Merge remote-tracking branch 'upstream/3.4' into merge-3.4

CMakeLists.txt

@@ -715,7 +715,7 @@ if(UNIX)
     CHECK_INCLUDE_FILE(pthread.h HAVE_PTHREAD)
     if(ANDROID)
       set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} dl m log)
-    elseif(${CMAKE_SYSTEM_NAME} MATCHES "FreeBSD|NetBSD|DragonFly|OpenBSD|Haiku")
+    elseif(CMAKE_SYSTEM_NAME MATCHES "FreeBSD|NetBSD|DragonFly|OpenBSD|Haiku")
       set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} m pthread)
     elseif(EMSCRIPTEN)
       # no need to link to system libs with emscripten

cmake/OpenCVCompilerOptions.cmake

@@ -296,11 +296,18 @@ endif()
 # workaround gcc bug for aligned ld/st
 # https://github.com/opencv/opencv/issues/13211
 if((PPC64LE AND NOT CMAKE_CROSSCOMPILING) OR OPENCV_FORCE_COMPILER_CHECK_VSX_ALIGNED)
-  ocv_check_runtime_flag("${CPU_BASELINE_FLAGS}" "OPENCV_CHECK_VSX_ALIGNED" "${OpenCV_SOURCE_DIR}/cmake/checks/runtime/cpu_vsx_aligned.cpp")
+  ocv_check_runtime_flag("${CPU_BASELINE_FLAGS}" OPENCV_CHECK_VSX_ALIGNED "${OpenCV_SOURCE_DIR}/cmake/checks/runtime/cpu_vsx_aligned.cpp")
   if(NOT OPENCV_CHECK_VSX_ALIGNED)
     add_extra_compiler_option_force(-DCV_COMPILER_VSX_BROKEN_ALIGNED)
   endif()
 endif()
+# validate inline asm with fixes register number and constraints wa, wd, wf
+if(PPC64LE)
+  ocv_check_compiler_flag(CXX "${CPU_BASELINE_FLAGS}" OPENCV_CHECK_VSX_ASM "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_vsx_asm.cpp")
+  if(NOT OPENCV_CHECK_VSX_ASM)
+    add_extra_compiler_option_force(-DCV_COMPILER_VSX_BROKEN_ASM)
+  endif()
+endif()
 
 # combine all "extra" options
 if(NOT OPENCV_SKIP_EXTRA_COMPILER_FLAGS)

cmake/OpenCVDetectInferenceEngine.cmake

 # The script detects Intel(R) Inference Engine installation
 #
 # Cache variables:
-# INF_ENGINE_OMP_DIR - directory with OpenMP library to link with (needed by some versions of IE)
 # INF_ENGINE_RELEASE - a number reflecting IE source interface (linked with OpenVINO release)
 #
 # Detect parameters:
@@ -11,8 +10,8 @@
 #    - INF_ENGINE_INCLUDE_DIRS - headers search location
 #    - INF_ENGINE_LIB_DIRS     - library search location
 # 3. OpenVINO location:
-#    - environment variable INTEL_CVSDK_DIR is set to location of OpenVINO installation dir
-#    - INF_ENGINE_PLATFORM - part of name of library directory representing its platform (default ubuntu_16.04)
+#    - environment variable INTEL_OPENVINO_DIR is set to location of OpenVINO installation dir
+#    - INF_ENGINE_PLATFORM - part of name of library directory representing its platform
 #
 # Result:
 # INF_ENGINE_TARGET - set to name of imported library target representing InferenceEngine
@@ -36,11 +35,13 @@ function(add_custom_ie_build _inc _lib _lib_rel _lib_dbg _msg)
     IMPORTED_IMPLIB_DEBUG "${_lib_dbg}"
     INTERFACE_INCLUDE_DIRECTORIES "${_inc}"
   )
-  find_library(omp_lib iomp5 PATHS "${INF_ENGINE_OMP_DIR}" NO_DEFAULT_PATH)
-  if(NOT omp_lib)
+  if(NOT INF_ENGINE_RELEASE VERSION_GREATER "2018050000")
+    find_library(INF_ENGINE_OMP_LIBRARY iomp5 PATHS "${INF_ENGINE_OMP_DIR}" NO_DEFAULT_PATH)
+    if(NOT INF_ENGINE_OMP_LIBRARY)
       message(WARNING "OpenMP for IE have not been found. Set INF_ENGINE_OMP_DIR variable if you experience build errors.")
     else()
-    set_target_properties(inference_engine PROPERTIES IMPORTED_LINK_INTERFACE_LIBRARIES "${omp_lib}")
+      set_target_properties(inference_engine PROPERTIES IMPORTED_LINK_INTERFACE_LIBRARIES "${INF_ENGINE_OMP_LIBRARY}")
+    endif()
   endif()
   set(INF_ENGINE_VERSION "Unknown" CACHE STRING "")
   set(INF_ENGINE_TARGET inference_engine PARENT_SCOPE)
@@ -64,9 +65,17 @@ if(NOT INF_ENGINE_TARGET AND INF_ENGINE_LIB_DIRS AND INF_ENGINE_INCLUDE_DIRS)
   add_custom_ie_build("${ie_custom_inc}" "${ie_custom_lib}" "${ie_custom_lib_rel}" "${ie_custom_lib_dbg}" "INF_ENGINE_{INCLUDE,LIB}_DIRS")
 endif()
 
-set(_loc "$ENV{INTEL_CVSDK_DIR}")
+set(_loc "$ENV{INTEL_OPENVINO_DIR}")
+if(NOT _loc AND DEFINED ENV{INTEL_CVSDK_DIR})
+  set(_loc "$ENV{INTEL_CVSDK_DIR}")  # OpenVINO 2018.x
+endif()
 if(NOT INF_ENGINE_TARGET AND _loc)
-  set(INF_ENGINE_PLATFORM "ubuntu_16.04" CACHE STRING "InferenceEngine platform (library dir)")
+  if(NOT INF_ENGINE_RELEASE VERSION_GREATER "2018050000")
+    set(INF_ENGINE_PLATFORM_DEFAULT "ubuntu_16.04")
+  else()
+    set(INF_ENGINE_PLATFORM_DEFAULT "")
+  endif()
+  set(INF_ENGINE_PLATFORM "${INF_ENGINE_PLATFORM_DEFAULT}" CACHE STRING "InferenceEngine platform (library dir)")
   find_path(ie_custom_env_inc "inference_engine.hpp" PATHS "${_loc}/deployment_tools/inference_engine/include" NO_DEFAULT_PATH)
   find_library(ie_custom_env_lib "inference_engine" PATHS "${_loc}/deployment_tools/inference_engine/lib/${INF_ENGINE_PLATFORM}/intel64" NO_DEFAULT_PATH)
   find_library(ie_custom_env_lib_rel "inference_engine" PATHS "${_loc}/deployment_tools/inference_engine/lib/intel64/Release" NO_DEFAULT_PATH)

cmake/OpenCVUtils.cmake

@@ -822,6 +822,11 @@ function(ocv_output_status msg)
   message(STATUS "${msg}")
   string(REPLACE "\\" "\\\\" msg "${msg}")
   string(REPLACE "\"" "\\\"" msg "${msg}")
+  string(REGEX REPLACE "^\n+|\n+$" "" msg "${msg}")
+  if(msg MATCHES "\n")
+    message(WARNING "String to be inserted to version_string.inc has an unexpected line break: '${msg}'")
+    string(REPLACE "\n" "\\n" msg "${msg}")
+  endif()
   set(OPENCV_BUILD_INFO_STR "${OPENCV_BUILD_INFO_STR}\"${msg}\\n\"\n" CACHE INTERNAL "")
 endfunction()
 

