#include <algorithm>
#include "hungarian.h"
#include "Logger.h"
+#include "Utils.h"
using namespace suanzi;
using namespace cv;
static const std::string TAG = "MultiTracker";
static const cv::Size PREFERRED_SIZE = Size(64, 128);
-#define MaxCost 100000
+static const double MaxCost = 100000;
+static const int MaxPath = 5;
MultiTracker::MultiTracker(EngineWPtr e)
: engine(e)
{
LOG_DEBUG(TAG, "init - loading model.pkl");
- predictor = PredictorWrapper::create("./python/model.pkl");
+ predictor = PredictorWrapper::create("./python", "./python/model.pkl");
predictor->dump();
this->descriptor = {Size(64, 128), Size(16, 16), Size(8, 8), Size(8, 8), 9};
-
- std::vector<double> ff (40, 1);
- double prob = predictor->predict(4, ff);
}
MultiTracker::~MultiTracker()
trackers.clear();
}
-static Rect getRectInDetection(const Detection& d)
-{
- Rect r;
- r.x = d.center_x - d.width / 2;
- r.y = d.center_y - d.height / 2;
- r.width = d.width;
- r.height = d.height;
- return r;
-}
-
-static double calc_iou_ratio(const Detection& d1, const Detection& d2)
-{
- Rect r1 = getRectInDetection (d1);
- Rect r2 = getRectInDetection (d2);
- Rect r_inner = r1 & r1;
- Rect r_union = r1 | r2;
- return 1.0 * r_inner.area() / r_union.area();
-}
-
static std::vector<double> similarity(const PatchPtr p1, const PatchPtr p2)
{
std::vector<double> feature;
double center_distance = sqrt(pow((d1.center_x - d2.center_x), 2) + pow((d1.center_y - d2.center_y), 2));
feature.push_back(center_distance / (d1.width + d1.height + d2.width + d2.height) * 4);
- feature.push_back(calc_iou_ratio(d1, d2));
+ feature.push_back(calc_iou_ratio(getRectInDetection(d1), getRectInDetection(d2)));
return feature;
}
-
double MultiTracker::distance(TrackerPtr tracker, const cv::Mat& image, const Detection& d)
{
PatchPtr patch = createPatch(image, d);
return prob;
}
-static long cc = 0;
+static float calc_iou_ratio(const Detection& d1, const Detection& d2)
+{
+ return calc_iou_ratio(getRectInDetection(d1), getRectInDetection(d2));
+}
void MultiTracker::update(unsigned int total, const Detection* detections, const Mat& image)
{
- //////
- if ((cc % 50) == 0){
- if (EnginePtr e = engine.lock()){
- e->onStatusChanged();
- }
- }
- cc++;
-
- //////
int row = trackers.size();
int col = total;
Eigen::MatrixXi cost_matrix = Eigen::MatrixXi::Zero(row, col);
for (int i = 0; i < row; i++){
for (int j = 0; j < col; j++){
- //if (calc_iou_ratio(trackers[i], detections[j]) < -0.1)
- // cost_matrix(i, j) = MaxCost;
- //else
+ if (calc_iou_ratio(trackers[i]->detection, detections[j]) < -0.1)
+ cost_matrix(i, j) = MaxCost;
+ else
cost_matrix(i, j) = distance(trackers[i], image, detections[j]);
}
}