Spaces:
Sleeping
Sleeping
File size: 10,241 Bytes
265ae36 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 |
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the Apache License, Version 2.0
# found in the LICENSE file in the root directory of this source tree.
from dataclasses import dataclass
from enum import Enum
from functools import lru_cache
from gzip import GzipFile
from io import BytesIO
from mmap import ACCESS_READ, mmap
import os
from typing import Any, Callable, List, Optional, Set, Tuple
import warnings
import numpy as np
from .extended import ExtendedVisionDataset
_Labels = int
_DEFAULT_MMAP_CACHE_SIZE = 16 # Warning: This can exhaust file descriptors
@dataclass
class _ClassEntry:
block_offset: int
maybe_filename: Optional[str] = None
@dataclass
class _Entry:
class_index: int # noqa: E701
start_offset: int
end_offset: int
filename: str
class _Split(Enum):
TRAIN = "train"
VAL = "val"
@property
def length(self) -> int:
return {
_Split.TRAIN: 11_797_647,
_Split.VAL: 561_050,
}[self]
def entries_path(self):
return f"imagenet21kp_{self.value}.txt"
def _get_tarball_path(class_id: str) -> str:
return f"{class_id}.tar"
def _make_mmap_tarball(tarballs_root: str, mmap_cache_size: int):
@lru_cache(maxsize=mmap_cache_size)
def _mmap_tarball(class_id: str) -> mmap:
tarball_path = _get_tarball_path(class_id)
tarball_full_path = os.path.join(tarballs_root, tarball_path)
with open(tarball_full_path) as f:
return mmap(fileno=f.fileno(), length=0, access=ACCESS_READ)
return _mmap_tarball
class ImageNet22k(ExtendedVisionDataset):
_GZIPPED_INDICES: Set[int] = {
841_545,
1_304_131,
2_437_921,
2_672_079,
2_795_676,
2_969_786,
6_902_965,
6_903_550,
6_903_628,
7_432_557,
7_432_589,
7_813_809,
8_329_633,
10_296_990,
10_417_652,
10_492_265,
10_598_078,
10_782_398,
10_902_612,
11_203_736,
11_342_890,
11_397_596,
11_589_762,
11_705_103,
12_936_875,
13_289_782,
}
Labels = _Labels
def __init__(
self,
*,
root: str,
extra: str,
transforms: Optional[Callable] = None,
transform: Optional[Callable] = None,
target_transform: Optional[Callable] = None,
mmap_cache_size: int = _DEFAULT_MMAP_CACHE_SIZE,
) -> None:
super().__init__(root, transforms, transform, target_transform)
self._extra_root = extra
entries_path = self._get_entries_path(root)
self._entries = self._load_extra(entries_path)
class_ids_path = self._get_class_ids_path(root)
self._class_ids = self._load_extra(class_ids_path)
self._gzipped_indices = ImageNet22k._GZIPPED_INDICES
self._mmap_tarball = _make_mmap_tarball(self._tarballs_root, mmap_cache_size)
def _get_entries_path(self, root: Optional[str] = None) -> str:
return "entries.npy"
def _get_class_ids_path(self, root: Optional[str] = None) -> str:
return "class-ids.npy"
def _find_class_ids(self, path: str) -> List[str]:
class_ids = []
with os.scandir(path) as entries:
for entry in entries:
root, ext = os.path.splitext(entry.name)
if ext != ".tar":
continue
class_ids.append(root)
return sorted(class_ids)
def _load_entries_class_ids(self, root: Optional[str] = None) -> Tuple[List[_Entry], List[str]]:
root = self.get_root(root)
entries: List[_Entry] = []
class_ids = self._find_class_ids(root)
for class_index, class_id in enumerate(class_ids):
path = os.path.join(root, "blocks", f"{class_id}.log")
class_entries = []
try:
with open(path) as f:
for line in f:
line = line.rstrip()
block, filename = line.split(":")
block_offset = int(block[6:])
filename = filename[1:]
maybe_filename = None
if filename != "** Block of NULs **":
maybe_filename = filename
_, ext = os.path.splitext(filename)
# assert ext == ".JPEG"
class_entry = _ClassEntry(block_offset, maybe_filename)
class_entries.append(class_entry)
except OSError as e:
raise RuntimeError(f'can not read blocks file "{path}"') from e
assert class_entries[-1].maybe_filename is None
for class_entry1, class_entry2 in zip(class_entries, class_entries[1:]):
assert class_entry1.block_offset <= class_entry2.block_offset
start_offset = 512 * class_entry1.block_offset
end_offset = 512 * class_entry2.block_offset
assert class_entry1.maybe_filename is not None
