AravindKumarRajendran commited on
Commit
eb03e62
·
1 Parent(s): 78d57af

app file fix

Browse files
Files changed (3) hide show
  1. app.py +194 -79
  2. classes.json +0 -1002
  3. classes.txt +1000 -0
app.py CHANGED
@@ -1,85 +1,200 @@
 
1
  import torch
2
  import torchvision.transforms as transforms
3
  from PIL import Image
4
- import json
5
- import gradio as gr
6
  from torchvision.models import resnet50
7
- from huggingface_hub import hf_hub_download
8
-
9
- def load_model(model_path):
10
- model = resnet50(pretrained=False) # Create an instance of the ResNet-50 model
11
- state_dict = torch.load(model_path, map_location='cpu') # Load the state dictionary
12
- model.load_state_dict(state_dict) # Load the state dictionary
13
- model.eval() # Set the model to evaluation mode
14
- return model
15
-
16
-
17
- def preprocess_image(image):
18
- preprocess = transforms.Compose([
19
- transforms.Resize(256),
20
- transforms.CenterCrop(224),
21
- transforms.ToTensor(),
22
- transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
23
- ])
24
-
25
- image = image.convert("RGB") # Ensure image is in RGB format
26
- image = preprocess(image) # Apply transformations
27
- image = image.unsqueeze(0) # Add batch dimension
28
- return image
29
-
30
-
31
- # Prediction function
32
- def predict(image):
33
- image_tensor = preprocess_image(image)
34
- with torch.no_grad():
35
- output = model(image_tensor)
36
- probabilities = torch.nn.functional.softmax(output, dim=1)
37
- top5_probabilities, top5_indices = probabilities.topk(5)
38
-
39
- results = {}
40
- for i in range(5):
41
- class_index = top5_indices[0][i].item()
42
- class_label = class_labels.get(str(class_index), "Unknown class")
43
- results[class_label] = top5_probabilities[0][i].item() # Store label and probability in a dictionary
44
- print("See the prediction result : ", results)
45
- return results # Return the results as a dictionary
46
-
47
-
48
- # Load class index mapping
49
- def load_class_labels(label_path):
50
- with open(label_path, 'r') as f:
51
- class_labels = json.load(f)
52
- return class_labels
53
-
54
-
55
- def load_model(model_path):
56
- model = resnet50() # Create an instance of the ResNet-50 model
57
- checkpoint = torch.load(model_path, map_location='cpu') # Load the checkpoint
58
-
59
- # Access the 'model_state_dict' key within the checkpoint
60
- state_dict = checkpoint['model_state_dict']
61
-
62
- # Remove "module." prefix if present (common when using DataParallel)
63
- if 'module.' in next(iter(state_dict.keys())):
64
- state_dict = {k.replace('module.', ''): v for k, v in state_dict.items()}
65
-
66
- model.load_state_dict(state_dict) # Load the state dictionary
67
- model.eval() # Set the model to evaluation mode
68
- return model
69
-
70
- model_path = "models/resnet_50.pth"
71
- label_path = 'classes.json' # Path to the class index mapping
72
- model = load_model(model_path)
73
- class_labels = load_class_labels(label_path)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
74
 
75
- # Create Gradio interface
76
- iface = gr.Interface(
77
- fn=predict,
78
- inputs=gr.Image(type="pil"),
79
- outputs=gr.Label(num_top_classes=5),
80
- title="Image Classification using ResNet 50 Model trained on Imagenet 1000 dataset",
81
- description="Upload an image to get the top-5 predictions."
82
- )
83
- # Launch the app
84
  if __name__ == "__main__":
85
- iface.launch()
 
 
 
 
 
 
 
 
 
 
1
+ import gradio as gr
2
  import torch
3
  import torchvision.transforms as transforms
4
  from PIL import Image
 
 
5
  from torchvision.models import resnet50
6
+ import os
7
+ import logging
8
+ from typing import Optional, Union
9
+ import numpy as np
10
+ from pathlib import Path
11
+
12
+ # Set up logging
13
+ logging.basicConfig(level=logging.INFO)
14
+ logger = logging.getLogger(__name__)
15
+
16
+ # Directory Configuration
17
+ BASE_DIR = Path(__file__).resolve().parent
18
+ MODELS_DIR = BASE_DIR / "models"
19
+ EXAMPLES_DIR = BASE_DIR / "examples"
20
+ STATIC_DIR = BASE_DIR / "static" / "uploaded"
21
+
22
+ # Ensure directories exist
23
+ STATIC_DIR.mkdir(parents=True, exist_ok=True)
24
+
25
+ # Global variables
26
+ MODEL_PATH = MODELS_DIR / "resnet_50.pth"
27
+ CLASSES_PATH = BASE_DIR / "classes.txt"
28
+ DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
29
+
30
+ def load_class_labels() -> Optional[list]:
31
+ """
32
+ Load class labels from the classes.txt file
33
+ """
34
+ try:
35
+ if not CLASSES_PATH.exists():
36
+ raise FileNotFoundError(f"Classes file not found at {CLASSES_PATH}")
37
+
38
+ with open(CLASSES_PATH, 'r') as f:
39
+ return [line.strip() for line in f.readlines()]
40
+ except Exception as e:
41
+ logger.error(f"Error loading class labels: {str(e)}")
42
+ return None
43
+
44
+ # Load class labels
45
+ CLASS_NAMES = load_class_labels()
46
+ if CLASS_NAMES is None:
47
+ raise RuntimeError("Failed to load class labels from classes.txt")
48
+
49
+ # Cache the model to avoid reloading for each prediction
50
+ model = None
51
+
52
+ def load_model() -> Optional[torch.nn.Module]:
53
+ """
54
+ Load the ResNet50 model with error handling
55
+ """
56
+ global model
57
+
58
+ try:
59
+ if model is not None:
60
+ return model
61
+
62
+ if not MODEL_PATH.exists():
63
+ raise FileNotFoundError(f"Model file not found at {MODEL_PATH}")
64
+
65
+ logger.info(f"Loading model on {DEVICE}")
66
+ model = resnet50(pretrained=False)
67
+ model.fc = torch.nn.Linear(model.fc.in_features, len(CLASS_NAMES))
68
+
69
+ # Load the model weights
70
+ state_dict = torch.load(MODEL_PATH, map_location=DEVICE)
71
+
72
+ if 'state_dict' in state_dict:
73
+ state_dict = state_dict['state_dict']
74
+
75
+ model.load_state_dict(state_dict)
76
+ model.to(DEVICE)
77
+ model.eval()
78
+
79
+ logger.info("Model loaded successfully")
80
+ return model
81
+
82
+ except Exception as e:
83
+ logger.error(f"Error loading model: {str(e)}")
84
+ return None
85
+
86
+ def preprocess_image(image: Union[np.ndarray, Image.Image]) -> Optional[torch.Tensor]:
87
+ """
88
+ Preprocess the input image with error handling
89
+ """
90
+ try:
91
+ if isinstance(image, np.ndarray):
92
+ image = Image.fromarray(image)
93
+
94
+ transform = transforms.Compose([
95
+ transforms.Resize((224, 224)),
96
+ transforms.ToTensor(),
97
+ transforms.Normalize(
98
+ mean=[0.485, 0.456, 0.406],
99
+ std=[0.229, 0.224, 0.225]
100
+ )
101
+ ])
102
+
103
+ return transform(image).unsqueeze(0).to(DEVICE)
104
+
105
+ except Exception as e:
106
+ logger.error(f"Error preprocessing image: {str(e)}")
107
+ return None
108
+
109
+ def predict(image: Union[np.ndarray, None]) -> tuple[str, dict]:
110
+ """
111
+ Make predictions on the input image with comprehensive error handling
112
+ Returns the predicted class and top 5 confidence scores
113
+ """
114
+ try:
115
+ if image is None:
116
+ return "Error: No image provided", {}
117
+
118
+ model = load_model()
119
+ if model is None:
120
+ return "Error: Failed to load model", {}
121
+
122
+ # Ensure model is in eval mode
123
+ model.eval()
124
+
125
+ input_tensor = preprocess_image(image)
126
+ if input_tensor is None:
127
+ return "Error: Failed to preprocess image", {}
128
+
129
+ with torch.no_grad():
130
+ # Move input to same device as model
131
+ input_tensor = input_tensor.to(DEVICE)
132
+ output = model(input_tensor)
133
+ # Apply softmax to get probabilities
134
+ probabilities = torch.nn.functional.softmax(output[0], dim=0)
135
+
136
+ # Get predictions and confidences
137
+ top_5_probs, top_5_indices = torch.topk(probabilities, k=5)
138
+
139
+ # Convert to percentages and round to 2 decimal places
140
+ confidences = {
141
+ CLASS_NAMES[idx.item()]: float(round(prob.item() * 100, 2))
142
+ for prob, idx in zip(top_5_probs, top_5_indices)
143
+ }
144
+
145
+ # Get top prediction
146
+ predicted_class = CLASS_NAMES[top_5_indices[0].item()]
147
+
148
+ return predicted_class, confidences
149
+
150
+ except Exception as e:
151
+ logger.error(f"Prediction error: {str(e)}")
152
+ return f"Error during prediction: {str(e)}", {}
153
+
154
+ def get_example_list() -> list:
155
+ """
156
+ Get list of example images from the examples directory
157
+ """
158
+ try:
159
+ examples = []
160
+ for ext in ['.jpg', '.jpeg', '.png']:
161
+ examples.extend(list(EXAMPLES_DIR.glob(f'*{ext}')))
162
+ return [[str(ex)] for ex in sorted(examples)]
163
+ except Exception as e:
164
+ logger.error(f"Error loading examples: {str(e)}")
165
+ return []
166
+
167
+ # Create Gradio interface with error handling
168
+ try:
169
+ iface = gr.Interface(
170
+ fn=predict,
171
+ inputs=gr.Image(type="numpy", label="Upload Image"),
172
+ outputs=[
173
+ gr.Label(label="Predicted Class", num_top_classes=1),
174
+ gr.Label(label="Top 5 Predictions", num_top_classes=5)
175
+ ],
176
+ title="Image Classification with ResNet50",
177
+ description=(
178
+ "Upload an image to classify:\n"
179
+ "The model will predict the class and show top 5 confidence scores."
180
+ ),
181
+ examples=get_example_list(),
182
+ cache_examples=True,
183
+ theme=gr.themes.Base()
184
+ )
185
+
186
+ except Exception as e:
187
+ logger.error(f"Error creating Gradio interface: {str(e)}")
188
+ raise
189
 
