mirror of
https://github.com/opencv/opencv.git
synced 2026-07-29 07:13:02 +04:00
fixed 2 possible build problems (in opencv_gpu & docs) (ticket #1191 + fix from Steve Macao). removed obsolete stuff from opencv_extra_api.hpp, since with InputArray/OutputArray the existing C++ API can be successfully wrapped for Python.
This commit is contained in:
Vadim Pisarevsky
+6
-6
@@ -28,12 +28,12 @@ add_custom_target(docs
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${CMAKE_CURRENT_SOURCE_DIR}/pics ${CMAKE_CURRENT_BINARY_DIR}/doc/opencv1/pics
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COMMAND ${CMAKE_COMMAND} -E copy_if_different
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${CMAKE_CURRENT_SOURCE_DIR}/mymath.sty ${CMAKE_CURRENT_BINARY_DIR}
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COMMAND ${PDFLATEX_COMPILER} opencv2refman
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COMMAND ${PDFLATEX_COMPILER} opencv2refman
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COMMAND ${PDFLATEX_COMPILER} opencv_user
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COMMAND ${PDFLATEX_COMPILER} opencv_user
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COMMAND ${PDFLATEX_COMPILER} opencv_tutorials
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COMMAND ${PDFLATEX_COMPILER} opencv_tutorials
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COMMAND ${PDFLATEX_COMPILER} opencv2refman.tex
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COMMAND ${PDFLATEX_COMPILER} opencv2refman.tex
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COMMAND ${PDFLATEX_COMPILER} opencv_user.tex
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COMMAND ${PDFLATEX_COMPILER} opencv_user.tex
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COMMAND ${PDFLATEX_COMPILER} opencv_tutorials.tex
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COMMAND ${PDFLATEX_COMPILER} opencv_tutorials.tex
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DEPENDS ${OPENCV_DOC_DEPS}
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WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
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COMMENT "Generating the PDF Manuals")
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@@ -218,7 +218,7 @@ if(BUILD_TESTS AND EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/test)
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# Additional target properties
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set_target_properties(${the_test_target} PROPERTIES
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DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
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RUNTIME_OUTPUT_DIRECTORY ${EXECUTABLE_OUTPUT_PATH}
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RUNTIME_OUTPUT_DIRECTORY "${EXECUTABLE_OUTPUT_PATH}"
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)
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if(ENABLE_SOLUTION_FOLDERS)
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@@ -455,9 +455,9 @@ CV_EXPORTS_W void preCornerDetect( InputArray src, OutputArray dst, int ksize,
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int borderType=BORDER_DEFAULT );
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//! adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria
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CV_EXPORTS void cornerSubPix( InputArray image, InputOutputArray corners,
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Size winSize, Size zeroZone,
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TermCriteria criteria );
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CV_EXPORTS_W void cornerSubPix( InputArray image, InputOutputArray corners,
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Size winSize, Size zeroZone,
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TermCriteria criteria );
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//! finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima
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CV_EXPORTS_W void goodFeaturesToTrack( InputArray image, OutputArray corners,
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@@ -807,7 +807,7 @@ enum
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};
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//! retrieves contours and the hierarchical information from black-n-white image.
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CV_EXPORTS void findContours( InputOutputArray image, OutputArrayOfArrays contours,
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CV_EXPORTS_W void findContours( InputOutputArray image, OutputArrayOfArrays contours,
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OutputArray hierarchy, int mode,
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int method, Point offset=Point());
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@@ -816,16 +816,16 @@ CV_EXPORTS void findContours( InputOutputArray image, OutputArrayOfArrays contou
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int mode, int method, Point offset=Point());
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//! draws contours in the image
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CV_EXPORTS void drawContours( InputOutputArray image, InputArrayOfArrays contours,
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CV_EXPORTS_W void drawContours( InputOutputArray image, InputArrayOfArrays contours,
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int contourIdx, const Scalar& color,
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int thickness=1, int lineType=8,
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InputArray hierarchy=noArray(),
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int maxLevel=INT_MAX, Point offset=Point() );
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//! approximates contour or a curve using Douglas-Peucker algorithm
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CV_EXPORTS void approxPolyDP( InputArray curve,
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OutputArray approxCurve,
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double epsilon, bool closed );
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CV_EXPORTS_W void approxPolyDP( InputArray curve,
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OutputArray approxCurve,
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double epsilon, bool closed );
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//! computes the contour perimeter (closed=true) or a curve length
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CV_EXPORTS_W double arcLength( InputArray curve, bool closed );
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@@ -842,8 +842,8 @@ CV_EXPORTS_W void minEnclosingCircle( InputArray points,
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CV_EXPORTS_W double matchShapes( InputArray contour1, InputArray contour2,
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int method, double parameter );
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//! computes convex hull for a set of 2D points.
