Beginners • YOLO 11 and object tracking

Code:

import mathimport cv2from ultralytics import YOLOimport motioncontrol# Load a pretrained YOLOv11n modelmodel = YOLO("yolo11n.pt")source = 'https://ip_adress of pi goes here/robovision/' # so this takes an incoming video stream from the raspberry pi to my Mac.cap = cv2.VideoCapture(source)# Loop through the video frameswhile cap.isOpened():    # Read a frame from the video    success, frame = cap.read()    #----The rsp stream from raspberry pi4B is of ---- ---- --- format so ---this--- many pixels per centimeter----    pixel_per_centimeter=10 #should do calibration and needs to be precise    if success:        results = model.track(frame, stream=True, tracker="bytetrack.yaml")        centroids=[]        distances=[]        # calculate centroids and distances between objects and storing it in a list        for r in results:            boxes = r.boxes.xyxy.cpu()            if r.boxes.id is not None:                track_ids = r.boxes.id.int().cpu().tolist()                for box, track_id in zip(boxes, track_ids):                    #calculate centroids                    centroid =  ((box[0]+box[2])/2,(box[1] + box[3])/2,track_id) #centroid calcs                    centroids.append(centroid)                for i in range(len(centroids)):  #To calculate distance between centroids (in actual centimeters)                    distance= [math.sqrt((centroids[i+1][0]-centroids[i][0])**2+(centroids[i+1][1]-centroids[i][1])**2)/pixel_per_centimeter,(centroids[i][2]+"to"+centroids[i+1][2])]                    if distance[i][0] >= 12.50 : #input the min gap length for robot to pass through                        motioncontrol.front()                        distances.append(distance)    else:        # Break the loop if the end of the video is reached        break# Release the video capture object and close the display windowcap.release()cv2.destroyAllWindows()