 
 
 
 
 
 
 
 
 
190
  if __name__ == "__main__":
191
+ try:
192
+ load_model() # Pre-load the model
193
+ iface.launch(
194
+ share=False,
195
+ server_name="0.0.0.0",
196
+ server_port=7860,
197
+ debug=False
198
+ )
199
+ except Exception as e:
200
+ logger.error(f"Error launching application: {str(e)}")
classes.json DELETED
@@ -1,1002 +0,0 @@
1
- {
2
- "0": "tench, Tinca tinca",
3
- "1": "goldfish, Carassius auratus",
4
- "2": "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias",
5
- "3": "tiger shark, Galeocerdo cuvieri",
6
- "4": "hammerhead, hammerhead shark",
7
- "5": "electric ray, crampfish, numbfish, torpedo",
8
- "6": "stingray",
9
- "7": "cock",
10
- "8": "hen",
11
- "9": "ostrich, Struthio camelus",
12
- "10": "brambling, Fringilla montifringilla",
13
- "11": "goldfinch, Carduelis carduelis",
14
- "12": "house finch, linnet, Carpodacus mexicanus",
15
- "13": "junco, snowbird",
16
- "14": "indigo bunting, indigo finch, indigo bird, Passerina cyanea",
17
- "15": "robin, American robin, Turdus migratorius",
18
- "16": "bulbul",
19
- "17": "jay",
20
- "18": "magpie",
21
- "19": "chickadee",
22
- "20": "water ouzel, dipper",
23
- "21": "kite",
24
- "22": "bald eagle, American eagle, Haliaeetus leucocephalus",
25
- "23": "vulture",
26
- "24": "great grey owl, great gray owl, Strix nebulosa",
27
- "25": "European fire salamander, Salamandra salamandra",
28
- "26": "common newt, Triturus vulgaris",
29
- "27": "eft",
30
- "28": "spotted salamander, Ambystoma maculatum",
31
- "29": "axolotl, mud puppy, Ambystoma mexicanum",
32
- "30": "bullfrog, Rana catesbeiana",
33
- "31": "tree frog, tree-frog",
34
- "32": "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui",
35
- "33": "loggerhead, loggerhead turtle, Caretta caretta",
36
- "34": "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea",
37
- "35": "mud turtle",
38
- "36": "terrapin",
39
- "37": "box turtle, box tortoise",
40
- "38": "banded gecko",
41
- "39": "common iguana, iguana, Iguana iguana",
42
- "40": "American chameleon, anole, Anolis carolinensis",
43
- "41": "whiptail, whiptail lizard",
44
- "42": "agama",
45
- "43": "frilled lizard, Chlamydosaurus kingi",
46
- "44": "alligator lizard",
47
- "45": "Gila monster, Heloderma suspectum",
48
- "46": "green lizard, Lacerta viridis",
49
- "47": "African chameleon, Chamaeleo chamaeleon",
50
- "48": "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis",
51
- "49": "African crocodile, Nile crocodile, Crocodylus niloticus",
52
- "50": "American alligator, Alligator mississipiensis",
53
- "51": "triceratops",
54
- "52": "thunder snake, worm snake, Carphophis amoenus",
55
- "53": "ringneck snake, ring-necked snake, ring snake",
56
- "54": "hognose snake, puff adder, sand viper",
57
- "55": "green snake, grass snake",
58
- "56": "king snake, kingsnake",
59
- "57": "garter snake, grass snake",
60
- "58": "water snake",
61
- "59": "vine snake",
62
- "60": "night snake, Hypsiglena torquata",
63
- "61": "boa constrictor, Constrictor constrictor",
64
- "62": "rock python, rock snake, Python sebae",
65
- "63": "Indian cobra, Naja naja",
66
- "64": "green mamba",
67
- "65": "sea snake",
68
- "66": "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus",
69
- "67": "diamondback, diamondback rattlesnake, Crotalus adamanteus",
70
- "68": "sidewinder, horned rattlesnake, Crotalus cerastes",
71
- "69": "trilobite",
72
- "70": "harvestman, daddy longlegs, Phalangium opilio",
73
- "71": "scorpion",
74
- "72": "black and gold garden spider, Argiope aurantia",
75
- "73": "barn spider, Araneus cavaticus",
76
- "74": "garden spider, Aranea diademata",
77
- "75": "black widow, Latrodectus mactans",
78
- "76": "tarantula",
79
- "77": "wolf spider, hunting spider",
80
- "78": "tick",
81
- "79": "centipede",
82
- "80": "black grouse",
83
- "81": "ptarmigan",
84
- "82": "ruffed grouse, partridge, Bonasa umbellus",
85
- "83": "prairie chicken, prairie grouse, prairie fowl",
86
- "84": "peacock",
87
- "85": "quail",
88
- "86": "partridge",
89
- "87": "African grey, African gray, Psittacus erithacus",
90
- "88": "macaw",
91
- "89": "sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita",
92
- "90": "lorikeet",
93
- "91": "coucal",
94
- "92": "bee eater",
95
- "93": "hornbill",
96
- "94": "hummingbird",
97
- "95": "jacamar",
98
- "96": "toucan",
99
- "97": "drake",
100
- "98": "red-breasted merganser, Mergus serrator",
101
- "99": "goose",
102
- "100": "black swan, Cygnus atratus",
103
- "101": "tusker",
104
- "102": "echidna, spiny anteater, anteater",
105
- "103": "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus",
106
- "104": "wallaby, brush kangaroo",
107
- "105": "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus",
108
- "106": "wombat",
109
- "107": "jellyfish",
110
- "108": "sea anemone, anemone",
111
- "109": "brain coral",
112
- "110": "flatworm, platyhelminth",
113
- "111": "nematode, nematode worm, roundworm",
114
- "112": "conch",
115
- "113": "snail",
116
- "114": "slug",
117
- "115": "sea slug, nudibranch",
118
- "116": "chiton, coat-of-mail shell, sea cradle, polyplacophore",
119
- "117": "chambered nautilus, pearly nautilus, nautilus",
120
- "118": "Dungeness crab, Cancer magister",
121
- "119": "rock crab, Cancer irroratus",
122
- "120": "fiddler crab",
123
- "121": "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica",
124
- "122": "American lobster, Northern lobster, Maine lobster, Homarus americanus",
125
- "123": "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish",
126
- "124": "crayfish, crawfish, crawdad, crawdaddy",
127
- "125": "hermit crab",
128
- "126": "isopod",
129
- "127": "white stork, Ciconia ciconia",
130
- "128": "black stork, Ciconia nigra",
131
- "129": "spoonbill",
132
- "130": "flamingo",
133
- "131": "little blue heron, Egretta caerulea",
134
- "132": "American egret, great white heron, Egretta albus",
