I am using YOLOV5 to train a binary classifier. After training the model I downloaded the weights to use it in my code:
import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim import lr_scheduler
import numpy as np
import torchvision
from torchvision import datasets, models, transforms
import matplotlib.pyplot as plt
import time
import os
import pandas as pd
from sklearn.model_selection import train_test_split
import shutil
import time
import copy
from PIL import Image
import glob
import cv2
from pygame import mixer

from models.experimental import attempt_load 
from utils.datasets import LoadStreams, LoadImages
from utils.general import check_img_size, non_max_suppression, apply_classifier, scale_coords, xyxy2xywh, \
    strip_optimizer, set_logging, increment_path
from utils.plots import plot_one_box
from utils.torch_utils import select_device, load_classifier, time_synchronized

# Load the model
filepath = 'weights/best.pt'
device = torch.device('cpu')
model = attempt_load(filepath, map_location = device)

# model = torch.load(filepath)

class_names = ['class1', ' class2']

mixer.init()
sound = mixer.Sound('files/alarm.wav')

def process_image(image):
    
    pil_image = image
    
    image_transformation = transforms.Compose([
        transforms.Resize(256),
        transforms.CenterCrop(224),
        transforms.ToTensor(),
        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])
    img = image_transformation(pil_image)
    return img

def classify_face(image):
    device = torch.device("cpu")
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    im = Image.fromarray(image)
    image = process_image(im)
    print('Image processed')
    img = image.unsqueeze_(0)
    img = image.float()
    
    model.eval()
    model.cpu()
    output = model(image)
    print("#################")
    print(output)
    print("#################")
    _, predicted = torch.max(output, 1)
    print(predicted.data[0], "predicted")
    
    classification1 = predicted.data[0]
    index = int(classification1)
    print(class_names[index])
    return class_names[index]

cap = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_COMPLEX_SMALL
score = 0
thicc = 2

while(True):
    ret, frame = cap.read()
    height, width = frame.shape[:2]
    label = classify_face(frame)
    if label == "class1":
        print("Recognition")
    else:
        sound.play()
        print("Beep")
    cv2.putText(frame, str(label), (100, height-20), font, 1, (255,255,255), 1, cv2.LINE_AA)
    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break 

cap.release()
cv2.destroyAllWindows()


So after executing this code I get the following error:
Fusing layers...
Image processed
#################
(tensor([[[6.69752e+00, 8.04415e+00, 3.28937e+01,  ..., 2.50250e-01, 8.44748e-01, 6.81155e-02],
         [1.33582e+01, 8.66212e+00, 3.57769e+01,  ..., 2.49377e-01, 9.11782e-01, 5.36799e-02],
         [2.17681e+01, 8.39124e+00, 3.61725e+01,  ..., 1.95423e-01, 9.29966e-01, 4.44486e-02],
         ...,
         [1.26728e+02, 2.13414e+02, 2.50512e+02,  ..., 1.54672e-03, 4.71090e-01, 6.19469e-01],
         [1.65840e+02, 2.11068e+02, 2.44700e+02,  ..., 3.60577e-03, 6.32448e-01, 4.47742e-01],
         [1.97628e+02, 1.99194e+02, 1.87245e+02,  ..., 2.99891e-02, 5.68435e-01, 4.69893e-01]]]), [tensor([[[[[ 7.01838e-01,  1.11338e+00,  2.27554e+00,  ..., -1.09728e+00,  1.69399e+00, -2.61600e+00],
.
.
.
.

         [[[-9.98679e-01,  1.22741e+00,  3.44763e-02,  ..., -1.80213e+01, -2.14888e+00,  9.24265e+00],
           [-2.50130e+00,  1.01704e+00,  1.38206e-01,  ..., -2.42873e+01,  1.88566e-02,  9.59896e+00],
           [-2.42535e+00,  2.87720e-01,  1.67901e-01,  ..., -2.35991e+01, -7.32914e-01,  1.00338e+01],
           ...,
           [-1.85729e+00,  9.89787e-02,  1.70667e-02,  ..., -1.84327e+01,  3.36290e-01,  6.32527e+00],
           [-1.38407e+00,  1.97428e-01, -6.90677e-02,  ..., -1.46897e+01,  1.04981e+00,  4.01571e+00],
           [-8.79307e-01, -2.48860e-01, -2.99195e-01,  ..., -8.85421e+00,  1.25883e+00,  7.27224e-01]],

          [[-2.68999e+00,  2.96068e+00,  1.58570e-01,  ..., -2.82125e+01,  8.48523e-01,  1.34653e+01],
           [-4.10724e+00,  2.13760e+00,  3.61649e-01,  ..., -3.43560e+01,  6.56664e+00,  1.07199e+01],
           [-4.23445e+00,  8.68277e-01,  4.84210e-01,  ..., -3.45495e+01,  6.51605e+00,  1.09539e+01],
           ...,
           [-3.44668e+00,  4.01725e-01,  3.10529e-01,  ..., -2.52625e+01,  4.36256e+00,  7.46622e+00],
           [-2.37642e+00,  2.04813e-01,  1.78175e-01,  ..., -1.82195e+01,  3.01713e+00,  4.74489e+00],
           [-1.33341e+00, -3.53624e-01, -2.47158e-01,  ..., -1.18629e+01,  5.18395e-01,  3.28432e+00]],

