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opencv_contrib
Commit 34d91fa9 authored by Vladimir's avatar Vladimir
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Warnings Fix #1

parent 5a4184b6
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Showing with 28 additions and 30 deletions
modules/tracking/src/tldDetector.cpp
View file @ 34d91fa9
...@@ -81,9 +81,9 @@ namespace cv ...@@ -81,9 +81,9 @@ namespace cv
return 0.0; return 0.0;
return splus / (sminus + splus); return splus / (sminus + splus);
*/ */
int64 e1, e2; //int64 e1, e2;
float t; //float t;
e1 = getTickCount(); //e1 = getTickCount();
double splus = 0.0, sminus = 0.0; double splus = 0.0, sminus = 0.0;
Mat_<uchar> modelSample(STANDARD_PATCH_SIZE, STANDARD_PATCH_SIZE); Mat_<uchar> modelSample(STANDARD_PATCH_SIZE, STANDARD_PATCH_SIZE);
for (int i = 0; i < *posNum; i++) for (int i = 0; i < *posNum; i++)
...@@ -96,8 +96,8 @@ namespace cv ...@@ -96,8 +96,8 @@ namespace cv
modelSample.data = &(negExp->data[i * 225]); modelSample.data = &(negExp->data[i * 225]);
sminus = std::max(sminus, 0.5 * (NCC(modelSample, patch) + 1.0)); sminus = std::max(sminus, 0.5 * (NCC(modelSample, patch) + 1.0));
} }
e2 = getTickCount(); //e2 = getTickCount();
t = (e2 - e1) / getTickFrequency()*1000.0; //t = (e2 - e1) / getTickFrequency()*1000.0;
//printf("Sr CPU: %f\n", t); //printf("Sr CPU: %f\n", t);
if (splus + sminus == 0.0) if (splus + sminus == 0.0)
return 0.0; return 0.0;
...@@ -107,7 +107,7 @@ namespace cv ...@@ -107,7 +107,7 @@ namespace cv
double TLDDetector::ocl_Sr(const Mat_<uchar>& patch) double TLDDetector::ocl_Sr(const Mat_<uchar>& patch)
{ {
int64 e1, e2, e3, e4; int64 e1, e2, e3, e4;
float t; double t;
e1 = getTickCount(); e1 = getTickCount();
e3 = getTickCount(); e3 = getTickCount();
double splus = 0.0, sminus = 0.0; double splus = 0.0, sminus = 0.0;
...@@ -131,8 +131,8 @@ namespace cv ...@@ -131,8 +131,8 @@ namespace cv
ocl::KernelArg::PtrReadOnly(devPositiveSamples), ocl::KernelArg::PtrReadOnly(devPositiveSamples),
ocl::KernelArg::PtrReadOnly(devNegativeSamples), ocl::KernelArg::PtrReadOnly(devNegativeSamples),
ocl::KernelArg::PtrWriteOnly(devNCC), ocl::KernelArg::PtrWriteOnly(devNCC),
(int)posNum, posNum,
(int)negNum); negNum);
e4 = getTickCount(); e4 = getTickCount();
t = (e4 - e3) / getTickFrequency()*1000.0; t = (e4 - e3) / getTickFrequency()*1000.0;
...@@ -186,7 +186,7 @@ namespace cv ...@@ -186,7 +186,7 @@ namespace cv
void TLDDetector::ocl_batchSrSc(const Mat_<uchar>& patches, double *resultSr, double *resultSc, int numOfPatches) void TLDDetector::ocl_batchSrSc(const Mat_<uchar>& patches, double *resultSr, double *resultSc, int numOfPatches)
{ {
int64 e1, e2, e3, e4; int64 e1, e2, e3, e4;
float t; double t;
e1 = getTickCount(); e1 = getTickCount();
e3 = getTickCount(); e3 = getTickCount();
...@@ -235,28 +235,28 @@ namespace cv ...@@ -235,28 +235,28 @@ namespace cv
//printf("Read Mem GPU: %f\n", t); //printf("Read Mem GPU: %f\n", t);
//Calculate Srs //Calculate Srs
for (int k = 0; k < numOfPatches; k++) for (int id = 0; id < numOfPatches; id++)