filename = class_entry1.maybe_filename
entry = _Entry(class_index, start_offset, end_offset, filename)
# Skip invalid image files (PIL throws UnidentifiedImageError)
if filename == "n06470073_47249.JPEG":
continue
entries.append(entry)
return entries, class_ids
def _load_extra(self, extra_path: str) -> np.ndarray:
extra_root = self._extra_root
extra_full_path = os.path.join(extra_root, extra_path)
return np.load(extra_full_path, mmap_mode="r")
def _save_extra(self, extra_array: np.ndarray, extra_path: str) -> None:
extra_root = self._extra_root
extra_full_path = os.path.join(extra_root, extra_path)
os.makedirs(extra_root, exist_ok=True)
np.save(extra_full_path, extra_array)
@property
def _tarballs_root(self) -> str:
return self.root
def find_class_id(self, class_index: int) -> str:
return str(self._class_ids[class_index])
def get_image_data(self, index: int) -> bytes:
entry = self._entries[index]
class_id = entry["class_id"]
class_mmap = self._mmap_tarball(class_id)
start_offset, end_offset = entry["start_offset"], entry["end_offset"]
try:
mapped_data = class_mmap[start_offset:end_offset]
data = mapped_data[512:] # Skip entry header block
if len(data) >= 2 and tuple(data[:2]) == (0x1F, 0x8B):
assert index in self._gzipped_indices, f"unexpected gzip header for sample {index}"
with GzipFile(fileobj=BytesIO(data)) as g:
data = g.read()
except Exception as e:
raise RuntimeError(f"can not retrieve image data for sample {index} " f'from "{class_id}" tarball') from e
return data
def get_target(self, index: int) -> Any:
return int(self._entries[index]["class_index"])
def get_targets(self) -> np.ndarray:
return self._entries["class_index"]
def get_class_id(self, index: int) -> str:
return str(self._entries[index]["class_id"])
def get_class_ids(self) -> np.ndarray:
return self._entries["class_id"]
def __getitem__(self, index: int) -> Tuple[Any, Any]:
with warnings.catch_warnings():
warnings.simplefilter("ignore")
return super().__getitem__(index)
def __len__(self) -> int:
return len(self._entries)
def _dump_entries(self, *args, **kwargs) -> None:
entries, class_ids = self._load_entries_class_ids(*args, **kwargs)
max_class_id_length, max_filename_length, max_class_index = -1, -1, -1
for entry in entries:
class_id = class_ids[entry.class_index]
max_class_index = max(entry.class_index, max_class_index)
max_class_id_length = max(len(class_id), max_class_id_length)
max_filename_length = max(len(entry.filename), max_filename_length)
dtype = np.dtype(
[
("class_index", "<u4"),
("class_id", f"U{max_class_id_length}"),
("start_offset", "<u4"),
("end_offset", "<u4"),
("filename", f"U{max_filename_length}"),
]
)
sample_count = len(entries)
entries_array = np.empty(sample_count, dtype=dtype)
for i, entry in enumerate(entries):
class_index = entry.class_index
class_id = class_ids[class_index]
start_offset = entry.start_offset
end_offset = entry.end_offset
filename = entry.filename
entries_array[i] = (
class_index,
class_id,
start_offset,
end_offset,
filename,
)
entries_path = self._get_entries_path(*args, **kwargs)
self._save_extra(entries_array, entries_path)
def _dump_class_ids(self, *args, **kwargs) -> None:
entries_path = self._get_entries_path(*args, **kwargs)
entries_array = self._load_extra(entries_path)
max_class_id_length, max_class_index = -1, -1
for entry in entries_array:
class_index, class_id = entry["class_index"], entry["class_id"]
max_class_index = max(int(class_index), max_class_index)
max_class_id_length = max(len(str(class_id)), max_class_id_length)
class_ids_array = np.empty(max_class_index + 1, dtype=f"U{max_class_id_length}")
for entry in entries_array:
class_index, class_id = entry["class_index"], entry["class_id"]
class_ids_array[class_index] = class_id
class_ids_path = self._get_class_ids_path(*args, **kwargs)
self._save_extra(class_ids_array, class_ids_path)
def _dump_extra(self, *args, **kwargs) -> None:
self._dump_entries(*args, *kwargs)
self._dump_class_ids(*args, *kwargs)
def dump_extra(self, root: Optional[str] = None) -> None:
return self._dump_extra(root)
|