          [[-3.01659e+00,  4.08582e+00,  1.84225e-01,  ..., -3.20945e+01,  1.73300e+00,  1.47701e+01],
           [-4.09202e+00,  3.22706e+00,  5.14679e-01,  ..., -3.99877e+01,  8.27533e+00,  1.20588e+01],
           [-4.40775e+00,  2.37793e+00,  8.85271e-01,  ..., -4.28225e+01,  1.12920e+01,  1.06002e+01],
           ...,
           [-3.21899e+00,  6.00486e-01,  5.33032e-01,  ..., -2.79490e+01,  7.23887e+00,  5.49865e+00],
           [-1.86446e+00,  3.16312e-01,  1.72526e-01,  ..., -1.91241e+01,  3.27271e+00,  4.72650e+00],
           [-1.28665e+00, -5.96457e-01, -2.56735e-01,  ..., -1.18503e+01,  1.95543e-01,  3.55386e+00]],

          ...,

          [[-3.18089e+00,  4.74764e+00,  3.08528e-01,  ..., -3.67707e+01,  4.93246e+00,  1.43625e+01],
           [-3.82487e+00,  3.55594e+00,  7.72573e-01,  ..., -4.49166e+01,  1.31486e+01,  9.88138e+00],
           [-2.27103e+00,  1.16540e+00,  7.74492e-01,  ..., -4.00071e+01,  1.10363e+01,  8.79684e+00],
           ...,
           [-1.56786e+00,  1.75814e-01, -3.25143e-03,  ..., -1.74488e+01,  2.27494e+00,  5.53798e+00],
           [-1.38396e+00,  2.08026e-01, -1.17126e-01,  ..., -1.32549e+01,  2.37821e+00,  3.00369e+00],
           [-1.30192e+00, -7.80406e-01, -3.65586e-01,  ..., -8.80362e+00, -6.79248e-02,  2.24451e+00]],
          ...,

          [[-6.45747e+00,  5.52765e+00, -6.96355e-02,  ..., -2.89378e+01,  1.76833e+00,  6.23220e+00],
           [-9.18074e+00,  5.90005e+00,  1.11971e+00,  ..., -3.84686e+01,  7.98066e+00,  2.76979e+00],
           [-7.06971e+00,  4.38462e+00,  1.45152e+00,  ..., -3.41044e+01,  6.05271e+00,  3.31685e+00],
           ...,
           [-2.54191e+00,  1.53113e+00,  1.44606e-02,  ..., -1.48724e+01,  6.23257e-01,  2.63972e+00],
           [-2.62895e+00,  1.35553e+00, -1.88812e-01,  ..., -1.17762e+01,  8.47540e-01,  1.90525e+00],
           [-2.10761e+00, -2.75716e-01, -3.36237e-01,  ..., -6.97977e+00, -4.41530e-01,  1.87154e+00]],

          [[-5.89622e+00,  4.53648e+00,  1.84505e-02,  ..., -2.80769e+01,  3.20636e+00,  4.17765e+00],
           [-7.71760e+00,  4.57286e+00,  1.15239e+00,  ..., -3.59879e+01,  8.78807e+00,  5.63405e-01],
           [-5.05829e+00,  3.16673e+00,  1.08323e+00,  ..., -2.70402e+01,  4.91386e+00,  2.79420e+00],
           ...,
           [-2.26254e+00,  8.64523e-01, -3.60977e-01,  ..., -1.08126e+01,  8.49348e-01,  9.47680e-01],
           [-2.00815e+00,  7.68478e-01, -3.30762e-01,  ..., -9.98294e+00,  1.89936e+00, -1.13327e-01],
           [-1.20806e+00, -4.77093e-01, -3.70990e-01,  ..., -6.13591e+00,  4.18642e-01,  5.03567e-01]],

          [[-3.65250e+00,  2.69710e+00,  3.47386e-01,  ..., -2.28330e+01,  5.96863e+00, -1.50741e+00],
           [-3.48414e+00,  3.47050e+00,  9.23297e-01,  ..., -2.72244e+01,  8.49592e+00, -2.85586e+00],
           [-8.46303e-01,  1.84489e+00,  2.89578e-01,  ..., -1.80682e+01,  4.94311e+00, -6.00901e-01],
           ...,
           [-1.20757e+00,  3.41630e-01, -3.64955e-01,  ..., -6.47007e+00, -1.15771e-01,  4.87296e-01],
           [-6.57739e-01,  1.92338e-01, -3.84763e-01,  ..., -5.62161e+00,  5.42731e-01, -2.09800e-01],
           [-6.72526e-01, -5.64906e-01, -6.00370e-01,  ..., -3.47647e+00,  2.75467e-01, -1.20575e-01]]]]])])
#################
Traceback (most recent call last):
  File "WEBCAM_DETECT.py", line 94, in <module>
    label = classify_face(frame)
  File "WEBCAM_DETECT.py", line 78, in classify_face
    _, predicted = torch.max(output, 1)
TypeError: max() received an invalid combination of arguments - got (tuple, int), but expected one of:
 * (Tensor input)
 * (Tensor input, name dim, bool keepdim, *, tuple of Tensors out)
 * (Tensor input, Tensor other, *, Tensor out)
 * (Tensor input, int dim, bool keepdim, *, tuple of Tensors out)

[ WARN:0] global C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-h4wtvo23\opencv\modules\videoio\src\cap_msmf.cpp (435) `anonymous-namespace'::SourceReaderCB::~SourceReaderCB terminating async callback

Please let me know how can I solve this error?