Add processor_image_params.h to store parameters used by both image

processors

src/examples/processor_image_ORB.yaml

@@ -7,7 +7,6 @@ image:
 
 detector-descriptor:
     type: "ORB"         # This affects the structure below. See processor_image_BRISK.yaml for another example
-    nominal pattern radius: 2 # 0 # 18?
     nfeatures: 500
     scale factor: 1.2
     nlevels: 8
@@ -27,7 +26,7 @@ matcher:
 active search:
     grid width: 10
     grid height: 8
-    separation: 0
+    separation: 5
 
 algorithm:
     maximum new features: 40

src/examples/test_tracker_ORB.cpp

@@ -16,7 +16,8 @@ int main(int argc, char** argv)
     const char * filename;
     if (argc == 1)
     {
-        filename = "/home/jtarraso/Vídeos/gray.mp4";
+//        filename = "/home/jtarraso/Vídeos/gray.mp4";
+        filename = "/home/jtarraso/Imágenes/Test_ORB.png";
         capture.open(filename);
     }
     else if (std::string(argv[1]) == "0")

src/examples/test_yaml.cpp

@@ -96,7 +96,6 @@ int main()
         {
             DetectorDescriptorParamsOrb* dd = new DetectorDescriptorParamsOrb;
             dd->type                    = DD_ORB;
-            dd->nominal_pattern_radius  = dd_yaml["nominal pattern radius"].as<unsigned int>();
             dd->nfeatures               = dd_yaml["nfeatures"].as<unsigned int>();
             dd->scaleFactor             = dd_yaml["scale factor"].as<float>();
             dd->nlevels                 = dd_yaml["nlevels"].as<unsigned int>();

src/processor_image.cpp

@@ -25,8 +25,8 @@ ProcessorImage::ProcessorImage(ProcessorParamsImage _params) :
                                                      params_brisk->octaves, //
                                                      params_brisk->pattern_scale);
 
-            detector_descriptor_params_.pattern_radius_ = std::max((unsigned int)((_dd_params->nominal_pattern_radius)*pow(2,params_brisk->octaves)),
-                                                                   (unsigned int)((_dd_params->nominal_pattern_radius)*params_brisk->pattern_scale));
+            detector_descriptor_params_.pattern_radius_ = std::max((unsigned int)((params_brisk->nominal_pattern_radius)*pow(2,params_brisk->octaves)),
+                                                                   (unsigned int)((params_brisk->nominal_pattern_radius)*params_brisk->pattern_scale));
 
             detector_descriptor_params_.size_bits_ = detector_descriptor_ptr_->descriptorSize() * 8;
 
@@ -44,9 +44,7 @@ ProcessorImage::ProcessorImage(ProcessorParamsImage _params) :
                                                    params_orb->scoreType, //
                                                    params_orb->patchSize);
 
-            detector_descriptor_params_.pattern_radius_ =
-                    (unsigned int)( (_dd_params->nominal_pattern_radius) * pow(params_orb->scaleFactor, params_orb->nlevels-1) );
-
+            detector_descriptor_params_.pattern_radius_ = params_orb->edgeThreshold;
             detector_descriptor_params_.size_bits_ = detector_descriptor_ptr_->descriptorSize() * 8;
 
             break;

src/processor_image.h

@@ -9,6 +9,8 @@
 #include "active_search.h"
 #include "processor_tracker_feature.h"
 #include "constraint_epipolar.h"
+#include "processor_image_params.h"
+
 
 // OpenCV includes
 #include "opencv2/features2d/features2d.hpp"
@@ -24,83 +26,6 @@
 