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CV_EXPORTS void convexHull( InputArray points, OutputArray hull,
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bool clockwise=false, bool returnPoints=true );
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CV_EXPORTS_W void convexHull( InputArray points, OutputArray hull,
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bool clockwise=false, bool returnPoints=true );
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//! returns true iff the contour is convex. Does not support contours with self-intersection
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CV_EXPORTS_W bool isContourConvex( InputArray contour );
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@@ -852,8 +852,8 @@ CV_EXPORTS_W bool isContourConvex( InputArray contour );
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CV_EXPORTS_W RotatedRect fitEllipse( InputArray points );
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//! fits line to the set of 2D points using M-estimator algorithm
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CV_EXPORTS void fitLine( InputArray points, OutputArray line, int distType,
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double param, double reps, double aeps );
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CV_EXPORTS_W void fitLine( InputArray points, OutputArray line, int distType,
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double param, double reps, double aeps );
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//! checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary
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CV_EXPORTS_W double pointPolygonTest( InputArray contour, Point2f pt, bool measureDist );
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@@ -205,207 +205,8 @@ CV_WRAP void calcBackProject( const vector<Mat>& images, const vector<int>& chan
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}
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static void addChildContour(const vector<Mat>& contours,
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const Mat& hierarchy,
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int i, vector<CvSeq>& seq,
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vector<CvSeqBlock>& block)
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{
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size_t count = contours.size();
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for( ; i >= 0; i = ((const Vec4i*)hierarchy.data)[i][0] )
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{
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const vector<Point>& ci = contours[i];
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cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
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!ci.empty() ? (void*)&ci[0] : 0, (int)ci.size(),
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&seq[i], &block[i] );
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const Vec4i h_i = ((const Vec4i*)hierarchy.data)[i];
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int h_next = h_i[0], h_prev = h_i[1], v_next = h_i[2], v_prev = h_i[3];
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seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0;
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seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0;
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seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0;
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seq[i].v_prev = (size_t)v_prev < count ? &seq[v_prev] : 0;
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if( v_next >= 0 )
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addChildContour(contours, hierarchy, v_next, seq, block);
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}
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}
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//! draws contours in the image
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CV_WRAP static inline void drawContours( Mat& image, const vector<Mat>& contours,
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int contourIdx, const Scalar& color,
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int thickness=1, int lineType=8,
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const Mat& hierarchy=Mat(),
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int maxLevel=INT_MAX, Point offset=Point() )
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{
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CvMat _image = image;
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size_t i = 0, first = 0, last = contours.size();
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vector<CvSeq> seq;
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vector<CvSeqBlock> block;
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if( !last )
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return;
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seq.resize(last);
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block.resize(last);
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for( i = first; i < last; i++ )
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seq[i].first = 0;
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if( contourIdx >= 0 )
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{
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CV_Assert( 0 <= contourIdx && contourIdx < (int)last );
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first = contourIdx;
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last = contourIdx + 1;
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}
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for( i = first; i < last; i++ )
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{
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const Mat& ci = contours[i];
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int ci_size = ci.checkVector(2, CV_32S);
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CV_Assert( ci_size >= 0 );
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cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
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ci_size > 0 ? ci.data : 0, ci_size, &seq[i], &block[i] );
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}
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if( hierarchy.empty() || maxLevel == 0 )
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for( i = first; i < last; i++ )
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{
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seq[i].h_next = i < last-1 ? &seq[i+1] : 0;
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seq[i].h_prev = i > first ? &seq[i-1] : 0;
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}
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else
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{
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int hsz = hierarchy.checkVector(4, CV_32S);
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size_t count = last - first;
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CV_Assert((size_t)hsz == contours.size());
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if( count == contours.size() )
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{
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for( i = first; i < last; i++ )
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{
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const Vec4i& h_i = ((const Vec4i*)hierarchy.data)[i];
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int h_next = h_i[0], h_prev = h_i[1], v_next = h_i[2], v_prev = h_i[3];
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seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0;
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seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0;
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seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0;
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seq[i].v_prev = (size_t)v_prev < count ? &seq[v_prev] : 0;
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}
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}
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else
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{
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int child = ((const Vec4i*)hierarchy.data)[first][2];
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if( child >= 0 )
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{
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addChildContour(contours, hierarchy, child, seq, block);
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seq[first].v_next = &seq[child];
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}
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}
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}
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cvDrawContours( &_image, &seq[first], color, color, contourIdx >= 0 ?
