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Fix gcc build errors and warnings

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This commit is contained in:
Andrey Kamaev 2012-09-05 15:51:51 +04:00
parent 5eac0419b2
commit bcd0aefbca
6 changed files with 147 additions and 138 deletions
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28
3rdparty/libjasper/jpc_qmfb.c vendored
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@ -94,14 +94,14 @@
#define QMFB_SPLITBUFSIZE 4096
#define QMFB_JOINBUFSIZE 4096
int jpc_ft_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
int jpc_ft_analyze(int *a, int xstart, int ystart, int width, int height,
int stride);
int jpc_ft_synthesize(int *a, int xstart, int ystart, int width, int height,
int stride);
int jpc_ns_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
int jpc_ns_analyze(int *a, int xstart, int ystart, int width, int height,
int stride);
int jpc_ns_synthesize(jpc_fix_t *a, int xstart, int ystart, int width,
int jpc_ns_synthesize(int *a, int xstart, int ystart, int width,
int height, int stride);
void jpc_ft_fwdlift_row(jpc_fix_t *a, int numcols, int parity);
@ -1556,7 +1556,7 @@ void jpc_ft_invlift_colres(jpc_fix_t *a, int numrows, int numcols, int stride,
}
int jpc_ft_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
int jpc_ft_analyze(int *a, int xstart, int ystart, int width, int height,
int stride)
{
int numrows = height;
@ -1568,7 +1568,7 @@ int jpc_ft_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
int maxcols;
maxcols = (numcols / JPC_QMFB_COLGRPSIZE) * JPC_QMFB_COLGRPSIZE;
startptr = &a[0];
startptr = (jpc_fix_t*)&a[0];
for (i = 0; i < maxcols; i += JPC_QMFB_COLGRPSIZE) {
jpc_qmfb_split_colgrp(startptr, numrows, stride, rowparity);
jpc_ft_fwdlift_colgrp(startptr, numrows, stride, rowparity);
@ -1581,7 +1581,7 @@ int jpc_ft_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
rowparity);
}
startptr = &a[0];
startptr = (jpc_fix_t*)&a[0];
for (i = 0; i < numrows; ++i) {
jpc_qmfb_split_row(startptr, numcols, colparity);
jpc_ft_fwdlift_row(startptr, numcols, colparity);
@ -1604,7 +1604,7 @@ int jpc_ft_synthesize(int *a, int xstart, int ystart, int width, int height,
jpc_fix_t *startptr;
int i;
startptr = &a[0];
startptr = (jpc_fix_t*)&a[0];
for (i = 0; i < numrows; ++i) {
jpc_ft_invlift_row(startptr, numcols, colparity);
jpc_qmfb_join_row(startptr, numcols, colparity);
@ -1612,7 +1612,7 @@ int jpc_ft_synthesize(int *a, int xstart, int ystart, int width, int height,
}
maxcols = (numcols / JPC_QMFB_COLGRPSIZE) * JPC_QMFB_COLGRPSIZE;
startptr = &a[0];
startptr = (jpc_fix_t*)&a[0];
for (i = 0; i < maxcols; i += JPC_QMFB_COLGRPSIZE) {
jpc_ft_invlift_colgrp(startptr, numrows, stride, rowparity);
jpc_qmfb_join_colgrp(startptr, numrows, stride, rowparity);
@ -3068,7 +3068,7 @@ void jpc_ns_invlift_col(jpc_fix_t *a, int numrows, int stride,
}
int jpc_ns_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
int jpc_ns_analyze(int *a, int xstart, int ystart, int width, int height,
int stride)
{
@ -3081,7 +3081,7 @@ int jpc_ns_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
int maxcols;
maxcols = (numcols / JPC_QMFB_COLGRPSIZE) * JPC_QMFB_COLGRPSIZE;
startptr = &a[0];
startptr = (jpc_fix_t*)&a[0];
for (i = 0; i < maxcols; i += JPC_QMFB_COLGRPSIZE) {
jpc_qmfb_split_colgrp(startptr, numrows, stride, rowparity);
