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from PIL import Image
import torch
import torchvision.transforms as transforms
def preprocess_img_from_path(path_to_image, img_size):
img = Image.open(path_to_image)
return preprocess_img(img, img_size)
def preprocess_img(img: Image, img_size):
original_size = img.size
transform = transforms.Compose([
transforms.Resize((img_size, img_size)),
transforms.ToTensor()
])
img = transform(img).unsqueeze(0)
return img, original_size
def postprocess_img(img, original_size):
img = img.detach().cpu().squeeze(0)
# address tensor value scaling and quantization
img = torch.clamp(img, 0, 1)
img = img.mul(255).byte()
img = transforms.ToPILImage()(img)
img = img.resize(original_size, Image.Resampling.LANCZOS)
return img |