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fixed the ordering of parameters in PyArg_ParseTupleAndKeywords, added correct Ptr<CvDTreeSplit>::delete_obj() (ticket #406)

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Vadim Pisarevsky 2010-11-25 23:16:32 +00:00
parent 40e1fd5b1e
commit 59e2afe4d2
4 changed files with 27 additions and 21 deletions
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16
modules/imgproc/include/opencv2/imgproc/imgproc.hpp
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@ -383,7 +383,7 @@ CV_EXPORTS_W void copyMakeBorder( const Mat& src, CV_OUT Mat& dst,
//! smooths the image using median filter.
CV_EXPORTS_W void medianBlur( const Mat& src, CV_OUT Mat& dst, int ksize );
//! smooths the image using Gaussian filter.
CV_EXPORTS_W void GaussianBlur( const Mat& src, CV_OUT Mat& dst, Size ksize,
CV_EXPORTS_AS(gaussianBlur) void GaussianBlur( const Mat& src, CV_OUT Mat& dst, Size ksize,
double sigma1, double sigma2=0,
int borderType=BORDER_DEFAULT );
//! smooths the image using bilateral filter
@ -412,23 +412,23 @@ CV_EXPORTS_W void sepFilter2D( const Mat& src, CV_OUT Mat& dst, int ddepth,
double delta=0, int borderType=BORDER_DEFAULT );
//! applies generalized Sobel operator to the image
CV_EXPORTS_W void Sobel( const Mat& src, CV_OUT Mat& dst, int ddepth,
CV_EXPORTS_AS(sobel) void Sobel( const Mat& src, CV_OUT Mat& dst, int ddepth,
int dx, int dy, int ksize=3,
double scale=1, double delta=0,
int borderType=BORDER_DEFAULT );
//! applies the vertical or horizontal Scharr operator to the image
CV_EXPORTS_W void Scharr( const Mat& src, CV_OUT Mat& dst, int ddepth,
CV_EXPORTS_AS(scharr) void Scharr( const Mat& src, CV_OUT Mat& dst, int ddepth,
int dx, int dy, double scale=1, double delta=0,
int borderType=BORDER_DEFAULT );
//! applies Laplacian operator to the image
CV_EXPORTS_W void Laplacian( const Mat& src, CV_OUT Mat& dst, int ddepth,
CV_EXPORTS_AS(laplacian) void Laplacian( const Mat& src, CV_OUT Mat& dst, int ddepth,
int ksize=1, double scale=1, double delta=0,
int borderType=BORDER_DEFAULT );
//! applies Canny edge detector and produces the edge map.
CV_EXPORTS_W void Canny( const Mat& image, CV_OUT Mat& edges,
CV_EXPORTS_AS(canny) void Canny( const Mat& image, CV_OUT Mat& edges,
double threshold1, double threshold2,
int apertureSize=3, bool L2gradient=false );
@ -463,17 +463,17 @@ CV_EXPORTS_W void goodFeaturesToTrack( const Mat& image, CV_OUT vector<Point2f>&
bool useHarrisDetector=false, double k=0.04 );
//! finds lines in the black-n-white image using the standard or pyramid Hough transform
CV_EXPORTS_W void HoughLines( const Mat& image, CV_OUT vector<Vec2f>& lines,
CV_EXPORTS_AS(houghLines) void HoughLines( const Mat& image, CV_OUT vector<Vec2f>& lines,
double rho, double theta, int threshold,
double srn=0, double stn=0 );
//! finds line segments in the black-n-white image using probabalistic Hough transform
CV_EXPORTS_W void HoughLinesP( Mat& image, CV_OUT vector<Vec4i>& lines,
CV_EXPORTS_AS(houghLinesP) void HoughLinesP( Mat& image, CV_OUT vector<Vec4i>& lines,
double rho, double theta, int threshold,
double minLineLength=0, double maxLineGap=0 );
//! finds circles in the grayscale image using 2+1 gradient Hough transform
CV_EXPORTS_W void HoughCircles( const Mat& image, CV_OUT vector<Vec3f>& circles,
CV_EXPORTS_AS(houghCircles) void HoughCircles( const Mat& image, CV_OUT vector<Vec3f>& circles,
int method, double dp, double minDist,
double param1=100, double param2=100,
int minRadius=0, int maxRadius=0 );