{ {
double spr = 0.0, smr = 0.0, spc = 0.0, smc = 0; double spr = 0.0, smr = 0.0, spc = 0.0, smc = 0;
int med = getMedian((*timeStampsPositive)); int med = getMedian((*timeStampsPositive));
for (int i = 0; i < *posNum; i++) for (int i = 0; i < *posNum; i++)
{ {
spr = std::max(spr, 0.5 * (posNCC.at<float>(k * 500 + i) + 1.0)); spr = std::max(spr, 0.5 * (posNCC.at<float>(id * 500 + i) + 1.0));
if ((int)(*timeStampsPositive)[i] <= med) if ((int)(*timeStampsPositive)[i] <= med)
spc = std::max(spr, 0.5 * (posNCC.at<float>(k * 500 + i) + 1.0)); spc = std::max(spr, 0.5 * (posNCC.at<float>(id * 500 + i) + 1.0));
} }
for (int i = 0; i < *negNum; i++) for (int i = 0; i < *negNum; i++)
smc = smr = std::max(smr, 0.5 * (negNCC.at<float>(k * 500 + i) + 1.0)); smc = smr = std::max(smr, 0.5 * (negNCC.at<float>(id * 500 + i) + 1.0));
if (spr + smr == 0.0) if (spr + smr == 0.0)
resultSr[k] = 0.0; resultSr[id] = 0.0;
else else
resultSr[k] = spr / (smr + spr); resultSr[id] = spr / (smr + spr);
if (spc + smc == 0.0) if (spc + smc == 0.0)
resultSc[k] = 0.0; resultSc[id] = 0.0;
else else
resultSc[k] = spc / (smc + spc); resultSc[id] = spc / (smc + spc);
} }
////Compare positive NCCs ////Compare positive NCCs
...@@ -367,8 +367,8 @@ namespace cv ...@@ -367,8 +367,8 @@ namespace cv
ocl::KernelArg::PtrReadOnly(devPositiveSamples), ocl::KernelArg::PtrReadOnly(devPositiveSamples),
ocl::KernelArg::PtrReadOnly(devNegativeSamples), ocl::KernelArg::PtrReadOnly(devNegativeSamples),
ocl::KernelArg::PtrWriteOnly(devNCC), ocl::KernelArg::PtrWriteOnly(devNCC),
(int)posNum, posNum,
(int)negNum); negNum);
e4 = getTickCount(); e4 = getTickCount();
t = (e4 - e3) / getTickFrequency()*1000.0; t = (e4 - e3) / getTickFrequency()*1000.0;
...@@ -466,7 +466,6 @@ namespace cv ...@@ -466,7 +466,6 @@ namespace cv
int dx = initSize.width / 10, dy = initSize.height / 10; int dx = initSize.width / 10, dy = initSize.height / 10;
Size2d size = img.size(); Size2d size = img.size();
double scale = 1.0; double scale = 1.0;
int total = 0, pass = 0;
int npos = 0, nneg = 0; int npos = 0, nneg = 0;
double maxSc = -5.0; double maxSc = -5.0;
Rect2d maxScRect; Rect2d maxScRect;
...@@ -477,7 +476,7 @@ namespace cv ...@@ -477,7 +476,7 @@ namespace cv
int64 e1, e2; int64 e1, e2;
double t; double t;
e1 = cvGetTickCount(); e1 = getTickCount();
//Detection part //Detection part
<<<<<<< HEAD <<<<<<< HEAD
======= =======
...@@ -514,8 +513,8 @@ namespace cv ...@@ -514,8 +513,8 @@ namespace cv
//printf("Variance: %d\t%f\n", varBuffer.size(), t); //printf("Variance: %d\t%f\n", varBuffer.size(), t);
//Encsemble classification //Encsemble classification
e1 = cvGetTickCount(); e1 = getTickCount();
for (int i = 0; i < varBuffer.size(); i++) for (int i = 0; i < (int)varBuffer.size(); i++)
{ {
prepareClassifiers((int)blurred_imgs[varScaleIDs[i]].step[0]); prepareClassifiers((int)blurred_imgs[varScaleIDs[i]].step[0]);
if (ensembleClassifierNum(&blurred_imgs[varScaleIDs[i]].at<uchar>(varBuffer[i].y, varBuffer[i].x)) <= ENSEMBLE_THRESHOLD) if (ensembleClassifierNum(&blurred_imgs[varScaleIDs[i]].at<uchar>(varBuffer[i].y, varBuffer[i].x)) <= ENSEMBLE_THRESHOLD)
