Commit 7e934bf1 authored by Vladimir's avatar Vladimir

Warnings Fix #1

parent d82f20ad
...@@ -1251,11 +1251,16 @@ class CV_EXPORTS_W MultiTracker ...@@ -1251,11 +1251,16 @@ class CV_EXPORTS_W MultiTracker
{ {
public: public:
MultiTracker()
{
targetNum = 0;
}
bool addTarget(const Mat& image, const Rect2d& boundingBox, char* tracker_algorithm_name); bool addTarget(const Mat& image, const Rect2d& boundingBox, char* tracker_algorithm_name);
bool update(const Mat& image); bool update(const Mat& image);
int targetNum = 0; int targetNum;
std::vector <Ptr<Tracker> > trackers; std::vector <Ptr<Tracker> > trackers;
std::vector <Rect2d> boundingBoxes; std::vector <Rect2d> boundingBoxes;
std::vector<Scalar> colors; std::vector<Scalar> colors;
......
...@@ -98,7 +98,7 @@ int main() ...@@ -98,7 +98,7 @@ int main()
// //
// "MIL", "BOOSTING", "MEDIANFLOW", "TLD" // "MIL", "BOOSTING", "MEDIANFLOW", "TLD"
// //
char* tracker_algorithm_name = "TLD"; const char* tracker_algorithm_name = "TLD";
Mat frame; Mat frame;
paused = false; paused = false;
......
...@@ -76,7 +76,7 @@ namespace cv ...@@ -76,7 +76,7 @@ namespace cv
bool MultiTracker::update(const Mat& image) bool MultiTracker::update(const Mat& image)
{ {
printf("Naive-Loop MO-TLD Update....\n"); printf("Naive-Loop MO-TLD Update....\n");
for (int i = 0; i < trackers.size(); i++) for (int i = 0; i < (int)trackers.size(); i++)
if (!trackers[i]->update(image, boundingBoxes[i])) if (!trackers[i]->update(image, boundingBoxes[i]))
return false; return false;
...@@ -132,11 +132,11 @@ namespace cv ...@@ -132,11 +132,11 @@ namespace cv
for (int k = 0; k < targetNum; k++) for (int k = 0; k < targetNum; k++)
{ {
//TLD Tracker data extraction //TLD Tracker data extraction
Tracker* trackerPtr = trackers[k]; trackerPtr = trackers[k];
tld::TrackerTLDImpl* tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr); tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr);
//TLD Model Extraction //TLD Model Extraction
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
Ptr<tld::Data> data = tracker->data; data = tracker->data;
data->frameNum++; data->frameNum++;
...@@ -254,7 +254,7 @@ namespace cv ...@@ -254,7 +254,7 @@ namespace cv
//Debug display candidates after Variance Filter //Debug display candidates after Variance Filter
//////////////////////////////////////////////// ////////////////////////////////////////////////
Mat tmpImg = image; Mat tmpImg = image;
for (int i = 0; i < debugStack[0].size(); i++) for (int i = 0; i < (int)debugStack[0].size(); i++)
//rectangle(tmpImg, debugStack[0][i], Scalar(255, 255, 255), 1, 1, 0); //rectangle(tmpImg, debugStack[0][i], Scalar(255, 255, 255), 1, 1, 0);
debugStack[0].clear(); debugStack[0].clear();
tmpImg.copyTo(image); tmpImg.copyTo(image);
...@@ -272,7 +272,7 @@ namespace cv ...@@ -272,7 +272,7 @@ namespace cv
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
Size initSize = tldModel->getMinSize(); Size initSize = tldModel->getMinSize();
for (int k = 0; k < trackers.size(); k++) for (int k = 0; k < (int)trackers.size(); k++)
patches[k].clear(); patches[k].clear();
Mat_<uchar> standardPatch(tld::STANDARD_PATCH_SIZE, tld::STANDARD_PATCH_SIZE); Mat_<uchar> standardPatch(tld::STANDARD_PATCH_SIZE, tld::STANDARD_PATCH_SIZE);
