fixed typo in opencv_stitching

modules/stitching/autocalib.cpp

@@ -38,80 +38,80 @@
 // 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 "autocalib.hpp"
-#include "util.hpp"
-
-using namespace std;
-using namespace cv;
-
-void focalsFromHomography(const Mat& H, double &f0, double &f1, bool &f0_ok, bool &f1_ok)
-{
-    CV_Assert(H.type() == CV_64F && H.size() == Size(3, 3));
-
-    const double* h = reinterpret_cast<const double*>(H.data);
-
-    double d1, d2; // Denominators
-    double v1, v2; // Focal squares value candidates
-
-    f1_ok = true;
-    d1 = h[6] * h[7];
-    d2 = (h[7] - h[6]) * (h[7] + h[6]);
-    v1 = -(h[0] * h[1] + h[3] * h[4]) / d1;
-    v2 = (h[0] * h[0] + h[3] * h[3] - h[1] * h[1] - h[4] * h[4]) / d2;
-    if (v1 < v2) swap(v1, v2);
-    if (v1 > 0 && v2 > 0) f1 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
-    else if (v1 > 0) f1 = sqrt(v1);
-    else f1_ok = false;
-
-    f0_ok = true;
-    d1 = h[0] * h[3] + h[1] * h[4];
-    d2 = h[0] * h[0] + h[1] * h[1] - h[3] * h[3] - h[4] * h[4];
-    v1 = -h[2] * h[5] / d1;
-    v2 = (h[5] * h[5] - h[2] * h[2]) / d2;
-    if (v1 < v2) swap(v1, v2);
-    if (v1 > 0 && v2 > 0) f0 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
-    else if (v1 > 0) f0 = sqrt(v1);
-    else f0_ok = false;
-}
-
-
-void estimateFocal(const vector<ImageFeatures> &features, const vector<MatchesInfo> &pairwise_matches, 
-                   vector<double> &focals)
-{
-    const int num_images = static_cast<int>(features.size());
-    focals.resize(num_images);
-
-    vector<double> all_focals;
-
-    for (int i = 0; i < num_images; ++i)
-    {        
-        for (int j = 0; j < num_images; ++j)
-        {
-            const MatchesInfo &m = pairwise_matches[i*num_images + j];
-            if (m.H.empty())
-                continue;
-            double f0, f1;
-            bool f0ok, f1ok;
-            focalsFromHomography(m.H, f0, f1, f0ok, f1ok);
-            if (f0ok && f1ok) 
-                all_focals.push_back(sqrt(f0 * f1));
-        }
-    }
-
-    if (static_cast<int>(all_focals.size()) < num_images - 1)
-    {
-        LOGLN("Can't estimate focal length, will use anaive approach");
-        double focals_sum = 0;
-        for (int i = 0; i < num_images; ++i)
-            focals_sum += features[i].img_size.width + features[i].img_size.height;
-        for (int i = 0; i < num_images; ++i)
-            focals[i] = focals_sum / num_images;
-    }
-    else
-    {
-        nth_element(all_focals.begin(), all_focals.begin() + all_focals.size()/2, all_focals.end());
-        for (int i = 0; i < num_images; ++i)
-            focals[i] = all_focals[all_focals.size()/2];
-    }
-}
+//M*/
+#include "autocalib.hpp"
+#include "util.hpp"
+
+using namespace std;
+using namespace cv;
+
+void focalsFromHomography(const Mat& H, double &f0, double &f1, bool &f0_ok, bool &f1_ok)
+{
+    CV_Assert(H.type() == CV_64F && H.size() == Size(3, 3));
+
+    const double* h = reinterpret_cast<const double*>(H.data);
+
+    double d1, d2; // Denominators
+    double v1, v2; // Focal squares value candidates
+
+    f1_ok = true;
+    d1 = h[6] * h[7];
+    d2 = (h[7] - h[6]) * (h[7] + h[6]);
+    v1 = -(h[0] * h[1] + h[3] * h[4]) / d1;
+    v2 = (h[0] * h[0] + h[3] * h[3] - h[1] * h[1] - h[4] * h[4]) / d2;
+    if (v1 < v2) swap(v1, v2);
+    if (v1 > 0 && v2 > 0) f1 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
+    else if (v1 > 0) f1 = sqrt(v1);
+    else f1_ok = false;
+
+    f0_ok = true;
+    d1 = h[0] * h[3] + h[1] * h[4];
+    d2 = h[0] * h[0] + h[1] * h[1] - h[3] * h[3] - h[4] * h[4];
+    v1 = -h[2] * h[5] / d1;
+    v2 = (h[5] * h[5] - h[2] * h[2]) / d2;
+    if (v1 < v2) swap(v1, v2);
+    if (v1 > 0 && v2 > 0) f0 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
+    else if (v1 > 0) f0 = sqrt(v1);
+    else f0_ok = false;
+}
+
+
+void estimateFocal(const vector<ImageFeatures> &features, const vector<MatchesInfo> &pairwise_matches, 
+                   vector<double> &focals)
+{
+    const int num_images = static_cast<int>(features.size());
+    focals.resize(num_images);
+
+    vector<double> all_focals;
+
+    for (int i = 0; i < num_images; ++i)
+    {        
+        for (int j = 0; j < num_images; ++j)
+        {
+            const MatchesInfo &m = pairwise_matches[i*num_images + j];
+            if (m.H.empty())
+                continue;
+            double f0, f1;
+            bool f0ok, f1ok;
+            focalsFromHomography(m.H, f0, f1, f0ok, f1ok);
+            if (f0ok && f1ok) 
+                all_focals.push_back(sqrt(f0 * f1));
+        }
+    }
+
+    if (static_cast<int>(all_focals.size()) >= num_images - 1)
+    {
+        nth_element(all_focals.begin(), all_focals.begin() + all_focals.size()/2, all_focals.end());
+        for (int i = 0; i < num_images; ++i)
+            focals[i] = all_focals[all_focals.size()/2];
+    }
+    else
+    {
+        LOGLN("Can't estimate focal length, will use naive approach");
+        double focals_sum = 0;
+        for (int i = 0; i < num_images; ++i)
+            focals_sum += features[i].img_size.width + features[i].img_size.height;
+        for (int i = 0; i < num_images; ++i)
+            focals[i] = focals_sum / num_images;
+    }
+}