cmake/checks/cpu_vsx_asm.cpp

+#if defined(__VSX__)
+    #if defined(__PPC64__) && defined(__LITTLE_ENDIAN__)
+        #include <altivec.h>
+    #else
+        #error "OpenCV only supports little-endian mode"
+    #endif
+#else
+    #error "VSX is not supported"
+#endif
+
+/*
+ * xlc and wide versions of clang don't support %x<n> in the inline asm template which fixes register number
+ * when using any of the register constraints wa, wd, wf
+*/
+int main()
+{
+    __vector float vf;
+    __vector signed int vi;
+    __asm__ __volatile__ ("xvcvsxwsp %x0,%x1" : "=wf" (vf) : "wa" (vi));
+    return 0;
+}
\ No newline at end of file

cmake/checks/runtime/cpu_vsx_aligned.cpp

@@ -2,6 +2,7 @@
 // https://github.com/opencv/opencv/issues/13211
 
 #include <altivec.h>
+#undef bool
 
 #define vsx_ld vec_vsx_ld
 #define vsx_st vec_vsx_st

doc/tutorials/imgproc/anisotropic_image_segmentation/anisotropic_image_segmentation.markdown

 Anisotropic image segmentation by a gradient structure tensor {#tutorial_anisotropic_image_segmentation_by_a_gst}
 ==========================
 
+@prev_tutorial{tutorial_motion_deblur_filter}
+@next_tutorial{tutorial_periodic_noise_removing_filter}
+
 Goal
 ----
 
@@ -45,28 +48,65 @@ The orientation of an anisotropic image:
 Coherency:
 \f[C = \frac{\lambda_1 - \lambda_2}{\lambda_1 + \lambda_2}\f]
 
-The coherency ranges from 0 to 1. For ideal local orientation (\f$\lambda_2\f$ = 0, \f$\lambda_1\f$ > 0) it is one, for an isotropic gray value structure (\f$\lambda_1\f$ = \f$\lambda_2\f$ > 0) it is zero.
+The coherency ranges from 0 to 1. For ideal local orientation (\f$\lambda_2\f$ = 0, \f$\lambda_1\f$ > 0) it is one, for an isotropic gray value structure (\f$\lambda_1\f$ = \f$\lambda_2\f$ \> 0) it is zero.
 
 Source code
 -----------
 
 You can find source code in the `samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp` of the OpenCV source code library.
 
-@include cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp
+@add_toggle_cpp
+    @include cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp
+@end_toggle
+
+@add_toggle_python
+    @include samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py
+@end_toggle
 
 Explanation
 -----------
 An anisotropic image segmentation algorithm consists of a gradient structure tensor calculation, an orientation calculation, a coherency calculation and an orientation and coherency thresholding:
-@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp main
+
+@add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp main
+@end_toggle
+
+@add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py main
+@end_toggle
 
 A function calcGST() calculates orientation and coherency by using a gradient structure tensor. An input parameter w defines a window size:
-@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp calcGST
+
+@add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp calcGST
+@end_toggle
+
+@add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py calcGST
+@end_toggle
+
 
 The below code applies a thresholds LowThr and HighThr to image orientation and a threshold C_Thr to image coherency calculated by the previous function. LowThr and HighThr define orientation range:
-@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp thresholding
+
+@add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp thresholding
+@end_toggle
+
+@add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py thresholding
+@end_toggle
+
 
 And finally we combine thresholding results:
-@snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp combining
+
+@add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.cpp combining
+@end_toggle
+
+@add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py combining
+@end_toggle
+
 
 Result
 ------

doc/tutorials/imgproc/motion_deblur_filter/motion_deblur_filter.markdown

 Motion Deblur Filter {#tutorial_motion_deblur_filter}
 ==========================
 
+@prev_tutorial{tutorial_out_of_focus_deblur_filter}
+@next_tutorial{tutorial_anisotropic_image_segmentation_by_a_gst}
+
 Goal
 ----
 

doc/tutorials/imgproc/out_of_focus_deblur_filter/out_of_focus_deblur_filter.markdown

@@ -2,6 +2,7 @@ Out-of-focus Deblur Filter {#tutorial_out_of_focus_deblur_filter}
 ==========================
 
 @prev_tutorial{tutorial_distance_transform}
+@next_tutorial{tutorial_motion_deblur_filter}
 
 Goal
 ----

doc/tutorials/imgproc/periodic_noise_removing_filter/periodic_noise_removing_filter.markdown

 Periodic Noise Removing Filter {#tutorial_periodic_noise_removing_filter}
 ==========================
 
+@prev_tutorial{tutorial_anisotropic_image_segmentation_by_a_gst}
+
 Goal
 ----
 

modules/calib3d/include/opencv2/calib3d.hpp

@@ -177,8 +177,6 @@ pattern (every view is described by several 3D-2D point correspondences).
         opencv_source_code/samples/cpp/calibration.cpp
     -   A calibration sample in order to do 3D reconstruction can be found at
         opencv_source_code/samples/cpp/build3dmodel.cpp
-    -   A calibration sample of an artificially generated camera and chessboard patterns can be
-        found at opencv_source_code/samples/cpp/calibration_artificial.cpp
     -   A calibration example on stereo calibration can be found at
         opencv_source_code/samples/cpp/stereo_calib.cpp
     -   A calibration example on stereo matching can be found at

modules/core/CMakeLists.txt

@@ -3,7 +3,7 @@ set(the_description "The Core Functionality")
 ocv_add_dispatched_file(mathfuncs_core SSE2 AVX AVX2)
 ocv_add_dispatched_file(stat SSE4_2 AVX2)
 ocv_add_dispatched_file(arithm SSE2 SSE4_1 AVX2 VSX3)
-ocv_add_dispatched_file(convert SSE2 AVX2)
+ocv_add_dispatched_file(convert SSE2 AVX2 VSX3)
 ocv_add_dispatched_file(convert_scale SSE2 AVX2)
 ocv_add_dispatched_file(count_non_zero SSE2 AVX2)
 ocv_add_dispatched_file(matmul SSE2 AVX2)

modules/core/include/opencv2/core/vsx_utils.hpp

@@ -291,6 +291,8 @@ VSX_IMPL_1RG(vec_udword2, wi, vec_float4,  wf, xvcvspuxds, vec_ctulo)
  *
  * So we're not able to use inline asm and only use built-in functions that CLANG supports
  * and use __builtin_convertvector if clang missng any of vector conversions built-in functions
+ *
+ * todo: clang asm template bug is fixed, need to reconsider the current workarounds.
 */
 
 // convert vector helper

modules/core/src/lda.cpp

@@ -322,6 +322,8 @@ private:
         //  Fortran subroutine in EISPACK.
 
