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data.py
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data.py
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# -*- coding: utf-8 -*-
"""Data code.
* Author: Minseong Kim([email protected])
"""
import torch
from PIL import Image
from pathlib import Path
from random import randint
from utils import get_transformer
from torch.utils.data import DataLoader
class Dataset(torch.utils.data.Dataset):
"""Dataset for training."""
def __init__(self, root_path, max_iter, transforms):
"""Init."""
super(Dataset, self).__init__()
path = Path(root_path)
self.file_paths = sorted(list(path.glob('*.jpg')))
self.length = len(self.file_paths)
self.max_iter = max_iter
self.transforms = transforms
def __len__(self):
"""Length for training iteration."""
return self.max_iter
def __getitem__(self, _):
"""Get item randomly."""
index = randint(0, self.length - 1)
image = Image.open(self.file_paths[index]).convert('RGB')
return self.transforms(image)
def get_dataloader(path, imsize, cropsize, cencrop, max_iter, batch_size):
"""Get dataloder."""
transforms = get_transformer(imsize, cropsize, cencrop)
dataset = Dataset(path, max_iter * batch_size, transforms)
dataloader = DataLoader(dataset, batch_size=batch_size)
return dataloader