I am currently using Raspberry pi $4$ Bullseye $64-$bit version. I am also using the raspberry pi camera to run my object detection project with basic GUI but it is currently in YOLOv$5$ format. Can you please convert this code so that it would work in YOLOV$8$ with custom object detection using raspberry pi camera?

import tkinter as tk

from tkinter import Label, Frame

import torch

from picamera$2$ import Picamera$2$ #based on the Picamera$2$ library pdf file

import numpy as np

import cv$2$

from PIL import Image, ImageTk

model $=$ torch.hub.load$(\text{'}$ultralytics$/$yolov$5\text{'},$ 'custom', path$=$'yolov$5/$best$.$pt$\text{'},$ force$\_$reload$=$True$)$

model.conf $=0\mathrm{.}2$

app $=$ tk$.$Tk$()$

app.geometry$("700$x$600")$

app.title$("$GUI$")$

label$1=$ Label$($app$,$ text$=$'detectionTest', font$=("$Arial$",24))$

label$1.$pack$($side$=$'top', pady$=20)$

vid$\_$frame $=$ Frame$($height$=600,$ width$=600)$

vid$\_$frame.pack$()$

vid $=$ Label$($vid$\_$frame$)$

vid.pack$()$

camera $=$ Picamera$2()$

camera$\_$config $=$ camera.create$\_$preview$\_$configuration$($main$=\{"$size$"$: $(640,480)\})$

camera.configure$($camera$\_$config$)$

camera.start$()$

def detect$()$:

request $=$ camera.capture$\_$array$()$

results $=$ model$($request$)$

output$\_$image $=$ np$.$squeeze$($results$.$render$())$

display$\_$image $=$ Image.fromarray$($output$\_$image$)$

imgtk $=$ ImageTk.PhotoImage$($image$=$display$\_$image$)$

vid.imgtk $=$ imgtk

vid.configure$($image$=$imgtk$)$

vid.after$(10,$ detect$)$

detect$()$

app.mainloop$()$