Improve CenterTrack.

Signed-off-by: Davide Sapienza <sapienza.dav@gmail.com>

include/tkDNN/CenternetDetection3D.h

@@ -27,6 +27,8 @@ private:
     tk::dnn::dataDim_t dim_dep;
     tk::dnn::dataDim_t dim_rot;
     tk::dnn::dataDim_t dim_dim;
+
+    std::vector<cv::Mat> inputCalibs;
     float *topk_scores;
     int *topk_inds_;
     float *topk_ys_;
@@ -58,32 +60,33 @@ private:
         dnnType *input;
     #endif
     cv::Mat r;
-    cv::Mat calibs;
     float *d_ptrs;
 
     cv::Mat src;
     cv::Mat dst;
     cv::Mat dst2;  
     cv::Mat trans, trans2;
+    std::vector<cv::Mat> calibs;
+
     //processing
     int K = 100;
     int width = 128;//56;        // TODO
 
     // pointer used in the kernels
-    float *src_out;
-    int *ids_out;
+    float *srcOut;
+    int *idsOut;
 
     struct threshold op;
     cv::Mat corners, pts3DHomo;  
 
-    std::vector<std::vector<int>> face_id;
+    std::vector<std::vector<int>> faceId;
 
 public:
     CenternetDetection3D() {};
     ~CenternetDetection3D() {}; 
 
     bool init(const std::string& tensor_path, const int n_classes=3, const int n_batches=1, const float conf_thresh=0.3, const std::vector<cv::Mat>& k_calibs=std::vector<cv::Mat>());
-    void preprocess(cv::Mat &frame, const int bi=0, const std::vector<cv::Size>& stream_size=std::vector<cv::Size>());
+    void preprocess(cv::Mat &frame, const int bi=0);
     void postprocess(const int bi=0,const bool mAP=false);
     void draw(std::vector<cv::Mat>& frames);
 };

include/tkDNN/CenternetDetection3DTrack.h

@@ -76,12 +76,12 @@ public:
 
     std::vector<cv::Mat> inputCalibs;
 
-    std::vector<cv::Size> sz_old;
+    std::vector<cv::Size> szOld;
 
     cv::Mat src;
     cv::Mat dst;
     cv::Mat dst2;  
-    cv::Mat trans, trans2, trans_out;
+    cv::Mat trans, trans2, transOut;
 
     /* pre inf */
     bool iter0;
@@ -131,27 +131,25 @@ public:
     std::vector<cv::Mat> calibs;
     cv::Mat corners, pts3DHomo;  
 
-    std::vector<std::vector<int>> face_id;
-    cv::Scalar tr_colors[256];
+    std::vector<std::vector<int>> faceId;
+    cv::Scalar trColors[256];
     bool view2d = false;
 
     //processing
     struct threshold op;
-    float out_thresh = 0.1;
-    float new_thresh = 0.3;
-    float vis_thresh = 0.3;
-    float peakThreshold = 0.2;
-    float centerThreshold = 0.3; //default 0.5
+    float outThresh = 0.1;
+    float newThresh = 0.3;
+    // float peakThreshold = 0.2;
+    // float centerThreshold = 0.3; //default 0.5
     
 
     //detections
-    std::vector<struct detectionRes> det_res;
-    int count_det;
+    std::vector<struct detectionRes> detRes;
+    int countDet;
     //tracks
-    std::vector<std::vector<struct trackingRes>> tr_res;
-    std::vector<std::vector<struct trackingRes>> batchTracked;
-    std::vector<int> count_tr;
-    std::vector<int> track_id;
+    std::vector<std::vector<struct trackingRes>> trRes;
+    std::vector<int> countTr;
+    std::vector<int> trackId;
   
     
     bool init_preprocessing();
@@ -168,7 +166,7 @@ public:
     CenternetDetection3DTrack() {};
     ~CenternetDetection3DTrack() {};
     bool init(const std::string& tensor_path, const int n_classes=3, const int n_batches=1, const float conf_thresh=0.3, const std::vector<cv::Mat>& k_calibs=std::vector<cv::Mat>());
-    void preprocess(cv::Mat &frame, const int bi=0, const std::vector<cv::Size>& stream_size=std::vector<cv::Size>());
+    void preprocess(cv::Mat &frame, const int bi=0);
     void postprocess(const int bi=0,const bool mAP=false);
     void draw(std::vector<cv::Mat>& frames);
 };

include/tkDNN/DetectionNN3D.h

@@ -54,7 +54,7 @@ class DetectionNN3D {
          * @param frame original frame to adapt for inference.
          * @param bi batch index
          */
-        virtual void preprocess(cv::Mat &frame, const int bi=0 , const std::vector<cv::Size>& stream_size=std::vector<cv::Size>()) = 0;
+        virtual void preprocess(cv::Mat &frame, const int bi=0) = 0;
 
         /**
          * This method postprocess the output of the NN to obtain the correct 
@@ -102,7 +102,7 @@ class DetectionNN3D {
          *            box are needed, as in some cases for the mAP calculation.
          */
         void update(std::vector<cv::Mat>& frames, const int cur_batches=1, bool save_times=false, 
-                    std::ofstream *times=nullptr, const bool mAP=false, const std::vector<cv::Size>& stream_size=std::vector<cv::Size>()){
+                    std::ofstream *times=nullptr, const bool mAP=false){
             if(save_times && times==nullptr)
                 FatalError("save_times set to true, but no valid ofstream given");
             if(cur_batches > nBatches)
@@ -116,7 +116,7 @@ class DetectionNN3D {
                     if(!frames[bi].data)
                         FatalError("No image data feed to detection");
                     originalSize.push_back(frames[bi].size());
-                    preprocess(frames[bi], bi, stream_size);   
+                    preprocess(frames[bi], bi);   
                 }
                 TKDNN_TSTOP
                 pre_stats.push_back(t_ns);