135
- "133": "bittern",
136
- "134": "crane",
137
- "135": "limpkin, Aramus pictus",
138
- "136": "European gallinule, Porphyrio porphyrio",
139
- "137": "American coot, marsh hen, mud hen, water hen, Fulica americana",
140
- "138": "bustard",
141
- "139": "ruddy turnstone, Arenaria interpres",
142
- "140": "red-backed sandpiper, dunlin, Erolia alpina",
143
- "141": "redshank, Tringa totanus",
144
- "142": "dowitcher",
145
- "143": "oystercatcher, oyster catcher",
146
- "144": "pelican",
147
- "145": "king penguin, Aptenodytes patagonica",
148
- "146": "albatross, mollymawk",
149
- "147": "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus",
150
- "148": "killer whale, killer, orca, grampus, sea wolf, Orcinus orca",
151
- "149": "dugong, Dugong dugon",
152
- "150": "sea lion",
153
- "151": "Chihuahua",
154
- "152": "Japanese spaniel",
155
- "153": "Maltese dog, Maltese terrier, Maltese",
156
- "154": "Pekinese, Pekingese, Peke",
157
- "155": "Shih-Tzu",
158
- "156": "Blenheim spaniel",
159
- "157": "papillon",
160
- "158": "toy terrier",
161
- "159": "Rhodesian ridgeback",
162
- "160": "Afghan hound, Afghan",
163
- "161": "basset, basset hound",
164
- "162": "beagle",
165
- "163": "bloodhound, sleuthhound",
166
- "164": "bluetick",
167
- "165": "black-and-tan coonhound",
168
- "166": "Walker hound, Walker foxhound",
169
- "167": "English foxhound",
170
- "168": "redbone",
171
- "169": "borzoi, Russian wolfhound",
172
- "170": "Irish wolfhound",
173
- "171": "Italian greyhound",
174
- "172": "whippet",
175
- "173": "Ibizan hound, Ibizan Podenco",
176
- "174": "Norwegian elkhound, elkhound",
177
- "175": "otterhound, otter hound",
178
- "176": "Saluki, gazelle hound",
179
- "177": "Scottish deerhound, deerhound",
180
- "178": "Weimaraner",
181
- "179": "Staffordshire bullterrier, Staffordshire bull terrier",
182
- "180": "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier",
183
- "181": "Bedlington terrier",
184
- "182": "Border terrier",
185
- "183": "Kerry blue terrier",
186
- "184": "Irish terrier",
187
- "185": "Norfolk terrier",
188
- "186": "Norwich terrier",
189
- "187": "Yorkshire terrier",
190
- "188": "wire-haired fox terrier",
191
- "189": "Lakeland terrier",
192
- "190": "Sealyham terrier, Sealyham",
193
- "191": "Airedale, Airedale terrier",
194
- "192": "cairn, cairn terrier",
195
- "193": "Australian terrier",
196
- "194": "Dandie Dinmont, Dandie Dinmont terrier",
197
- "195": "Boston bull, Boston terrier",
198
- "196": "miniature schnauzer",
199
- "197": "giant schnauzer",
200
- "198": "standard schnauzer",
201
- "199": "Scotch terrier, Scottish terrier, Scottie",
202
- "200": "Tibetan terrier, chrysanthemum dog",
203
- "201": "silky terrier, Sydney silky",
204
- "202": "soft-coated wheaten terrier",
205
- "203": "West Highland white terrier",
206
- "204": "Lhasa, Lhasa apso",
207
- "205": "flat-coated retriever",
208
- "206": "curly-coated retriever",
209
- "207": "golden retriever",
210
- "208": "Labrador retriever",
211
- "209": "Chesapeake Bay retriever",
212
- "210": "German short-haired pointer",
213
- "211": "vizsla, Hungarian pointer",
214
- "212": "English setter",
215
- "213": "Irish setter, red setter",
216
- "214": "Gordon setter",
217
- "215": "Brittany spaniel",
218
- "216": "clumber, clumber spaniel",
219
- "217": "English springer, English springer spaniel",
220
- "218": "Welsh springer spaniel",
221
- "219": "cocker spaniel, English cocker spaniel, cocker",
222
- "220": "Sussex spaniel",
223
- "221": "Irish water spaniel",
224
- "222": "kuvasz",
225
- "223": "schipperke",
226
- "224": "groenendael",
227
- "225": "malinois",
228
- "226": "briard",
229
- "227": "kelpie",
230
- "228": "komondor",
231
- "229": "Old English sheepdog, bobtail",
232
- "230": "Shetland sheepdog, Shetland sheep dog, Shetland",
233
- "231": "collie",
234
- "232": "Border collie",
235
- "233": "Bouvier des Flandres, Bouviers des Flandres",
236
- "234": "Rottweiler",
237
- "235": "German shepherd, German shepherd dog, German police dog, alsatian",
238
- "236": "Doberman, Doberman pinscher",
239
- "237": "miniature pinscher",
240
- "238": "Greater Swiss Mountain dog",
241
- "239": "Bernese mountain dog",
242
- "240": "Appenzeller",
243
- "241": "EntleBucher",
244
- "242": "boxer",
245
- "243": "bull mastiff",
246
- "244": "Tibetan mastiff",
247
- "245": "French bulldog",
248
- "246": "Great Dane",
249
- "247": "Saint Bernard, St Bernard",
250
- "248": "Eskimo dog, husky",
251
- "249": "malamute, malemute, Alaskan malamute",
252
- "250": "Siberian husky",
253
- "251": "dalmatian, coach dog, carriage dog",
254
- "252": "affenpinscher, monkey pinscher, monkey dog",
255
- "253": "basenji",
256
- "254": "pug, pug-dog",
257
- "255": "Leonberg",
258
- "256": "Newfoundland, Newfoundland dog",
259
- "257": "Great Pyrenees",
260
- "258": "Samoyed, Samoyede",
261
- "259": "Pomeranian",
262
- "260": "chow, chow chow",
263
- "261": "keeshond",
264
- "262": "Brabancon griffon",
265
- "263": "Pembroke, Pembroke Welsh corgi",
266
- "264": "Cardigan, Cardigan Welsh corgi",
267
- "265": "toy poodle",
268
- "266": "miniature poodle",
269
- "267": "standard poodle",
270
- "268": "Mexican hairless",
271
- "269": "timber wolf, grey wolf, gray wolf, Canis lupus",
272
- "270": "white wolf, Arctic wolf, Canis lupus tundrarum",
273
- "271": "red wolf, maned wolf, Canis rufus, Canis niger",
274
- "272": "coyote, prairie wolf, brush wolf, Canis latrans",
275
- "273": "dingo, warrigal, warragal, Canis dingo",
276
- "274": "dhole, Cuon alpinus",
277
- "275": "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus",
278
- "276": "hyena, hyaena",
279
- "277": "red fox, Vulpes vulpes",
280
- "278": "kit fox, Vulpes macrotis",
281
- "279": "Arctic fox, white fox, Alopex lagopus",
282
- "280": "grey fox, gray fox, Urocyon cinereoargenteus",
283
- "281": "tabby, tabby cat",
284