         // Initialize
+        const int max_iters_count = 1000 * this->n;
+
         int nn = this->n;
         int n1 = nn - 1;
         int low = 0;
@@ -487,7 +489,9 @@ private:
                     }
                 }
 
-                iter = iter + 1; // (Could check iteration count here.)
+                iter = iter + 1;
+                if (iter > max_iters_count)
+                    CV_Error(Error::StsNoConv, "Algorithm doesn't converge (complex eigen values?)");
 
                 // Look for two consecutive small sub-diagonal elements
                 int m = n1 - 2;

modules/core/test/test_eigen.cpp

@@ -519,4 +519,27 @@ TEST_P(Core_EigenZero, double)
 }
 INSTANTIATE_TEST_CASE_P(/**/, Core_EigenZero, testing::Values(2, 3, 5));
 
+TEST(Core_EigenNonSymmetric, convergence)
+{
+    Matx33d m(
+        0, -1, 0,
+        1, 0, 1,
+        0, -1, 0);
+    Mat eigenvalues, eigenvectors;
+    // eigen values are complex, algorithm doesn't converge
+    try
+    {
+        cv::eigenNonSymmetric(m, eigenvalues, eigenvectors);
+        std::cout << Mat(eigenvalues.t()) << std::endl;
+    }
+    catch (const cv::Exception& e)
+    {
+        EXPECT_EQ(Error::StsNoConv, e.code) << e.what();
+    }
+    catch (...)
+    {
+        FAIL() << "Unknown exception has been raised";
+    }
+}
+
 }} // namespace

modules/flann/include/opencv2/flann/kmeans_index.h

@@ -276,17 +276,15 @@ public:
     public:
         KMeansDistanceComputer(Distance _distance, const Matrix<ElementType>& _dataset,
             const int _branching, const int* _indices, const Matrix<double>& _dcenters, const size_t _veclen,
-            int* _count, int* _belongs_to, std::vector<DistanceType>& _radiuses, bool& _converged)
+            std::vector<int> &_new_centroids, std::vector<DistanceType> &_sq_dists)
             : distance(_distance)
             , dataset(_dataset)
             , branching(_branching)
             , indices(_indices)
             , dcenters(_dcenters)
             , veclen(_veclen)
-            , count(_count)
-            , belongs_to(_belongs_to)
-            , radiuses(_radiuses)
-            , converged(_converged)
+            , new_centroids(_new_centroids)
+            , sq_dists(_sq_dists)
         {
         }
 
@@ -297,8 +295,8 @@ public:
 
             for( int i = begin; i<end; ++i)
             {
-                DistanceType sq_dist = distance(dataset[indices[i]], dcenters[0], veclen);
-                int new_centroid = 0;
+                DistanceType sq_dist(distance(dataset[indices[i]], dcenters[0], veclen));
+                int new_centroid(0);
                 for (int j=1; j<branching; ++j) {
                     DistanceType new_sq_dist = distance(dataset[indices[i]], dcenters[j], veclen);
                     if (sq_dist>new_sq_dist) {
@@ -306,15 +304,8 @@ public:
                         sq_dist = new_sq_dist;
                     }
                 }
-                if (sq_dist > radiuses[new_centroid]) {
-                    radiuses[new_centroid] = sq_dist;
-                }
-                if (new_centroid != belongs_to[i]) {
-                    CV_XADD(&count[belongs_to[i]], -1);
-                    CV_XADD(&count[new_centroid], 1);
-                    belongs_to[i] = new_centroid;
-                    converged = false;
-                }
+                sq_dists[i] = sq_dist;
+                new_centroids[i] = new_centroid;
             }
         }
 
@@ -325,10 +316,8 @@ public:
         const int* indices;
         const Matrix<double>& dcenters;
         const size_t veclen;
-        int* count;
-        int* belongs_to;
-        std::vector<DistanceType>& radiuses;
-        bool& converged;
+        std::vector<int> &new_centroids;
+        std::vector<DistanceType> &sq_dists;
         KMeansDistanceComputer& operator=( const KMeansDistanceComputer & ) { return *this; }
     };
 
@@ -796,10 +785,27 @@ private:
                 }
             }
 
+            std::vector<int> new_centroids(indices_length);
+            std::vector<DistanceType> sq_dists(indices_length);
+
             // reassign points to clusters
-            KMeansDistanceComputer invoker(distance_, dataset_, branching, indices, dcenters, veclen_, count, belongs_to, radiuses, converged);
+            KMeansDistanceComputer invoker(distance_, dataset_, branching, indices, dcenters, veclen_, new_centroids, sq_dists);
             parallel_for_(cv::Range(0, (int)indices_length), invoker);
 
+            for (int i=0; i < (int)indices_length; ++i) {
+                DistanceType sq_dist(sq_dists[i]);
+                int new_centroid(new_centroids[i]);
+                if (sq_dist > radiuses[new_centroid]) {
+                    radiuses[new_centroid] = sq_dist;
+                }
+                if (new_centroid != belongs_to[i]) {
+                    count[belongs_to[i]]--;
+                    count[new_centroid]++;
+                    belongs_to[i] = new_centroid;
+                    converged = false;
+                }
+            }
+
             for (int i=0; i<branching; ++i) {
                 // if one cluster converges to an empty cluster,
                 // move an element into that cluster

samples/python/asift.py

@@ -106,9 +106,8 @@ def affine_detect(detector, img, mask=None, pool=None):
     print()
     return keypoints, np.array(descrs)
 
-if __name__ == '__main__':
-    print(__doc__)
 
+def main():
     import sys, getopt
     opts, args = getopt.getopt(sys.argv[1:], '', ['feature='])
     opts = dict(opts)
@@ -160,4 +159,10 @@ if __name__ == '__main__':
 
     match_and_draw('affine find_obj')
     cv.waitKey()
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/browse.py

@@ -26,11 +26,7 @@ import cv2 as cv
 # built-in modules
 import sys
 
-if __name__ == '__main__':
-    print('This sample shows how to implement a simple hi resolution image navigation.')
-    print('USAGE: browse.py [image filename]')
-    print()
-
+def main():
     if len(sys.argv) > 1:
         fn = cv.samples.findFile(sys.argv[1])
         print('loading %s ...' % fn)
@@ -62,4 +58,10 @@ if __name__ == '__main__':
     cv.imshow('preview', small)
     cv.setMouseCallback('preview', onmouse)
     cv.waitKey()
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/calibrate.py

@@ -25,7 +25,7 @@ from common import splitfn
 # built-in modules
 import os
 
-if __name__ == '__main__':
+def main():
     import sys
     import getopt
     from glob import glob
@@ -126,4 +126,10 @@ if __name__ == '__main__':
         print('Undistorted image written to: %s' % outfile)
         cv.imwrite(outfile, dst)
 
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/camera_calibration_show_extrinsics.py

 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
-from mpl_toolkits.mplot3d import Axes3D
-import matplotlib.pyplot as plt
+# Python 2/3 compatibility
+from __future__ import print_function
+
 import numpy as np
-from matplotlib import cm
-from numpy import linspace
-import argparse
 import cv2 as cv
 
+from numpy import linspace
+
 def inverse_homogeneoux_matrix(M):
     R = M[0:3, 0:3]
     T = M[0:3, 3]
@@ -119,6 +119,8 @@ def create_board_model(extrinsics, board_width, board_height, square_size, draw_
 def draw_camera_boards(ax, camera_matrix, cam_width, cam_height, scale_focal,
                        extrinsics, board_width, board_height, square_size,
                        patternCentric):
+    from matplotlib import cm
+
     min_values = np.zeros((3,1))
     min_values = np.inf
     max_values = np.zeros((3,1))
@@ -158,6 +160,8 @@ def draw_camera_boards(ax, camera_matrix, cam_width, cam_height, scale_focal,
     return min_values, max_values
 
 def main():
+    import argparse
+
     parser = argparse.ArgumentParser(description='Plot camera calibration extrinsics.',
                                      formatter_class=argparse.ArgumentDefaultsHelpFormatter)
     parser.add_argument('--calibration', type=str, default='left_intrinsics.yml',
@@ -179,6 +183,9 @@ def main():
     camera_matrix = fs.getNode('camera_matrix').mat()
     extrinsics = fs.getNode('extrinsic_parameters').mat()
 
