacOutliers;
1271  bool m_ransacParallel;
1273  unsigned int m_ransacParallelNbThreads;
1276  double m_ransacReprojectionError;
1279  double m_ransacThreshold;
1282  // detected in the train images).
1283  cv::Mat m_trainDescriptors;
1285  std::vector<cv::KeyPoint> m_trainKeyPoints;
1288  std::vector<cv::Point3f> m_trainPoints;
1291  std::vector<vpPoint> m_trainVpPoints;
1294  bool m_useAffineDetection;
1295 #if (VISP_HAVE_OPENCV_VERSION >= 0x020400 && VISP_HAVE_OPENCV_VERSION < 0x030000)
1296  bool m_useBruteForceCrossCheck;
1300 #endif
1301  bool m_useConsensusPercentage;
1305  bool m_useKnn;
1310  bool m_useMatchTrainToQuery;
1312  bool m_useRansacVVS;
1315  bool m_useSingleMatchFilter;
1319  int m_maxFeatures;
1320 
1321  void affineSkew(double tilt, double phi, cv::Mat &img, cv::Mat &mask, cv::Mat &Ai);
1322 
1323  double computePoseEstimationError(const std::vector<std::pair<cv::KeyPoint, cv::Point3f> > &matchKeyPoints,
1324  const vpCameraParameters &cam, const vpHomogeneousMatrix &cMo_est);
1325 
1326  void filterMatches();
1327 
1328  void init();
1329  void initDetector(const std::string &detectorNames);
1330  void initDetectors(const std::vector<std::string> &detectorNames);
1331 
1332  void initExtractor(const std::string &extractorName);
1333  void initExtractors(const std::vector<std::string> &extractorNames);
1334 
1335  void initFeatureNames();
1336 
1337  inline size_t myKeypointHash(const cv::KeyPoint &kp)
1338  {
1339  size_t _Val = 2166136261U, scale = 16777619U;
1340  Cv32suf u;
1341  u.f = kp.pt.x;
1342  _Val = (scale * _Val) ^ u.u;
1343  u.f = kp.pt.y;
1344  _Val = (scale * _Val) ^ u.u;
1345  u.f = kp.size;
1346  _Val = (scale * _Val) ^ u.u;
1347  // As the keypoint angle can be computed for certain type of keypoint only
1348  // when extracting the corresponding descriptor, the angle field is not
1349  // taking into account for the hash
1350  // u.f = kp.angle; _Val = (scale * _Val) ^ u.u;
1351  u.f = kp.response;
1352  _Val = (scale * _Val) ^ u.u;
1353  _Val = (scale * _Val) ^ ((size_t)kp.octave);
1354  _Val = (scale * _Val) ^ ((size_t)kp.class_id);
1355  return _Val;
1356  }
1357 
1358 #if (VISP_HAVE_OPENCV_VERSION >= 0x030000)
1359  /*
1360  * Adapts a detector to detect points over multiple levels of a Gaussian
1361  * pyramid. Useful for detectors that are not inherently scaled.
1362  * From OpenCV 2.4.11 source code.
1363  */
1364  class PyramidAdaptedFeatureDetector : public cv::FeatureDetector
1365  {
1366  public:
1367  // maxLevel - The 0-based index of the last pyramid layer
1368  PyramidAdaptedFeatureDetector(const cv::Ptr<cv::FeatureDetector> &detector, int maxLevel = 2);
1369 
1370  // TODO implement read/write
1371  virtual bool empty() const;
1372 
1373  protected:
1374  virtual void detect(cv::InputArray image, CV_OUT std::vector<cv::KeyPoint> &keypoints,
1375  cv::InputArray mask = cv::noArray());
1376  virtual void detectImpl(const cv::Mat &image, std::vector<cv::KeyPoint> &keypoints,
1377  const cv::Mat &mask = cv::Mat()) const;
1378 
1379  cv::Ptr<cv::FeatureDetector> detector;
1380  int maxLevel;
1381  };
1382 
1383  /*
1384  * A class filters a vector of keypoints.