jpc_ns_fwdlift_colgrp(startptr, numrows, stride, rowparity);
@ -3094,7 +3094,7 @@ int jpc_ns_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
rowparity);
}
startptr = &a[0];
startptr = (jpc_fix_t*)&a[0];
for (i = 0; i < numrows; ++i) {
jpc_qmfb_split_row(startptr, numcols, colparity);
jpc_ns_fwdlift_row(startptr, numcols, colparity);
@ -3105,7 +3105,7 @@ int jpc_ns_analyze(jpc_fix_t *a, int xstart, int ystart, int width, int height,
}
int jpc_ns_synthesize(jpc_fix_t *a, int xstart, int ystart, int width,
int jpc_ns_synthesize(int *a, int xstart, int ystart, int width,
int height, int stride)
{
@ -3117,7 +3117,7 @@ int jpc_ns_synthesize(jpc_fix_t *a, int xstart, int ystart, int width,
jpc_fix_t *startptr;
int i;
startptr = &a[0];
startptr = (jpc_fix_t*)&a[0];
for (i = 0; i < numrows; ++i) {
jpc_ns_invlift_row(startptr, numcols, colparity);
jpc_qmfb_join_row(startptr, numcols, colparity);
@ -3125,7 +3125,7 @@ int jpc_ns_synthesize(jpc_fix_t *a, int xstart, int ystart, int width,
}
maxcols = (numcols / JPC_QMFB_COLGRPSIZE) * JPC_QMFB_COLGRPSIZE;
startptr = &a[0];
startptr = (jpc_fix_t*)&a[0];
for (i = 0; i < maxcols; i += JPC_QMFB_COLGRPSIZE) {
jpc_ns_invlift_colgrp(startptr, numrows, stride, rowparity);
jpc_qmfb_join_colgrp(startptr, numrows, stride, rowparity);

5
modules/core/include/opencv2/core/internal.hpp
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@ -135,6 +135,11 @@ CV_INLINE IppiSize ippiSize(int width, int height)
# if defined __AVX__ || (defined _MSC_FULL_VER && _MSC_FULL_VER >= 160040219)
# include <immintrin.h>
# define CV_AVX 1
# if defined(_XCR_XFEATURE_ENABLED_MASK)
# define __xgetbv() _xgetbv(_XCR_XFEATURE_ENABLED_MASK)
# else
# define __xgetbv() 0
# endif
# else
# define CV_AVX 0
# endif

8
modules/highgui/src/cap_gstreamer.cpp
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@ -183,7 +183,7 @@ bool CvCapture_GStreamer::grabFrame()
IplImage * CvCapture_GStreamer::retrieveFrame(int)
{
if(!buffer)
return false;
return 0;
if(!frame) {
gint height, width;
@ -193,7 +193,7 @@ IplImage * CvCapture_GStreamer::retrieveFrame(int)
if(!gst_structure_get_int(structure, "width", &width) ||
!gst_structure_get_int(structure, "height", &height))
return false;
return 0;
frame = cvCreateImageHeader(cvSize(width, height), IPL_DEPTH_8U, 3);
gst_caps_unref(buff_caps);
@ -572,7 +572,7 @@ CvVideoWriter* cvCreateVideoWriter_GStreamer(const char* filename, int fourcc, d
return wrt;
delete wrt;
return false;
return 0;
}
void CvCapture_GStreamer::close()
@ -746,5 +746,5 @@ CvCapture* cvCreateCapture_GStreamer(int type, const char* filename )
return capture;
delete capture;
return false;
return 0;
}

163
modules/nonfree/src/surf.cpp
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@ -257,16 +257,97 @@ interpolateKeypoint( float N9[3][9], int dx, int dy, int ds, KeyPoint& kpt )
return ok;
}
// Multi-threaded construction of the scale-space pyramid
struct SURFBuildInvoker
{
SURFBuildInvoker( const Mat& _sum, const vector<int>& _sizes,
const vector<int>& _sampleSteps,
vector<Mat>& _dets, vector<Mat>& _traces )
{
sum = &_sum;
sizes = &_sizes;
sampleSteps = &_sampleSteps;
dets = &_dets;
traces = &_traces;
}
void operator()(const BlockedRange& range) const
{
for( int i=range.begin(); i<range.end(); i++ )
calcLayerDetAndTrace( *sum, (*sizes)[i], (*sampleSteps)[i], (*dets)[i], (*traces)[i] );