 namespace wolf {
 
-enum DetectorDescriptorType
-{
-    DD_BRISK,
-    DD_ORB
-};
-
-struct DetectorDescriptorParamsBase
-{
-        DetectorDescriptorType type; ///< Type of algorithm. Accepted values in wolf.h
-        unsigned int nominal_pattern_radius = 18; ///< Radius of the pattern before scaling
-        //should this be here? doesn't it depend on the descriptor?
-};
-
-struct DetectorDescriptorParamsBrisk : public DetectorDescriptorParamsBase
-{
-        unsigned int threshold=30; ///< on the keypoint strength to declare it key-point
-        unsigned int octaves=0; ///< Multi-scale evaluation. 0: no multi-scale
-        float pattern_scale=1.0f; ///< Scale of the base pattern wrt the nominal one
-};
-
-struct DetectorDescriptorParamsOrb : public DetectorDescriptorParamsBase
-{
-        unsigned int nfeatures=500; ///< Nbr of features to extract
-        float scaleFactor=1.2f; ///< Scale factor between two consecutive scales of the image pyramid
-        unsigned int nlevels=1;///< Number of levels in the pyramid. Default: 8
-        unsigned int edgeThreshold=4; ///< ? //Default: 31
-        unsigned int firstLevel=0;
-        unsigned int WTA_K=2;
-        unsigned int scoreType=cv::ORB::HARRIS_SCORE; ///< Type of score to rank the detected points
-        unsigned int patchSize=31;
-};
-
-struct ProcessorParamsImage : public ProcessorParamsBase
-{
-        struct Image
-        {
-                unsigned int width; ///< image width (horizontal dimension or nbr of columns)
-                unsigned int height; ///< image height (vertical dimension or nbr of rows)
-        }image;
-
-        DetectorDescriptorParamsBase* detector_descriptor_params_ptr;
-
-//        struct Detector
-//        {
-//                unsigned int threshold; ///< on the keypoint strength to declare it key-point
-//                unsigned int threshold_new_features; ///< on the keypoint strength to declare it key-point
-//                unsigned int octaves; ///< Multi-scale evaluation. 0: no multi-scale
-//                unsigned int nominal_pattern_radius; ///< Radius of the detector pattern before scaling
-//                unsigned int pattern_radius; ///< radius of the pattern used to detect a key-point at pattern_scale = 1.0 and octaves = 0
-//        }detector;
-//        struct Descriptor
-//        {
-//                unsigned int nominal_pattern_radius; ///< Radius of the descriptor pattern before scaling
-//                float pattern_scale; ///< Scale of the base pattern wrt the nominal one
-//                unsigned int pattern_radius; ///< radius of the pattern used to describe a key-point at pattern_scale = 1.0 and octaves = 0
-//                unsigned int size_bits; ///< length of the descriptor vector in bits
-//        }descriptor;
-        struct Matcher
-        {
-                Scalar min_normalized_score; ///< [-1..0]: awful match; 1: perfect match; out of [-1,1]: error
-                int similarity_norm; ///< Norm used to measure the distance between two descriptors
-                unsigned int roi_width; ///< Width of the roi used in tracking
-                unsigned int roi_height; ///< Height of the roi used in tracking
-        }matcher;
-        struct Active_search
-        {
-                unsigned int grid_width; ///< cells per horizontal dimension of image
-                unsigned int grid_height; ///< cells per vertical dimension of image
-                unsigned int separation; ///< Distance between the border of the cell and the border of the associated ROI
-        }active_search;
-        struct Algorithm
-        {
-                unsigned int max_new_features; ///< Max nbr. of features to detect in one frame
-                unsigned int min_features_for_keyframe; ///< minimum nbr. of features to vote for keyframe
-        }algorithm;
-};
-
 class ProcessorImage : public ProcessorTrackerFeature
 {
 

src/processor_image_landmark.cpp

@@ -31,8 +31,8 @@ ProcessorImageLandmark::ProcessorImageLandmark(ProcessorParamsImage _params) :
                                                      params_brisk->octaves, //
                                                      params_brisk->pattern_scale);
 
-            detector_descriptor_params_.pattern_radius_ = std::max((unsigned int)((_dd_params->nominal_pattern_radius)*pow(2,params_brisk->octaves)),
-                                                                   (unsigned int)((_dd_params->nominal_pattern_radius)*params_brisk->pattern_scale));
+            detector_descriptor_params_.pattern_radius_ = std::max((unsigned int)((params_brisk->nominal_pattern_radius)*pow(2,params_brisk->octaves)),
+                                                                   (unsigned int)((params_brisk->nominal_pattern_radius)*params_brisk->pattern_scale));
 
             detector_descriptor_params_.size_bits_ = detector_descriptor_ptr_->descriptorSize() * 8;
 
@@ -50,13 +50,9 @@ ProcessorImageLandmark::ProcessorImageLandmark(ProcessorParamsImage _params) :
                                                    params_orb->scoreType, //
                                                    params_orb->patchSize);
 
