revert orientation computation in jeypoint detection for efficiency (like done originally)

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

@@ -307,6 +307,11 @@ protected:
     void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
     void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
 
+    void computeKeypointsNoOrientation(InputArray image, InputArray mask, vector<KeyPoint>& keypoints) const;
+    void computeDescriptorsAndOrOrientation(InputArray image, InputArray mask, vector<KeyPoint>& keypoints,
+                                       OutputArray descriptors, bool doDescriptors, bool doOrientation,
+                                       bool useProvidedKeypoints) const;
+
     // Feature parameters
     CV_PROP_RW int threshold;
     CV_PROP_RW int octaves;

modules/features2d/src/brisk.cpp

@@ -528,13 +528,28 @@ RoiPredicate(const float minX, const float minY, const float maxX, const float m
 void
 BRISK::operator()( InputArray _image, InputArray _mask, vector<KeyPoint>& keypoints,
                    OutputArray _descriptors, bool useProvidedKeypoints) const
+{
+  bool doOrientation;
+  if (useProvidedKeypoints)
+    doOrientation = false;
+  computeDescriptorsAndOrOrientation(_image, _mask, keypoints, _descriptors, true, doOrientation,
+                                       useProvidedKeypoints);
+}
+
+void
+BRISK::computeDescriptorsAndOrOrientation(InputArray _image, InputArray _mask, vector<KeyPoint>& keypoints,
+                                     OutputArray _descriptors, bool doDescriptors, bool doOrientation,
+                                     bool useProvidedKeypoints) const
 {
   Mat image = _image.getMat(), mask = _mask.getMat();
   if( image.type() != CV_8UC1 )
       cvtColor(image, image, CV_BGR2GRAY);
 
   if (!useProvidedKeypoints)
-    detectImpl(image, keypoints, mask);
+  {
+    doOrientation = true;
+    computeKeypointsNoOrientation(_image, _mask, keypoints);
+  }
 
   //Remove keypoints very close to the border
   size_t ksize = keypoints.size();
@@ -578,9 +593,13 @@ BRISK::operator()( InputArray _image, InputArray _mask, vector<KeyPoint>& keypoi
   int* _values = new int[points_]; // for temporary use
 
   // resize the descriptors:
-  _descriptors.create(ksize, strings_, CV_8U);
-  cv::Mat descriptors = _descriptors.getMat();
-  descriptors.setTo(0);
+  cv::Mat descriptors;
+  if (doDescriptors)
+  {
+    _descriptors.create(ksize, strings_, CV_8U);
+    descriptors = _descriptors.getMat();
+    descriptors.setTo(0);
+  }
 
   // now do the extraction for all keypoints:
 
@@ -592,13 +611,44 @@ BRISK::operator()( InputArray _image, InputArray _mask, vector<KeyPoint>& keypoi
   uchar* ptr = descriptors.data;
   for (size_t k = 0; k < ksize; k++)
   {
-    int theta;
     cv::KeyPoint& kp = keypoints[k];
     const int& scale = kscales[k];
-    int shifter = 0;
     int* pvalues = _values;
     const float& x = kp.pt.x;
     const float& y = kp.pt.y;
+
+    if (doOrientation)
+    {
+        // get the gray values in the unrotated pattern
+        for (unsigned int i = 0; i < points_; i++)
+        {
+          *(pvalues++) = smoothedIntensity(image, _integral, x, y, scale, 0, i);
+        }
+
+        int direction0 = 0;
+        int direction1 = 0;
+        // now iterate through the long pairings
+        const BriskLongPair* max = longPairs_ + noLongPairs_;
+        for (BriskLongPair* iter = longPairs_; iter < max; ++iter)
+        {
+          t1 = *(_values + iter->i);
+          t2 = *(_values + iter->j);
+          const int delta_t = (t1 - t2);
+          // update the direction:
+          const int tmp0 = delta_t * (iter->weighted_dx) / 1024;
+          const int tmp1 = delta_t * (iter->weighted_dy) / 1024;
+          direction0 += tmp0;
+          direction1 += tmp1;
+        }
+        kp.angle = atan2((float) direction1, (float) direction0) / M_PI * 180.0;
+        if (kp.angle < 0)
+          kp.angle += 360;
+    }
+
+    if (!doDescriptors)
+      continue;
+
+    int theta;
     if (kp.angle==-1)
     {
         // don't compute the gradient direction, just assign a rotation of 0°
@@ -615,7 +665,7 @@ BRISK::operator()( InputArray _image, InputArray _mask, vector<KeyPoint>& keypoi
 
