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data_utils.py
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data_utils.py
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from PIL import Image
from torchvision.transforms import Compose, ToTensor, ToPILImage, CenterCrop, transforms, Resize
from torch.utils.data.dataset import Dataset
def is_image_file(filename):
return any(filename.endswith(extension) for extension in ['.png', '.jpg', '.jpeg', '.PNG', '.JPG', '.JPEG'])
hr_target_size = (1020, 2040)
hr_transform = transforms.Compose([
transforms.Lambda(lambda img: img.rotate(0) if img.size[0] > img.size[1] else img.rotate(90)),
transforms.CenterCrop(hr_target_size),
transforms.ToTensor()
])
lr_target_size = (1020 // 4, 2040 // 4)
lr_transform = transforms.Compose([
transforms.Lambda(lambda img: img.rotate(0) if img.size[0] > img.size[1] else img.rotate(90)),
transforms.CenterCrop(lr_target_size),
transforms.ToTensor()
])
class Div2kTrainDataset(Dataset):
def __init__(self, hr_base_dir, lr_base_dir):
super(Div2kTrainDataset, self).__init__()
self.hr_base_dir = hr_base_dir
self.lr_base_dir = lr_base_dir
self.hr_image_filenames = [f'{self.hr_base_dir}/{i:0>4}.png' for i in range(1, 801)]
self.lr_image_filenames = [f'{self.lr_base_dir}/{i:0>4}x4d.png' for i in range(1, 801)]
self.hr_transform = hr_transform
self.lr_transform = lr_transform
def __getitem__(self, index):
hr_image = self.hr_transform(Image.open(self.hr_image_filenames[index]))
lr_image = self.lr_transform(Image.open(self.lr_image_filenames[index]))
return hr_image, lr_image
def __len__(self):
return len(self.hr_image_filenames)
class Div2kValDataset(Dataset):
def __init__(self, hr_base_dir, lr_base_dir):
super(Div2kValDataset, self).__init__()
self.hr_base_dir = hr_base_dir
self.lr_base_dir = lr_base_dir
self.hr_image_filenames = [f'{self.hr_base_dir}/{i:0>4}.png' for i in range(801, 901)]
self.lr_image_filenames = [f'{self.lr_base_dir}/{i:0>4}x4d.png' for i in range(801, 901)]
self.hr_transform = hr_transform
self.lr_transform = lr_transform
def __getitem__(self, index):
hr_image = self.hr_transform(Image.open(self.hr_image_filenames[index]))
lr_image = self.lr_transform(Image.open(self.lr_image_filenames[index]))
return hr_image, lr_image
def __len__(self):
return len(self.hr_image_filenames)
def display_transform():
return Compose([
ToPILImage(),
Resize(400),
CenterCrop(400),
ToTensor()
])