Tracking seems to work OK initially

src/main.py

@@ -5,17 +5,18 @@ time python src/_detector.py --input ~/Desktop/5min.mp4 -l
 
 """
 # import the necessary packages
-import numpy as np
+import time
 import argparse
+import pprint
+import numpy as np
 import imutils
-import time
 import cv2
-import pprint
 from utils import (
     check_if_inside_the_boxes,
     is_it_the_same_obj,
     box_distance,
     get_heading,
+    get_avg_heading,
 )
 
 pp = pprint.PrettyPrinter(indent=2)
@@ -25,6 +26,7 @@ OPENCV_OBJECT_TRACKERS = {"csrt": cv2.TrackerCSRT_create}
 cv_trackers = cv2.MultiTracker_create()
 trackers = []
 finished = []
+W4A = {}  # this stands for "wait for arrival [at ...]"
 
 # construct the argument parse and parse the arguments
 ap = argparse.ArgumentParser()
@@ -72,7 +74,7 @@ ln = net.getLayerNames()
 ln = [ln[i[0] - 1] for i in net.getUnconnectedOutLayers()]
 
 
-def detect_stuffs(net, frame):
+def detect_stuffs(frame):
     # construct a blob from the input frame and then perform a forward
     # pass of the YOLO object detector, giving us our bounding boxes
     # and associated probabilities
@@ -228,11 +230,25 @@ while True:
             if trackers[idx]["still"] > 30 or x < 5 or x > 1250:
                 untracking.append(trackers[idx])
 
-            # DRAW on FRAME
             tk = trackers[idx]
-            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+            # check if it's hit the first
-            # cv2.rectangle(frame, (startX, startY), (endX, endY), (0, 255, 0), 2)
+            avg_heading = get_avg_heading(trackers[idx]["heading"])
-            color = [int(c) for c in COLORS[0]]
+            print(f"    ---> avg heading: ", avg_heading)
+            if (
+                tk["first"]["id"] == 4
+                and avg_heading == "N"
+                and (x > 140 or x + w > 175)
+            ):
+                print("gone!")
+                _nid = f"id_5"
+                if _nid not in W4A:
+                    W4A[_nid] = {"objects": []}
+                _expected_frame = 30 * 4  # at least 4 sec later
+                has_this = [_ for _ in W4A[_nid]["objects"] if _[0]["id"] == tk["id"]]
+                if not has_this:
+                    W4A[_nid]["objects"].append((tk, _frame_count, _expected_frame))
+                    untracking.append(trackers[idx])
+
             print(
                 f"[{tk['id']}-{tk['type']}] (x,y)=({x},{y})"
                 f" | still #{tk['still']} | distance:  "
@@ -240,6 +256,10 @@ while True:
             )
             _htxt = ",".join(trackers[idx]["heading"])
             print(f" ------  heading: {_htxt}")
+
+            # DRAW on FRAME
+            color = [int(c) for c in COLORS[0]]
+            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
             cv2.putText(
                 frame,
                 f"{tk['id']} - {tk['type']}",
@@ -252,7 +272,7 @@ while True:
 
     # only detect once a sec
     if _frame_count % 15 == 1:
-        idxs, boxes, confidences, classIDs, start, end = detect_stuffs(net, frame)
+        idxs, boxes, confidences, classIDs, start, end = detect_stuffs(frame)
         # loop over the indexes we are keeping
         for i in idxs.flatten():
             # extract the bounding box coordinates
@@ -277,6 +297,20 @@ while True:
                     break
 
             if not is_same:
+                gid = None
+                if found_at["id"] == 5:
+                    print(f"FOUND AT 5 ON {_frame_count}")
+                    _po = W4A["id_5"]["objects"]
+                    _po = [_ for _ in _po if _frame_count > _[2]]
+                    _po = sorted(_po, key=lambda kk: kk[2])
+                    print(' ------ ', _po)
+                    if _po:
+                        gid = _po[0][0]["id"]
+                        # remove this id out of next W4A
+                        W4A["id_5"]["objects"] = [
+                            _ for _ in W4A["id_5"]["objects"] if _[0]["id"] == gid
+                        ]
+                        print(f" >> possibly this obj: ", _po)
                 # add tracker to this obj
                 # create a new object tracker for the bounding box and add it
                 # to our multi-object tracker
@@ -286,7 +320,7 @@ while True:
                 bbox = (x, y, w, h)
                 cv_trackers.add(_tracker, frame, bbox)
                 t = {
-                    "id": tracker_counter,
+                    "id": tracker_counter if gid is None else gid,
                     "type": _class,
                     "curr_position": bbox,
                     "heading": [],
@@ -295,7 +329,8 @@ while True:
                     "last_position": bbox,
                     "still": 0,
                 }
-                tracker_counter += 1
+                if gid is None:
+                    tracker_counter += 1
                 trackers.append(t)
                 print(f"trackers ADD - now total #{len(trackers)}")
                 pp.pprint(t)

src/utils.py

@@ -1,3 +1,4 @@
+import collections
 import math
 
 # detecting area
@@ -64,6 +65,14 @@ AREAS = [
 ]
 
 
+def get_avg_heading(headings):
+    latest = headings[:15]
+    chars = collections.Counter(''.join(latest)).most_common(10)
+    if chars:
+        return chars[0][0]
+    return None
+
+
 def get_heading(x1, y1, x2, y2):
     diff_x, diff_y = x2 - x1, y2 - y1
     if diff_x > 0 and diff_y > 0:
@@ -72,7 +81,6 @@ def get_heading(x1, y1, x2, y2):
         return "N"
     if diff_x > 0:
         return "NW"
-
     if diff_y > 0:
         return "SE"
     if diff_y == 0:

src/yolo.py

@@ -1,10 +0,0 @@
-import cv2
-import time
-import numpy as np
-
-
-
-def detect_stuffs(frame, net, ln, confidence, threshold, W, H):
-
-
-    return idxs, start, end