...@@ -529,7 +528,7 @@ namespace cv ...@@ -529,7 +528,7 @@ namespace cv
//NN classification //NN classification
e1 = getTickCount(); e1 = getTickCount();
for (int i = 0; i < ensBuffer.size(); i++) for (int i = 0; i < (int)ensBuffer.size(); i++)
{ {
LabeledPatch labPatch; LabeledPatch labPatch;
double curScale = pow(SCALE_STEP, ensScaleIDs[i]); double curScale = pow(SCALE_STEP, ensScaleIDs[i]);
...@@ -580,7 +579,6 @@ namespace cv ...@@ -580,7 +579,6 @@ namespace cv
int dx = initSize.width / 10, dy = initSize.height / 10; int dx = initSize.width / 10, dy = initSize.height / 10;
Size2d size = img.size(); Size2d size = img.size();
double scale = 1.0; double scale = 1.0;
int total = 0, pass = 0;
int npos = 0, nneg = 0; int npos = 0, nneg = 0;
double maxSc = -5.0; double maxSc = -5.0;
Rect2d maxScRect; Rect2d maxScRect;
...@@ -591,7 +589,7 @@ namespace cv ...@@ -591,7 +589,7 @@ namespace cv
int64 e1, e2; int64 e1, e2;
double t; double t;
e1 = cvGetTickCount(); e1 = getTickCount();
//Detection part //Detection part
//Generate windows and filter by variance //Generate windows and filter by variance
scaleID = 0; scaleID = 0;
...@@ -625,8 +623,8 @@ namespace cv ...@@ -625,8 +623,8 @@ namespace cv
//printf("Variance: %d\t%f\n", varBuffer.size(), t); //printf("Variance: %d\t%f\n", varBuffer.size(), t);
//Encsemble classification //Encsemble classification
e1 = cvGetTickCount(); e1 = getTickCount();
for (int i = 0; i < varBuffer.size(); i++) for (int i = 0; i < (int)varBuffer.size(); i++)
{ {
prepareClassifiers((int)blurred_imgs[varScaleIDs[i]].step[0]); prepareClassifiers((int)blurred_imgs[varScaleIDs[i]].step[0]);
if (ensembleClassifierNum(&blurred_imgs[varScaleIDs[i]].at<uchar>(varBuffer[i].y, varBuffer[i].x)) <= ENSEMBLE_THRESHOLD) if (ensembleClassifierNum(&blurred_imgs[varScaleIDs[i]].at<uchar>(varBuffer[i].y, varBuffer[i].x)) <= ENSEMBLE_THRESHOLD)
...@@ -647,7 +645,7 @@ namespace cv ...@@ -647,7 +645,7 @@ namespace cv
double *resultSc = new double[numOfPatches]; double *resultSc = new double[numOfPatches];
uchar *patchesData = stdPatches.data; uchar *patchesData = stdPatches.data;
for (int i = 0; i < ensBuffer.size(); i++) for (int i = 0; i < (int)ensBuffer.size(); i++)
{ {
resample(resized_imgs[ensScaleIDs[i]], Rect2d(ensBuffer[i], initSize), standardPatch); resample(resized_imgs[ensScaleIDs[i]], Rect2d(ensBuffer[i], initSize), standardPatch);
uchar *stdPatchData = standardPatch.data; uchar *stdPatchData = standardPatch.data;
...@@ -658,7 +656,7 @@ namespace cv ...@@ -658,7 +656,7 @@ namespace cv
ocl_batchSrSc(stdPatches, resultSr, resultSc, numOfPatches); ocl_batchSrSc(stdPatches, resultSr, resultSc, numOfPatches);
for (int i = 0; i < ensBuffer.size(); i++) for (int i = 0; i < (int)ensBuffer.size(); i++)
{ {
LabeledPatch labPatch; LabeledPatch labPatch;
standardPatch.data = &stdPatches.data[225 * i]; standardPatch.data = &stdPatches.data[225 * i];
......
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