text_plain_output_2.png application_vnd.jupyter.stderr_output_1.png
import torch

import numpy as np
import pandas as pd
import os
import cv2
import matplotlib.pyplot as plt
import torch
from torch import nn
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms
from torch.optim import Adam
import glob
from tqdm.notebook import tqdm
from PIL import Image
import torchvision
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, classification_report, ConfusionMatrixDisplay, confusion_matrix, roc_curve, auc
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
print('The model will be running on', device, 'device')