image_preprocessing.py

#Image preprocessing functions

import numpy as np
from torchvision import datasets, transforms
from PIL import Image

# Define transforms for the training and testing sets
data_transforms = {'train': transforms.Compose([transforms.RandomRotation(30),
                                      transforms.RandomResizedCrop(224),
                                      transforms.RandomHorizontalFlip(),
                                      transforms.ToTensor(),
                                      transforms.Normalize([0.485, 0.456, 0.406],
                                                           [0.229, 0.224, 0.225])]),

                    'test': transforms.Compose([transforms.Resize(256),
                                      transforms.CenterCrop(224),
                                      transforms.ToTensor(),
                                      transforms.Normalize([0.485, 0.456, 0.406],
                                                           [0.229, 0.224, 0.225])])}

#Convert the image to numby array
def process_image(image):   
    img = Image.open(image)
    pre_img = 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 = pre_img(img) 
    np_image = np.array(img)
    
    return(np_image)