-            detector_descriptor_params_.pattern_radius_ =
-                    (unsigned int)( (_dd_params->nominal_pattern_radius) * pow(params_orb->scaleFactor, params_orb->nlevels-1) );
-
-            std::cout << "nominal pattern radius: " << _dd_params->nominal_pattern_radius << std::endl;
-            std::cout << "scale factor: " << params_orb->scaleFactor << std::endl;
-            std::cout << "nlevels: " << params_orb->nlevels << std::endl;
+            std::cout << "===================edgeTh size: " << params_orb->edgeThreshold << std::endl;
 
+            detector_descriptor_params_.pattern_radius_ = params_orb->edgeThreshold;
             detector_descriptor_params_.size_bits_ = detector_descriptor_ptr_->descriptorSize() * 8;
 
             break;
@@ -465,7 +461,7 @@ void ProcessorImageLandmark::inflateRoi(cv::Rect& _roi)
 void ProcessorImageLandmark::adaptRoi(cv::Mat& _image_roi, cv::Mat _image, cv::Rect& _roi)
 {
 
-    //inflateRoi(_roi);
+    inflateRoi(_roi);
     trimRoi(_roi);
 
     tracker_roi_inflated_.push_back(_roi);

src/processor_image_landmark.h

@@ -9,8 +9,8 @@
 #include "state_quaternion.h"
 #include "active_search.h"
 #include "processor_tracker_landmark.h"
-#include "constraint_epipolar.h"
 #include "landmark_AHP.h"
+#include "processor_image_params.h"
 
 // OpenCV includes
 #include "opencv2/features2d/features2d.hpp"
@@ -25,68 +25,6 @@
 
 namespace wolf {
 
-enum DetectorDescriptorType
-{
-    DD_BRISK,
-    DD_ORB
-};
-
-struct DetectorDescriptorParamsBase
-{
-        DetectorDescriptorType type; ///< Type of algorithm. Accepted values in wolf.h
-        unsigned int nominal_pattern_radius = 0; ///< Radius of the pattern before scaling //18 for brisk
-        // should this be here? doesn't it depend on the descriptor?
-};
-
-struct DetectorDescriptorParamsBrisk : public DetectorDescriptorParamsBase
-{
-        unsigned int threshold=30; ///< on the keypoint strength to declare it key-point
-        unsigned int octaves=0; ///< Multi-scale evaluation. 0: no multi-scale
-        float pattern_scale=1.0f; ///< Scale of the base pattern wrt the nominal one
-};
-
-struct DetectorDescriptorParamsOrb : public DetectorDescriptorParamsBase
-{
-        unsigned int nfeatures=500; ///< Nbr of features to extract
-        float scaleFactor=1.2f; ///< Scale factor between two consecutive scales of the image pyramid
-        unsigned int nlevels=1;///< Number of levels in the pyramid. Default: 8
-        unsigned int edgeThreshold=4; ///< ? //Default: 31
-        unsigned int firstLevel=0;
-        unsigned int WTA_K=2;
-        unsigned int scoreType=cv::ORB::HARRIS_SCORE; ///< Type of score to rank the detected points
-        unsigned int patchSize=31;
-};
-
-struct ProcessorParamsImage : public ProcessorParamsBase
-{
-        struct Image
-        {
-                unsigned int width; ///< image width (horizontal dimension or nbr of columns)
-                unsigned int height; ///< image height (vertical dimension or nbr of rows)
-        }image;
-
-        DetectorDescriptorParamsBase* detector_descriptor_params_ptr;
-
-        struct Matcher
-        {
-                Scalar min_normalized_score; ///< [-1..0]: awful match; 1: perfect match; out of [-1,1]: error
-                int similarity_norm; ///< Norm used to measure the distance between two descriptors
-                unsigned int roi_width; ///< Width of the roi used in tracking
-                unsigned int roi_height; ///< Height of the roi used in tracking
-        }matcher;
-        struct Active_search
-        {
-                unsigned int grid_width; ///< cells per horizontal dimension of image
-                unsigned int grid_height; ///< cells per vertical dimension of image
-                unsigned int separation; ///< Distance between the border of the cell and the border of the associated ROI
-        }active_search;
-        struct Algorithm
-        {
-                unsigned int max_new_features; ///< Max nbr. of features to detect in one frame
-                unsigned int min_features_for_keyframe; ///< minimum nbr. of features to vote for keyframe
-        }algorithm;
-};
-
 class ProcessorImageLandmark : public ProcessorTrackerLandmark
 {
     protected:

