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Fixed mingw build.

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This commit is contained in:
Andrey Kamaev
2012-06-08 03:15:08 +00:00
parent bee982b492
commit f62028dc16
41 changed files with 624 additions and 585 deletions
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35
apps/haartraining/cvboost.cpp
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@@ -213,13 +213,10 @@ static int icvFindStumpThreshold_##suffix(
float* curval = NULL; \
float curlerror = 0.0F; \
float currerror = 0.0F; \
float wposl; \
float wposr; \
\
int i = 0; \
int idx = 0; \
\
wposl = wposr = 0.0F; \
if( *sumw == FLT_MAX ) \
{ \
/* calculate sums */ \
@@ -298,8 +295,8 @@ static int icvFindStumpThreshold_##suffix(
*/
#define ICV_DEF_FIND_STUMP_THRESHOLD_MISC( suffix, type ) \
ICV_DEF_FIND_STUMP_THRESHOLD( misc_##suffix, type, \
wposl = 0.5F * ( wl + wyl ); \
wposr = 0.5F * ( wr + wyr ); \
float wposl = 0.5F * ( wl + wyl ); \
float wposr = 0.5F * ( wr + wyr ); \
curleft = 0.5F * ( 1.0F + curleft ); \
curright = 0.5F * ( 1.0F + curright ); \
curlerror = MIN( wposl, wl - wposl ); \
@@ -311,8 +308,8 @@ static int icvFindStumpThreshold_##suffix(
*/
#define ICV_DEF_FIND_STUMP_THRESHOLD_GINI( suffix, type ) \
ICV_DEF_FIND_STUMP_THRESHOLD( gini_##suffix, type, \
wposl = 0.5F * ( wl + wyl ); \
wposr = 0.5F * ( wr + wyr ); \
float wposl = 0.5F * ( wl + wyl ); \
float wposr = 0.5F * ( wr + wyr ); \
curleft = 0.5F * ( 1.0F + curleft ); \
curright = 0.5F * ( 1.0F + curright ); \
curlerror = 2.0F * wposl * ( 1.0F - curleft ); \
@@ -326,8 +323,8 @@ static int icvFindStumpThreshold_##suffix(
*/
#define ICV_DEF_FIND_STUMP_THRESHOLD_ENTROPY( suffix, type ) \
ICV_DEF_FIND_STUMP_THRESHOLD( entropy_##suffix, type, \
wposl = 0.5F * ( wl + wyl ); \
wposr = 0.5F * ( wr + wyr ); \
float wposl = 0.5F * ( wl + wyl ); \
float wposr = 0.5F * ( wr + wyr ); \
curleft = 0.5F * ( 1.0F + curleft ); \
curright = 0.5F * ( 1.0F + curright ); \
curlerror = currerror = 0.0F; \
@@ -1560,7 +1557,7 @@ CvBoostTrainer* icvBoostStartTraining( CvMat* trainClasses,
CV_MAT2VEC( *trainClasses, ydata, ystep, m );
CV_MAT2VEC( *weakTrainVals, traindata, trainstep, trainnum );
assert( m == trainnum );
CV_Assert( m == trainnum );
idxnum = 0;
idxstep = 0;
@@ -1640,8 +1637,8 @@ float icvBoostNextWeakClassifierDAB( CvMat* weakEvalVals,
CV_MAT2VEC( *trainClasses, ydata, ystep, ynum );
CV_MAT2VEC( *weights, wdata, wstep, wnum );
assert( m == ynum );
assert( m == wnum );
CV_Assert( m == ynum );
CV_Assert( m == wnum );
sumw = 0.0F;
err = 0.0F;
@@ -1808,8 +1805,8 @@ CvBoostTrainer* icvBoostStartTrainingLB( CvMat* trainClasses,
CV_MAT2VEC( *weakTrainVals, traindata, trainstep, trainnum );
CV_MAT2VEC( *weights, wdata, wstep, wnum );
assert( m == trainnum );
assert( m == wnum );
CV_Assert( m == trainnum );
CV_Assert( m == wnum );
idxnum = 0;
@@ -1889,9 +1886,9 @@ float icvBoostNextWeakClassifierLB( CvMat* weakEvalVals,
CV_MAT2VEC( *weakTrainVals, traindata, trainstep, trainnum );
CV_MAT2VEC( *weights, wdata, wstep, wnum );
assert( m == ynum );
assert( m == wnum );
assert( m == trainnum );
CV_Assert( m == ynum );
CV_Assert( m == wnum );
CV_Assert( m == trainnum );
//assert( m == trainer->count );
for( i = 0; i < trainer->count; i++ )
@@ -1944,8 +1941,8 @@ float icvBoostNextWeakClassifierGAB( CvMat* weakEvalVals,
CV_MAT2VEC( *trainClasses, ydata, ystep, ynum );
CV_MAT2VEC( *weights, wdata, wstep, wnum );
assert( m == ynum );
assert( m == wnum );
CV_Assert( m == ynum );
CV_Assert( m == wnum );
sumw = 0.0F;
for( i = 0; i < trainer->count; i++ )

4
apps/haartraining/cvhaarclassifier.cpp
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@@ -525,9 +525,9 @@ float icvEvalTreeCascadeClassifierFilter( CvIntHaarClassifier* classifier, sum_t
sum_type* tilted, float normfactor )
{
CvTreeCascadeNode* ptr;
CvTreeCascadeClassifier* tree;
//CvTreeCascadeClassifier* tree;
tree = (CvTreeCascadeClassifier*) classifier;
//tree = (CvTreeCascadeClassifier*) classifier;

3
apps/haartraining/cvhaartraining.cpp
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@@ -169,10 +169,11 @@ CvIntHaarFeatures* icvCreateIntHaarFeatures( CvSize winsize,
int dx = 0;
int dy = 0;
#if 0
float factor = 1.0F;
factor = ((float) winsize.width) * winsize.height / (24 * 24);
#if 0
s0 = (int) (s0 * factor);
s1 = (int) (s1 * factor);
s2 = (int) (s2 * factor);