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tracker.py

@@ -43,31 +43,31 @@ def update_tracker(target_detector, image):
 
         bbox_xywh = []
         confs = []
+        bboxes2draw = []
+        face_bboxes = []
+        if len(bboxes):
 
-        # Adapt detections to deep sort input format
+            # Adapt detections to deep sort input format
-        for x1, y1, x2, y2, _, conf in bboxes:
+            for x1, y1, x2, y2, _, conf in bboxes:
-            
+                
-            obj = [
+                obj = [
-                int((x1+x2)/2), int((y1+y2)/2),
+                    int((x1+x2)/2), int((y1+y2)/2),
-                x2-x1, y2-y1
+                    x2-x1, y2-y1
-            ]
+                ]
-            bbox_xywh.append(obj)
+                bbox_xywh.append(obj)
-            confs.append(conf)
+                confs.append(conf)
-
-        xywhs = torch.Tensor(bbox_xywh)
-        confss = torch.Tensor(confs)
 
-        # Pass detections to deepsort
+            xywhs = torch.Tensor(bbox_xywh)
-        outputs = deepsort.update(xywhs, confss, image)
+            confss = torch.Tensor(confs)
 
+            # Pass detections to deepsort
+            outputs = deepsort.update(xywhs, confss, image)
 
-        bboxes2draw = []
+            for value in list(outputs):
-        face_bboxes = []
+                x1,y1,x2,y2,track_id = value
-        for value in list(outputs):
+                bboxes2draw.append(
-            x1,y1,x2,y2,track_id = value
+                    (x1, y1, x2, y2, '', track_id)
-            bboxes2draw.append(
+                )
-                (x1, y1, x2, y2, '', track_id)
-            )
 
         image = plot_bboxes(image, bboxes2draw)