+    import matplotlib.pyplot as plt
+    from mpl_toolkits.mplot3d import Axes3D
+
     fig = plt.figure()
     ax = fig.gca(projection='3d')
     ax.set_aspect("equal")
@@ -211,6 +218,10 @@ def main():
     ax.set_title('Extrinsic Parameters Visualization')
 
     plt.show()
+    print('Done')
+
 
-if __name__ == "__main__":
+if __name__ == '__main__':
+    print(__doc__)
     main()
+    cv.destroyAllWindows()

samples/python/camshift.py

@@ -119,10 +119,10 @@ class App(object):
 
 
 if __name__ == '__main__':
+    print(__doc__)
     import sys
     try:
         video_src = sys.argv[1]
     except:
         video_src = 0
-    print(__doc__)
     App(video_src).run()

samples/python/coherence.py

@@ -46,7 +46,7 @@ def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
     return img
 
 
-if __name__ == '__main__':
+def main():
     import sys
     try:
         fn = sys.argv[1]
@@ -82,4 +82,11 @@ if __name__ == '__main__':
             update()
         if ch == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/color_histogram.py

@@ -8,6 +8,9 @@ Keys:
 
 '''
 
+# Python 2/3 compatibility
+from __future__ import print_function
+
 import numpy as np
 import cv2 as cv
 
@@ -17,8 +20,12 @@ import sys
 # local modules
 import video
 
-if __name__ == '__main__':
+class App():
 
+    def set_scale(self, val):
+        self.hist_scale = val
+
+    def run(self):
         hsv_map = np.zeros((180, 256, 3), np.uint8)
         h, s = np.indices(hsv_map.shape[:2])
         hsv_map[:,:,0] = h
@@ -28,12 +35,9 @@ if __name__ == '__main__':
         cv.imshow('hsv_map', hsv_map)
 
         cv.namedWindow('hist', 0)
-    hist_scale = 10
+        self.hist_scale = 10
 
-    def set_scale(val):
-        global hist_scale
-        hist_scale = val
-    cv.createTrackbar('scale', 'hist', hist_scale, 32, set_scale)
+        cv.createTrackbar('scale', 'hist', self.hist_scale, 32, self.set_scale)
 
         try:
             fn = sys.argv[1]
@@ -52,11 +56,18 @@ if __name__ == '__main__':
             hsv[dark] = 0
             h = cv.calcHist([hsv], [0, 1], None, [180, 256], [0, 180, 0, 256])
 
-        h = np.clip(h*0.005*hist_scale, 0, 1)
+            h = np.clip(h*0.005*self.hist_scale, 0, 1)
             vis = hsv_map*h[:,:,np.newaxis] / 255.0
             cv.imshow('hist', vis)
 
             ch = cv.waitKey(1)
             if ch == 27:
                 break
+
+        print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    App().run()
     cv.destroyAllWindows()

samples/python/contours.py

@@ -48,9 +48,7 @@ def make_image():
         cv.ellipse( img, (dx+273, dy+100), (20,35), 0, 0, 360, white, -1 )
     return img
 
-if __name__ == '__main__':
-    print(__doc__)
-
+def main():
     img = make_image()
     h, w = img.shape[:2]
 
@@ -67,4 +65,10 @@ if __name__ == '__main__':
     cv.createTrackbar( "levels+3", "contours", 3, 7, update )
     cv.imshow('image', img)
     cv.waitKey()
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/deconvolution.py

@@ -65,8 +65,7 @@ def defocus_kernel(d, sz=65):
     return kern
 
 
-if __name__ == '__main__':
-    print(__doc__)
+def main():
     import sys, getopt
     opts, args = getopt.getopt(sys.argv[1:], '', ['circle', 'angle=', 'd=', 'snr='])
     opts = dict(opts)
@@ -128,3 +127,11 @@ if __name__ == '__main__':
         if ch == ord(' '):
             defocus = not defocus
             update(None)
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/dft.py

@@ -11,8 +11,9 @@ USAGE:
 # Python 2/3 compatibility
 from __future__ import print_function
 
-import cv2 as cv
 import numpy as np
+import cv2 as cv
+
 import sys
 
 
@@ -62,8 +63,8 @@ def shift_dft(src, dst=None):
 
     return dst
 
-if __name__ == "__main__":
 
+def main():
     if len(sys.argv) > 1:
         fname = sys.argv[1]
     else:
@@ -110,4 +111,10 @@ if __name__ == "__main__":
     cv.imshow("magnitude", log_spectrum)
 
     cv.waitKey(0)
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/digits.py

@@ -27,12 +27,12 @@ Usage:
 # Python 2/3 compatibility
 from __future__ import print_function
 
+import numpy as np
+import cv2 as cv
+
 # built-in modules
 from multiprocessing.pool import ThreadPool
 
-import cv2 as cv
-
-import numpy as np
 from numpy.linalg import norm
 
 # local modules

samples/python/digits_adjust.py

@@ -23,6 +23,7 @@ if PY3:
 
 import numpy as np
 import cv2 as cv
+
 from multiprocessing.pool import ThreadPool
 
 from digits import *

samples/python/digits_video.py

@@ -96,6 +96,10 @@ def main():
         if ch == 27:
             break
 
+    print('Done')
+
+
 if __name__ == '__main__':
+    print(__doc__)
     main()
     cv.destroyAllWindows()

samples/python/distrans.py

@@ -19,13 +19,12 @@ import cv2 as cv
 
 from common import make_cmap
 
-if __name__ == '__main__':
+def main():
     import sys
     try:
         fn = sys.argv[1]
     except:
         fn = 'fruits.jpg'
-    print(__doc__)
 
     fn = cv.samples.findFile(fn)
     img = cv.imread(fn, cv.IMREAD_GRAYSCALE)
@@ -69,4 +68,11 @@ if __name__ == '__main__':
             update()
         if need_update:
             update()
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/edge.py

@@ -23,9 +23,7 @@ import video
 import sys
 
 
-if __name__ == '__main__':
-    print(__doc__)
-
+def main():
     try:
         fn = sys.argv[1]
     except:
@@ -52,4 +50,11 @@ if __name__ == '__main__':
         ch = cv.waitKey(5)
         if ch == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/facedetect.py

@@ -30,9 +30,8 @@ def draw_rects(img, rects, color):
     for x1, y1, x2, y2 in rects:
         cv.rectangle(img, (x1, y1), (x2, y2), color, 2)
 
-if __name__ == '__main__':
+def main():
     import sys, getopt
-    print(__doc__)
 
     args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade='])
     try:
@@ -70,4 +69,11 @@ if __name__ == '__main__':
 
         if cv.waitKey(5) == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/find_obj.py

@@ -19,6 +19,7 @@ from __future__ import print_function
 
 import numpy as np
 import cv2 as cv
+
 from common import anorm, getsize
 
 FLANN_INDEX_KDTREE = 1  # bug: flann enums are missing
@@ -137,9 +138,7 @@ def explore_match(win, img1, img2, kp_pairs, status = None, H = None):
     return vis
 
 
-if __name__ == '__main__':
-    print(__doc__)
-
+def main():
     import sys, getopt
     opts, args = getopt.getopt(sys.argv[1:], '', ['feature='])
     opts = dict(opts)
@@ -187,4 +186,11 @@ if __name__ == '__main__':
 
     match_and_draw('find_obj')
     cv.waitKey()
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/fitline.py

