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using namespace cv; | |
using namespace std; | |
enum TrackState { New = 0, Tracked, Lost, Removed }; | |
class STrack | |
{ | |
public: | |
STrack(vector<float> tlwh_, float score); | |
~STrack(); | |
vector<float> static tlbr_to_tlwh(vector<float> &tlbr); | |
void static multi_predict(vector<STrack*> &stracks, byte_kalman::KalmanFilter &kalman_filter); | |
void static_tlwh(); | |
void static_tlbr(); | |
vector<float> tlwh_to_xyah(vector<float> tlwh_tmp); | |
vector<float> to_xyah(); | |
void mark_lost(); | |
void mark_removed(); | |
int next_id(); | |
int end_frame(); | |
void activate(byte_kalman::KalmanFilter &kalman_filter, int frame_id); | |
void re_activate(STrack &new_track, int frame_id, bool new_id = false); | |
void update(STrack &new_track, int frame_id); | |
public: | |
bool is_activated; | |
int track_id; | |
int state; | |
vector<float> _tlwh; | |
vector<float> tlwh; | |
vector<float> tlbr; | |
int frame_id; | |
int tracklet_len; | |
int start_frame; | |
KAL_MEAN mean; | |
KAL_COVA covariance; | |
float score; | |
private: | |
byte_kalman::KalmanFilter kalman_filter; | |
}; |