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from io import BytesIO
import lmdb
from PIL import Image
from torch.utils.data import Dataset
class MultiResolutionDataset(Dataset):
def __init__(self, path, transform, resolution=256):
self.env = lmdb.open(
path,
max_readers=32,
readonly=True,
lock=False,
readahead=False,
meminit=False,
)
if not self.env:
raise IOError('Cannot open lmdb dataset', path)
with self.env.begin(write=False) as txn:
self.length = int(txn.get('length'.encode('utf-8')).decode('utf-8'))
self.resolution = resolution
self.transform = transform
def __len__(self):
return self.length
def __getitem__(self, index):
with self.env.begin(write=False) as txn:
key = f'{self.resolution}-{str(index).zfill(5)}'.encode('utf-8')
img_bytes = txn.get(key)
buffer = BytesIO(img_bytes)
img = Image.open(buffer)
img = self.transform(img)
return img
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