@@ -79,9 +79,7 @@ def update(_=None):
     draw_str(img, (20, 20), cur_func_name)
     cv.imshow('fit line', img)
 
-if __name__ == '__main__':
-    print(__doc__)
-
+def main():
     cv.namedWindow('fit line')
     cv.createTrackbar('noise', 'fit line', 3, 50, update)
     cv.createTrackbar('point n', 'fit line', 100, 500, update)
@@ -96,3 +94,11 @@ if __name__ == '__main__':
                 cur_func_name = dist_func_names.next()
         if ch == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/floodfill.py

@@ -20,61 +20,69 @@ from __future__ import print_function
 import numpy as np
 import cv2 as cv
 
-if __name__ == '__main__':
-    import sys
-    try:
-        fn = sys.argv[1]
-    except:
-        fn = 'fruits.jpg'
-    print(__doc__)
+import sys
 
-    img = cv.imread(cv.samples.findFile(fn))
-    if img is None:
-        print('Failed to load image file:', fn)
-        sys.exit(1)
-
-    h, w = img.shape[:2]
-    mask = np.zeros((h+2, w+2), np.uint8)
-    seed_pt = None
-    fixed_range = True
-    connectivity = 4
+class App():
 
-    def update(dummy=None):
-        if seed_pt is None:
-            cv.imshow('floodfill', img)
+    def update(self, dummy=None):
+        if self.seed_pt is None:
+            cv.imshow('floodfill', self.img)
             return
-        flooded = img.copy()
-        mask[:] = 0
+        flooded = self.img.copy()
+        self.mask[:] = 0
         lo = cv.getTrackbarPos('lo', 'floodfill')
         hi = cv.getTrackbarPos('hi', 'floodfill')
-        flags = connectivity
-        if fixed_range:
+        flags = self.connectivity
+        if self.fixed_range:
             flags |= cv.FLOODFILL_FIXED_RANGE
-        cv.floodFill(flooded, mask, seed_pt, (255, 255, 255), (lo,)*3, (hi,)*3, flags)
-        cv.circle(flooded, seed_pt, 2, (0, 0, 255), -1)
+        cv.floodFill(flooded, self.mask, self.seed_pt, (255, 255, 255), (lo,)*3, (hi,)*3, flags)
+        cv.circle(flooded, self.seed_pt, 2, (0, 0, 255), -1)
         cv.imshow('floodfill', flooded)
 
-    def onmouse(event, x, y, flags, param):
-        global seed_pt
+    def onmouse(self, event, x, y, flags, param):
         if flags & cv.EVENT_FLAG_LBUTTON:
-            seed_pt = x, y
-            update()
+            self.seed_pt = x, y
+            self.update()
 
-    update()
-    cv.setMouseCallback('floodfill', onmouse)
-    cv.createTrackbar('lo', 'floodfill', 20, 255, update)
-    cv.createTrackbar('hi', 'floodfill', 20, 255, update)
+    def run(self):
+        try:
+            fn = sys.argv[1]
+        except:
+            fn = 'fruits.jpg'
+
+        self.img = cv.imread(cv.samples.findFile(fn))
+        if self.img is None:
+            print('Failed to load image file:', fn)
+            sys.exit(1)
+
+        h, w = self.img.shape[:2]
+        self.mask = np.zeros((h+2, w+2), np.uint8)
+        self.seed_pt = None
+        self.fixed_range = True
+        self.connectivity = 4
+
+        self.update()
+        cv.setMouseCallback('floodfill', self.onmouse)
+        cv.createTrackbar('lo', 'floodfill', 20, 255, self.update)
+        cv.createTrackbar('hi', 'floodfill', 20, 255, self.update)
 
         while True:
             ch = cv.waitKey()
             if ch == 27:
                 break
             if ch == ord('f'):
-            fixed_range = not fixed_range
-            print('using %s range' % ('floating', 'fixed')[fixed_range])
-            update()
+                self.fixed_range = not self.fixed_range
+                print('using %s range' % ('floating', 'fixed')[self.fixed_range])
+                self.update()
             if ch == ord('c'):
-            connectivity = 12-connectivity
-            print('connectivity =', connectivity)
-            update()
+                self.connectivity = 12-self.connectivity
+                print('connectivity =', self.connectivity)
+                self.update()
+
+        print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    App().run()
     cv.destroyAllWindows()

samples/python/gabor_threads.py

@@ -19,6 +19,7 @@ from __future__ import print_function
 
 import numpy as np
 import cv2 as cv
+
 from multiprocessing.pool import ThreadPool
 
 
@@ -47,11 +48,10 @@ def process_threaded(img, filters, threadn = 8):
         np.maximum(accum, fimg, accum)
     return accum
 
-if __name__ == '__main__':
+def main():
     import sys
     from common import Timer
 
-    print(__doc__)
     try:
         img_fn = sys.argv[1]
     except:
@@ -73,4 +73,10 @@ if __name__ == '__main__':
     cv.imshow('img', img)
     cv.imshow('result', res2)
     cv.waitKey()
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/gaussian_mix.py

@@ -9,9 +9,10 @@ if PY3:
     xrange = range
 
 import numpy as np
-from numpy import random
 import cv2 as cv
 
+from numpy import random
+
 def make_gaussians(cluster_n, img_size):
     points = []
     ref_distrs = []
@@ -34,7 +35,7 @@ def draw_gaussain(img, mean, cov, color):
     cv.ellipse(img, (x, y), (s1, s2), ang, 0, 360, color, 1, cv.LINE_AA)
 
 
-if __name__ == '__main__':
+def main():
     cluster_n = 5
     img_size = 512
 
@@ -66,4 +67,11 @@ if __name__ == '__main__':
         ch = cv.waitKey(0)
         if ch == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/hist.py

@@ -18,8 +18,8 @@ Abid Rahman 3/14/12 debug Gary Bradski
 # Python 2/3 compatibility
 from __future__ import print_function
 
-import cv2 as cv
 import numpy as np
+import cv2 as cv
 
 bins = np.arange(256).reshape(256,1)
 
@@ -53,8 +53,7 @@ def hist_lines(im):
     return y
 
 
-if __name__ == '__main__':
-
+def main():
     import sys
 
     if len(sys.argv)>1:
@@ -116,4 +115,11 @@ if __name__ == '__main__':
             print('ESC')
             cv.destroyAllWindows()
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/houghcircles.py

@@ -11,13 +11,12 @@ Usage:
 # Python 2/3 compatibility
 from __future__ import print_function
 
-import cv2 as cv
 import numpy as np
-import sys
+import cv2 as cv
 
-if __name__ == '__main__':
-    print(__doc__)
+import sys
 
+def main():
     try:
         fn = sys.argv[1]
     except IndexError:
@@ -40,3 +39,10 @@ if __name__ == '__main__':
 
     cv.imshow("source", src)
     cv.waitKey(0)
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/houghlines.py

@@ -13,12 +13,11 @@ from __future__ import print_function
 
 import cv2 as cv
 import numpy as np
+
 import sys
 import math
 
-if __name__ == '__main__':
-    print(__doc__)
-
+def main():
     try:
         fn = sys.argv[1]
     except IndexError:
@@ -52,3 +51,10 @@ if __name__ == '__main__':
 
     cv.imshow("source", src)
     cv.waitKey(0)
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/inpaint.py

@@ -20,17 +20,16 @@ from __future__ import print_function
 
 import numpy as np
 import cv2 as cv
+
 from common import Sketcher
 
-if __name__ == '__main__':
+def main():
     import sys
     try:
         fn = sys.argv[1]
     except:
         fn = 'fruits.jpg'
 