...@@ -331,13 +331,13 @@ namespace cv ...@@ -331,13 +331,13 @@ namespace cv
double windowVar = p2 - p * p; double windowVar = p2 - p * p;
//Loop for on all objects //Loop for on all objects
for (int k=0; k < trackers.size(); k++) for (int k = 0; k < (int)trackers.size(); k++)
{ {
//TLD Tracker data extraction //TLD Tracker data extraction
Tracker* trackerPtr = trackers[k]; trackerPtr = trackers[k];
cv::tld::TrackerTLDImpl* tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr); tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr);
//TLD Model Extraction //TLD Model Extraction
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
//Optimized variance calculation //Optimized variance calculation
bool varPass = (windowVar > tld::VARIANCE_THRESHOLD * *tldModel->detector->originalVariancePtr); bool varPass = (windowVar > tld::VARIANCE_THRESHOLD * *tldModel->detector->originalVariancePtr);
...@@ -373,13 +373,13 @@ namespace cv ...@@ -373,13 +373,13 @@ namespace cv
//Encsemble classification //Encsemble classification
//e1 = getTickCount(); //e1 = getTickCount();
for (int k = 0; k < trackers.size(); k++) for (int k = 0; k < (int)trackers.size(); k++)
{ {
//TLD Tracker data extraction //TLD Tracker data extraction
Tracker* trackerPtr = trackers[k]; trackerPtr = trackers[k];
cv::tld::TrackerTLDImpl* tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr); tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr);
//TLD Model Extraction //TLD Model Extraction
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
for (int i = 0; i < (int)varBuffer[k].size(); i++) for (int i = 0; i < (int)varBuffer[k].size(); i++)
...@@ -435,13 +435,13 @@ namespace cv ...@@ -435,13 +435,13 @@ namespace cv
//NN classification //NN classification
//e1 = getTickCount(); //e1 = getTickCount();
for (int k = 0; k < trackers.size(); k++) for (int k = 0; k < (int)trackers.size(); k++)
{ {
//TLD Tracker data extraction //TLD Tracker data extraction
Tracker* trackerPtr = trackers[k]; trackerPtr = trackers[k];
cv::tld::TrackerTLDImpl* tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr); tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr);
//TLD Model Extraction //TLD Model Extraction
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
npos = 0; npos = 0;
nneg = 0; nneg = 0;
...@@ -508,7 +508,7 @@ namespace cv ...@@ -508,7 +508,7 @@ namespace cv
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
Size initSize = tldModel->getMinSize(); Size initSize = tldModel->getMinSize();
for (int k = 0; k < trackers.size(); k++) for (int k = 0; k < (int)trackers.size(); k++)
patches[k].clear(); patches[k].clear();
Mat_<uchar> standardPatch(tld::STANDARD_PATCH_SIZE, tld::STANDARD_PATCH_SIZE); Mat_<uchar> standardPatch(tld::STANDARD_PATCH_SIZE, tld::STANDARD_PATCH_SIZE);
...@@ -567,13 +567,13 @@ namespace cv ...@@ -567,13 +567,13 @@ namespace cv
double windowVar = p2 - p * p; double windowVar = p2 - p * p;
//Loop for on all objects //Loop for on all objects
for (int k = 0; k < trackers.size(); k++) for (int k = 0; k < (int)trackers.size(); k++)
{ {
//TLD Tracker data extraction //TLD Tracker data extraction
Tracker* trackerPtr = trackers[k]; trackerPtr = trackers[k];
cv::tld::TrackerTLDImpl* tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr); tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr);