- "282": "tiger cat",
285
- "283": "Persian cat",
286
- "284": "Siamese cat, Siamese",
287
- "285": "Egyptian cat",
288
- "286": "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor",
289
- "287": "lynx, catamount",
290
- "288": "leopard, Panthera pardus",
291
- "289": "snow leopard, ounce, Panthera uncia",
292
- "290": "jaguar, panther, Panthera onca, Felis onca",
293
- "291": "lion, king of beasts, Panthera leo",
294
- "292": "tiger, Panthera tigris",
295
- "293": "cheetah, chetah, Acinonyx jubatus",
296
- "294": "brown bear, bruin, Ursus arctos",
297
- "295": "American black bear, black bear, Ursus americanus, Euarctos americanus",
298
- "296": "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus",
299
- "297": "sloth bear, Melursus ursinus, Ursus ursinus",
300
- "298": "mongoose",
301
- "299": "meerkat, mierkat",
302
- "300": "tiger beetle",
303
- "301": "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle",
304
- "302": "ground beetle, carabid beetle",
305
- "303": "long-horned beetle, longicorn, longicorn beetle",
306
- "304": "leaf beetle, chrysomelid",
307
- "305": "dung beetle",
308
- "306": "rhinoceros beetle",
309
- "307": "weevil",
310
- "308": "fly",
311
- "309": "bee",
312
- "310": "ant, emmet, pismire",
313
- "311": "grasshopper, hopper",
314
- "312": "cricket",
315
- "313": "walking stick, walkingstick, stick insect",
316
- "314": "cockroach, roach",
317
- "315": "mantis, mantid",
318
- "316": "cicada, cicala",
319
- "317": "leafhopper",
320
- "318": "lacewing, lacewing fly",
321
- "319": "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk",
322
- "320": "damselfly",
323
- "321": "admiral",
324
- "322": "ringlet, ringlet butterfly",
325
- "323": "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus",
326
- "324": "cabbage butterfly",
327
- "325": "sulphur butterfly, sulfur butterfly",
328
- "326": "lycaenid, lycaenid butterfly",
329
- "327": "starfish, sea star",
330
- "328": "sea urchin",
331
- "329": "sea cucumber, holothurian",
332
- "330": "wood rabbit, cottontail, cottontail rabbit",
333
- "331": "hare",
334
- "332": "Angora, Angora rabbit",
335
- "333": "hamster",
336
- "334": "porcupine, hedgehog",
337
- "335": "fox squirrel, eastern fox squirrel, Sciurus niger",
338
- "336": "marmot",
339
- "337": "beaver",
340
- "338": "guinea pig, Cavia cobaya",
341
- "339": "sorrel",
342
- "340": "zebra",
343
- "341": "hog, pig, grunter, squealer, Sus scrofa",
344
- "342": "wild boar, boar, Sus scrofa",
345
- "343": "warthog",
346
- "344": "hippopotamus, hippo, river horse, Hippopotamus amphibius",
347
- "345": "ox",
348
- "346": "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis",
349
- "347": "bison",
350
- "348": "ram, tup",
351
- "349": "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis",
352
- "350": "ibex, Capra ibex",
353
- "351": "hartebeest",
354
- "352": "impala, Aepyceros melampus",
355
- "353": "gazelle",
356
- "354": "Arabian camel, dromedary, Camelus dromedarius",
357
- "355": "llama",
358
- "356": "weasel",
359
- "357": "mink",
360
- "358": "polecat, fitch, foulmart, foumart, Mustela putorius",
361
- "359": "black-footed ferret, ferret, Mustela nigripes",
362
- "360": "otter",
363
- "361": "skunk, polecat, wood pussy",
364
- "362": "badger",
365
- "363": "armadillo",
366
- "364": "three-toed sloth, ai, Bradypus tridactylus",
367
- "365": "orangutan, orang, orangutang, Pongo pygmaeus",
368
- "366": "gorilla, Gorilla gorilla",
369
- "367": "chimpanzee, chimp, Pan troglodytes",
370
- "368": "gibbon, Hylobates lar",
371
- "369": "siamang, Hylobates syndactylus, Symphalangus syndactylus",
372
- "370": "guenon, guenon monkey",
373
- "371": "patas, hussar monkey, Erythrocebus patas",
374
- "372": "baboon",
375
- "373": "macaque",
376
- "374": "langur",
377
- "375": "colobus, colobus monkey",
378
- "376": "proboscis monkey, Nasalis larvatus",
379
- "377": "marmoset",
380
- "378": "capuchin, ringtail, Cebus capucinus",
381
- "379": "howler monkey, howler",
382
- "380": "titi, titi monkey",
383
- "381": "spider monkey, Ateles geoffroyi",
384
- "382": "squirrel monkey, Saimiri sciureus",
385
- "383": "Madagascar cat, ring-tailed lemur, Lemur catta",
386
- "384": "indri, indris, Indri indri, Indri brevicaudatus",
387
- "385": "Indian elephant, Elephas maximus",
388
- "386": "African elephant, Loxodonta africana",
389
- "387": "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens",
390
- "388": "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca",
391
- "389": "barracouta, snoek",
392
- "390": "eel",
393
- "391": "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch",
394
- "392": "rock beauty, Holocanthus tricolor",
395
- "393": "anemone fish",
396
- "394": "sturgeon",
397
- "395": "gar, garfish, garpike, billfish, Lepisosteus osseus",
398
- "396": "lionfish",
399
- "397": "puffer, pufferfish, blowfish, globefish",
400
- "398": "abacus",
401
- "399": "abaya",
402
- "400": "academic gown, academic robe, judge's robe",
403
- "401": "accordion, piano accordion, squeeze box",
404
- "402": "acoustic guitar",
405
- "403": "aircraft carrier, carrier, flattop, attack aircraft carrier",
406
- "404": "airliner",
407
- "405": "airship, dirigible",
408
- "406": "altar",
409
- "407": "ambulance",
410
- "408": "amphibian, amphibious vehicle",
411
- "409": "analog clock",
412
- "410": "apiary, bee house",
413
- "411": "apron",
414
- "412": "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin",
415
- "413": "assault rifle, assault gun",
416
- "414": "backpack, back pack, knapsack, packsack, rucksack, haversack",
417
- "415": "bakery, bakeshop, bakehouse",
418
- "416": "balance beam, beam",
419
- "417": "balloon",
420
- "418": "ballpoint, ballpoint pen, ballpen, Biro",
421
- "419": "Band Aid",
422
- "420": "banjo",
423
- "421": "bannister, banister, balustrade, balusters, handrail",
424
- "422": "barbell",
425