1385  * Because now it is difficult to provide a convenient interface for all
1386  * usage scenarios of the keypoints filter class, it has only several needed
1387  * by now static methods.
1388  */
1389  class KeyPointsFilter
1390  {
1391  public:
1392  KeyPointsFilter() {}
1393 
1394  /*
1395  * Remove keypoints within borderPixels of an image edge.
1396  */
1397  static void runByImageBorder(std::vector<cv::KeyPoint> &keypoints, cv::Size imageSize, int borderSize);
1398  /*
1399  * Remove keypoints of sizes out of range.
1400  */
1401  static void runByKeypointSize(std::vector<cv::KeyPoint> &keypoints, float minSize, float maxSize = FLT_MAX);
1402  /*
1403  * Remove keypoints from some image by mask for pixels of this image.
1404  */
1405  static void runByPixelsMask(std::vector<cv::KeyPoint> &keypoints, const cv::Mat &mask);
1406  /*
1407  * Remove duplicated keypoints.
1408  */
1409  static void removeDuplicated(std::vector<cv::KeyPoint> &keypoints);
1410 
1411  /*
1412  * Retain the specified number of the best keypoints (according to the
1413  * response)
1414  */
1415  static void retainBest(std::vector<cv::KeyPoint> &keypoints, int npoints);
1416  };
1417 
1418 #endif
1419 };
1420 
1421 #endif
1422 #endif
Used to indicate that a value is not in the allowed range.
Definition: vpException.h:97
Implementation of a matrix and operations on matrices.
Definition: vpMatrix.h:153
cv::Ptr< cv::FeatureDetector > getDetector(const vpFeatureDetectorType &type) const
Definition: vpKeyPoint.h:493
class that defines what is a Keypoint. This class provides all the basic elements to implement classe...
void setUseMatchTrainToQuery(bool useMatchTrainToQuery)
Definition: vpKeyPoint.h:1148
void setUseRansacConsensusPercentage(bool usePercentage)
Definition: vpKeyPoint.h:1160
std::vector< std::pair< cv::KeyPoint, cv::KeyPoint > > getMatchQueryToTrainKeyPoints() const
Definition: vpKeyPoint.h:627
void setRansacIteration(int nbIter)
Definition: vpKeyPoint.h:1035
Implementation of an homogeneous matrix and operations on such kind of matrices.
void setRansacMinInlierCount(int minCount)
Definition: vpKeyPoint.h:1088
cv::Ptr< cv::DescriptorMatcher > getMatcher() const
Definition: vpKeyPoint.h:610
void setExtractor(const std::string &extractorName)
Definition: vpKeyPoint.h:854
Class to define RGB colors available for display functionnalities.
Definition: vpColor.h:157
std::map< vpFeatureDetectorType, std::string > getDetectorNames() const
Definition: vpKeyPoint.h:533
double getDetectionTime() const
Definition: vpKeyPoint.h:484
error that can be emited by ViSP classes.
Definition: vpException.h:71
void setDetectors(const std::vector< std::string > &detectorNames)
Definition: vpKeyPoint.h:827
void setMaxFeatures(int maxFeatures)
Definition: vpKeyPoint.h:927
cv::Mat getTrainDescriptors() const
Definition: vpKeyPoint.h:688
vpMatrix getCovarianceMatrix() const
Definition: vpKeyPoint.h:456
void setRansacParallel(bool parallel)
Definition: vpKeyPoint.h:1049
static const vpColor green
Definition: vpColor.h:220
Class that defines a 3D point in the object frame and allows forward projection of a 3D point in the ...