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-maxLevel : maxLevel, thickness, lineType, offset );
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}
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CV_WRAP static inline void approxPolyDP( const Mat& curve,
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CV_OUT Mat& approxCurve,
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double epsilon, bool closed )
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{
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if( curve.depth() == CV_32S )
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{
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vector<Point> result;
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approxPolyDP(curve, result, epsilon, closed);
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Mat(result).copyTo(approxCurve);
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}
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else if( curve.depth() == CV_32F )
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{
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vector<Point2f> result;
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approxPolyDP(curve, result, epsilon, closed);
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Mat(result).copyTo(approxCurve);
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}
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else
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CV_Error(CV_StsUnsupportedFormat, "");
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}
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CV_WRAP static inline void convexHull( const Mat& points, CV_OUT Mat& hull, bool returnPoints=true, bool clockwise=false )
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{
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if( !returnPoints )
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{
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vector<int> h;
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convexHull(points, h, clockwise);
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Mat(h).copyTo(hull);
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}
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else if( points.depth() == CV_32S )
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{
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vector<Point> h;
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convexHull(points, h, clockwise);
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Mat(h).copyTo(hull);
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}
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else if( points.depth() == CV_32F )
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{
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vector<Point2f> h;
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convexHull(points, h, clockwise);
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Mat(h).copyTo(hull);
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}
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}
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CV_WRAP static inline void fitLine( const Mat& points, CV_OUT vector<float>& line,
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int distType, double param, double reps, double aeps )
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{
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if(points.channels() == 2 || points.cols == 2)
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{
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line.resize(4);
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fitLine(points, *(Vec4f*)&line[0], distType, param, reps, aeps);
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}
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else
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{
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line.resize(6);
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fitLine(points, *(Vec6f*)&line[0], distType, param, reps, aeps);
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}
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}
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CV_WRAP static inline int estimateAffine3D( const Mat& from, const Mat& to,
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CV_OUT Mat& dst, CV_OUT Mat& outliers,
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double param1 = 3.0, double param2 = 0.99 )
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{
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vector<uchar> outliers_vec;
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int res = estimateAffine3D(from, to, dst, outliers_vec, param1, param2);
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Mat(outliers_vec).copyTo(outliers);
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return res;
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}
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CV_WRAP static inline void cornerSubPix( const Mat& image, Mat& corners,
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Size winSize, Size zeroZone,
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TermCriteria criteria )
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{
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int n = corners.checkVector(2, CV_32F);
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CV_Assert(n >= 0);
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if( n == 0 )
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return;
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CvMat _image = image;
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cvFindCornerSubPix(&_image, (CvPoint2D32f*)corners.data, n, winSize, zeroZone, criteria);
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}
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/////////////////////////////// calib3d ///////////////////////////////////////////
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CV_WRAP static inline void convertPointsHomogeneous( const Mat& src, CV_OUT Mat& dst )
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{
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int n;
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if( (n = src.checkVector(2)) >= 0 )
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dst.create(n, 2, src.depth());
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else if( (n = src.checkVector(3)) >= 0 )
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dst.create(n, 3, src.depth());
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else
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CV_Error(CV_StsBadSize, "");
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CvMat _src = src, _dst = dst;
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cvConvertPointsHomogeneous(&_src, &_dst);
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}
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//! finds circles' grid pattern of the specified size in the image
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CV_WRAP static inline void findCirclesGridDefault( InputArray image, Size patternSize,
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OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID )
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