- "423": "barber chair",
426
- "424": "barbershop",
427
- "425": "barn",
428
- "426": "barometer",
429
- "427": "barrel, cask",
430
- "428": "barrow, garden cart, lawn cart, wheelbarrow",
431
- "429": "baseball",
432
- "430": "basketball",
433
- "431": "bassinet",
434
- "432": "bassoon",
435
- "433": "bathing cap, swimming cap",
436
- "434": "bath towel",
437
- "435": "bathtub, bathing tub, bath, tub",
438
- "436": "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon",
439
- "437": "beacon, lighthouse, beacon light, pharos",
440
- "438": "beaker",
441
- "439": "bearskin, busby, shako",
442
- "440": "beer bottle",
443
- "441": "beer glass",
444
- "442": "bell cote, bell cot",
445
- "443": "bib",
446
- "444": "bicycle-built-for-two, tandem bicycle, tandem",
447
- "445": "bikini, two-piece",
448
- "446": "binder, ring-binder",
449
- "447": "binoculars, field glasses, opera glasses",
450
- "448": "birdhouse",
451
- "449": "boathouse",
452
- "450": "bobsled, bobsleigh, bob",
453
- "451": "bolo tie, bolo, bola tie, bola",
454
- "452": "bonnet, poke bonnet",
455
- "453": "bookcase",
456
- "454": "bookshop, bookstore, bookstall",
457
- "455": "bottlecap",
458
- "456": "bow",
459
- "457": "bow tie, bow-tie, bowtie",
460
- "458": "brass, memorial tablet, plaque",
461
- "459": "brassiere, bra, bandeau",
462
- "460": "breakwater, groin, groyne, mole, bulwark, seawall, jetty",
463
- "461": "breastplate, aegis, egis",
464
- "462": "broom",
465
- "463": "bucket, pail",
466
- "464": "buckle",
467
- "465": "bulletproof vest",
468
- "466": "bullet train, bullet",
469
- "467": "butcher shop, meat market",
470
- "468": "cab, hack, taxi, taxicab",
471
- "469": "caldron, cauldron",
472
- "470": "candle, taper, wax light",
473
- "471": "cannon",
474
- "472": "canoe",
475
- "473": "can opener, tin opener",
476
- "474": "cardigan",
477
- "475": "car mirror",
478
- "476": "carousel, carrousel, merry-go-round, roundabout, whirligig",
479
- "477": "carpenter's kit, tool kit",
480
- "478": "carton",
481
- "479": "car wheel",
482
- "480": "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM",
483
- "481": "cassette",
484
- "482": "cassette player",
485
- "483": "castle",
486
- "484": "catamaran",
487
- "485": "CD player",
488
- "486": "cello, violoncello",
489
- "487": "cellular telephone, cellular phone, cellphone, cell, mobile phone",
490
- "488": "chain",
491
- "489": "chainlink fence",
492
- "490": "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour",
493
- "491": "chain saw, chainsaw",
494
- "492": "chest",
495
- "493": "chiffonier, commode",
496
- "494": "chime, bell, gong",
497
- "495": "china cabinet, china closet",
498
- "496": "Christmas stocking",
499
- "497": "church, church building",
500
- "498": "cinema, movie theater, movie theatre, movie house, picture palace",
501
- "499": "cleaver, meat cleaver, chopper",
502
- "500": "cliff dwelling",
503
- "501": "cloak",
504
- "502": "clog, geta, patten, sabot",
505
- "503": "cocktail shaker",
506
- "504": "coffee mug",
507
- "505": "coffeepot",
508
- "506": "coil, spiral, volute, whorl, helix",
509
- "507": "combination lock",
510
- "508": "computer keyboard, keypad",
511
- "509": "confectionery, confectionary, candy store",
512
- "510": "container ship, containership, container vessel",
513
- "511": "convertible",
514
- "512": "corkscrew, bottle screw",
515
- "513": "cornet, horn, trumpet, trump",
516
- "514": "cowboy boot",
517
- "515": "cowboy hat, ten-gallon hat",
518
- "516": "cradle",
519
- "517": "crane",
520
- "518": "crash helmet",
521
- "519": "crate",
522
- "520": "crib, cot",
523
- "521": "Crock Pot",
524
- "522": "croquet ball",
525
- "523": "crutch",
526
- "524": "cuirass",
527
- "525": "dam, dike, dyke",
528
- "526": "desk",
529
- "527": "desktop computer",
530
- "528": "dial telephone, dial phone",
531
- "529": "diaper, nappy, napkin",
532
- "530": "digital clock",
533
- "531": "digital watch",
534
- "532": "dining table, board",
535
- "533": "dishrag, dishcloth",
536
- "534": "dishwasher, dish washer, dishwashing machine",
537
- "535": "disk brake, disc brake",
538
- "536": "dock, dockage, docking facility",
539
- "537": "dogsled, dog sled, dog sleigh",
540
- "538": "dome",
541
- "539": "doormat, welcome mat",
542
- "540": "drilling platform, offshore rig",
543
- "541": "drum, membranophone, tympan",
544
- "542": "drumstick",
545
- "543": "dumbbell",
546
- "544": "Dutch oven",
547
- "545": "electric fan, blower",
548
- "546": "electric guitar",
549
- "547": "electric locomotive",
550
- "548": "entertainment center",
551
- "549": "envelope",
552
- "550": "espresso maker",
553
- "551": "face powder",
554
- "552": "feather boa, boa",
555
- "553": "file, file cabinet, filing cabinet",
556
- "554": "fireboat",
557
- "555": "fire engine, fire truck",
558
- "556": "fire screen, fireguard",
559
- "557": "flagpole, flagstaff",
560
- "558": "flute, transverse flute",
561
- "559": "folding chair",
562
- "560": "football helmet",
563
- "561": "forklift",
564
- "562": "fountain",
565
- "563": "fountain pen",
566
- "564": "four-poster",
567
- "565": "freight car",
568
- "566": "French horn, horn",
569
- "567": "frying pan, frypan, skillet",
570
- "568": "fur coat",
571
- "569": "garbage truck, dustcart",
572
- "570": "gasmask, respirator, gas helmet",
573
- "571": "gas pump, gasoline pump, petrol pump, island dispenser",
574
- "572": "goblet",
575
- "573": "go-kart",
576
- "574": "golf ball",
577
- "575": "golfcart, golf cart",
578
- "576": "gondola",
579
- "577": "gong, tam-tam",
580
- "578": "gown",
581
- "579": "grand piano, grand",
582
- "580": "greenhouse, nursery, glasshouse",
583
- "581": "grille, radiator grille",
584
- "582": "grocery store, grocery, food market, market",
585
- "583": "guillotine",
586
- "584": "hair slide",
587
- "585": "hair spray",
588
- "586": "half track",
589
- "587": "hammer",
590
- "588": "hamper",