Definition: vpPoint.h:81
std::vector< vpImagePoint > getRansacOutliers() const
Definition: vpKeyPoint.h:680
void setExtractors(const std::vector< std::string > &extractorNames)
Definition: vpKeyPoint.h:886
void setMatcher(const std::string &matcherName)
Definition: vpKeyPoint.h:916
void setRansacFilterFlag(const vpPose::RANSAC_FILTER_FLAGS &flag)
Definition: vpKeyPoint.h:1024
cv::Mat getQueryDescriptors() const
Definition: vpKeyPoint.h:663
std::map< vpFeatureDescriptorType, std::string > getExtractorNames() const
Definition: vpKeyPoint.h:589
std::vector< vpImagePoint > getRansacInliers() const
Definition: vpKeyPoint.h:673
vpFeatureDetectorType
Definition: vpKeyPoint.h:258
virtual unsigned int buildReference(const vpImage< unsigned char > &I)=0
Generic class defining intrinsic camera parameters.
vpFeatureDescriptorType
Definition: vpKeyPoint.h:289
void setDetector(const vpFeatureDetectorType &detectorType)
Definition: vpKeyPoint.h:782
void setUseAffineDetection(bool useAffine)
Definition: vpKeyPoint.h:1119
double getPoseTime() const
Definition: vpKeyPoint.h:655
void setRansacConsensusPercentage(double percentage)
Definition: vpKeyPoint.h:1011
unsigned int getNbImages() const
Definition: vpKeyPoint.h:643
void setDetectionMethod(const vpDetectionMethodType &method)
Definition: vpKeyPoint.h:775
void setMatchingRatioThreshold(double ratio)
Definition: vpKeyPoint.h:996
void setUseSingleMatchFilter(bool singleMatchFilter)
Definition: vpKeyPoint.h:1177
void setImageFormat(const vpImageFormatType &imageFormat)
Definition: vpKeyPoint.h:899
virtual void display(const vpImage< unsigned char > &Iref, const vpImage< unsigned char > &Icurrent, unsigned int size=3)=0
void setRansacParallelNbThreads(unsigned int nthreads)
Definition: vpKeyPoint.h:1060
void setUseRansacVVS(bool ransacVVS)
Definition: vpKeyPoint.h:1169
virtual unsigned int matchPoint(const vpImage< unsigned char > &I)=0
cv::Ptr< cv::DescriptorExtractor > getExtractor(const std::string &name) const
Definition: vpKeyPoint.h:575
Class that allows keypoints detection (and descriptors extraction) and matching thanks to OpenCV libr...
Definition: vpKeyPoint.h:222
cv::Ptr< cv::FeatureDetector > getDetector(const std::string &name) const
Definition: vpKeyPoint.h:519
vpDetectionMethodType
Definition: vpKeyPoint.h:241
double getExtractionTime() const
Definition: vpKeyPoint.h:540
vpFilterMatchingType
Definition: vpKeyPoint.h:227
std::vector< cv::DMatch > getMatches() const
Definition: vpKeyPoint.h:618
double getMatchingTime() const
Definition: vpKeyPoint.h:603
cv::Ptr< cv::DescriptorExtractor > getExtractor(const vpFeatureDescriptorType &type) const
Definition: vpKeyPoint.h:549
void setDetector(const std::string &detectorName)
Definition: vpKeyPoint.h:795
Defines a rectangle in the plane.
Definition: vpRect.h:79
vpImageFormatType getImageFormat() const
Definition: vpKeyPoint.h:596
void setRansacThreshold(double threshold)
Definition: vpKeyPoint.h:1103
void setRansacReprojectionError(double reprojectionError)
Definition: vpKeyPoint.h:1072
Class that defines a 2D point in an image. This class is useful for image processing and stores only ...
Definition: vpImagePoint.h:87
void setFilterMatchingType(const vpFilterMatchingType &filterType)
Definition: vpKeyPoint.h:947
void setMatchingFactorThreshold(const double factor)
Definition: vpKeyPoint.h:982
void setExtractor(const vpFeatureDescriptorType &extractorType)
Definition: vpKeyPoint.h:840
void setCovarianceComputation(const bool &flag)
Definition: vpKeyPoint.h:756
RANSAC_FILTER_FLAGS
Definition: vpPose.h:103