poxtest_1_import.py

import torch
import torchvision
from torchvision import datasets, models, transforms
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torch.backends.cudnn as cudnn

import numpy as np
import time
import os
from PIL import Image
import copy
import validators

from torchvision.datasets import ImageFolder
from torch.utils.data import DataLoader, random_split
from torchvision import transforms

from PIL import Image
import requests
from io import BytesIO

label_map={
    0:"Chickenpox",
    1:"Measles",
    2:"Monkeypox",
    3:"Normal"
}
classes = ('Chickenpox', 'Measles', 'Monkeypox', 'Normal')
PATH = './resnet18_net.pth'
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
data_transform = transforms.Compose([transforms.Grayscale(num_output_channels=1),
                                     transforms.Resize((64,64)),
                                     transforms.ToTensor()])