591
- "589": "hand blower, blow dryer, blow drier, hair dryer, hair drier",
592
- "590": "hand-held computer, hand-held microcomputer",
593
- "591": "handkerchief, hankie, hanky, hankey",
594
- "592": "hard disc, hard disk, fixed disk",
595
- "593": "harmonica, mouth organ, harp, mouth harp",
596
- "594": "harp",
597
- "595": "harvester, reaper",
598
- "596": "hatchet",
599
- "597": "holster",
600
- "598": "home theater, home theatre",
601
- "599": "honeycomb",
602
- "600": "hook, claw",
603
- "601": "hoopskirt, crinoline",
604
- "602": "horizontal bar, high bar",
605
- "603": "horse cart, horse-cart",
606
- "604": "hourglass",
607
- "605": "iPod",
608
- "606": "iron, smoothing iron",
609
- "607": "jack-o'-lantern",
610
- "608": "jean, blue jean, denim",
611
- "609": "jeep, landrover",
612
- "610": "jersey, T-shirt, tee shirt",
613
- "611": "jigsaw puzzle",
614
- "612": "jinrikisha, ricksha, rickshaw",
615
- "613": "joystick",
616
- "614": "kimono",
617
- "615": "knee pad",
618
- "616": "knot",
619
- "617": "lab coat, laboratory coat",
620
- "618": "ladle",
621
- "619": "lampshade, lamp shade",
622
- "620": "laptop, laptop computer",
623
- "621": "lawn mower, mower",
624
- "622": "lens cap, lens cover",
625
- "623": "letter opener, paper knife, paperknife",
626
- "624": "library",
627
- "625": "lifeboat",
628
- "626": "lighter, light, igniter, ignitor",
629
- "627": "limousine, limo",
630
- "628": "liner, ocean liner",
631
- "629": "lipstick, lip rouge",
632
- "630": "Loafer",
633
- "631": "lotion",
634
- "632": "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system",
635
- "633": "loupe, jeweler's loupe",
636
- "634": "lumbermill, sawmill",
637
- "635": "magnetic compass",
638
- "636": "mailbag, postbag",
639
- "637": "mailbox, letter box",
640
- "638": "maillot",
641
- "639": "maillot, tank suit",
642
- "640": "manhole cover",
643
- "641": "maraca",
644
- "642": "marimba, xylophone",
645
- "643": "mask",
646
- "644": "matchstick",
647
- "645": "maypole",
648
- "646": "maze, labyrinth",
649
- "647": "measuring cup",
650
- "648": "medicine chest, medicine cabinet",
651
- "649": "megalith, megalithic structure",
652
- "650": "microphone, mike",
653
- "651": "microwave, microwave oven",
654
- "652": "military uniform",
655
- "653": "milk can",
656
- "654": "minibus",
657
- "655": "miniskirt, mini",
658
- "656": "minivan",
659
- "657": "missile",
660
- "658": "mitten",
661
- "659": "mixing bowl",
662
- "660": "mobile home, manufactured home",
663
- "661": "Model T",
664
- "662": "modem",
665
- "663": "monastery",
666
- "664": "monitor",
667
- "665": "moped",
668
- "666": "mortar",
669
- "667": "mortarboard",
670
- "668": "mosque",
671
- "669": "mosquito net",
672
- "670": "motor scooter, scooter",
673
- "671": "mountain bike, all-terrain bike, off-roader",
674
- "672": "mountain tent",
675
- "673": "mouse, computer mouse",
676
- "674": "mousetrap",
677
- "675": "moving van",
678
- "676": "muzzle",
679
- "677": "nail",
680
- "678": "neck brace",
681
- "679": "necklace",
682
- "680": "nipple",
683
- "681": "notebook, notebook computer",
684
- "682": "obelisk",
685
- "683": "oboe, hautboy, hautbois",
686
- "684": "ocarina, sweet potato",
687
- "685": "odometer, hodometer, mileometer, milometer",
688
- "686": "oil filter",
689
- "687": "organ, pipe organ",
690
- "688": "oscilloscope, scope, cathode-ray oscilloscope, CRO",
691
- "689": "overskirt",
692
- "690": "oxcart",
693
- "691": "oxygen mask",
694
- "692": "packet",
695
- "693": "paddle, boat paddle",
696
- "694": "paddlewheel, paddle wheel",
697
- "695": "padlock",
698
- "696": "paintbrush",
699
- "697": "pajama, pyjama, pj's, jammies",
700
- "698": "palace",
701
- "699": "panpipe, pandean pipe, syrinx",
702
- "700": "paper towel",
703
- "701": "parachute, chute",
704
- "702": "parallel bars, bars",
705
- "703": "park bench",
706
- "704": "parking meter",
707
- "705": "passenger car, coach, carriage",
708
- "706": "patio, terrace",
709
- "707": "pay-phone, pay-station",
710
- "708": "pedestal, plinth, footstall",
711
- "709": "pencil box, pencil case",
712
- "710": "pencil sharpener",
713
- "711": "perfume, essence",
714
- "712": "Petri dish",
715
- "713": "photocopier",
716
- "714": "pick, plectrum, plectron",
717
- "715": "pickelhaube",
718
- "716": "picket fence, paling",
719
- "717": "pickup, pickup truck",
720
- "718": "pier",
721
- "719": "piggy bank, penny bank",
722
- "720": "pill bottle",
723
- "721": "pillow",
724
- "722": "ping-pong ball",
725
- "723": "pinwheel",
726
- "724": "pirate, pirate ship",
727
- "725": "pitcher, ewer",
728
- "726": "plane, carpenter's plane, woodworking plane",
729
- "727": "planetarium",
730
- "728": "plastic bag",
731
- "729": "plate rack",
732
- "730": "plow, plough",
733
- "731": "plunger, plumber's helper",
734
- "732": "Polaroid camera, Polaroid Land camera",
735
- "733": "pole",
736
- "734": "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria",
737
- "735": "poncho",
738
- "736": "pool table, billiard table, snooker table",
739
- "737": "pop bottle, soda bottle",
740
- "738": "pot, flowerpot",
741
- "739": "potter's wheel",
742
- "740": "power drill",
743
- "741": "prayer rug, prayer mat",
744
- "742": "printer",
745
- "743": "prison, prison house",
746
- "744": "projectile, missile",
747
- "745": "projector",
748
- "746": "puck, hockey puck",
749
- "747": "punching bag, punch bag, punching ball, punchball",
750
- "748": "purse",
751
- "749": "quill, quill pen",
752
- "750": "quilt, comforter, comfort, puff",
753
- "751": "racer, race car, racing car",
754
- "752": "racket, racquet",
755
- "753": "radiator",
756
- "754": "radio, wireless",
757
- "755": "radio telescope, radio reflector",
758
- "756": "rain barrel",
759
- "757": "recreational vehicle, RV, R.V.",
760
- "758": "reel",
761
- "759": "reflex camera",
762
- "760": "refrigerator, icebox",
763