3
modules/ml/include/opencv2/ml/ml.hpp
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@ -748,7 +748,6 @@ struct CvDTreeSplit
};
};
struct CvDTreeNode
{
int class_idx;
@ -2211,6 +2210,8 @@ typedef CvANN_MLP_TrainParams ANN_MLP_TrainParams;
typedef CvANN_MLP NeuralNet_MLP;
typedef CvGBTreesParams GradientBoostingTreeParams;
typedef CvGBTrees GradientBoostingTrees;
template<> CV_EXPORTS void Ptr<CvDTreeSplit>::delete_obj();
}

13
modules/ml/src/tree.cpp
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@ -1803,17 +1803,22 @@ double CvDTree::calc_node_dir( CvDTreeNode* node )
namespace cv
{
template<> CV_EXPORTS void Ptr<CvDTreeSplit>::delete_obj()
{
fastFree(obj);
}
DTreeBestSplitFinder::DTreeBestSplitFinder( CvDTree* _tree, CvDTreeNode* _node)
{
tree = _tree;
node = _node;
splitSize = tree->get_data()->split_heap->elem_size;
bestSplit = (CvDTreeSplit*)(new char[splitSize]);
bestSplit = (CvDTreeSplit*)fastMalloc(splitSize);
memset((CvDTreeSplit*)bestSplit, 0, splitSize);
bestSplit->quality = -1;
bestSplit->condensed_idx = INT_MIN;
split = (CvDTreeSplit*)(new char[splitSize]);
split = (CvDTreeSplit*)fastMalloc(splitSize);
memset((CvDTreeSplit*)split, 0, splitSize);
//haveSplit = false;
}
@ -1824,9 +1829,9 @@ DTreeBestSplitFinder::DTreeBestSplitFinder( const DTreeBestSplitFinder& finder,
node = finder.node;
splitSize = tree->get_data()->split_heap->elem_size;
bestSplit = (CvDTreeSplit*)(new char[splitSize]);
bestSplit = (CvDTreeSplit*)fastMalloc(splitSize);
memcpy((CvDTreeSplit*)(bestSplit), (const CvDTreeSplit*)finder.bestSplit, splitSize);
split = (CvDTreeSplit*)(new char[splitSize]);
split = (CvDTreeSplit*)fastMalloc(splitSize);
memset((CvDTreeSplit*)split, 0, splitSize);
}

16
modules/python/gen2.py
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@ -513,15 +513,15 @@ class FuncInfo(object):
sys.exit(-1)
amapping = simple_argtype_mapping.get(tp, (tp, "O", defval0))
all_cargs.append(amapping)
parse_name = a.name
if a.py_inputarg:
if amapping[1] == "O":
code_decl += " PyObject* pyobj_%s = NULL;\n" % (a.name,)
parse_arglist.append("pyobj_" + a.name)
parse_name = "pyobj_" + a.name
code_cvt_list.append("pyopencv_to(pyobj_%s, %s)" % (a.name, a.name))
else:
parse_arglist.append(a.name)
all_cargs.append([amapping, parse_name])
defval = a.defval
if not defval:
defval = amapping[2]
@ -556,7 +556,7 @@ class FuncInfo(object):
if v.args:
# form the format spec for PyArg_ParseTupleAndKeywords
fmtspec = "".join([all_cargs[argno][1] for aname, argno in v.py_arglist])
fmtspec = "".join([all_cargs[argno][0][1] for aname, argno in v.py_arglist])
if v.py_noptargs > 0:
fmtspec = fmtspec[:-v.py_noptargs] + "|" + fmtspec[-v.py_noptargs:]
fmtspec += ":" + fullname
@ -568,7 +568,7 @@ class FuncInfo(object):
code_parse = gen_template_parse_args.substitute(
kw_list = ", ".join(['"' + aname + '"' for aname, argno in v.py_arglist]),
fmtspec = fmtspec,
parse_arglist = ", ".join(["&" + aname for aname in parse_arglist]),
parse_arglist = ", ".join(["&" + all_cargs[argno][1] for aname, argno in v.py_arglist]),
code_cvt = " &&\n ".join(code_cvt_list))
else:
code_parse = "if(PyObject_Size(args) == 0 && PyObject_Size(kw) == 0)"
@ -586,7 +586,7 @@ class FuncInfo(object):
fmtspec = "N"*len(v.py_outlist)
backcvt_arg_list = []
for aname, argno in v.py_outlist:
amapping = all_cargs[argno]
amapping = all_cargs[argno][0]
backcvt_arg_list.append("%s(%s)" % (amapping[2], aname))
code_ret = "return Py_BuildValue(\"(%s)\", %s)" % \
(fmtspec, ", ".join(["pyopencv_from(" + aname + ")" for aname, argno in v.py_outlist]))