//TLD Model Extraction //TLD Model Extraction
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
//Optimized variance calculation //Optimized variance calculation
bool varPass = (windowVar > tld::VARIANCE_THRESHOLD * *tldModel->detector->originalVariancePtr); bool varPass = (windowVar > tld::VARIANCE_THRESHOLD * *tldModel->detector->originalVariancePtr);
...@@ -609,13 +609,13 @@ namespace cv ...@@ -609,13 +609,13 @@ namespace cv
//Encsemble classification //Encsemble classification
//e1 = getTickCount(); //e1 = getTickCount();
for (int k = 0; k < trackers.size(); k++) for (int k = 0; k < (int)trackers.size(); k++)
{ {
//TLD Tracker data extraction //TLD Tracker data extraction
Tracker* trackerPtr = trackers[k]; trackerPtr = trackers[k];
cv::tld::TrackerTLDImpl* tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr); tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr);
//TLD Model Extraction //TLD Model Extraction
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
for (int i = 0; i < (int)varBuffer[k].size(); i++) for (int i = 0; i < (int)varBuffer[k].size(); i++)
...@@ -670,13 +670,13 @@ namespace cv ...@@ -670,13 +670,13 @@ namespace cv
//NN classification //NN classification
//e1 = getTickCount(); //e1 = getTickCount();
for (int k = 0; k < trackers.size(); k++) for (int k = 0; k < (int)trackers.size(); k++)
{ {
//TLD Tracker data extraction //TLD Tracker data extraction
Tracker* trackerPtr = trackers[k]; trackerPtr = trackers[k];
cv::tld::TrackerTLDImpl* tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr); tracker = static_cast<tld::TrackerTLDImpl*>(trackerPtr);
//TLD Model Extraction //TLD Model Extraction
tld::TrackerTLDModel* tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model)); tldModel = ((tld::TrackerTLDModel*)static_cast<TrackerModel*>(tracker->model));
//Size InitSize = tldModel->getMinSize(); //Size InitSize = tldModel->getMinSize();
npos = 0; npos = 0;
nneg = 0; nneg = 0;
......
...@@ -51,7 +51,7 @@ namespace cv ...@@ -51,7 +51,7 @@ namespace cv
bool flagVOT = false; bool flagVOT = false;
//TLD Dataset Parameters //TLD Dataset Parameters
char* tldFolderName[10] = { const char* tldFolderName[10] = {
"01_david", "01_david",
"02_jumping", "02_jumping",
"03_pedestrian1", "03_pedestrian1",
...@@ -63,7 +63,7 @@ namespace cv ...@@ -63,7 +63,7 @@ namespace cv
"09_carchase", "09_carchase",
"10_panda" "10_panda"
}; };
char* votFolderName[60] = { const char* votFolderName[60] = {
"bag", "ball1", "ball2", "basketball", "birds1", "birds2", "blanket", "bmx", "bolt1", "bolt2", "bag", "ball1", "ball2", "basketball", "birds1", "birds2", "blanket", "bmx", "bolt1", "bolt2",
"book", "butterfly", "car1", "car2", "crossing", "dinosaur", "fernando", "fish1", "fish2", "fish3", "book", "butterfly", "car1", "car2", "crossing", "dinosaur", "fernando", "fish1", "fish2", "fish3",
"fish4", "girl", "glove", "godfather", "graduate", "gymnastics1", "gymnastics2 ", "gymnastics3", "gymnastics4", "hand", "fish4", "girl", "glove", "godfather", "graduate", "gymnastics1", "gymnastics2 ", "gymnastics3", "gymnastics4", "hand",
...@@ -72,11 +72,11 @@ namespace cv ...@@ -72,11 +72,11 @@ namespace cv
