Normalized file endings.

modules/imgproc/doc/filtering.rst

@@ -1642,4 +1642,3 @@ is equivalent to
 .. seealso::
 
     :ocv:func:`cartToPolar`
-

modules/imgproc/doc/geometric_transformations.rst

@@ -705,5 +705,3 @@ The function is similar to
 where ``undistort()`` is an approximate iterative algorithm that estimates the normalized original point coordinates out of the normalized distorted point coordinates ("normalized" means that the coordinates do not depend on the camera matrix).
 
 The function can be used for both a stereo camera head or a monocular camera (when R is empty).
-
-

modules/imgproc/doc/miscellaneous_transformations.rst

@@ -815,4 +815,4 @@ See the sample ``grabcut.cpp`` to learn how to use the function.
 
    * An example using the GrabCut algorithm can be found at opencv_source_code/samples/cpp/grabcut.cpp
 
-   * (Python) An example using the GrabCut algorithm can be found at opencv_source_code/samples/python2/grabcut.py
+   * (Python) An example using the GrabCut algorithm can be found at opencv_source_code/samples/python2/grabcut.py

modules/imgproc/doc/object_detection.rst

@@ -76,4 +76,4 @@ After the function finishes the comparison, the best matches can be found as glo
 
 .. note::
 
-   * (Python) An example on how to match mouse selected regions in an image can be found at opencv_source_code/samples/python2/mouse_and_match.py
+   * (Python) An example on how to match mouse selected regions in an image can be found at opencv_source_code/samples/python2/mouse_and_match.py

modules/imgproc/perf/perf_cornerEigenValsAndVecs.cpp

@@ -37,4 +37,4 @@ PERF_TEST_P(Img_BlockSize_ApertureSize_BorderType, cornerEigenValsAndVecs,
     extractChannel(dst, l1, 0);
 
     SANITY_CHECK(l1, 2e-5);
-}
+}

modules/imgproc/perf/perf_cornerHarris.cpp

@@ -36,4 +36,4 @@ PERF_TEST_P(Img_BlockSize_ApertureSize_k_BorderType, cornerHarris,
     TEST_CYCLE() cornerHarris(src, dst, blockSize, apertureSize, k, borderType);
 
     SANITY_CHECK(dst, 2e-5);
-}
+}

modules/imgproc/perf/perf_filter2d.cpp

@@ -72,5 +72,3 @@ PERF_TEST_P( Image_KernelSize, GaborFilter2d,
 
     SANITY_CHECK(filteredImage, 1e-3);
 }
-
-

modules/imgproc/perf/perf_warp.cpp

@@ -221,4 +221,3 @@ PERF_TEST(Transform, getPerspectiveTransform)
 
     SANITY_CHECK(transformCoefficient, 1e-5);
 }
-

modules/imgproc/src/rotcalipers.cpp

@@ -438,4 +438,3 @@ cvMinAreaRect2( const CvArr* array, CvMemStorage* storage )
     box.angle = (float)(box.angle*180/CV_PI);
     return box;
 }
-

modules/imgproc/test/test_approxpoly.cpp

@@ -356,4 +356,3 @@ _exit_:
 }
 
 TEST(Imgproc_ApproxPoly, accuracy) { CV_ApproxPolyTest test; test.safe_run(); }
-

modules/imgproc/test/test_convhull.cpp

@@ -1700,4 +1700,3 @@ TEST(Imgproc_ContourPerimeterSlice, accuracy) { CV_PerimeterAreaSliceTest test;
 TEST(Imgproc_FitEllipse, small) { CV_FitEllipseSmallTest test; test.safe_run(); }
 
 /* End of file. */
-

modules/imgproc/test/test_distancetransform.cpp

@@ -293,5 +293,3 @@ void CV_DisTransTest::prepare_to_validation( int /*test_case_idx*/ )
 
 
 TEST(Imgproc_DistanceTransform, accuracy) { CV_DisTransTest test; test.safe_run(); }
-
-

modules/imgproc/test/test_filter.cpp

@@ -1886,4 +1886,3 @@ protected:
 };
 
 TEST(Imgproc_Filtering, supportedFormats) { CV_FilterSupportedFormatsTest test; test.safe_run(); }
-

modules/imgproc/test/test_houghLines.cpp

@@ -146,4 +146,3 @@ void CV_HoughLinesTest::run_test(int type)
 TEST(Imgproc_HoughLines, regression) { CV_StandartHoughLinesTest test; test.safe_run(); }
 
 TEST(Imgproc_HoughLinesP, regression) { CV_ProbabilisticHoughLinesTest test; test.safe_run(); }
-

modules/imgproc/test/test_thresh.cpp

@@ -318,4 +318,3 @@ void CV_ThreshTest::prepare_to_validation( int /*test_case_idx*/ )
 }
 
 TEST(Imgproc_Threshold, accuracy) { CV_ThreshTest test; test.safe_run(); }
-

modules/imgproc/test/test_watershed.cpp

@@ -130,4 +130,3 @@ void CV_WatershedTest::run( int /* start_from */)
 }
 
 TEST(Imgproc_Watershed, regression) { CV_WatershedTest test; test.safe_run(); }
-