-    print(__doc__)
-
     img = cv.imread(cv.samples.findFile(fn))
     if img is None:
         print('Failed to load image file:', fn)
@@ -51,4 +50,11 @@ if __name__ == '__main__':
             img_mark[:] = img
             mark[:] = 0
             sketch.show()
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/kalman.py

@@ -18,12 +18,13 @@ PY3 = sys.version_info[0] == 3
 if PY3:
     long = int
 
+import numpy as np
 import cv2 as cv
+
 from math import cos, sin, sqrt
 import numpy as np
 
-if __name__ == "__main__":
-
+def main():
     img_height = 500
     img_width = 500
     kalman = cv.KalmanFilter(2, 1, 0)
@@ -93,4 +94,10 @@ if __name__ == "__main__":
         if code in [27, ord('q'), ord('Q')]:
             break
 
-    cv.destroyWindow("Kalman")
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/kmeans.py

@@ -18,12 +18,10 @@ import cv2 as cv
 
 from gaussian_mix import make_gaussians
 
-if __name__ == '__main__':
+def main():
     cluster_n = 5
     img_size = 512
 
-    print(__doc__)
-
     # generating bright palette
     colors = np.zeros((1, cluster_n, 3), np.uint8)
     colors[0,:] = 255
@@ -43,8 +41,15 @@ if __name__ == '__main__':
 
             cv.circle(img, (x, y), 1, c, -1)
 
-        cv.imshow('gaussian mixture', img)
+        cv.imshow('kmeans', img)
         ch = cv.waitKey(0)
         if ch == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/lappyr.py

@@ -22,6 +22,7 @@ if PY3:
 
 import numpy as np
 import cv2 as cv
+
 import video
 from common import nothing, getsize
 
@@ -44,9 +45,8 @@ def merge_lappyr(levels):
     return np.uint8(np.clip(img, 0, 255))
 
 
-if __name__ == '__main__':
+def main():
     import sys
-    print(__doc__)
 
     try:
         fn = sys.argv[1]
@@ -72,3 +72,11 @@ if __name__ == '__main__':
 
         if cv.waitKey(1) == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/letter_recog.py

@@ -145,12 +145,10 @@ class MLP(LetterStatModel):
 
 
 
-if __name__ == '__main__':
+def main():
     import getopt
     import sys
 
-    print(__doc__)
-
     models = [RTrees, KNearest, Boost, SVM, MLP] # NBayes
     models = dict( [(cls.__name__.lower(), cls) for cls in models] )
 
@@ -186,4 +184,11 @@ if __name__ == '__main__':
         fn = args['--save']
         print('saving model to %s ...' % fn)
         model.save(fn)
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/lk_homography.py

@@ -25,6 +25,7 @@ from __future__ import print_function
 
 import numpy as np
 import cv2 as cv
+
 import video
 from common import draw_str
 from video import presets
@@ -112,9 +113,11 @@ def main():
     except:
         video_src = 0
 
-    print(__doc__)
     App(video_src).run()
-    cv.destroyAllWindows()
+    print('Done')
+
 
 if __name__ == '__main__':
+    print(__doc__)
     main()
+    cv.destroyAllWindows()

samples/python/lk_track.py

@@ -23,6 +23,7 @@ from __future__ import print_function
 
 import numpy as np
 import cv2 as cv
+
 import video
 from common import anorm2, draw_str
 from time import clock
@@ -96,9 +97,11 @@ def main():
     except:
         video_src = 0
 
-    print(__doc__)
     App(video_src).run()
-    cv.destroyAllWindows()
+    print('Done')
+
 
 if __name__ == '__main__':
+    print(__doc__)
     main()
+    cv.destroyAllWindows()

samples/python/logpolar.py

@@ -13,11 +13,10 @@ Keys:
 # Python 2/3 compatibility
 from __future__ import print_function
 
+import numpy as np
 import cv2 as cv
 
-if __name__ == '__main__':
-    print(__doc__)
-
+def main():
     import sys
     try:
         fn = sys.argv[1]
@@ -37,3 +36,10 @@ if __name__ == '__main__':
     cv.imshow('linearpolar', img3)
 
     cv.waitKey(0)
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/morphology.py

@@ -21,9 +21,7 @@ import numpy as np
 import cv2 as cv
 
 
-if __name__ == '__main__':
-    print(__doc__)
-
+def main():
     import sys
     from itertools import cycle
     from common import draw_str
@@ -93,4 +91,11 @@ if __name__ == '__main__':
             else:
                 cur_str_mode = str_modes.next()
         update()
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/mouse_and_match.py

@@ -25,59 +25,64 @@ import argparse
 from math import *
 
 
-drag_start = None
-sel = (0,0,0,0)
+class App():
+    drag_start = None
+    sel = (0,0,0,0)
 
-def onmouse(event, x, y, flags, param):
-    global drag_start, sel
+    def onmouse(self, event, x, y, flags, param):
         if event == cv.EVENT_LBUTTONDOWN:
-        drag_start = x, y
-        sel = 0,0,0,0
+            self.drag_start = x, y
+            self.sel = (0,0,0,0)
         elif event == cv.EVENT_LBUTTONUP:
-        if sel[2] > sel[0] and sel[3] > sel[1]:
-            patch = gray[sel[1]:sel[3],sel[0]:sel[2]]
-            result = cv.matchTemplate(gray,patch,cv.TM_CCOEFF_NORMED)
+            if self.sel[2] > self.sel[0] and self.sel[3] > self.sel[1]:
+                patch = self.gray[self.sel[1]:self.sel[3], self.sel[0]:self.sel[2]]
+                result = cv.matchTemplate(self.gray, patch, cv.TM_CCOEFF_NORMED)
                 result = np.abs(result)**3
                 _val, result = cv.threshold(result, 0.01, 0, cv.THRESH_TOZERO)
-            result8 = cv.normalize(result,None,0,255,cv.NORM_MINMAX,cv.CV_8U)
+                result8 = cv.normalize(result, None, 0, 255, cv.NORM_MINMAX, cv.CV_8U)
                 cv.imshow("result", result8)
-        drag_start = None
-    elif drag_start:
+            self.drag_start = None
+        elif self.drag_start:
             #print flags
             if flags & cv.EVENT_FLAG_LBUTTON:
-            minpos = min(drag_start[0], x), min(drag_start[1], y)
-            maxpos = max(drag_start[0], x), max(drag_start[1], y)
-            sel = minpos[0], minpos[1], maxpos[0], maxpos[1]
-            img = cv.cvtColor(gray, cv.COLOR_GRAY2BGR)
-            cv.rectangle(img, (sel[0], sel[1]), (sel[2], sel[3]), (0,255,255), 1)
+                minpos = min(self.drag_start[0], x), min(self.drag_start[1], y)
+                maxpos = max(self.drag_start[0], x), max(self.drag_start[1], y)
+                self.sel = (minpos[0], minpos[1], maxpos[0], maxpos[1])
+                img = cv.cvtColor(self.gray, cv.COLOR_GRAY2BGR)
+                cv.rectangle(img, (self.sel[0], self.sel[1]), (self.sel[2], self.sel[3]), (0,255,255), 1)
                 cv.imshow("gray", img)
             else:
                 print("selection is complete")
-            drag_start = None
-
-if __name__ == '__main__':
-    print(__doc__)
+                self.drag_start = None
 
