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Merged the trunk r8589:8653 - all changes related to build warnings

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This commit is contained in:
Andrey Kamaev
2012-06-15 13:04:17 +00:00
parent 73c152abc4
commit bd0e0b5800
438 changed files with 20374 additions and 19674 deletions
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32
modules/objdetect/src/matching.cpp
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@@ -23,7 +23,7 @@
*/
int convolution(const CvLSVMFilterObject *Fi, const CvLSVMFeatureMap *map, float *f)
{
int n1, m1, n2, m2, p, size, diff1, diff2;
int n1, m1, n2, m2, p, /*size,*/ diff1, diff2;
int i1, i2, j1, j2, k;
float tmp_f1, tmp_f2, tmp_f3, tmp_f4;
float *pMap = NULL;
@@ -37,7 +37,7 @@ int convolution(const CvLSVMFilterObject *Fi, const CvLSVMFeatureMap *map, float
diff1 = n1 - n2 + 1;
diff2 = m1 - m2 + 1;
size = diff1 * diff2;
//size = diff1 * diff2;
for (j1 = diff2 - 1; j1 >= 0; j1--)
{
@@ -333,7 +333,7 @@ int filterDispositionLevel(const CvLSVMFilterObject *Fi, const CvLSVMFeatureMap
float **scoreFi,
int **pointsX, int **pointsY)
{
int n1, m1, n2, m2, p, size, diff1, diff2;
int n1, m1, n2, m2, /*p,*/ size, diff1, diff2;
float *f;
int i1, j1;
int res;
@@ -342,7 +342,7 @@ int filterDispositionLevel(const CvLSVMFilterObject *Fi, const CvLSVMFeatureMap
m1 = pyramid->sizeX;
n2 = Fi->sizeY;
m2 = Fi->sizeX;
p = pyramid->numFeatures;
//p = pyramid->numFeatures;
(*scoreFi) = NULL;
(*pointsX) = NULL;
(*pointsY) = NULL;
@@ -418,7 +418,7 @@ int filterDispositionLevelFFT(const CvLSVMFilterObject *Fi, const CvLSVMFftImage
float **scoreFi,
int **pointsX, int **pointsY)
{
int n1, m1, n2, m2, p, size, diff1, diff2;
int n1, m1, n2, m2, /*p,*/ size, diff1, diff2;
float *f;
int i1, j1;
int res;
@@ -428,7 +428,7 @@ int filterDispositionLevelFFT(const CvLSVMFilterObject *Fi, const CvLSVMFftImage
m1 = featMapImage->dimX;
n2 = Fi->sizeY;
m2 = Fi->sizeX;
p = featMapImage->numFeatures;
//p = featMapImage->numFeatures;
(*scoreFi) = NULL;
(*pointsX) = NULL;
(*pointsY) = NULL;
@@ -547,7 +547,7 @@ int addNullableBorder(CvLSVMFeatureMap *map, int bx, int by)
return LATENT_SVM_OK;
}
CvLSVMFeatureMap* featureMapBorderPartFilter(CvLSVMFeatureMap *map,
static CvLSVMFeatureMap* featureMapBorderPartFilter(CvLSVMFeatureMap *map,
int maxXBorder, int maxYBorder)
{
int bx, by;
@@ -611,7 +611,7 @@ int maxFunctionalScoreFixedLevel(const CvLSVMFilterObject **all_F, int n,
float *score, CvPoint **points,
int *kPoints, CvPoint ***partsDisplacement)
{
int i, j, k, dimX, dimY, nF0, mF0, p;
int i, j, k, dimX, dimY, nF0, mF0/*, p*/;
int diff1, diff2, index, last, partsLevel;
CvLSVMFilterDisposition **disposition;
float *f;
@@ -639,7 +639,7 @@ int maxFunctionalScoreFixedLevel(const CvLSVMFilterObject **all_F, int n,
dimY = H->pyramid[level]->sizeY;
// Number of features
p = H->pyramid[level]->numFeatures;
//p = H->pyramid[level]->numFeatures;
// Getting dimension of root filter
nF0 = all_F[0]->sizeY;
@@ -860,7 +860,7 @@ int thresholdFunctionalScoreFixedLevel(const CvLSVMFilterObject **all_F, int n,
float **score, CvPoint **points, int *kPoints,
CvPoint ***partsDisplacement)
{
int i, j, k, dimX, dimY, nF0, mF0, p;
int i, j, k, dimX, dimY, nF0, mF0/*, p*/;
int diff1, diff2, index, last, partsLevel;
CvLSVMFilterDisposition **disposition;
float *f;
@@ -887,7 +887,7 @@ int thresholdFunctionalScoreFixedLevel(const CvLSVMFilterObject **all_F, int n,
dimY = H->pyramid[level]->sizeY;
// Number of features
p = H->pyramid[level]->numFeatures;
//p = H->pyramid[level]->numFeatures;
// Getting dimension of root filter
nF0 = all_F[0]->sizeY;
@@ -1366,6 +1366,7 @@ int thresholdFunctionalScore(const CvLSVMFilterObject **all_F, int n,
return LATENT_SVM_OK;
}
#ifdef HAVE_TBB
/*
// Creating schedule of pyramid levels processing
//
@@ -1390,12 +1391,12 @@ int thresholdFunctionalScore(const CvLSVMFilterObject **all_F, int n,
// RESULT
// Error status
*/
int createSchedule(const CvLSVMFeaturePyramid *H, const CvLSVMFilterObject **all_F,
static int createSchedule(const CvLSVMFeaturePyramid *H, const CvLSVMFilterObject **all_F,
const int n, const int bx, const int by,
const int threadsNum, int *kLevels, int **processingLevels)
{
int rootFilterDim, sumPartFiltersDim, i, numLevels, dbx, dby, numDotProducts;
int averNumDotProd, j, minValue, argMin, lambda, maxValue, k;
int j, minValue, argMin, lambda, maxValue, k;
int *dotProd, *weights, *disp;
if (H == NULL || all_F == NULL)
{
@@ -1429,8 +1430,6 @@ int createSchedule(const CvLSVMFeaturePyramid *H, const CvLSVMFilterObject **all
(H->pyramid[i]->sizeY + dby) * sumPartFiltersDim;
numDotProducts += dotProd[i];
}
// Average number of dot products that would be performed at the best
averNumDotProd = numDotProducts / threadsNum;
// Allocation memory for saving dot product number performed by each thread
weights = (int *)malloc(sizeof(int) * threadsNum);
// Allocation memory for saving dispertion
@@ -1521,7 +1520,6 @@ int createSchedule(const CvLSVMFeaturePyramid *H, const CvLSVMFilterObject **all
return LATENT_SVM_OK;
}
#ifdef HAVE_TBB
/*
// int tbbThresholdFunctionalScore(const CvLSVMFilterObject **all_F, int n,
const CvLSVMFeaturePyramid *H,
@@ -1679,7 +1677,7 @@ int tbbThresholdFunctionalScore(const CvLSVMFilterObject **all_F, int n,
}
#endif
void sort(int n, const float* x, int* indices)
static void sort(int n, const float* x, int* indices)
{
int i, j;
for (i = 0; i < n; i++)