- "761": "remote control, remote",
764
- "762": "restaurant, eating house, eating place, eatery",
765
- "763": "revolver, six-gun, six-shooter",
766
- "764": "rifle",
767
- "765": "rocking chair, rocker",
768
- "766": "rotisserie",
769
- "767": "rubber eraser, rubber, pencil eraser",
770
- "768": "rugby ball",
771
- "769": "rule, ruler",
772
- "770": "running shoe",
773
- "771": "safe",
774
- "772": "safety pin",
775
- "773": "saltshaker, salt shaker",
776
- "774": "sandal",
777
- "775": "sarong",
778
- "776": "sax, saxophone",
779
- "777": "scabbard",
780
- "778": "scale, weighing machine",
781
- "779": "school bus",
782
- "780": "schooner",
783
- "781": "scoreboard",
784
- "782": "screen, CRT screen",
785
- "783": "screw",
786
- "784": "screwdriver",
787
- "785": "seat belt, seatbelt",
788
- "786": "sewing machine",
789
- "787": "shield, buckler",
790
- "788": "shoe shop, shoe-shop, shoe store",
791
- "789": "shoji",
792
- "790": "shopping basket",
793
- "791": "shopping cart",
794
- "792": "shovel",
795
- "793": "shower cap",
796
- "794": "shower curtain",
797
- "795": "ski",
798
- "796": "ski mask",
799
- "797": "sleeping bag",
800
- "798": "slide rule, slipstick",
801
- "799": "sliding door",
802
- "800": "slot, one-armed bandit",
803
- "801": "snorkel",
804
- "802": "snowmobile",
805
- "803": "snowplow, snowplough",
806
- "804": "soap dispenser",
807
- "805": "soccer ball",
808
- "806": "sock",
809
- "807": "solar dish, solar collector, solar furnace",
810
- "808": "sombrero",
811
- "809": "soup bowl",
812
- "810": "space bar",
813
- "811": "space heater",
814
- "812": "space shuttle",
815
- "813": "spatula",
816
- "814": "speedboat",
817
- "815": "spider web, spider's web",
818
- "816": "spindle",
819
- "817": "sports car, sport car",
820
- "818": "spotlight, spot",
821
- "819": "stage",
822
- "820": "steam locomotive",
823
- "821": "steel arch bridge",
824
- "822": "steel drum",
825
- "823": "stethoscope",
826
- "824": "stole",
827
- "825": "stone wall",
828
- "826": "stopwatch, stop watch",
829
- "827": "stove",
830
- "828": "strainer",
831
- "829": "streetcar, tram, tramcar, trolley, trolley car",
832
- "830": "stretcher",
833
- "831": "studio couch, day bed",
834
- "832": "stupa, tope",
835
- "833": "submarine, pigboat, sub, U-boat",
836
- "834": "suit, suit of clothes",
837
- "835": "sundial",
838
- "836": "sunglass",
839
- "837": "sunglasses, dark glasses, shades",
840
- "838": "sunscreen, sunblock, sun blocker",
841
- "839": "suspension bridge",
842
- "840": "swab, swob, mop",
843
- "841": "sweatshirt",
844
- "842": "swimming trunks, bathing trunks",
845
- "843": "swing",
846
- "844": "switch, electric switch, electrical switch",
847
- "845": "syringe",
848
- "846": "table lamp",
849
- "847": "tank, army tank, armored combat vehicle, armoured combat vehicle",
850
- "848": "tape player",
851
- "849": "teapot",
852
- "850": "teddy, teddy bear",
853
- "851": "television, television system",
854
- "852": "tennis ball",
855
- "853": "thatch, thatched roof",
856
- "854": "theater curtain, theatre curtain",
857
- "855": "thimble",
858
- "856": "thresher, thrasher, threshing machine",
859
- "857": "throne",
860
- "858": "tile roof",
861
- "859": "toaster",
862
- "860": "tobacco shop, tobacconist shop, tobacconist",
863
- "861": "toilet seat",
864
- "862": "torch",
865
- "863": "totem pole",
866
- "864": "tow truck, tow car, wrecker",
867
- "865": "toyshop",
868
- "866": "tractor",
869
- "867": "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi",
870
- "868": "tray",
871
- "869": "trench coat",
872
- "870": "tricycle, trike, velocipede",
873
- "871": "trimaran",
874
- "872": "tripod",
875
- "873": "triumphal arch",
876
- "874": "trolleybus, trolley coach, trackless trolley",
877
- "875": "trombone",
878
- "876": "tub, vat",
879
- "877": "turnstile",
880
- "878": "typewriter keyboard",
881
- "879": "umbrella",
882
- "880": "unicycle, monocycle",
883
- "881": "upright, upright piano",
884
- "882": "vacuum, vacuum cleaner",
885
- "883": "vase",
886
- "884": "vault",
887
- "885": "velvet",
888
- "886": "vending machine",
889
- "887": "vestment",
890
- "888": "viaduct",
891
- "889": "violin, fiddle",
892
- "890": "volleyball",
893
- "891": "waffle iron",
894
- "892": "wall clock",
895
- "893": "wallet, billfold, notecase, pocketbook",
896
- "894": "wardrobe, closet, press",
897
- "895": "warplane, military plane",
898
- "896": "washbasin, handbasin, washbowl, lavabo, wash-hand basin",
899
- "897": "washer, automatic washer, washing machine",
900
- "898": "water bottle",
901
- "899": "water jug",
902
- "900": "water tower",
903
- "901": "whiskey jug",
904
- "902": "whistle",
905
- "903": "wig",
906
- "904": "window screen",
907
- "905": "window shade",
908
- "906": "Windsor tie",
909
- "907": "wine bottle",
910
- "908": "wing",
911
- "909": "wok",
912
- "910": "wooden spoon",
913
- "911": "wool, woolen, woollen",
914
- "912": "worm fence, snake fence, snake-rail fence, Virginia fence",
915
- "913": "wreck",
916
- "914": "yawl",
917
- "915": "yurt",
918
- "916": "web site, website, internet site, site",
919
- "917": "comic book",
920
- "918": "crossword puzzle, crossword",
921
- "919": "street sign",
922
- "920": "traffic light, traffic signal, stoplight",
923
- "921": "book jacket, dust cover, dust jacket, dust wrapper",
924
- "922": "menu",
925
- "923": "plate",
926
- "924": "guacamole",
927
- "925": "consomme",
928
- "926": "hot pot, hotpot",
929
- "927": "trifle",
930
- "928": "ice cream, icecream",
931
- "929": "ice lolly, lolly, lollipop, popsicle",
932
- "930": "French loaf",
933
- "931": "bagel, beigel",
934
- "932": "pretzel",
935
- "933": "cheeseburger",
936
- "934": "hotdog, hot dog, red hot",
937
- "935": "mashed potato",
938
- "936": "head cabbage",
939
- "937": "broccoli",
940
- "938": "cauliflower",
941
- "939": "zucchini, courgette",
942