+    def run(self):
         parser = argparse.ArgumentParser(description='Demonstrate mouse interaction with images')
         parser.add_argument("-i","--input", default='../data/', help="Input directory.")
         args = parser.parse_args()
         path = args.input
 
         cv.namedWindow("gray",1)
-    cv.setMouseCallback("gray", onmouse)
+        cv.setMouseCallback("gray", self.onmouse)
         '''Loop through all the images in the directory'''
         for infile in glob.glob( os.path.join(path, '*.*') ):
             ext = os.path.splitext(infile)[1][1:] #get the filename extension
             if ext == "png" or ext == "jpg" or ext == "bmp" or ext == "tiff" or ext == "pbm":
                 print(infile)
 
-            img=cv.imread(infile,1)
+                img = cv.imread(infile,1)
                 if img is None:
                     continue
-            sel = (0,0,0,0)
-            drag_start = None
-            gray=cv.cvtColor(img, cv.COLOR_BGR2GRAY)
-            cv.imshow("gray",gray)
+                self.sel = (0,0,0,0)
+                self.drag_start = None
+                self.gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+                cv.imshow("gray", self.gray)
                 if cv.waitKey() == 27:
                     break
+
+        print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    App().run()
     cv.destroyAllWindows()

samples/python/mser.py

@@ -14,12 +14,16 @@ Keys:
 
 '''
 
+# Python 2/3 compatibility
+from __future__ import print_function
+
 import numpy as np
 import cv2 as cv
+
 import video
 import sys
 
-if __name__ == '__main__':
+def main():
     try:
         video_src = sys.argv[1]
     except:
@@ -42,4 +46,11 @@ if __name__ == '__main__':
         cv.imshow('img', vis)
         if cv.waitKey(5) == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/opencv_version.py

@@ -13,11 +13,11 @@ Usage:
 # Python 2/3 compatibility
 from __future__ import print_function
 
+import numpy as np
 import cv2 as cv
 
-if __name__ == '__main__':
+def main():
     import sys
-    print(__doc__)
 
     try:
         param = sys.argv[1]
@@ -31,3 +31,11 @@ if __name__ == '__main__':
         print("\t--help\n\t\tprint this help")
     else:
         print("Welcome to OpenCV")
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/opt_flow.py

@@ -18,6 +18,7 @@ from __future__ import print_function
 
 import numpy as np
 import cv2 as cv
+
 import video
 
 
@@ -55,9 +56,8 @@ def warp_flow(img, flow):
     res = cv.remap(img, flow, None, cv.INTER_LINEAR)
     return res
 
-if __name__ == '__main__':
+def main():
     import sys
-    print(__doc__)
     try:
         fn = sys.argv[1]
     except IndexError:
@@ -94,4 +94,11 @@ if __name__ == '__main__':
             if show_glitch:
                 cur_glitch = img.copy()
             print('glitch is', ['off', 'on'][show_glitch])
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/peopledetect.py

@@ -30,13 +30,11 @@ def draw_detections(img, rects, thickness = 1):
         cv.rectangle(img, (x+pad_w, y+pad_h), (x+w-pad_w, y+h-pad_h), (0, 255, 0), thickness)
 
 
-if __name__ == '__main__':
+def main():
     import sys
     from glob import glob
     import itertools as it
 
-    print(__doc__)
-
     hog = cv.HOGDescriptor()
     hog.setSVMDetector( cv.HOGDescriptor_getDefaultPeopleDetector() )
 
@@ -68,4 +66,11 @@ if __name__ == '__main__':
         ch = cv.waitKey()
         if ch == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/squares.py

@@ -7,6 +7,7 @@ Loads several images sequentially and tries to find squares in each image.
 '''
 
 # Python 2/3 compatibility
+from __future__ import print_function
 import sys
 PY3 = sys.version_info[0] == 3
 
@@ -42,7 +43,7 @@ def find_squares(img):
                         squares.append(cnt)
     return squares
 
-if __name__ == '__main__':
+def main():
     from glob import glob
     for fn in glob('../data/pic*.png'):
         img = cv.imread(fn)
@@ -52,4 +53,11 @@ if __name__ == '__main__':
         ch = cv.waitKey()
         if ch == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/stereo_match.py

@@ -33,7 +33,7 @@ def write_ply(fn, verts, colors):
         np.savetxt(f, verts, fmt='%f %f %f %d %d %d ')
 
 
-if __name__ == '__main__':
+def main():
     print('loading images...')
     imgL = cv.pyrDown(cv.imread(cv.samples.findFile('aloeL.jpg')))  # downscale images for faster processing
     imgR = cv.pyrDown(cv.imread(cv.samples.findFile('aloeR.jpg')))
@@ -75,4 +75,11 @@ if __name__ == '__main__':
     cv.imshow('left', imgL)
     cv.imshow('disparity', (disp-min_disp)/num_disp)
     cv.waitKey()
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/texture_flow.py

@@ -16,7 +16,7 @@ from __future__ import print_function
 import numpy as np
 import cv2 as cv
 
-if __name__ == '__main__':
+def main():
     import sys
     try:
         fn = sys.argv[1]
@@ -45,3 +45,11 @@ if __name__ == '__main__':
     cv.imshow('input', img)
     cv.imshow('flow', vis)
     cv.waitKey()
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/tst_scene_render.py

@@ -5,9 +5,10 @@
 from __future__ import print_function
 
 import numpy as np
+import cv2 as cv
+
 from numpy import pi, sin, cos
 
-import cv2 as cv
 
 defaultSize = 512
 
@@ -86,7 +87,7 @@ class TestSceneRender():
         else:
             self.currentRect = self.initialRect + np.int( 30*cos(self.time*self.speed) + 50*sin(self.time*self.speed))
             if self.deformation:
-                self.currentRect[1:3] += self.h/20*cos(self.time)
+                self.currentRect[1:3] += int(self.h/20*cos(self.time))
             cv.fillConvexPoly(img, self.currentRect, (0, 0, 255))
 
         self.time += self.timeStep
@@ -96,8 +97,7 @@ class TestSceneRender():
         self.time = 0.0
 
 
-if __name__ == '__main__':
-
+def main():
     backGr = cv.imread(cv.samples.findFile('graf1.png'))
     fgr = cv.imread(cv.samples.findFile('box.png'))
 
@@ -111,6 +111,11 @@ if __name__ == '__main__':
         ch = cv.waitKey(3)
         if  ch == 27:
             break
-    #import os
-    #print (os.environ['PYTHONPATH'])
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/turing.py

@@ -27,7 +27,7 @@ USAGE: turing.py [-o <output.avi>]
 Press ESC to stop.
 '''
 
-if __name__ == '__main__':
+def main():
     print(help_message)
 
     w, h = 512, 512
@@ -71,4 +71,11 @@ if __name__ == '__main__':
         cv.imshow('a', vis)
         if cv.waitKey(5) == 27:
             break
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
     cv.destroyAllWindows()

samples/python/tutorial_code/imgProc/anisotropic_image_segmentation/anisotropic_image_segmentation.py

+
+import cv2 as cv
+import numpy as np
+import argparse
+
+W = 52          # window size is WxW
+C_Thr = 0.43    # threshold for coherency
+LowThr = 35     # threshold1 for orientation, it ranges from 0 to 180
+HighThr = 57    # threshold2 for orientation, it ranges from 0 to 180
+
+## [calcGST]
+## [calcJ_header]
+## [calcGST_proto]
+def calcGST(inputIMG, w):
+## [calcGST_proto]
+    img = inputIMG.astype(np.float32)
+
+    # GST components calculation (start)
+    # J =  (J11 J12; J12 J22) - GST
+    imgDiffX = cv.Sobel(img, cv.CV_32F, 1, 0, 3)
+    imgDiffY = cv.Sobel(img, cv.CV_32F, 0, 1, 3)
+    imgDiffXY = cv.multiply(imgDiffX, imgDiffY)
+    ## [calcJ_header]
+
+    imgDiffXX = cv.multiply(imgDiffX, imgDiffX)
+    imgDiffYY = cv.multiply(imgDiffY, imgDiffY)
+
+    J11 = cv.boxFilter(imgDiffXX, cv.CV_32F, (w,w))
+    J22 = cv.boxFilter(imgDiffYY, cv.CV_32F, (w,w))
+    J12 = cv.boxFilter(imgDiffXY, cv.CV_32F, (w,w))
+    # GST components calculations (stop)
+
+    # eigenvalue calculation (start)
+    # lambda1 = J11 + J22 + sqrt((J11-J22)^2 + 4*J12^2)
+    # lambda2 = J11 + J22 - sqrt((J11-J22)^2 + 4*J12^2)
+    tmp1 = J11 + J22
+    tmp2 = J11 - J22
+    tmp2 = cv.multiply(tmp2, tmp2)
+    tmp3 = cv.multiply(J12, J12)
+    tmp4 = np.sqrt(tmp2 + 4.0 * tmp3)
+
+    lambda1 = tmp1 + tmp4    # biggest eigenvalue
+    lambda2 = tmp1 - tmp4    # smallest eigenvalue
+    # eigenvalue calculation (stop)
+
+    # Coherency calculation (start)
+    # Coherency = (lambda1 - lambda2)/(lambda1 + lambda2)) - measure of anisotropism
+    # Coherency is anisotropy degree (consistency of local orientation)
+    imgCoherencyOut = cv.divide(lambda1 - lambda2, lambda1 + lambda2)
+    # Coherency calculation (stop)
+
+    # orientation angle calculation (start)
+    # tan(2*Alpha) = 2*J12/(J22 - J11)
+    # Alpha = 0.5 atan2(2*J12/(J22 - J11))
+    imgOrientationOut = cv.phase(J22 - J11, 2.0 * J12, angleInDegrees = True)
+    imgOrientationOut = 0.5 * imgOrientationOut
+    # orientation angle calculation (stop)
+
+    return imgCoherencyOut, imgOrientationOut
+## [calcGST]
+
+parser = argparse.ArgumentParser(description='Code for Anisotropic image segmentation tutorial.')
+parser.add_argument('-i', '--input', help='Path to input image.', required=True)
+args = parser.parse_args()
+
+imgIn = cv.imread(args.input, cv.IMREAD_GRAYSCALE)
+if imgIn is None:
+    print('Could not open or find the image: {}'.format(args.input))
+    exit(0)
+
+## [main_extra]
+## [main]
+imgCoherency, imgOrientation = calcGST(imgIn, W)
+
+## [thresholding]
+_, imgCoherencyBin = cv.threshold(imgCoherency, C_Thr, 255, cv.THRESH_BINARY)
+_, imgOrientationBin = cv.threshold(imgOrientation, LowThr, HighThr, cv.THRESH_BINARY)
+## [thresholding]
+
+## [combining]
+imgBin = cv.bitwise_and(imgCoherencyBin, imgOrientationBin)
+## [combining]
+## [main]
+
+imgCoherency = cv.normalize(imgCoherency, None, alpha=0, beta=1, norm_type=cv.NORM_MINMAX, dtype=cv.CV_32F)
+imgOrientation = cv.normalize(imgOrientation, None, alpha=0, beta=1, norm_type=cv.NORM_MINMAX, dtype=cv.CV_32F)
+
+cv.imshow('result.jpg', np.uint8(0.5*(imgIn + imgBin)))
+cv.imshow('Coherency.jpg', imgCoherency)
+cv.imshow('Orientation.jpg', imgOrientation)
+cv.waitKey(0)
+## [main_extra]

samples/python/video.py

@@ -32,13 +32,13 @@ Keys:
 # Python 2/3 compatibility
 from __future__ import print_function
 
+import numpy as np
+import cv2 as cv
+
 import re
 
-import numpy as np
 from numpy import pi, sin, cos
 
-import cv2 as cv
-
 # built-in modules
 from time import clock
 

samples/python/video_threaded.py

@@ -36,11 +36,9 @@ class DummyTask:
     def get(self):
         return self.data
 
-if __name__ == '__main__':
+def main():
     import sys
 
-    print(__doc__)
-
     try:
         fn = sys.argv[1]
     except:
@@ -86,4 +84,11 @@ if __name__ == '__main__':
             threaded_mode = not threaded_mode
         if ch == 27:
             break
-cv.destroyAllWindows()
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/video_v4l2.py

@@ -17,28 +17,31 @@ Keys:
 # Python 2/3 compatibility
 from __future__ import print_function
 
+import numpy as np
 import cv2 as cv
 
-def decode_fourcc(v):
+def main():
+
+    def decode_fourcc(v):
         v = int(v)
         return "".join([chr((v >> 8 * i) & 0xFF) for i in range(4)])
 
-font = cv.FONT_HERSHEY_SIMPLEX
-color = (0, 255, 0)
+    font = cv.FONT_HERSHEY_SIMPLEX
+    color = (0, 255, 0)
 
-cap = cv.VideoCapture(0)
-cap.set(cv.CAP_PROP_AUTOFOCUS, False)  # Known bug: https://github.com/opencv/opencv/pull/5474
+    cap = cv.VideoCapture(0)
+    cap.set(cv.CAP_PROP_AUTOFOCUS, False)  # Known bug: https://github.com/opencv/opencv/pull/5474
 
-cv.namedWindow("Video")
+    cv.namedWindow("Video")
 
-convert_rgb = True
-fps = int(cap.get(cv.CAP_PROP_FPS))
-focus = int(min(cap.get(cv.CAP_PROP_FOCUS) * 100, 2**31-1))  # ceil focus to C_LONG as Python3 int can go to +inf
+    convert_rgb = True
+    fps = int(cap.get(cv.CAP_PROP_FPS))
+    focus = int(min(cap.get(cv.CAP_PROP_FOCUS) * 100, 2**31-1))  # ceil focus to C_LONG as Python3 int can go to +inf
 
-cv.createTrackbar("FPS", "Video", fps, 30, lambda v: cap.set(cv.CAP_PROP_FPS, v))
-cv.createTrackbar("Focus", "Video", focus, 100, lambda v: cap.set(cv.CAP_PROP_FOCUS, v / 100))
+    cv.createTrackbar("FPS", "Video", fps, 30, lambda v: cap.set(cv.CAP_PROP_FPS, v))
+    cv.createTrackbar("Focus", "Video", focus, 100, lambda v: cap.set(cv.CAP_PROP_FOCUS, v / 100))
 
-while True:
+    while True:
         status, img = cap.read()
 
         fourcc = decode_fourcc(cap.get(cv.CAP_PROP_FOURCC))
@@ -65,3 +68,11 @@ while True:
         elif k == ord('g'):
             convert_rgb = not convert_rgb
             cap.set(cv.CAP_PROP_CONVERT_RGB, convert_rgb)
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()

samples/python/watershed.py

@@ -76,10 +76,10 @@ class App:
 
 
 if __name__ == '__main__':
+    print(__doc__)
     import sys
     try:
         fn = sys.argv[1]
     except:
         fn = 'fruits.jpg'
-    print(__doc__)
     App(cv.samples.findFile(fn)).run()