Initial setup for CLion

ANSMOT/ByteTrackNCNN/include/NCNNSTrack.h

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+#pragma once
+#include "NCNNBytekalmanFilter.h"
+#include <unordered_map>
+namespace ByteTrackNCNN {
+	enum TrackState { New = 0, Tracked, Lost, Removed };
+	class STrack
+	{
+	public:
+		STrack(std::vector<float> tlwh_, float _score,
+			int _class_id, float _left, float _top,
+			float _right, float _bottom, std::string _object_id);
+		~STrack();
+
+		std::vector<float> static tlbr_to_tlwh(std::vector<float>& tlbr);
+		void static multi_predict(std::vector<STrack*>& stracks, ByteTrackNCNN::ByteKalmanFilter& kalman_filter);
+		void static_tlwh();
+		void static_tlbr();
+		std::vector<float> tlwh_to_xyah(std::vector<float> tlwh_tmp);
+		std::vector<float> to_xyah();
+		void mark_lost();
+		void mark_removed();
+		int next_id();
+		int end_frame();
+		void reset_count();
+
+		void activate(ByteTrackNCNN::ByteKalmanFilter& kalman_filter, int frame_id);
+		void activate(ByteTrackNCNN::ByteKalmanFilter& kalman_filter, int frame_id, int track_id_count);
+		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;
+		int count;
+
+		std::vector<float> _tlwh;
+		std::vector<float> tlwh;
+		std::vector<float> tlbr;
+		float left; // left, top, right, bottom (original bounding of detected object) 
+		float top;
+		float right;
+		float bottom;
+		int frame_id;
+		int tracklet_len;
+		int start_frame;
+		std::string object_id;
+
+		KAL_MEAN mean;
+		KAL_COVA covariance;
+		float score;
+		int class_id;
+
+	private:
+		ByteTrackNCNN::ByteKalmanFilter kalman_filter;
+		std::unordered_map<int, float> class_id_scores_;
+		int detection_count_;
+		bool class_id_locked_;
+		static const int CLASS_ID_LOCK_FRAMES = 10;
+		void voteClassId(int new_class_id, float score);
+	};
+}
+