     // now also extract the stuff for the actual direction:
     // let us compute the smoothed values
-    shifter = 0;
+    int shifter = 0;
 
     //unsigned int mean=0;
     pvalues = _values;
@@ -675,7 +725,14 @@ BRISK::~BRISK()
 }
 
 void
-BRISK::operator()(InputArray _image, InputArray _mask, vector<KeyPoint>& keypoints) const
+BRISK::operator()(InputArray image, InputArray mask, vector<KeyPoint>& keypoints) const
+{
+  computeKeypointsNoOrientation(image, mask, keypoints);
+  computeDescriptorsAndOrOrientation(image, mask, keypoints, cv::noArray(), false, true, true);
+}
+
+void
+BRISK::computeKeypointsNoOrientation(InputArray _image, InputArray _mask, vector<KeyPoint>& keypoints) const
 {
   Mat image = _image.getMat(), mask = _mask.getMat();
   if( image.type() != CV_8UC1 )
@@ -687,91 +744,6 @@ BRISK::operator()(InputArray _image, InputArray _mask, vector<KeyPoint>& keypoin
 
   // remove invalid points
   removeInvalidPoints(mask, keypoints);
-
-  // Compute the orientations of the keypoints
-  //Remove keypoints very close to the border
-  size_t ksize = keypoints.size();
-  std::vector<int> kscales; // remember the scale per keypoint
-  kscales.resize(ksize);
-  static const float log2 = 0.693147180559945;
-  static const float lb_scalerange = log(scalerange_) / (log2);
-  std::vector<cv::KeyPoint>::iterator beginning = keypoints.begin();
-  std::vector<int>::iterator beginningkscales = kscales.begin();
-  static const float basicSize06 = basicSize_ * 0.6;
-  for (size_t k = 0; k < ksize; k++)
-  {
-    unsigned int scale;
-      scale = std::max((int) (scales_ / lb_scalerange * (log(keypoints[k].size / (basicSize06)) / log2) + 0.5), 0);
-      // saturate
-      if (scale >= scales_)
-        scale = scales_ - 1;
-      kscales[k] = scale;
-    const int border = sizeList_[scale];
-    const int border_x = image.cols - border;
-    const int border_y = image.rows - border;
-    if (RoiPredicate(border, border, border_x, border_y, keypoints[k]))
-    {
-      keypoints.erase(beginning + k);
-      kscales.erase(beginningkscales + k);
-      if (k == 0)
-      {
-        beginning = keypoints.begin();
-        beginningkscales = kscales.begin();
-      }
-      ksize--;
-      k--;
-    }
-  }
-
-  // first, calculate the integral image over the whole image:
-  // current integral image
-  cv::Mat _integral; // the integral image
-  cv::integral(image, _integral);
-
-  int* _values = new int[points_]; // for temporary use
-
-  // now do the extraction for all keypoints:
-
-  // temporary variables containing gray values at sample points:
-  int t1;
-  int t2;
-
-  // the feature orientation
-  int direction0;
-  int direction1;
-
-  for (size_t k = 0; k < ksize; k++)
-  {
-    cv::KeyPoint& kp = keypoints[k];
-    const int& scale = kscales[k];
-    int* pvalues = _values;
-    const float& x = kp.pt.x;
-    const float& y = kp.pt.y;
-        // get the gray values in the unrotated pattern
-        for (unsigned int i = 0; i < points_; i++)
-        {
-          *(pvalues++) = smoothedIntensity(image, _integral, x, y, scale, 0, i);
-        }
-
-        direction0 = 0;
-        direction1 = 0;
-        // now iterate through the long pairings
-        const BriskLongPair* max = longPairs_ + noLongPairs_;
-        for (BriskLongPair* iter = longPairs_; iter < max; ++iter)
-        {
-          t1 = *(_values + iter->i);
-          t2 = *(_values + iter->j);
-          const int delta_t = (t1 - t2);
-          // update the direction:
-          const int tmp0 = delta_t * (iter->weighted_dx) / 1024;
-          const int tmp1 = delta_t * (iter->weighted_dy) / 1024;
-          direction0 += tmp0;
-          direction1 += tmp1;
-        }
-        kp.angle = atan2((float) direction1, (float) direction0) / M_PI * 180.0;
-        if (kp.angle < 0)
-          kp.angle += 360;
-  }
 }