}
const Mat *sum;
const vector<int> *sizes;
const vector<int> *sampleSteps;
vector<Mat>* dets;
vector<Mat>* traces;
};
// Multi-threaded search of the scale-space pyramid for keypoints
struct SURFFindInvoker
{
SURFFindInvoker( const Mat& _sum, const Mat& _mask_sum,
const vector<Mat>& _dets, const vector<Mat>& _traces,
const vector<int>& _sizes, const vector<int>& _sampleSteps,
const vector<int>& _middleIndices, vector<KeyPoint>& _keypoints,
int _nOctaveLayers, float _hessianThreshold )
{
sum = &_sum;
mask_sum = &_mask_sum;
dets = &_dets;
traces = &_traces;
sizes = &_sizes;
sampleSteps = &_sampleSteps;
middleIndices = &_middleIndices;
keypoints = &_keypoints;
nOctaveLayers = _nOctaveLayers;
hessianThreshold = _hessianThreshold;
}
static void findMaximaInLayer( const Mat& sum, const Mat& mask_sum,
const vector<Mat>& dets, const vector<Mat>& traces,
const vector<int>& sizes, vector<KeyPoint>& keypoints,
int octave, int layer, float hessianThreshold, int sampleStep );
void operator()(const BlockedRange& range) const
{
for( int i=range.begin(); i<range.end(); i++ )
{
int layer = (*middleIndices)[i];
int octave = i / nOctaveLayers;
findMaximaInLayer( *sum, *mask_sum, *dets, *traces, *sizes,
*keypoints, octave, layer, hessianThreshold,
(*sampleSteps)[layer] );
}
}
const Mat *sum;
const Mat *mask_sum;
const vector<Mat>* dets;
const vector<Mat>* traces;
const vector<int>* sizes;
const vector<int>* sampleSteps;
const vector<int>* middleIndices;
vector<KeyPoint>* keypoints;
int nOctaveLayers;
float hessianThreshold;
#ifdef HAVE_TBB
static tbb::mutex findMaximaInLayer_m;
#endif
};
#ifdef HAVE_TBB
tbb::mutex SURFFindInvoker::findMaximaInLayer_m;
#endif
/*
* Find the maxima in the determinant of the Hessian in a layer of the
* scale-space pyramid
*/
static void
findMaximaInLayer( const Mat& sum, const Mat& mask_sum,
void SURFFindInvoker::findMaximaInLayer( const Mat& sum, const Mat& mask_sum,
const vector<Mat>& dets, const vector<Mat>& traces,
const vector<int>& sizes, vector<KeyPoint>& keypoints,
int octave, int layer, float hessianThreshold, int sampleStep )
@ -367,84 +448,6 @@ findMaximaInLayer( const Mat& sum, const Mat& mask_sum,
}
}
// Multi-threaded construction of the scale-space pyramid
struct SURFBuildInvoker
{
SURFBuildInvoker( const Mat& _sum, const vector<int>& _sizes,
const vector<int>& _sampleSteps,
vector<Mat>& _dets, vector<Mat>& _traces )
{
sum = &_sum;
sizes = &_sizes;
sampleSteps = &_sampleSteps;
dets = &_dets;
traces = &_traces;
}
void operator()(const BlockedRange& range) const
{
for( int i=range.begin(); i<range.end(); i++ )
calcLayerDetAndTrace( *sum, (*sizes)[i], (*sampleSteps)[i], (*dets)[i], (*traces)[i] );
}
const Mat *sum;
const vector<int> *sizes;
const vector<int> *sampleSteps;
vector<Mat>* dets;
vector<Mat>* traces;
};
// Multi-threaded search of the scale-space pyramid for keypoints
struct SURFFindInvoker
{
SURFFindInvoker( const Mat& _sum, const Mat& _mask_sum,
const vector<Mat>& _dets, const vector<Mat>& _traces,
const vector<int>& _sizes, const vector<int>& _sampleSteps,
const vector<int>& _middleIndices, vector<KeyPoint>& _keypoints,
int _nOctaveLayers, float _hessianThreshold )
{
sum = &_sum;
mask_sum = &_mask_sum;
dets = &_dets;
traces = &_traces;
sizes = &_sizes;
sampleSteps = &_sampleSteps;
middleIndices = &_middleIndices;