"singer2", "singer3", "soccer1", "soccer2", "soldier", "sphere", "tiger", "traffic", "tunnel", "wiper" "singer2", "singer3", "soccer1", "soccer2", "soldier", "sphere", "tiger", "traffic", "tunnel", "wiper"
}; };
Rect2d tldInitBB[10] = { const Rect2d tldInitBB[10] = {
Rect2d(165, 93, 51, 54), Rect2d(147, 110, 33, 32), Rect2d(47, 51, 21, 36), Rect2d(130, 134, 21, 53), Rect2d(154, 102, 24, 52), Rect2d(165, 93, 51, 54), Rect2d(147, 110, 33, 32), Rect2d(47, 51, 21, 36), Rect2d(130, 134, 21, 53), Rect2d(154, 102, 24, 52),
Rect2d(142, 125, 90, 39), Rect2d(290, 43, 23, 40), Rect2d(273, 77, 27, 25), Rect2d(337, 219, 54, 37), Rect2d(58, 100, 27, 22) Rect2d(142, 125, 90, 39), Rect2d(290, 43, 23, 40), Rect2d(273, 77, 27, 25), Rect2d(337, 219, 54, 37), Rect2d(58, 100, 27, 22)
}; };
Rect2d votInitBB[60] = { const Rect2d votInitBB[60] = {
Rect2d(142, 125, 90, 39), Rect2d(490, 400, 40, 40), Rect2d(273, 77, 27, 25), Rect2d(145, 84, 54, 37), Rect2d(58, 100, 27, 22), Rect2d(142, 125, 90, 39), Rect2d(490, 400, 40, 40), Rect2d(273, 77, 27, 25), Rect2d(145, 84, 54, 37), Rect2d(58, 100, 27, 22),
Rect2d(450, 380, 60, 60), Rect2d(290, 43, 23, 40), Rect2d(273, 77, 27, 25), Rect2d(225, 175, 50, 50), Rect2d(58, 100, 27, 22), Rect2d(450, 380, 60, 60), Rect2d(290, 43, 23, 40), Rect2d(273, 77, 27, 25), Rect2d(225, 175, 50, 50), Rect2d(58, 100, 27, 22),
...@@ -118,7 +118,10 @@ namespace cv ...@@ -118,7 +118,10 @@ namespace cv
cv::Rect2d tld_InitDataset(int videoInd, const char* rootPath, int datasetInd) cv::Rect2d tld_InitDataset(int videoInd, const char* rootPath, int datasetInd)
{ {
char* folderName = (char *)""; char* folderName = (char *)"";
int x, y, w, h; int x = 0,
y = 0,
w = 0,
h = 0;
//Index range //Index range
// 1-10 TLD Dataset // 1-10 TLD Dataset
...@@ -127,7 +130,7 @@ namespace cv ...@@ -127,7 +130,7 @@ namespace cv
if (datasetInd == 0) if (datasetInd == 0)
{ {
folderName = tldFolderName[id]; folderName = (char*)tldFolderName[id];
x = tldInitBB[id].x; x = tldInitBB[id].x;
y = tldInitBB[id].y; y = tldInitBB[id].y;
w = tldInitBB[id].width; w = tldInitBB[id].width;
...@@ -138,7 +141,7 @@ namespace cv ...@@ -138,7 +141,7 @@ namespace cv
} }
if (datasetInd == 1) if (datasetInd == 1)
{ {
folderName = votFolderName[id]; folderName = (char*)votFolderName[id];
x = votInitBB[id].x; x = votInitBB[id].x;
y = votInitBB[id].y; y = votInitBB[id].y;
w = votInitBB[id].width; w = votInitBB[id].width;
......
...@@ -238,7 +238,7 @@ bool TrackerTLDImpl::updateImpl(const Mat& image, Rect2d& boundingBox) ...@@ -238,7 +238,7 @@ bool TrackerTLDImpl::updateImpl(const Mat& image, Rect2d& boundingBox)
//Debug display candidates after Variance Filter //Debug display candidates after Variance Filter
//////////////////////////////////////////////// ////////////////////////////////////////////////
Mat tmpImg = image; Mat tmpImg = image;
for (int i = 0; i < tldModel->detector->debugStack[0].size(); i++) for (int i = 0; i < (int)tldModel->detector->debugStack[0].size(); i++)
//rectangle(tmpImg, tldModel->detector->debugStack[0][i], Scalar(255, 255, 255), 1, 1, 0); //rectangle(tmpImg, tldModel->detector->debugStack[0][i], Scalar(255, 255, 255), 1, 1, 0);
tldModel->detector->debugStack[0].clear(); tldModel->detector->debugStack[0].clear();
tmpImg.copyTo(image); tmpImg.copyTo(image);
......
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