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separate pytwrpper from predictorWrappery
[trackerpp.git]
/
src
/
MultiTracker.cpp
diff --git
a/src/MultiTracker.cpp
b/src/MultiTracker.cpp
index
547a195
..
bbfc6f3
100644
(file)
--- a/
src/MultiTracker.cpp
+++ b/
src/MultiTracker.cpp
@@
-11,16
+11,15
@@
using namespace std;
static const std::string TAG = "MultiTracker";
static const cv::Size PREFERRED_SIZE = Size(64, 128);
static const std::string TAG = "MultiTracker";
static const cv::Size PREFERRED_SIZE = Size(64, 128);
-
static const double MaxCost = 100000;
static const double MaxCost = 100000;
-static const int MaxPatch = 5;
static const double ProbThreshold = 0.05;
MultiTracker::MultiTracker(EngineWPtr e)
: engine(e)
{
LOG_DEBUG(TAG, "init - loading model.pkl");
static const double ProbThreshold = 0.05;
MultiTracker::MultiTracker(EngineWPtr e)
: engine(e)
{
LOG_DEBUG(TAG, "init - loading model.pkl");
- predictor = PredictorWrapper::create("./python", "./python/model.pkl");
+ predictor = PredictorWrapperPtr(new PredictorWrapper());
+ predictor->load("./resources/model.pkl");
predictor->dump();
this->descriptor = {Size(64, 128), Size(16, 16), Size(8, 8), Size(8, 8), 9};
}
predictor->dump();
this->descriptor = {Size(64, 128), Size(16, 16), Size(8, 8), Size(8, 8), 9};
}
@@
-75,7
+74,7
@@
double MultiTracker::distance(TrackerPtr tracker, const cv::Mat& image, const De
ss = similarity(i, patch);
features.insert(features.end(), ss.begin(), ss.end());
}
ss = similarity(i, patch);
features.insert(features.end(), ss.begin(), ss.end());
}
- double prob = predictor->predict(
MaxPatch - 1, features); // TODO ???
+ double prob = predictor->predict(
Tracker::MaxPatch - 1, features); // TODO why is MaxPatch-1
if (prob > ProbThreshold)
return -log(prob);
else
if (prob > ProbThreshold)
return -log(prob);
else
@@
-94,7
+93,7
@@
void MultiTracker::update(unsigned int total, const Detection* detections, const
t->predict();
}
t->predict();
}
- // match the trackers with the detections
+ // match the trackers with the detections
using linear sum assignment (hungarian)
int row = trackers.size();
int col = total;
Eigen::MatrixXi cost_matrix = Eigen::MatrixXi::Zero(row, col);
int row = trackers.size();
int col = total;
Eigen::MatrixXi cost_matrix = Eigen::MatrixXi::Zero(row, col);