fixed typo in opencv_stitching

diff --git a/modules/stitching/autocalib.cpp b/modules/stitching/autocalib.cpp
index de1c5ef..fbd2967 100644 (file)
--- a/modules/stitching/autocalib.cpp
+++ b/modules/stitching/autocalib.cpp
@@ -38,80 +38,80 @@
 // or tort (including negligence or otherwise) arising in any way out of\r
 // the use of this software, even if advised of the possibility of such damage.\r
 //\r
-//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*/\r
+#include "autocalib.hpp"\r
+#include "util.hpp"\r
+\r
+using namespace std;\r
+using namespace cv;\r
+\r
+void focalsFromHomography(const Mat& H, double &f0, double &f1, bool &f0_ok, bool &f1_ok)\r
+{\r
+    CV_Assert(H.type() == CV_64F && H.size() == Size(3, 3));\r
+\r
+    const double* h = reinterpret_cast<const double*>(H.data);\r
+\r
+    double d1, d2; // Denominators\r
+    double v1, v2; // Focal squares value candidates\r
+\r
+    f1_ok = true;\r
+    d1 = h[6] * h[7];\r
+    d2 = (h[7] - h[6]) * (h[7] + h[6]);\r
+    v1 = -(h[0] * h[1] + h[3] * h[4]) / d1;\r
+    v2 = (h[0] * h[0] + h[3] * h[3] - h[1] * h[1] - h[4] * h[4]) / d2;\r
+    if (v1 < v2) swap(v1, v2);\r
+    if (v1 > 0 && v2 > 0) f1 = sqrt(abs(d1) > abs(d2) ? v1 : v2);\r
+    else if (v1 > 0) f1 = sqrt(v1);\r
+    else f1_ok = false;\r
+\r
+    f0_ok = true;\r
+    d1 = h[0] * h[3] + h[1] * h[4];\r
+    d2 = h[0] * h[0] + h[1] * h[1] - h[3] * h[3] - h[4] * h[4];\r
+    v1 = -h[2] * h[5] / d1;\r
+    v2 = (h[5] * h[5] - h[2] * h[2]) / d2;\r
+    if (v1 < v2) swap(v1, v2);\r
+    if (v1 > 0 && v2 > 0) f0 = sqrt(abs(d1) > abs(d2) ? v1 : v2);\r
+    else if (v1 > 0) f0 = sqrt(v1);\r
+    else f0_ok = false;\r
+}\r
+\r
+\r
+void estimateFocal(const vector<ImageFeatures> &features, const vector<MatchesInfo> &pairwise_matches, \r
+                   vector<double> &focals)\r
+{\r
+    const int num_images = static_cast<int>(features.size());\r
+    focals.resize(num_images);\r
+\r
+    vector<double> all_focals;\r
+\r
+    for (int i = 0; i < num_images; ++i)\r
+    {        \r
+        for (int j = 0; j < num_images; ++j)\r
+        {\r
+            const MatchesInfo &m = pairwise_matches[i*num_images + j];\r
+            if (m.H.empty())\r
+                continue;\r
+            double f0, f1;\r
+            bool f0ok, f1ok;\r
+            focalsFromHomography(m.H, f0, f1, f0ok, f1ok);\r
+            if (f0ok && f1ok) \r
+                all_focals.push_back(sqrt(f0 * f1));\r
+        }\r
+    }\r
+\r
+    if (static_cast<int>(all_focals.size()) >= num_images - 1)\r
+    {\r
+        nth_element(all_focals.begin(), all_focals.begin() + all_focals.size()/2, all_focals.end());\r
+        for (int i = 0; i < num_images; ++i)\r
+            focals[i] = all_focals[all_focals.size()/2];\r
+    }\r
+    else\r
+    {\r
+        LOGLN("Can't estimate focal length, will use naive approach");\r
+        double focals_sum = 0;\r
+        for (int i = 0; i < num_images; ++i)\r
+            focals_sum += features[i].img_size.width + features[i].img_size.height;\r
+        for (int i = 0; i < num_images; ++i)\r
+            focals[i] = focals_sum / num_images;\r
+    }\r
+}\r