I am completely new to Pytorch and I created my first model. I made a similar model in keras and use this code to test it on data it never seen before:
> from keras.models import load_model
> import numpy as np
> from keras.preprocessing import image
> import time
> import sys
> import PIL
>    
> start_time =time.time()
> classifier = load_model("C:/Users/deonh/Pictures/Summer Work/model/Covid-19.h5")
> #classifier.summary()
> 
> test_image = image.load_img('C:/Users/deonh/Pictures/Summer Work/Prediction/pnemonia_Covid_or_Normal_1.jpeg', target_size = (64, 64))
> #test_image.show()
> test_image = image.img_to_array(test_image)
> 
> test_image = np.expand_dims(test_image, axis = 0)
> result = classifier.predict(test_image)
> print(result)
> #training_set.class_indices
> print("%s seconds" %(time.time() - start_time) + " run time")

My goal is to do something similar with my Pytorch model. This is what I have so far, but it is not working.

import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
from torchvision import datasets, transforms, models # add models to the list
import os
import time
from PIL import Image
from IPython.display import display
model = torch.load(‘C:/Users/deonh/Pictures/Summer Work/xrays/PythonApplication1/scans’)
photo = Image.open(‘C:/Users/deonh/Pictures/Summer Work/prediction/Covid_Normal_or_Pnemonia.jpg’)
photo.show()
transform = transforms.Compose([
    transforms.Resize(224),
    transforms.ToTensor(),
    transforms.Normalize([0.485, 0.456, 0.406],
                         [0.229, 0.224, 0.225])
])

im = transform(photo)
#with torch.no_grad():
prediction = model(im)

I am getting a    ‘collections.OrderedDict’ object is not callable  error