src/processor_image_params.h

 #ifndef PROCESSOR_IMAGE_PARAMS_H
 #define PROCESSOR_IMAGE_PARAMS_H
 
+namespace wolf
+{
+
+enum DetectorDescriptorType
+{
+    DD_BRISK,
+    DD_ORB
+};
+
+struct DetectorDescriptorParamsBase
+{
+        DetectorDescriptorType type; ///< Type of algorithm. Accepted values in wolf.h
+};
+
+struct DetectorDescriptorParamsBrisk : public DetectorDescriptorParamsBase
+{
+        unsigned int threshold=30; ///< on the keypoint strength to declare it key-point
+        unsigned int octaves=0; ///< Multi-scale evaluation. 0: no multi-scale
+        float pattern_scale=1.0f; ///< Scale of the base pattern wrt the nominal one
+        unsigned int nominal_pattern_radius = 18; ///< Radius of the pattern before scaling //18 for brisk
+};
+
+struct DetectorDescriptorParamsOrb : public DetectorDescriptorParamsBase
+{
+        unsigned int nfeatures=500; ///< Nbr of features to extract
+        float scaleFactor=1.2f; ///< Scale factor between two consecutive scales of the image pyramid
+        unsigned int nlevels=8;///< Number of levels in the pyramid. Default: 8
+        unsigned int edgeThreshold=16; ///< Default: 16
+        unsigned int firstLevel=0;
+        unsigned int WTA_K=2;
+        unsigned int scoreType=cv::ORB::HARRIS_SCORE; ///< Type of score to rank the detected points
+        unsigned int patchSize=31;
+};
+
+struct ProcessorParamsImage : public ProcessorParamsBase
+{
+        struct Image
+        {
+                unsigned int width; ///< image width (horizontal dimension or nbr of columns)
+                unsigned int height; ///< image height (vertical dimension or nbr of rows)
+        }image;
+
+        DetectorDescriptorParamsBase* detector_descriptor_params_ptr;
+
+        struct Matcher
+        {
+                Scalar min_normalized_score; ///< [-1..0]: awful match; 1: perfect match; out of [-1,1]: error
+                int similarity_norm; ///< Norm used to measure the distance between two descriptors
+                unsigned int roi_width; ///< Width of the roi used in tracking
+                unsigned int roi_height; ///< Height of the roi used in tracking
+        }matcher;
+        struct Active_search
+        {
+                unsigned int grid_width; ///< cells per horizontal dimension of image
+                unsigned int grid_height; ///< cells per vertical dimension of image
+                unsigned int separation; ///< Distance between the border of the cell and the border of the associated ROI
+        }active_search;
+        struct Algorithm
+        {
+                unsigned int max_new_features; ///< Max nbr. of features to detect in one frame
+                unsigned int min_features_for_keyframe; ///< minimum nbr. of features to vote for keyframe
+        }algorithm;
+};
+}
+
 #endif // PROCESSOR_IMAGE_PARAMS_H

src/yaml/processor_image_yaml.cpp

@@ -35,11 +35,11 @@ static ProcessorParamsBase* createProcessorParamsImage(const std::string & _file
         {
             DetectorDescriptorParamsOrb* dd = new DetectorDescriptorParamsOrb;
             dd->type                        = DD_ORB;
-            dd->nominal_pattern_radius      = dd_yaml["nominal pattern radius"].as<unsigned int>();
             dd->nfeatures                   = dd_yaml["nfeatures"].as<unsigned int>();
             dd->scaleFactor                 = dd_yaml["scale factor"].as<float>();
             dd->nlevels                     = dd_yaml["nlevels"].as<unsigned int>();
             dd->edgeThreshold               = dd_yaml["edge threshold"].as<unsigned int>();
+            std::cout << "edgeThreshold: " << dd->edgeThreshold << std::endl;
             dd->firstLevel                  = dd_yaml["first level"].as<unsigned int>();
             dd->WTA_K                       = dd_yaml["WTA_K"].as<unsigned int>();
             dd->scoreType                   = dd_yaml["score type"].as<int>(); // enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };