Datasets:

TNauen
/

ForNet

@@ -8,6 +8,7 @@ import queue
 import re
 import urllib
 import zipfile
 from math import floor
 from typing import Optional
@@ -22,11 +23,1015 @@ from PIL import Image, ImageFilter
 from torchvision import transforms as T
 from tqdm import tqdm
-from classes import IMAGENET2012_CLASSES
 logger = datasets.logging.get_logger(__name__)
 _CITATION = """\
 @misc{nauen2025foraug,
     title={ForAug: Recombining Foregrounds and Backgrounds to Improve Vision Transformer Training with Bias Mitigation},
@@ -69,6 +1074,8 @@ class RecombineDataset(Dataset):
         mask_smoothing_sigma,
         rel_jut_out,
         orig_img_prob,
         **kwargs,
     ):
         """Create the ForNet recombination dataset.
@@ -100,6 +1107,7 @@ class RecombineDataset(Dataset):
             "max",
             "mean",
         ], f"Invalid fg_size_mode {fg_size_mode}"
         self.background_combination = background_combination
         self.fg_scale_jitter = fg_scale_jitter
         self.pruning_ratio = pruning_ratio
@@ -111,6 +1119,8 @@ class RecombineDataset(Dataset):
         self.epochs = 0
         self._epoch = 0
         self.cls_to_idx = {}
         bg_rat_indices = super()._getitem(0)["bg_rat_idx_file"]
         self.train = "train" in bg_rat_indices.split("/")[-1]
@@ -178,6 +1188,9 @@ class RecombineDataset(Dataset):
         bg_img = bg_item["bg"].convert("RGB")
         bg_size = bg_img.size
         bg_area = bg_size[0] * bg_size[1]
         orig_fg_ratio = fg_item["fg/bg_area"]
         bg_fg_ratio = bg_item["fg/bg_area"]
@@ -200,6 +1213,7 @@ class RecombineDataset(Dataset):
                 goal_fg_ratio_upper * (1 + self.fg_scale_jitter),
             )
             / fg_size_factor
         )
         goal_shape_y = round(np.sqrt(bg_area * fg_scale * fg_img.size[1] / fg_img.size[0]))
@@ -233,6 +1247,12 @@ class RecombineDataset(Dataset):
         y_min = -self.rel_jut_out * fg_img.size[1]
         y_max = bg_size[1] - fg_img.size[1] * (1 - self.rel_jut_out)
         if x_min > x_max:
             x_min = x_max = (x_min + x_max) / 2
         if y_min > y_max:
@@ -267,6 +1287,8 @@ _CONFIG_HASH_IGNORE_KWARGS = [
     "mask_smoothing_sigma",
     "rel_jut_out",
     "orig_img_prob",
 ]
@@ -283,6 +1305,8 @@ class ForNetConfig(datasets.BuilderConfig):
         mask_smoothing_sigma,
         rel_jut_out,
         orig_img_prob,
         **kwargs,
     ):
         """BuilderConfig for ForNet.
@@ -299,6 +1323,8 @@ class ForNetConfig(datasets.BuilderConfig):
         self.mask_smoothing_sigma = mask_smoothing_sigma
         self.rel_jut_out = rel_jut_out
         self.orig_img_prob = orig_img_prob
     def __str__(self):
         return f"ForNetConfig(name={self.name}, version={self.version}, data_dir={self.data_dir}, data_files={self.data_files}, description={self.description}, background_combination={self.background_combination}, fg_scale_jitter={self.fg_scale_jitter}, pruning_ratio={self.pruning_ratio}, fg_size_mode={self.fg_size_mode}, fg_bates_n={self.fg_bates_n}, mask_smoothing_sigma={self.mask_smoothing_sigma}, rel_jut_out={self.rel_jut_out}, orig_img_prob={self.orig_img_prob})"
@@ -393,6 +1419,8 @@ class ForNet(datasets.GeneratorBasedBuilder):
             mask_smoothing_sigma=4.0,
             rel_jut_out=0.0,
             orig_img_prob=0.0,
         )
     ]
@@ -418,6 +1446,9 @@ class ForNet(datasets.GeneratorBasedBuilder):
         )
     def _split_generators(self, dl_manager: datasets.DownloadManager):
         urls_to_download = _CONST_URLS + _PATCH_URLS
         dl_paths = dl_manager.download(urls_to_download)
@@ -599,10 +1630,6 @@ class ForNet(datasets.GeneratorBasedBuilder):
         )
         fingerprint = self._get_dataset_fingerprint(split)
-        # print("config", self.config)
-        # print("rel data dir", self._relative_data_dir())
-        # print("split", str(split))
-        # print("fingerprint", fingerprint)
         splitname = str(split)
         if splitname == "validation":
@@ -618,6 +1645,8 @@ class ForNet(datasets.GeneratorBasedBuilder):
             mask_smoothing_sigma=self.config.mask_smoothing_sigma,
             rel_jut_out=self.config.rel_jut_out,
             orig_img_prob=self.config.orig_img_prob,
             **dataset_kwargs,
         )
@@ -633,7 +1662,7 @@ class ForNet(datasets.GeneratorBasedBuilder):
 def _in_iterator(in_queue, split):
     if split == "val":
         split = "validation"
-    imagenet = datasets.load_dataset("ILSVRC/imagenet-1k", split=split)
     for idx, ex in enumerate(imagenet):
         in_queue.put((idx, ex["image"]))

 import re
 import urllib
 import zipfile
+from collections import OrderedDict
 from math import floor
 from typing import Optional
 from torchvision import transforms as T
 from tqdm import tqdm
 logger = datasets.logging.get_logger(__name__)
+IMAGENET2012_CLASSES = OrderedDict(
+    {
+        "n01440764": "tench, Tinca tinca",
+        "n01443537": "goldfish, Carassius auratus",
+        "n01484850": "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias",
+        "n01491361": "tiger shark, Galeocerdo cuvieri",
+        "n01494475": "hammerhead, hammerhead shark",
+        "n01496331": "electric ray, crampfish, numbfish, torpedo",
+        "n01498041": "stingray",
+        "n01514668": "cock",
+        "n01514859": "hen",
+        "n01518878": "ostrich, Struthio camelus",
+        "n01530575": "brambling, Fringilla montifringilla",
+        "n01531178": "goldfinch, Carduelis carduelis",
+        "n01532829": "house finch, linnet, Carpodacus mexicanus",
+        "n01534433": "junco, snowbird",
+        "n01537544": "indigo bunting, indigo finch, indigo bird, Passerina cyanea",
+        "n01558993": "robin, American robin, Turdus migratorius",
+        "n01560419": "bulbul",
+        "n01580077": "jay",
+        "n01582220": "magpie",
+        "n01592084": "chickadee",
+        "n01601694": "water ouzel, dipper",
+        "n01608432": "kite",
+        "n01614925": "bald eagle, American eagle, Haliaeetus leucocephalus",
+        "n01616318": "vulture",
+        "n01622779": "great grey owl, great gray owl, Strix nebulosa",
+        "n01629819": "European fire salamander, Salamandra salamandra",
+        "n01630670": "common newt, Triturus vulgaris",
+        "n01631663": "eft",
+        "n01632458": "spotted salamander, Ambystoma maculatum",
+        "n01632777": "axolotl, mud puppy, Ambystoma mexicanum",
+        "n01641577": "bullfrog, Rana catesbeiana",
+        "n01644373": "tree frog, tree-frog",
+        "n01644900": "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui",
+        "n01664065": "loggerhead, loggerhead turtle, Caretta caretta",
+        "n01665541": "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea",
+        "n01667114": "mud turtle",
+        "n01667778": "terrapin",
+        "n01669191": "box turtle, box tortoise",
+        "n01675722": "banded gecko",
+        "n01677366": "common iguana, iguana, Iguana iguana",
+        "n01682714": "American chameleon, anole, Anolis carolinensis",
+        "n01685808": "whiptail, whiptail lizard",
+        "n01687978": "agama",
+        "n01688243": "frilled lizard, Chlamydosaurus kingi",
+        "n01689811": "alligator lizard",
+        "n01692333": "Gila monster, Heloderma suspectum",
+        "n01693334": "green lizard, Lacerta viridis",
+        "n01694178": "African chameleon, Chamaeleo chamaeleon",
+        "n01695060": "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis",
+        "n01697457": "African crocodile, Nile crocodile, Crocodylus niloticus",
+        "n01698640": "American alligator, Alligator mississipiensis",
+        "n01704323": "triceratops",
+        "n01728572": "thunder snake, worm snake, Carphophis amoenus",
+        "n01728920": "ringneck snake, ring-necked snake, ring snake",
+        "n01729322": "hognose snake, puff adder, sand viper",
+        "n01729977": "green snake, grass snake",
+        "n01734418": "king snake, kingsnake",
+        "n01735189": "garter snake, grass snake",
+        "n01737021": "water snake",
+        "n01739381": "vine snake",
+        "n01740131": "night snake, Hypsiglena torquata",
+        "n01742172": "boa constrictor, Constrictor constrictor",
+        "n01744401": "rock python, rock snake, Python sebae",
+        "n01748264": "Indian cobra, Naja naja",
+        "n01749939": "green mamba",
+        "n01751748": "sea snake",
+        "n01753488": "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus",
+        "n01755581": "diamondback, diamondback rattlesnake, Crotalus adamanteus",
+        "n01756291": "sidewinder, horned rattlesnake, Crotalus cerastes",
+        "n01768244": "trilobite",
+        "n01770081": "harvestman, daddy longlegs, Phalangium opilio",
+        "n01770393": "scorpion",
+        "n01773157": "black and gold garden spider, Argiope aurantia",
+        "n01773549": "barn spider, Araneus cavaticus",
+        "n01773797": "garden spider, Aranea diademata",
+        "n01774384": "black widow, Latrodectus mactans",
+        "n01774750": "tarantula",
+        "n01775062": "wolf spider, hunting spider",
+        "n01776313": "tick",
+        "n01784675": "centipede",
+        "n01795545": "black grouse",
+        "n01796340": "ptarmigan",
+        "n01797886": "ruffed grouse, partridge, Bonasa umbellus",
+        "n01798484": "prairie chicken, prairie grouse, prairie fowl",
+        "n01806143": "peacock",
+        "n01806567": "quail",
+        "n01807496": "partridge",
+        "n01817953": "African grey, African gray, Psittacus erithacus",
+        "n01818515": "macaw",
+        "n01819313": "sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita",
+        "n01820546": "lorikeet",
+        "n01824575": "coucal",
+        "n01828970": "bee eater",
+        "n01829413": "hornbill",
+        "n01833805": "hummingbird",
+        "n01843065": "jacamar",
+        "n01843383": "toucan",
+        "n01847000": "drake",
+        "n01855032": "red-breasted merganser, Mergus serrator",
+        "n01855672": "goose",
+        "n01860187": "black swan, Cygnus atratus",
+        "n01871265": "tusker",
+        "n01872401": "echidna, spiny anteater, anteater",
+        "n01873310": "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus",
+        "n01877812": "wallaby, brush kangaroo",
+        "n01882714": "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus",
+        "n01883070": "wombat",
+        "n01910747": "jellyfish",
+        "n01914609": "sea anemone, anemone",
+        "n01917289": "brain coral",
+        "n01924916": "flatworm, platyhelminth",
+        "n01930112": "nematode, nematode worm, roundworm",
+        "n01943899": "conch",
+        "n01944390": "snail",
+        "n01945685": "slug",
+        "n01950731": "sea slug, nudibranch",
+        "n01955084": "chiton, coat-of-mail shell, sea cradle, polyplacophore",
+        "n01968897": "chambered nautilus, pearly nautilus, nautilus",
+        "n01978287": "Dungeness crab, Cancer magister",
+        "n01978455": "rock crab, Cancer irroratus",
+        "n01980166": "fiddler crab",
+        "n01981276": "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica",
+        "n01983481": "American lobster, Northern lobster, Maine lobster, Homarus americanus",
+        "n01984695": "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish",
+        "n01985128": "crayfish, crawfish, crawdad, crawdaddy",
+        "n01986214": "hermit crab",
+        "n01990800": "isopod",
+        "n02002556": "white stork, Ciconia ciconia",
+        "n02002724": "black stork, Ciconia nigra",
+        "n02006656": "spoonbill",
+        "n02007558": "flamingo",
+        "n02009229": "little blue heron, Egretta caerulea",
+        "n02009912": "American egret, great white heron, Egretta albus",
+        "n02011460": "bittern",
+        "n02012849": "crane",
+        "n02013706": "limpkin, Aramus pictus",
+        "n02017213": "European gallinule, Porphyrio porphyrio",
+        "n02018207": "American coot, marsh hen, mud hen, water hen, Fulica americana",
+        "n02018795": "bustard",
+        "n02025239": "ruddy turnstone, Arenaria interpres",
+        "n02027492": "red-backed sandpiper, dunlin, Erolia alpina",
+        "n02028035": "redshank, Tringa totanus",
+        "n02033041": "dowitcher",
+        "n02037110": "oystercatcher, oyster catcher",
+        "n02051845": "pelican",
+        "n02056570": "king penguin, Aptenodytes patagonica",
+        "n02058221": "albatross, mollymawk",
+        "n02066245": "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus",
+        "n02071294": "killer whale, killer, orca, grampus, sea wolf, Orcinus orca",
+        "n02074367": "dugong, Dugong dugon",
+        "n02077923": "sea lion",
+        "n02085620": "Chihuahua",
+        "n02085782": "Japanese spaniel",
+        "n02085936": "Maltese dog, Maltese terrier, Maltese",
+        "n02086079": "Pekinese, Pekingese, Peke",
+        "n02086240": "Shih-Tzu",
+        "n02086646": "Blenheim spaniel",
+        "n02086910": "papillon",
+        "n02087046": "toy terrier",
+        "n02087394": "Rhodesian ridgeback",
+        "n02088094": "Afghan hound, Afghan",
+        "n02088238": "basset, basset hound",
+        "n02088364": "beagle",
+        "n02088466": "bloodhound, sleuthhound",
+        "n02088632": "bluetick",
+        "n02089078": "black-and-tan coonhound",
+        "n02089867": "Walker hound, Walker foxhound",
+        "n02089973": "English foxhound",
+        "n02090379": "redbone",
+        "n02090622": "borzoi, Russian wolfhound",
+        "n02090721": "Irish wolfhound",
+        "n02091032": "Italian greyhound",
+        "n02091134": "whippet",
+        "n02091244": "Ibizan hound, Ibizan Podenco",
+        "n02091467": "Norwegian elkhound, elkhound",
+        "n02091635": "otterhound, otter hound",
+        "n02091831": "Saluki, gazelle hound",
+        "n02092002": "Scottish deerhound, deerhound",
+        "n02092339": "Weimaraner",
+        "n02093256": "Staffordshire bullterrier, Staffordshire bull terrier",
+        "n02093428": "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier",
+        "n02093647": "Bedlington terrier",
+        "n02093754": "Border terrier",
+        "n02093859": "Kerry blue terrier",
+        "n02093991": "Irish terrier",
+        "n02094114": "Norfolk terrier",
+        "n02094258": "Norwich terrier",
+        "n02094433": "Yorkshire terrier",
+        "n02095314": "wire-haired fox terrier",
+        "n02095570": "Lakeland terrier",
+        "n02095889": "Sealyham terrier, Sealyham",
+        "n02096051": "Airedale, Airedale terrier",
+        "n02096177": "cairn, cairn terrier",
+        "n02096294": "Australian terrier",
+        "n02096437": "Dandie Dinmont, Dandie Dinmont terrier",
+        "n02096585": "Boston bull, Boston terrier",
+        "n02097047": "miniature schnauzer",
+        "n02097130": "giant schnauzer",
+        "n02097209": "standard schnauzer",
+        "n02097298": "Scotch terrier, Scottish terrier, Scottie",
+        "n02097474": "Tibetan terrier, chrysanthemum dog",
+        "n02097658": "silky terrier, Sydney silky",
+        "n02098105": "soft-coated wheaten terrier",
+        "n02098286": "West Highland white terrier",
+        "n02098413": "Lhasa, Lhasa apso",
+        "n02099267": "flat-coated retriever",
+        "n02099429": "curly-coated retriever",
+        "n02099601": "golden retriever",
+        "n02099712": "Labrador retriever",
+        "n02099849": "Chesapeake Bay retriever",
+        "n02100236": "German short-haired pointer",
+        "n02100583": "vizsla, Hungarian pointer",
+        "n02100735": "English setter",
+        "n02100877": "Irish setter, red setter",
+        "n02101006": "Gordon setter",
+        "n02101388": "Brittany spaniel",
+        "n02101556": "clumber, clumber spaniel",
+        "n02102040": "English springer, English springer spaniel",
+        "n02102177": "Welsh springer spaniel",
+        "n02102318": "cocker spaniel, English cocker spaniel, cocker",
+        "n02102480": "Sussex spaniel",
+        "n02102973": "Irish water spaniel",
+        "n02104029": "kuvasz",
+        "n02104365": "schipperke",
+        "n02105056": "groenendael",
+        "n02105162": "malinois",
+        "n02105251": "briard",
+        "n02105412": "kelpie",
+        "n02105505": "komondor",
+        "n02105641": "Old English sheepdog, bobtail",
+        "n02105855": "Shetland sheepdog, Shetland sheep dog, Shetland",
+        "n02106030": "collie",
+        "n02106166": "Border collie",
+        "n02106382": "Bouvier des Flandres, Bouviers des Flandres",
+        "n02106550": "Rottweiler",
+        "n02106662": "German shepherd, German shepherd dog, German police dog, alsatian",
+        "n02107142": "Doberman, Doberman pinscher",
+        "n02107312": "miniature pinscher",
+        "n02107574": "Greater Swiss Mountain dog",
+        "n02107683": "Bernese mountain dog",
+        "n02107908": "Appenzeller",
+        "n02108000": "EntleBucher",
+        "n02108089": "boxer",
+        "n02108422": "bull mastiff",
+        "n02108551": "Tibetan mastiff",
+        "n02108915": "French bulldog",
+        "n02109047": "Great Dane",
+        "n02109525": "Saint Bernard, St Bernard",
+        "n02109961": "Eskimo dog, husky",
+        "n02110063": "malamute, malemute, Alaskan malamute",
+        "n02110185": "Siberian husky",
+        "n02110341": "dalmatian, coach dog, carriage dog",
+        "n02110627": "affenpinscher, monkey pinscher, monkey dog",
+        "n02110806": "basenji",
+        "n02110958": "pug, pug-dog",
+        "n02111129": "Leonberg",
+        "n02111277": "Newfoundland, Newfoundland dog",
+        "n02111500": "Great Pyrenees",
+        "n02111889": "Samoyed, Samoyede",
+        "n02112018": "Pomeranian",
+        "n02112137": "chow, chow chow",
+        "n02112350": "keeshond",
+        "n02112706": "Brabancon griffon",
+        "n02113023": "Pembroke, Pembroke Welsh corgi",
+        "n02113186": "Cardigan, Cardigan Welsh corgi",
+        "n02113624": "toy poodle",
+        "n02113712": "miniature poodle",
+        "n02113799": "standard poodle",
+        "n02113978": "Mexican hairless",
+        "n02114367": "timber wolf, grey wolf, gray wolf, Canis lupus",
+        "n02114548": "white wolf, Arctic wolf, Canis lupus tundrarum",
+        "n02114712": "red wolf, maned wolf, Canis rufus, Canis niger",
+        "n02114855": "coyote, prairie wolf, brush wolf, Canis latrans",
+        "n02115641": "dingo, warrigal, warragal, Canis dingo",
+        "n02115913": "dhole, Cuon alpinus",
+        "n02116738": "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus",
+        "n02117135": "hyena, hyaena",
+        "n02119022": "red fox, Vulpes vulpes",
+        "n02119789": "kit fox, Vulpes macrotis",
+        "n02120079": "Arctic fox, white fox, Alopex lagopus",
+        "n02120505": "grey fox, gray fox, Urocyon cinereoargenteus",
+        "n02123045": "tabby, tabby cat",
+        "n02123159": "tiger cat",
+        "n02123394": "Persian cat",
+        "n02123597": "Siamese cat, Siamese",
+        "n02124075": "Egyptian cat",
+        "n02125311": "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor",
+        "n02127052": "lynx, catamount",
+        "n02128385": "leopard, Panthera pardus",
+        "n02128757": "snow leopard, ounce, Panthera uncia",
+        "n02128925": "jaguar, panther, Panthera onca, Felis onca",
+        "n02129165": "lion, king of beasts, Panthera leo",
+        "n02129604": "tiger, Panthera tigris",
+        "n02130308": "cheetah, chetah, Acinonyx jubatus",
+        "n02132136": "brown bear, bruin, Ursus arctos",
+        "n02133161": "American black bear, black bear, Ursus americanus, Euarctos americanus",
+        "n02134084": "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus",
+        "n02134418": "sloth bear, Melursus ursinus, Ursus ursinus",
+        "n02137549": "mongoose",
+        "n02138441": "meerkat, mierkat",
+        "n02165105": "tiger beetle",
+        "n02165456": "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle",
+        "n02167151": "ground beetle, carabid beetle",
+        "n02168699": "long-horned beetle, longicorn, longicorn beetle",
+        "n02169497": "leaf beetle, chrysomelid",
+        "n02172182": "dung beetle",
+        "n02174001": "rhinoceros beetle",
+        "n02177972": "weevil",
+        "n02190166": "fly",
+        "n02206856": "bee",
+        "n02219486": "ant, emmet, pismire",
+        "n02226429": "grasshopper, hopper",
+        "n02229544": "cricket",
+        "n02231487": "walking stick, walkingstick, stick insect",
+        "n02233338": "cockroach, roach",
+        "n02236044": "mantis, mantid",
+        "n02256656": "cicada, cicala",
+        "n02259212": "leafhopper",
+        "n02264363": "lacewing, lacewing fly",
+        "n02268443": "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk",
+        "n02268853": "damselfly",
+        "n02276258": "admiral",
+        "n02277742": "ringlet, ringlet butterfly",
+        "n02279972": "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus",
+        "n02280649": "cabbage butterfly",
+        "n02281406": "sulphur butterfly, sulfur butterfly",
+        "n02281787": "lycaenid, lycaenid butterfly",
+        "n02317335": "starfish, sea star",
+        "n02319095": "sea urchin",
+        "n02321529": "sea cucumber, holothurian",
+        "n02325366": "wood rabbit, cottontail, cottontail rabbit",
+        "n02326432": "hare",
+        "n02328150": "Angora, Angora rabbit",
+        "n02342885": "hamster",
+        "n02346627": "porcupine, hedgehog",
+        "n02356798": "fox squirrel, eastern fox squirrel, Sciurus niger",
+        "n02361337": "marmot",
+        "n02363005": "beaver",
+        "n02364673": "guinea pig, Cavia cobaya",
+        "n02389026": "sorrel",
+        "n02391049": "zebra",
+        "n02395406": "hog, pig, grunter, squealer, Sus scrofa",
+        "n02396427": "wild boar, boar, Sus scrofa",
+        "n02397096": "warthog",
+        "n02398521": "hippopotamus, hippo, river horse, Hippopotamus amphibius",
+        "n02403003": "ox",
+        "n02408429": "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis",
+        "n02410509": "bison",
+        "n02412080": "ram, tup",
+        "n02415577": "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis",
+        "n02417914": "ibex, Capra ibex",
+        "n02422106": "hartebeest",
+        "n02422699": "impala, Aepyceros melampus",
+        "n02423022": "gazelle",
+        "n02437312": "Arabian camel, dromedary, Camelus dromedarius",
+        "n02437616": "llama",
+        "n02441942": "weasel",
+        "n02442845": "mink",
+        "n02443114": "polecat, fitch, foulmart, foumart, Mustela putorius",
+        "n02443484": "black-footed ferret, ferret, Mustela nigripes",
+        "n02444819": "otter",
+        "n02445715": "skunk, polecat, wood pussy",
+        "n02447366": "badger",
+        "n02454379": "armadillo",
+        "n02457408": "three-toed sloth, ai, Bradypus tridactylus",
+        "n02480495": "orangutan, orang, orangutang, Pongo pygmaeus",
+        "n02480855": "gorilla, Gorilla gorilla",
+        "n02481823": "chimpanzee, chimp, Pan troglodytes",
+        "n02483362": "gibbon, Hylobates lar",
+        "n02483708": "siamang, Hylobates syndactylus, Symphalangus syndactylus",
+        "n02484975": "guenon, guenon monkey",
+        "n02486261": "patas, hussar monkey, Erythrocebus patas",
+        "n02486410": "baboon",
+        "n02487347": "macaque",
+        "n02488291": "langur",
+        "n02488702": "colobus, colobus monkey",
+        "n02489166": "proboscis monkey, Nasalis larvatus",
+        "n02490219": "marmoset",
+        "n02492035": "capuchin, ringtail, Cebus capucinus",
+        "n02492660": "howler monkey, howler",
+        "n02493509": "titi, titi monkey",
+        "n02493793": "spider monkey, Ateles geoffroyi",
+        "n02494079": "squirrel monkey, Saimiri sciureus",
+        "n02497673": "Madagascar cat, ring-tailed lemur, Lemur catta",
+        "n02500267": "indri, indris, Indri indri, Indri brevicaudatus",
+        "n02504013": "Indian elephant, Elephas maximus",
+        "n02504458": "African elephant, Loxodonta africana",
+        "n02509815": "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens",
+        "n02510455": "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca",
+        "n02514041": "barracouta, snoek",
+        "n02526121": "eel",
+        "n02536864": "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch",
+        "n02606052": "rock beauty, Holocanthus tricolor",
+        "n02607072": "anemone fish",
+        "n02640242": "sturgeon",
+        "n02641379": "gar, garfish, garpike, billfish, Lepisosteus osseus",
+        "n02643566": "lionfish",
+        "n02655020": "puffer, pufferfish, blowfish, globefish",
+        "n02666196": "abacus",
+        "n02667093": "abaya",
+        "n02669723": "academic gown, academic robe, judge's robe",
+        "n02672831": "accordion, piano accordion, squeeze box",
+        "n02676566": "acoustic guitar",
+        "n02687172": "aircraft carrier, carrier, flattop, attack aircraft carrier",
+        "n02690373": "airliner",
+        "n02692877": "airship, dirigible",
+        "n02699494": "altar",
+        "n02701002": "ambulance",
+        "n02704792": "amphibian, amphibious vehicle",
+        "n02708093": "analog clock",
+        "n02727426": "apiary, bee house",
+        "n02730930": "apron",
+        "n02747177": "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin",
+        "n02749479": "assault rifle, assault gun",
+        "n02769748": "backpack, back pack, knapsack, packsack, rucksack, haversack",
+        "n02776631": "bakery, bakeshop, bakehouse",
+        "n02777292": "balance beam, beam",
+        "n02782093": "balloon",
+        "n02783161": "ballpoint, ballpoint pen, ballpen, Biro",
+        "n02786058": "Band Aid",
+        "n02787622": "banjo",
+        "n02788148": "bannister, banister, balustrade, balusters, handrail",
+        "n02790996": "barbell",
+        "n02791124": "barber chair",
+        "n02791270": "barbershop",
+        "n02793495": "barn",
+        "n02794156": "barometer",
+        "n02795169": "barrel, cask",
+        "n02797295": "barrow, garden cart, lawn cart, wheelbarrow",
+        "n02799071": "baseball",
+        "n02802426": "basketball",
+        "n02804414": "bassinet",
+        "n02804610": "bassoon",
+        "n02807133": "bathing cap, swimming cap",
+        "n02808304": "bath towel",
+        "n02808440": "bathtub, bathing tub, bath, tub",
+        "n02814533": "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon",
+        "n02814860": "beacon, lighthouse, beacon light, pharos",
+        "n02815834": "beaker",
+        "n02817516": "bearskin, busby, shako",
+        "n02823428": "beer bottle",
+        "n02823750": "beer glass",
+        "n02825657": "bell cote, bell cot",
+        "n02834397": "bib",
+        "n02835271": "bicycle-built-for-two, tandem bicycle, tandem",
+        "n02837789": "bikini, two-piece",
+        "n02840245": "binder, ring-binder",
+        "n02841315": "binoculars, field glasses, opera glasses",
+        "n02843684": "birdhouse",
+        "n02859443": "boathouse",
+        "n02860847": "bobsled, bobsleigh, bob",
+        "n02865351": "bolo tie, bolo, bola tie, bola",
+        "n02869837": "bonnet, poke bonnet",
+        "n02870880": "bookcase",
+        "n02871525": "bookshop, bookstore, bookstall",
+        "n02877765": "bottlecap",
+        "n02879718": "bow",
+        "n02883205": "bow tie, bow-tie, bowtie",
+        "n02892201": "brass, memorial tablet, plaque",
+        "n02892767": "brassiere, bra, bandeau",
+        "n02894605": "breakwater, groin, groyne, mole, bulwark, seawall, jetty",
+        "n02895154": "breastplate, aegis, egis",
+        "n02906734": "broom",
+        "n02909870": "bucket, pail",
+        "n02910353": "buckle",
+        "n02916936": "bulletproof vest",
+        "n02917067": "bullet train, bullet",
+        "n02927161": "butcher shop, meat market",
+        "n02930766": "cab, hack, taxi, taxicab",
+        "n02939185": "caldron, cauldron",
+        "n02948072": "candle, taper, wax light",
+        "n02950826": "cannon",
+        "n02951358": "canoe",
+        "n02951585": "can opener, tin opener",
+        "n02963159": "cardigan",
+        "n02965783": "car mirror",
+        "n02966193": "carousel, carrousel, merry-go-round, roundabout, whirligig",
+        "n02966687": "carpenter's kit, tool kit",
+        "n02971356": "carton",
+        "n02974003": "car wheel",
+        "n02977058": "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM",
+        "n02978881": "cassette",
+        "n02979186": "cassette player",
+        "n02980441": "castle",
+        "n02981792": "catamaran",
+        "n02988304": "CD player",
+        "n02992211": "cello, violoncello",
+        "n02992529": "cellular telephone, cellular phone, cellphone, cell, mobile phone",
+        "n02999410": "chain",
+        "n03000134": "chainlink fence",
+        "n03000247": "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour",
+        "n03000684": "chain saw, chainsaw",
+        "n03014705": "chest",
+        "n03016953": "chiffonier, commode",
+        "n03017168": "chime, bell, gong",
+        "n03018349": "china cabinet, china closet",
+        "n03026506": "Christmas stocking",
+        "n03028079": "church, church building",
+        "n03032252": "cinema, movie theater, movie theatre, movie house, picture palace",
+        "n03041632": "cleaver, meat cleaver, chopper",
+        "n03042490": "cliff dwelling",
+        "n03045698": "cloak",
+        "n03047690": "clog, geta, patten, sabot",
+        "n03062245": "cocktail shaker",
+        "n03063599": "coffee mug",
+        "n03063689": "coffeepot",
+        "n03065424": "coil, spiral, volute, whorl, helix",
+        "n03075370": "combination lock",
+        "n03085013": "computer keyboard, keypad",
+        "n03089624": "confectionery, confectionary, candy store",
+        "n03095699": "container ship, containership, container vessel",
+        "n03100240": "convertible",
+        "n03109150": "corkscrew, bottle screw",
+        "n03110669": "cornet, horn, trumpet, trump",
+        "n03124043": "cowboy boot",
+        "n03124170": "cowboy hat, ten-gallon hat",
+        "n03125729": "cradle",
+        "n03126707": "crane2",
+        "n03127747": "crash helmet",
+        "n03127925": "crate",
+        "n03131574": "crib, cot",
+        "n03133878": "Crock Pot",
+        "n03134739": "croquet ball",
+        "n03141823": "crutch",
+        "n03146219": "cuirass",
+        "n03160309": "dam, dike, dyke",
+        "n03179701": "desk",
+        "n03180011": "desktop computer",
+        "n03187595": "dial telephone, dial phone",
+        "n03188531": "diaper, nappy, napkin",
+        "n03196217": "digital clock",
+        "n03197337": "digital watch",
+        "n03201208": "dining table, board",
+        "n03207743": "dishrag, dishcloth",
+        "n03207941": "dishwasher, dish washer, dishwashing machine",
+        "n03208938": "disk brake, disc brake",
+        "n03216828": "dock, dockage, docking facility",
+        "n03218198": "dogsled, dog sled, dog sleigh",
+        "n03220513": "dome",
+        "n03223299": "doormat, welcome mat",
+        "n03240683": "drilling platform, offshore rig",
+        "n03249569": "drum, membranophone, tympan",
+        "n03250847": "drumstick",
+        "n03255030": "dumbbell",
+        "n03259280": "Dutch oven",
+        "n03271574": "electric fan, blower",
+        "n03272010": "electric guitar",
+        "n03272562": "electric locomotive",
+        "n03290653": "entertainment center",
+        "n03291819": "envelope",
+        "n03297495": "espresso maker",
+        "n03314780": "face powder",
+        "n03325584": "feather boa, boa",
+        "n03337140": "file, file cabinet, filing cabinet",
+        "n03344393": "fireboat",
+        "n03345487": "fire engine, fire truck",
+        "n03347037": "fire screen, fireguard",
+        "n03355925": "flagpole, flagstaff",
+        "n03372029": "flute, transverse flute",
+        "n03376595": "folding chair",
+        "n03379051": "football helmet",
+        "n03384352": "forklift",
+        "n03388043": "fountain",
+        "n03388183": "fountain pen",
+        "n03388549": "four-poster",
+        "n03393912": "freight car",
+        "n03394916": "French horn, horn",
+        "n03400231": "frying pan, frypan, skillet",
+        "n03404251": "fur coat",
+        "n03417042": "garbage truck, dustcart",
+        "n03424325": "gasmask, respirator, gas helmet",
+        "n03425413": "gas pump, gasoline pump, petrol pump, island dispenser",
+        "n03443371": "goblet",
+        "n03444034": "go-kart",
+        "n03445777": "golf ball",
+        "n03445924": "golfcart, golf cart",
+        "n03447447": "gondola",
+        "n03447721": "gong, tam-tam",
+        "n03450230": "gown",
+        "n03452741": "grand piano, grand",
+        "n03457902": "greenhouse, nursery, glasshouse",
+        "n03459775": "grille, radiator grille",
+        "n03461385": "grocery store, grocery, food market, market",
+        "n03467068": "guillotine",
+        "n03476684": "hair slide",
+        "n03476991": "hair spray",
+        "n03478589": "half track",
+        "n03481172": "hammer",
+        "n03482405": "hamper",
+        "n03483316": "hand blower, blow dryer, blow drier, hair dryer, hair drier",
+        "n03485407": "hand-held computer, hand-held microcomputer",
+        "n03485794": "handkerchief, hankie, hanky, hankey",
+        "n03492542": "hard disc, hard disk, fixed disk",
+        "n03494278": "harmonica, mouth organ, harp, mouth harp",
+        "n03495258": "harp",
+        "n03496892": "harvester, reaper",
+        "n03498962": "hatchet",
+        "n03527444": "holster",
+        "n03529860": "home theater, home theatre",
+        "n03530642": "honeycomb",
+        "n03532672": "hook, claw",
+        "n03534580": "hoopskirt, crinoline",
+        "n03535780": "horizontal bar, high bar",
+        "n03538406": "horse cart, horse-cart",
+        "n03544143": "hourglass",
+        "n03584254": "iPod",
+        "n03584829": "iron, smoothing iron",
+        "n03590841": "jack-o'-lantern",
+        "n03594734": "jean, blue jean, denim",
+        "n03594945": "jeep, landrover",
+        "n03595614": "jersey, T-shirt, tee shirt",
+        "n03598930": "jigsaw puzzle",
+        "n03599486": "jinrikisha, ricksha, rickshaw",
+        "n03602883": "joystick",
+        "n03617480": "kimono",
+        "n03623198": "knee pad",
+        "n03627232": "knot",
+        "n03630383": "lab coat, laboratory coat",
+        "n03633091": "ladle",
+        "n03637318": "lampshade, lamp shade",
+        "n03642806": "laptop, laptop computer",
+        "n03649909": "lawn mower, mower",
+        "n03657121": "lens cap, lens cover",
+        "n03658185": "letter opener, paper knife, paperknife",
+        "n03661043": "library",
+        "n03662601": "lifeboat",
+        "n03666591": "lighter, light, igniter, ignitor",
+        "n03670208": "limousine, limo",
+        "n03673027": "liner, ocean liner",
+        "n03676483": "lipstick, lip rouge",
+        "n03680355": "Loafer",
+        "n03690938": "lotion",
+        "n03691459": "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system",
+        "n03692522": "loupe, jeweler's loupe",
+        "n03697007": "lumbermill, sawmill",
+        "n03706229": "magnetic compass",
+        "n03709823": "mailbag, postbag",
+        "n03710193": "mailbox, letter box",
+        "n03710637": "maillot",
+        "n03710721": "maillot, tank suit",
+        "n03717622": "manhole cover",
+        "n03720891": "maraca",
+        "n03721384": "marimba, xylophone",
+        "n03724870": "mask",
+        "n03729826": "matchstick",
+        "n03733131": "maypole",
+        "n03733281": "maze, labyrinth",
+        "n03733805": "measuring cup",
+        "n03742115": "medicine chest, medicine cabinet",
+        "n03743016": "megalith, megalithic structure",
+        "n03759954": "microphone, mike",
+        "n03761084": "microwave, microwave oven",
+        "n03763968": "military uniform",
+        "n03764736": "milk can",
+        "n03769881": "minibus",
+        "n03770439": "miniskirt, mini",
+        "n03770679": "minivan",
+        "n03773504": "missile",
+        "n03775071": "mitten",
+        "n03775546": "mixing bowl",
+        "n03776460": "mobile home, manufactured home",
+        "n03777568": "Model T",
+        "n03777754": "modem",
+        "n03781244": "monastery",
+        "n03782006": "monitor",
+        "n03785016": "moped",
+        "n03786901": "mortar",
+        "n03787032": "mortarboard",
+        "n03788195": "mosque",
+        "n03788365": "mosquito net",
+        "n03791053": "motor scooter, scooter",
+        "n03792782": "mountain bike, all-terrain bike, off-roader",
+        "n03792972": "mountain tent",
+        "n03793489": "mouse, computer mouse",
+        "n03794056": "mousetrap",
+        "n03796401": "moving van",
+        "n03803284": "muzzle",
+        "n03804744": "nail",
+        "n03814639": "neck brace",
+        "n03814906": "necklace",
+        "n03825788": "nipple",
+        "n03832673": "notebook, notebook computer",
+        "n03837869": "obelisk",
+        "n03838899": "oboe, hautboy, hautbois",
+        "n03840681": "ocarina, sweet potato",
+        "n03841143": "odometer, hodometer, mileometer, milometer",
+        "n03843555": "oil filter",
+        "n03854065": "organ, pipe organ",
+        "n03857828": "oscilloscope, scope, cathode-ray oscilloscope, CRO",
+        "n03866082": "overskirt",
+        "n03868242": "oxcart",
+        "n03868863": "oxygen mask",
+        "n03871628": "packet",
+        "n03873416": "paddle, boat paddle",
+        "n03874293": "paddlewheel, paddle wheel",
+        "n03874599": "padlock",
+        "n03876231": "paintbrush",
+        "n03877472": "pajama, pyjama, pj's, jammies",
+        "n03877845": "palace",
+        "n03884397": "panpipe, pandean pipe, syrinx",
+        "n03887697": "paper towel",
+        "n03888257": "parachute, chute",
+        "n03888605": "parallel bars, bars",
+        "n03891251": "park bench",
+        "n03891332": "parking meter",
+        "n03895866": "passenger car, coach, carriage",
+        "n03899768": "patio, terrace",
+        "n03902125": "pay-phone, pay-station",
+        "n03903868": "pedestal, plinth, footstall",
+        "n03908618": "pencil box, pencil case",
+        "n03908714": "pencil sharpener",
+        "n03916031": "perfume, essence",
+        "n03920288": "Petri dish",
+        "n03924679": "photocopier",
+        "n03929660": "pick, plectrum, plectron",
+        "n03929855": "pickelhaube",
+        "n03930313": "picket fence, paling",
+        "n03930630": "pickup, pickup truck",
+        "n03933933": "pier",
+        "n03935335": "piggy bank, penny bank",
+        "n03937543": "pill bottle",
+        "n03938244": "pillow",
+        "n03942813": "ping-pong ball",
+        "n03944341": "pinwheel",
+        "n03947888": "pirate, pirate ship",
+        "n03950228": "pitcher, ewer",
+        "n03954731": "plane, carpenter's plane, woodworking plane",
+        "n03956157": "planetarium",
+        "n03958227": "plastic bag",
+        "n03961711": "plate rack",
+        "n03967562": "plow, plough",
+        "n03970156": "plunger, plumber's helper",
+        "n03976467": "Polaroid camera, Polaroid Land camera",
+        "n03976657": "pole",
+        "n03977966": "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria",
+        "n03980874": "poncho",
+        "n03982430": "pool table, billiard table, snooker table",
+        "n03983396": "pop bottle, soda bottle",
+        "n03991062": "pot, flowerpot",
+        "n03992509": "potter's wheel",
+        "n03995372": "power drill",
+        "n03998194": "prayer rug, prayer mat",
+        "n04004767": "printer",
+        "n04005630": "prison, prison house",
+        "n04008634": "projectile, missile",
+        "n04009552": "projector",
+        "n04019541": "puck, hockey puck",
+        "n04023962": "punching bag, punch bag, punching ball, punchball",
+        "n04026417": "purse",
+        "n04033901": "quill, quill pen",
+        "n04033995": "quilt, comforter, comfort, puff",
+        "n04037443": "racer, race car, racing car",
+        "n04039381": "racket, racquet",
+        "n04040759": "radiator",
+        "n04041544": "radio, wireless",
+        "n04044716": "radio telescope, radio reflector",
+        "n04049303": "rain barrel",
+        "n04065272": "recreational vehicle, RV, R.V.",
+        "n04067472": "reel",
+        "n04069434": "reflex camera",
+        "n04070727": "refrigerator, icebox",
+        "n04074963": "remote control, remote",
+        "n04081281": "restaurant, eating house, eating place, eatery",
+        "n04086273": "revolver, six-gun, six-shooter",
+        "n04090263": "rifle",
+        "n04099969": "rocking chair, rocker",
+        "n04111531": "rotisserie",
+        "n04116512": "rubber eraser, rubber, pencil eraser",
+        "n04118538": "rugby ball",
+        "n04118776": "rule, ruler",
+        "n04120489": "running shoe",
+        "n04125021": "safe",
+        "n04127249": "safety pin",
+        "n04131690": "saltshaker, salt shaker",
+        "n04133789": "sandal",
+        "n04136333": "sarong",
+        "n04141076": "sax, saxophone",
+        "n04141327": "scabbard",
+        "n04141975": "scale, weighing machine",
+        "n04146614": "school bus",
+        "n04147183": "schooner",
+        "n04149813": "scoreboard",
+        "n04152593": "screen, CRT screen",
+        "n04153751": "screw",
+        "n04154565": "screwdriver",
+        "n04162706": "seat belt, seatbelt",
+        "n04179913": "sewing machine",
+        "n04192698": "shield, buckler",
+        "n04200800": "shoe shop, shoe-shop, shoe store",
+        "n04201297": "shoji",
+        "n04204238": "shopping basket",
+        "n04204347": "shopping cart",
+        "n04208210": "shovel",
+        "n04209133": "shower cap",
+        "n04209239": "shower curtain",
+        "n04228054": "ski",
+        "n04229816": "ski mask",
+        "n04235860": "sleeping bag",
+        "n04238763": "slide rule, slipstick",
+        "n04239074": "sliding door",
+        "n04243546": "slot, one-armed bandit",
+        "n04251144": "snorkel",
+        "n04252077": "snowmobile",
+        "n04252225": "snowplow, snowplough",
+        "n04254120": "soap dispenser",
+        "n04254680": "soccer ball",
+        "n04254777": "sock",
+        "n04258138": "solar dish, solar collector, solar furnace",
+        "n04259630": "sombrero",
+        "n04263257": "soup bowl",
+        "n04264628": "space bar",
+        "n04265275": "space heater",
+        "n04266014": "space shuttle",
+        "n04270147": "spatula",
+        "n04273569": "speedboat",
+        "n04275548": "spider web, spider's web",
+        "n04277352": "spindle",
+        "n04285008": "sports car, sport car",
+        "n04286575": "spotlight, spot",
+        "n04296562": "stage",
+        "n04310018": "steam locomotive",
+        "n04311004": "steel arch bridge",
+        "n04311174": "steel drum",
+        "n04317175": "stethoscope",
+        "n04325704": "stole",
+        "n04326547": "stone wall",
+        "n04328186": "stopwatch, stop watch",
+        "n04330267": "stove",
+        "n04332243": "strainer",
+        "n04335435": "streetcar, tram, tramcar, trolley, trolley car",
+        "n04336792": "stretcher",
+        "n04344873": "studio couch, day bed",
+        "n04346328": "stupa, tope",
+        "n04347754": "submarine, pigboat, sub, U-boat",
+        "n04350905": "suit, suit of clothes",
+        "n04355338": "sundial",
+        "n04355933": "sunglass",
+        "n04356056": "sunglasses, dark glasses, shades",
+        "n04357314": "sunscreen, sunblock, sun blocker",
+        "n04366367": "suspension bridge",
+        "n04367480": "swab, swob, mop",
+        "n04370456": "sweatshirt",
+        "n04371430": "swimming trunks, bathing trunks",
+        "n04371774": "swing",
+        "n04372370": "switch, electric switch, electrical switch",
+        "n04376876": "syringe",
+        "n04380533": "table lamp",
+        "n04389033": "tank, army tank, armored combat vehicle, armoured combat vehicle",
+        "n04392985": "tape player",
+        "n04398044": "teapot",
+        "n04399382": "teddy, teddy bear",
+        "n04404412": "television, television system",
+        "n04409515": "tennis ball",
+        "n04417672": "thatch, thatched roof",
+        "n04418357": "theater curtain, theatre curtain",
+        "n04423845": "thimble",
+        "n04428191": "thresher, thrasher, threshing machine",
+        "n04429376": "throne",
+        "n04435653": "tile roof",
+        "n04442312": "toaster",
+        "n04443257": "tobacco shop, tobacconist shop, tobacconist",
+        "n04447861": "toilet seat",
+        "n04456115": "torch",
+        "n04458633": "totem pole",
+        "n04461696": "tow truck, tow car, wrecker",
+        "n04462240": "toyshop",
+        "n04465501": "tractor",
+        "n04467665": "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi",
+        "n04476259": "tray",
+        "n04479046": "trench coat",
+        "n04482393": "tricycle, trike, velocipede",
+        "n04483307": "trimaran",
+        "n04485082": "tripod",
+        "n04486054": "triumphal arch",
+        "n04487081": "trolleybus, trolley coach, trackless trolley",
+        "n04487394": "trombone",
+        "n04493381": "tub, vat",
+        "n04501370": "turnstile",
+        "n04505470": "typewriter keyboard",
+        "n04507155": "umbrella",
+        "n04509417": "unicycle, monocycle",
+        "n04515003": "upright, upright piano",
+        "n04517823": "vacuum, vacuum cleaner",
+        "n04522168": "vase",
+        "n04523525": "vault",
+        "n04525038": "velvet",
+        "n04525305": "vending machine",
+        "n04532106": "vestment",
+        "n04532670": "viaduct",
+        "n04536866": "violin, fiddle",
+        "n04540053": "volleyball",
+        "n04542943": "waffle iron",
+        "n04548280": "wall clock",
+        "n04548362": "wallet, billfold, notecase, pocketbook",
+        "n04550184": "wardrobe, closet, press",
+        "n04552348": "warplane, military plane",
+        "n04553703": "washbasin, handbasin, washbowl, lavabo, wash-hand basin",
+        "n04554684": "washer, automatic washer, washing machine",
+        "n04557648": "water bottle",
+        "n04560804": "water jug",
+        "n04562935": "water tower",
+        "n04579145": "whiskey jug",
+        "n04579432": "whistle",
+        "n04584207": "wig",
+        "n04589890": "window screen",
+        "n04590129": "window shade",
+        "n04591157": "Windsor tie",
+        "n04591713": "wine bottle",
+        "n04592741": "wing",
+        "n04596742": "wok",
+        "n04597913": "wooden spoon",
+        "n04599235": "wool, woolen, woollen",
+        "n04604644": "worm fence, snake fence, snake-rail fence, Virginia fence",
+        "n04606251": "wreck",
+        "n04612504": "yawl",
+        "n04613696": "yurt",
+        "n06359193": "web site, website, internet site, site",
+        "n06596364": "comic book",
+        "n06785654": "crossword puzzle, crossword",
+        "n06794110": "street sign",
+        "n06874185": "traffic light, traffic signal, stoplight",
+        "n07248320": "book jacket, dust cover, dust jacket, dust wrapper",
+        "n07565083": "menu",
+        "n07579787": "plate",
+        "n07583066": "guacamole",
+        "n07584110": "consomme",
+        "n07590611": "hot pot, hotpot",
+        "n07613480": "trifle",
+        "n07614500": "ice cream, icecream",
+        "n07615774": "ice lolly, lolly, lollipop, popsicle",
+        "n07684084": "French loaf",
+        "n07693725": "bagel, beigel",
+        "n07695742": "pretzel",
+        "n07697313": "cheeseburger",
+        "n07697537": "hotdog, hot dog, red hot",
+        "n07711569": "mashed potato",
+        "n07714571": "head cabbage",
+        "n07714990": "broccoli",
+        "n07715103": "cauliflower",
