How to draw that hand skeleton using mediapipe's mp.solutions.drawing_utils

Question

I am using mediapipe library to get landmark points in this code and using that landmark point I am detecting the hand gestures, but I want to use mp.solutions.drawing_utils in order to get the hand skeleton on the screen can someone tell me where write that in order to draw the hand on the screen. How can I use the mp.solutions.drawing_utils module in conjunction with the Mediapipe library to draw the hand skeleton on the screen? Specifically, where should I place the necessary code to achieve this while detecting hand gestures using landmark points with Mediapipe?

import cv2
import mediapipe as mp
import pandas as pd  
import os
import numpy as np 

def image_processed(hand_img):

    # Image processing
    # 1. Convert BGR to RGB
    img_rgb = cv2.cvtColor(hand_img, cv2.COLOR_BGR2RGB)

    # 2. Flip the img in Y-axis
    img_flip = cv2.flip(img_rgb, 1)

    # accessing MediaPipe solutions
    mp_hands = mp.solutions.hands

    # Initialize Hands
    hands = mp_hands.Hands(static_image_mode=True,
    max_num_hands=1, min_detection_confidence=0.7)

    # Results
    output = hands.process(img_flip)

    hands.close()

    try:
        data = output.multi_hand_landmarks[0]
        #print(data)
        data = str(data)

        data = data.strip().split('\n')

        garbage = ['landmark {', '  visibility: 0.0', '  presence: 0.0', '}']

        without_garbage = []

        for i in data:
            if i not in garbage:
                without_garbage.append(i)
                        
        clean = []

        for i in without_garbage:
            i = i.strip()
            clean.append(i[2:])

        for i in range(0, len(clean)):
            clean[i] = float(clean[i])
        return(clean)
    except:
        return(np.zeros([1,63], dtype=int)[0])

import pickle
# load model
with open('model.pkl', 'rb') as f:
    svm = pickle.load(f)


import cv2 as cv
cap = cv.VideoCapture(0)
if not cap.isOpened():
    print("Cannot open camera")
    exit()
i = 0    
while True:
    
    ret, frame = cap.read()

    if not ret:
        print("Can't receive frame (stream end?). Exiting ...")
        break
    # frame = cv.flip(frame,1)
    data = image_processed(frame)
    
    # print(data.shape)
    data = np.array(data)
    y_pred = svm.predict(data.reshape(-1,63))
    print(y_pred)
    # font
    font = cv2.FONT_HERSHEY_SIMPLEX
    
    # org
    org = (50, 100)
    
    # fontScale
    fontScale = 3
    
    # Blue color in BGR
    color = (255, 0, 0)
    
    # Line thickness of 2 px
    thickness = 5
    
    # Using cv2.putText() method
    frame = cv2.putText(frame, str(y_pred[0]), org, font, 
                    fontScale, color, thickness, cv2.LINE_AA)
    cv.imshow('frame', frame)
    if cv.waitKey(1) == ord('q'):
        break

cap.release()
cv.destroyAllWindows()