Wrote a code for tracking the objects

Tracking algorithm using OpenCV

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+import cv2
+import numpy as np
+import torch
+import time
+import random
+import os
+import torch.backends.cudnn as cudnn
+import math
+
+
+# print(os.getcwd())
+# paths
+model_weights = r'C:\Users\ronak\Desktop\velocity_estimation\tl_yolo5l6_78k_bs_3.pt'
+cap = cv2.VideoCapture(r'C:\Users\ronak\Desktop\velocity_estimation\test_1.mp4')
+model = torch.hub.load(r'C:\Users\ronak\Desktop\velocity_estimation\Traffic_Camera_Tracking\YoloV5\yolo_v5_main_files',
+                           'custom',
+                           path=model_weights,
+                           source='local')
+device = torch.device('cuda:0')
+cudnn.benchmark = True
+# print(torch.cuda.is_available())
+classID_dict = {0: ("Escooter", (0, 90, 255)), 1: ("Pedestrians", (255, 90, 0)), 2: ("Cyclists", (90, 255, 0))}
+count = 0
+center_pts_prev_frame = []
+tracking_objects = {}
+# box_coord = {}
+track_id = 0
+
+while True:
+    _, frame = cap.read()
+    count += 1
+    if _:
+
+        center_pts_cur_frame = []
+        box_coord = {}
+        results = model(frame, size=1920)
+        result = results.xyxy[0]
+        color_ls = []
+
+        if len(result) > 0: 
+            dets = []
+            for items in result:
+                # print(items[0:4])
+                dets.append(items[0:7].tolist())
+            #   dets = np.array(dets)
+            for bbox in dets:
+                (x1, y1, x2, y2, score, class_id) = bbox
+                color = classID_dict[class_id][1]
+                cx = int((int(x1) + int(x2))/2)
+                cy = int((int(y1) + int(y2))/2)
+                center_pts_cur_frame.append((cx, cy))
+                box_coord[(cx, cy)] = [int(x1), int(y1), int(x2), int(y2)]
+                label_2 = f'{classID_dict[class_id][0]} {round(score*100, 1)}%'
+                (w2, h2), _ = cv2.getTextSize(label_2, cv2.FONT_HERSHEY_SIMPLEX, 0.6, 1)
+                cv2.rectangle(frame, (int(x1), int(y1)), (int(x2), int(y2)), color, 2)
+                cv2.rectangle(frame, (int(x1), int(y1) - 20), (int(x1) + w2, int(y1)), color, -1)
+                text_color = (0, 0, 0)
+                cv2.putText(frame, label_2, (int(x1), int(y1) - 5),
+                            cv2.FONT_HERSHEY_SIMPLEX, 0.6, text_color, 1)
+                color_ls.append(color)
+
+            if count <= 2:
+                for pt in center_pts_cur_frame:
+                    for pt2 in center_pts_prev_frame:
+                        distance = math.hypot(pt2[0] - pt[0], pt2[1] - pt[1])
+                        if distance < 20:
+                            tracking_objects[track_id] = pt
+                            track_id += 1
+            else:
+                tracking_objects_copy = tracking_objects.copy()
+                center_pts_cur_frame_copy = center_pts_cur_frame.copy()
+                for object_id, pt2 in tracking_objects_copy.items():
+                    object_exists = False
+                    for pt in center_pts_cur_frame_copy:
+                        distance = math.hypot(pt2[0] - pt[0], pt2[1] - pt[1])
+
+                        # update object position
+                        if distance < 20:
+                            tracking_objects[object_id] = pt
+                            object_exists = True
+                            if pt in center_pts_cur_frame:
+                                center_pts_cur_frame.remove(pt)
+                                continue
+
+                    # remove the id
+                    if not object_exists:
+                        tracking_objects.pop(object_id)
+
+                for pt in center_pts_cur_frame:
+                    tracking_objects[track_id] = pt
+                    track_id += 1
+
+            temp_pt = []
+            for object_id, pt in tracking_objects.items():
+                cv2.circle(frame, pt, 4, (0, 0, 255), -1)
+                temp_pt.append([object_id, pt])
+
+
+
+            for t in temp_pt:
+                if t[1] in box_coord.keys():
+                    label_1 = f'Track_ID: {str(t[0]+1)}'
+                    (w1, h1), _ = cv2.getTextSize(label_1, cv2.FONT_HERSHEY_SIMPLEX, 0.6, 1)
+                    text_color = (0, 0, 0)
+                    cv2.rectangle(frame, (box_coord[t[1]][0], box_coord[t[1]][1] - 40), (box_coord[t[1]][0] + w1, box_coord[t[1]][1]-20), (0,255,255), -1)
+                    cv2.putText(frame, label_1, (box_coord[t[1]][0], box_coord[t[1]][1] -24), cv2.FONT_HERSHEY_SIMPLEX, 0.6, text_color, 1)
+
+            del color_ls
+
+            # print(f'tracking_obkects : {tracking_objects}')
+            # print(f'cur_frm : {center_pts_cur_frame}')
+            # print(f'prev_frm : {center_pts_prev_frame}')
+
+
+            cv2.imshow('frame', frame)
+            # cv2.resizeWindow('frame', 1200, 1600)
+
+            center_pts_prev_frame = center_pts_cur_frame.copy()
+
+            key = cv2.waitKey(0)
+            if key == ord('q'): 
+                break
+            if key == ord('p'):
+                cv2.waitKey(-1)
+    else:
+        break
+cap.release()
+cv2.destroyAllWindows()