+        "n07716358": "zucchini, courgette",
+        "n07716906": "spaghetti squash",
+        "n07717410": "acorn squash",
+        "n07717556": "butternut squash",
+        "n07718472": "cucumber, cuke",
+        "n07718747": "artichoke, globe artichoke",
+        "n07720875": "bell pepper",
+        "n07730033": "cardoon",
+        "n07734744": "mushroom",
+        "n07742313": "Granny Smith",
+        "n07745940": "strawberry",
+        "n07747607": "orange",
+        "n07749582": "lemon",
+        "n07753113": "fig",
+        "n07753275": "pineapple, ananas",
+        "n07753592": "banana",
+        "n07754684": "jackfruit, jak, jack",
+        "n07760859": "custard apple",
+        "n07768694": "pomegranate",
+        "n07802026": "hay",
+        "n07831146": "carbonara",
+        "n07836838": "chocolate sauce, chocolate syrup",
+        "n07860988": "dough",
+        "n07871810": "meat loaf, meatloaf",
+        "n07873807": "pizza, pizza pie",
+        "n07875152": "potpie",
+        "n07880968": "burrito",
+        "n07892512": "red wine",
+        "n07920052": "espresso",
+        "n07930864": "cup",
+        "n07932039": "eggnog",
+        "n09193705": "alp",
+        "n09229709": "bubble",
+        "n09246464": "cliff, drop, drop-off",
+        "n09256479": "coral reef",
+        "n09288635": "geyser",
+        "n09332890": "lakeside, lakeshore",
+        "n09399592": "promontory, headland, head, foreland",
+        "n09421951": "sandbar, sand bar",
+        "n09428293": "seashore, coast, seacoast, sea-coast",
+        "n09468604": "valley, vale",
+        "n09472597": "volcano",
+        "n09835506": "ballplayer, baseball player",
+        "n10148035": "groom, bridegroom",
+        "n10565667": "scuba diver",
+        "n11879895": "rapeseed",
+        "n11939491": "daisy",
+        "n12057211": "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum",
+        "n12144580": "corn",
+        "n12267677": "acorn",
+        "n12620546": "hip, rose hip, rosehip",
+        "n12768682": "buckeye, horse chestnut, conker",
+        "n12985857": "coral fungus",
+        "n12998815": "agaric",
+        "n13037406": "gyromitra",
+        "n13040303": "stinkhorn, carrion fungus",
+        "n13044778": "earthstar",
+        "n13052670": "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa",
+        "n13054560": "bolete",
+        "n13133613": "ear, spike, capitulum",
+        "n15075141": "toilet tissue, toilet paper, bathroom tissue",
+    }
+)
 _CITATION = """\
 @misc{nauen2025foraug,
     title={ForAug: Recombining Foregrounds and Backgrounds to Improve Vision Transformer Training with Bias Mitigation},
         mask_smoothing_sigma,
         rel_jut_out,
         orig_img_prob,
+        fg_in_nonant=None,
+        size_fact=1.0,
         **kwargs,
     ):
         """Create the ForNet recombination dataset.
             "max",
             "mean",
         ], f"Invalid fg_size_mode {fg_size_mode}"
+        assert fg_in_nonant is None or -1 <= fg_in_nonant < 9, f"fg_in_nonant={fg_in_nonant} not in [0, 8] or None"
         self.background_combination = background_combination
         self.fg_scale_jitter = fg_scale_jitter
         self.pruning_ratio = pruning_ratio
         self.epochs = 0
         self._epoch = 0
         self.cls_to_idx = {}
+        self.fg_in_nonant = fg_in_nonant
+        self.size_fact = size_fact
         bg_rat_indices = super()._getitem(0)["bg_rat_idx_file"]
         self.train = "train" in bg_rat_indices.split("/")[-1]
         bg_img = bg_item["bg"].convert("RGB")
         bg_size = bg_img.size
         bg_area = bg_size[0] * bg_size[1]
+        if self.fg_in_nonant is not None:
+            bg_area = bg_area / 9
         orig_fg_ratio = fg_item["fg/bg_area"]
         bg_fg_ratio = bg_item["fg/bg_area"]
                 goal_fg_ratio_upper * (1 + self.fg_scale_jitter),
             )
             / fg_size_factor
+            * self.size_fact
         )
         goal_shape_y = round(np.sqrt(bg_area * fg_scale * fg_img.size[1] / fg_img.size[0]))
         y_min = -self.rel_jut_out * fg_img.size[1]
         y_max = bg_size[1] - fg_img.size[1] * (1 - self.rel_jut_out)
+        if self.fg_in_nonant is not None and self.fg_in_nonant >= 0:
+            x_min = (self.fg_in_nonant % 3) * bg_size[0] / 3
+            x_max = ((self.fg_in_nonant % 3) + 1) * bg_size[0] / 3 - fg_img.size[0]
+            y_min = (self.fg_in_nonant // 3) * bg_size[1] / 3
+            y_max = ((self.fg_in_nonant // 3) + 1) * bg_size[1] / 3 - fg_img.size[1]
         if x_min > x_max:
             x_min = x_max = (x_min + x_max) / 2
         if y_min > y_max:
     "mask_smoothing_sigma",
     "rel_jut_out",
     "orig_img_prob",
+    "fg_in_nonant",
+    "size_fact",
 ]
         mask_smoothing_sigma,
         rel_jut_out,
         orig_img_prob,
+        fg_in_nonant=None,
+        size_fact=1.0,
         **kwargs,
     ):
         """BuilderConfig for ForNet.
         self.mask_smoothing_sigma = mask_smoothing_sigma
         self.rel_jut_out = rel_jut_out
         self.orig_img_prob = orig_img_prob
+        self.fg_in_nonant = fg_in_nonant
+        self.size_fact = size_fact
     def __str__(self):
         return f"ForNetConfig(name={self.name}, version={self.version}, data_dir={self.data_dir}, data_files={self.data_files}, description={self.description}, background_combination={self.background_combination}, fg_scale_jitter={self.fg_scale_jitter}, pruning_ratio={self.pruning_ratio}, fg_size_mode={self.fg_size_mode}, fg_bates_n={self.fg_bates_n}, mask_smoothing_sigma={self.mask_smoothing_sigma}, rel_jut_out={self.rel_jut_out}, orig_img_prob={self.orig_img_prob})"
             mask_smoothing_sigma=4.0,
             rel_jut_out=0.0,
             orig_img_prob=0.0,
+            fg_in_nonant=None,
+            size_fact=1.0,
         )
     ]
         )
     def _split_generators(self, dl_manager: datasets.DownloadManager):
+        # test if we have access to ILSVRC/imagenet-1k
+        _ = datasets.load_dataset("ILSVRC/imagenet-1k", split="train", trust_remote_code=True)
         urls_to_download = _CONST_URLS + _PATCH_URLS
         dl_paths = dl_manager.download(urls_to_download)
         )
         fingerprint = self._get_dataset_fingerprint(split)
         splitname = str(split)
         if splitname == "validation":
             mask_smoothing_sigma=self.config.mask_smoothing_sigma,
             rel_jut_out=self.config.rel_jut_out,
             orig_img_prob=self.config.orig_img_prob,
+            fg_in_nonant=self.config.fg_in_nonant,
+            size_fact=self.config.size_fact,
             **dataset_kwargs,
         )
 def _in_iterator(in_queue, split):
     if split == "val":
         split = "validation"
+    imagenet = datasets.load_dataset("ILSVRC/imagenet-1k", split=split, trust_remote_code=True)
     for idx, ex in enumerate(imagenet):
         in_queue.put((idx, ex["image"]))