Spaces:
Running
on
Zero
Running
on
Zero
File size: 4,964 Bytes
df13f4b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 |
# Copyright (C) 2022-present Naver Corporation. All rights reserved.
# Licensed under CC BY-NC-SA 4.0 (non-commercial use only).
import os
from torch.utils.data import Dataset
from PIL import Image
from datasets.transforms import get_pair_transforms
def load_image(impath):
return Image.open(impath)
def load_pairs_from_cache_file(fname, root=''):
assert os.path.isfile(fname), "cannot parse pairs from {:s}, file does not exist".format(fname)
with open(fname, 'r') as fid:
lines = fid.read().strip().splitlines()
pairs = [ (os.path.join(root,l.split()[0]), os.path.join(root,l.split()[1])) for l in lines]
return pairs
def load_pairs_from_list_file(fname, root=''):
assert os.path.isfile(fname), "cannot parse pairs from {:s}, file does not exist".format(fname)
with open(fname, 'r') as fid:
lines = fid.read().strip().splitlines()
pairs = [ (os.path.join(root,l+'_1.jpg'), os.path.join(root,l+'_2.jpg')) for l in lines if not l.startswith('#')]
return pairs
def write_cache_file(fname, pairs, root=''):
if len(root)>0:
if not root.endswith('/'): root+='/'
assert os.path.isdir(root)
s = ''
for im1, im2 in pairs:
if len(root)>0:
assert im1.startswith(root), im1
assert im2.startswith(root), im2
s += '{:s} {:s}\n'.format(im1[len(root):], im2[len(root):])
with open(fname, 'w') as fid:
fid.write(s[:-1])
def parse_and_cache_all_pairs(dname, data_dir='./data/'):
if dname=='habitat_release':
dirname = os.path.join(data_dir, 'habitat_release')
assert os.path.isdir(dirname), "cannot find folder for habitat_release pairs: "+dirname
cache_file = os.path.join(dirname, 'pairs.txt')
assert not os.path.isfile(cache_file), "cache file already exists: "+cache_file
print('Parsing pairs for dataset: '+dname)
pairs = []
for root, dirs, files in os.walk(dirname):
if 'val' in root: continue
dirs.sort()
pairs += [ (os.path.join(root,f), os.path.join(root,f[:-len('_1.jpeg')]+'_2.jpeg')) for f in sorted(files) if f.endswith('_1.jpeg')]
print('Found {:,} pairs'.format(len(pairs)))
print('Writing cache to: '+cache_file)
write_cache_file(cache_file, pairs, root=dirname)
else:
raise NotImplementedError('Unknown dataset: '+dname)
def dnames_to_image_pairs(dnames, data_dir='./data/'):
"""
dnames: list of datasets with image pairs, separated by +
"""
all_pairs = []
for dname in dnames.split('+'):
if dname=='habitat_release':
dirname = os.path.join(data_dir, 'habitat_release')
assert os.path.isdir(dirname), "cannot find folder for habitat_release pairs: "+dirname
cache_file = os.path.join(dirname, 'pairs.txt')
assert os.path.isfile(cache_file), "cannot find cache file for habitat_release pairs, please first create the cache file, see instructions. "+cache_file
pairs = load_pairs_from_cache_file(cache_file, root=dirname)
elif dname in ['ARKitScenes', 'MegaDepth', '3DStreetView', 'IndoorVL']:
dirname = os.path.join(data_dir, dname+'_crops')
assert os.path.isdir(dirname), "cannot find folder for {:s} pairs: {:s}".format(dname, dirname)
list_file = os.path.join(dirname, 'listing.txt')
assert os.path.isfile(list_file), "cannot find list file for {:s} pairs, see instructions. {:s}".format(dname, list_file)
pairs = load_pairs_from_list_file(list_file, root=dirname)
print(' {:s}: {:,} pairs'.format(dname, len(pairs)))
all_pairs += pairs
if '+' in dnames: print(' Total: {:,} pairs'.format(len(all_pairs)))
return all_pairs
class PairsDataset(Dataset):
def __init__(self, dnames, trfs='', totensor=True, normalize=True, data_dir='./data/'):
super().__init__()
self.image_pairs = dnames_to_image_pairs(dnames, data_dir=data_dir)
self.transforms = get_pair_transforms(transform_str=trfs, totensor=totensor, normalize=normalize)
def __len__(self):
return len(self.image_pairs)
def __getitem__(self, index):
im1path, im2path = self.image_pairs[index]
im1 = load_image(im1path)
im2 = load_image(im2path)
if self.transforms is not None: im1, im2 = self.transforms(im1, im2)
return im1, im2
if __name__=="__main__":
import argparse
parser = argparse.ArgumentParser(prog="Computing and caching list of pairs for a given dataset")
parser.add_argument('--data_dir', default='./data/', type=str, help="path where data are stored")
parser.add_argument('--dataset', default='habitat_release', type=str, help="name of the dataset")
args = parser.parse_args()
parse_and_cache_all_pairs(dname=args.dataset, data_dir=args.data_dir)
|