keypoints = &_keypoints;
nOctaveLayers = _nOctaveLayers;
hessianThreshold = _hessianThreshold;
#ifdef HAVE_TBB
//touch the mutex to ensure that it's initialization is finished
CV_Assert(&findMaximaInLayer_m > 0);
#endif
}
void operator()(const BlockedRange& range) const
{
for( int i=range.begin(); i<range.end(); i++ )
{
int layer = (*middleIndices)[i];
int octave = i / nOctaveLayers;
findMaximaInLayer( *sum, *mask_sum, *dets, *traces, *sizes,
*keypoints, octave, layer, hessianThreshold,
(*sampleSteps)[layer] );
}
}
const Mat *sum;
const Mat *mask_sum;
const vector<Mat>* dets;
const vector<Mat>* traces;
const vector<int>* sizes;
const vector<int>* sampleSteps;
const vector<int>* middleIndices;
vector<KeyPoint>* keypoints;
int nOctaveLayers;
float hessianThreshold;
};
struct KeypointGreater
{
inline bool operator()(const KeyPoint& kp1, const KeyPoint& kp2) const

15
modules/objdetect/src/haar.cpp
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@ -43,6 +43,7 @@
#include "precomp.hpp"
#include <stdio.h>
#include "opencv2/core/internal.hpp"
#if CV_SSE2 || CV_SSE3
@ -780,7 +781,7 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
#ifdef CV_HAAR_USE_AVX
bool haveAVX = false;
if(cv::checkHardwareSupport(CV_CPU_AVX))
if(_xgetbv(_XCR_XFEATURE_ENABLED_MASK)&0x6)// Check if the OS will save the YMM registers
if(__xgetbv()&0x6)// Check if the OS will save the YMM registers
{
haveAVX = true;
}
@ -867,7 +868,7 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
for( i = start_stage; i < cascade->count; i++ )
{
stage_sum = 0.0;
int j = 0;
j = 0;
float CV_DECL_ALIGNED(32) buf[8];
if( cascade->stage_classifier[i].two_rects )
{
@ -1020,12 +1021,12 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
}
else
#endif
#if defined CV_HAAR_USE_SSE && CV_HAAR_USE_SSE && !CV_HAAR_USE_AVX //old SSE optimization
#if defined CV_HAAR_USE_SSE && CV_HAAR_USE_SSE && (!defined CV_HAAR_USE_AVX || !CV_HAAR_USE_AVX) //old SSE optimization
if(haveSSE2)
{
for( i = start_stage; i < cascade->count; i++ )
{
__m128d stage_sum = _mm_setzero_pd();
__m128d vstage_sum = _mm_setzero_pd();
if( cascade->stage_classifier[i].two_rects )
{
for( j = 0; j < cascade->stage_classifier[i].count; j++ )
@ -1040,7 +1041,7 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
__m128d sum = _mm_set_sd(calc_sum(node->feature.rect[0],p_offset) * node->feature.rect[0].weight +
calc_sum(node->feature.rect[1],p_offset) * node->feature.rect[1].weight);
t = _mm_cmpgt_sd(t, sum);
stage_sum = _mm_add_sd(stage_sum, _mm_blendv_pd(b, a, t));
vstage_sum = _mm_add_sd(vstage_sum, _mm_blendv_pd(b, a, t));
}
}
else
@ -1060,11 +1061,11 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
__m128d sum = _mm_set_sd(_sum);
t = _mm_cmpgt_sd(t, sum);
stage_sum = _mm_add_sd(stage_sum, _mm_blendv_pd(b, a, t));
vstage_sum = _mm_add_sd(vstage_sum, _mm_blendv_pd(b, a, t));
}
}
__m128d i_threshold = _mm_set1_pd(cascade->stage_classifier[i].threshold);
if( _mm_comilt_sd(stage_sum, i_threshold) )
if( _mm_comilt_sd(vstage_sum, i_threshold) )
return -i;
}
}

2
modules/python/src2/cv2.cv.hpp
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@ -2875,7 +2875,7 @@ public:
rr = new float*[len];
for (Py_ssize_t i = 0; i < len; i++) {
PyObject *item = PySequence_Fast_GET_ITEM(fi, i);
floats ff;
floats ff; ff.f = 0;
if (!convert_to_floats(item, &ff))
return 0;
rr[i] = ff.f;