- "940": "spaghetti squash",
943
- "941": "acorn squash",
944
- "942": "butternut squash",
945
- "943": "cucumber, cuke",
946
- "944": "artichoke, globe artichoke",
947
- "945": "bell pepper",
948
- "946": "cardoon",
949
- "947": "mushroom",
950
- "948": "Granny Smith",
951
- "949": "strawberry",
952
- "950": "orange",
953
- "951": "lemon",
954
- "952": "fig",
955
- "953": "pineapple, ananas",
956
- "954": "banana",
957
- "955": "jackfruit, jak, jack",
958
- "956": "custard apple",
959
- "957": "pomegranate",
960
- "958": "hay",
961
- "959": "carbonara",
962
- "960": "chocolate sauce, chocolate syrup",
963
- "961": "dough",
964
- "962": "meat loaf, meatloaf",
965
- "963": "pizza, pizza pie",
966
- "964": "potpie",
967
- "965": "burrito",
968
- "966": "red wine",
969
- "967": "espresso",
970
- "968": "cup",
971
- "969": "eggnog",
972
- "970": "alp",
973
- "971": "bubble",
974
- "972": "cliff, drop, drop-off",
975
- "973": "coral reef",
976
- "974": "geyser",
977
- "975": "lakeside, lakeshore",
978
- "976": "promontory, headland, head, foreland",
979
- "977": "sandbar, sand bar",
980
- "978": "seashore, coast, seacoast, sea-coast",
981
- "979": "valley, vale",
982
- "980": "volcano",
983
- "981": "ballplayer, baseball player",
984
- "982": "groom, bridegroom",
985
- "983": "scuba diver",
986
- "984": "rapeseed",
987
- "985": "daisy",
988
- "986": "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum",
989
- "987": "corn",
990
- "988": "acorn",
991
- "989": "hip, rose hip, rosehip",
992
- "990": "buckeye, horse chestnut, conker",
993
- "991": "coral fungus",
994
- "992": "agaric",
995
- "993": "gyromitra",
996
- "994": "stinkhorn, carrion fungus",
997
- "995": "earthstar",
998
- "996": "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa",
999
- "997": "bolete",
1000
- "998": "ear, spike, capitulum",
1001
- "999": "toilet tissue, toilet paper, bathroom tissue"
1002
- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
classes.txt ADDED
@@ -0,0 +1,1000 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ tench
2
+ goldfish
3
+ great_white_shark
4
+ tiger_shark
5
+ hammerhead
6
+ electric_ray
7
+ stingray
8
+ cock
9
+ hen
10
+ ostrich
11
+ brambling
12
+ goldfinch
13
+ house_finch
14
+ junco
15
+ indigo_bunting
16
+ robin
17
+ bulbul
18
+ jay
19
+ magpie
20
+ chickadee
21
+ water_ouzel
22
+ kite
23
+ bald_eagle
24
+ vulture
25
+ great_grey_owl
26
+ European_fire_salamander
27
+ common_newt
28
+ eft
29
+ spotted_salamander
30
+ axolotl
31
+ bullfrog
32
+ tree_frog
33
+ tailed_frog
34
+ loggerhead
35
+ leatherback_turtle
36
+ mud_turtle
37
+ terrapin
38
+ box_turtle
39
+ banded_gecko
40
+ common_iguana
41
+ American_chameleon
42
+ whiptail
43
+ agama
44
+ frilled_lizard
45
+ alligator_lizard
46
+ Gila_monster
47
+ green_lizard
48
+ African_chameleon
49
+ Komodo_dragon
50
+ African_crocodile
51
+ American_alligator
52
+ triceratops
53
+ thunder_snake
54
+ ringneck_snake
55
+ hognose_snake
56
+ green_snake
57
+ king_snake
58
+ garter_snake
59
+ water_snake
60
+ vine_snake
61
+ night_snake
62
+ boa_constrictor
63
+ rock_python
64
+ Indian_cobra
65
+ green_mamba
66
+ sea_snake
67
+ horned_viper
68
+ diamondback
69
+ sidewinder
70
+ trilobite
71
+ harvestman
72
+ scorpion
73
+ black_and_gold_garden_spider
74
+ barn_spider
75
+ garden_spider
76
+ black_widow
77
+ tarantula
78
+ wolf_spider
79
+ tick
80
+ centipede
81
+ black_grouse
82
+ ptarmigan
83
+ ruffed_grouse
84
+ prairie_chicken
85
+ peacock
86
+ quail
87
+ partridge
88
+ African_grey
89
+ macaw
90
+ sulphur-crested_cockatoo
91
+ lorikeet
92
+ coucal
93
+ bee_eater
94
+ hornbill
95
+ hummingbird
96
+ jacamar
97
+ toucan
98
+ drake
99
+ red-breasted_merganser
100
+ goose
101
+ black_swan
102
+ tusker
103
+ echidna
104
+ platypus
105
+ wallaby
106
+ koala
107
+ wombat
108
+ jellyfish
109
+ sea_anemone
110
+ brain_coral
111
+ flatworm
112
+ nematode
113
+ conch
114
+ snail
115
+ slug
116
+ sea_slug
117
+ chiton
118
+ chambered_nautilus
119
+ Dungeness_crab
120
+ rock_crab
121
+ fiddler_crab
122
+ king_crab
123
+ American_lobster
124
+ spiny_lobster
125
+ crayfish
126
+ hermit_crab
127
+ isopod
128
+ white_stork
129
+ black_stork
130
+ spoonbill
131
+ flamingo
132
+ little_blue_heron
133
+ American_egret
134
+ bittern
135
+ crane
136
+ limpkin
137
+ European_gallinule
138
+ American_coot
139
+ bustard
140
+ ruddy_turnstone
141
+ red-backed_sandpiper
142
+ redshank
143
+ dowitcher
144
+ oystercatcher
145
+ pelican
146
+ king_penguin
147
+ albatross
148
+ grey_whale
149
+ killer_whale
150
+ dugong
151
+ sea_lion
152
+ Chihuahua
153
+ Japanese_spaniel
154
+ Maltese_dog
155
+ Pekinese
156
+ Shih-Tzu
157
+ Blenheim_spaniel
158
+ papillon
159
+ toy_terrier
160
+ Rhodesian_ridgeback
161
+ Afghan_hound
162
+ basset
163
+ beagle
164
+ bloodhound
165
+ bluetick
166
+ black-and-tan_coonhound
167
+ Walker_hound
168
+ English_foxhound
169
+ redbone
170
+ borzoi
171
+ Irish_wolfhound
172
+ Italian_greyhound
173
+ whippet
174
+ Ibizan_hound
175
+ Norwegian_elkhound
176
+ otterhound
177
+ Saluki
178
+ Scottish_deerhound
179
+ Weimaraner
180
+ Staffordshire_bullterrier
181
+ American_Staffordshire_terrier
182
+ Bedlington_terrier
183
+ Border_terrier
184
+ Kerry_blue_terrier
185
+ Irish_terrier
186
+ Norfolk_terrier
187
+ Norwich_terrier
188
+ Yorkshire_terrier
189
+ wire-haired_fox_terrier
190
+ Lakeland_terrier
191
+ Sealyham_terrier
192
+ Airedale
193
+ cairn
194
+ Australian_terrier
195
+ Dandie_Dinmont
196
+ Boston_bull
197
+ miniature_schnauzer
198
+ giant_schnauzer
199
+ standard_schnauzer
200
+ Scotch_terrier
201
+ Tibetan_terrier
202
+ silky_terrier
203
+ soft-coated_wheaten_terrier
204
+ West_Highland_white_terrier
205
+ Lhasa
206
+ flat-coated_retriever
207
+ curly-coated_retriever
208
+ golden_retriever
209
+ Labrador_retriever
210
+ Chesapeake_Bay_retriever
211
+ German_short-haired_pointer
212
+ vizsla
213
+ English_setter
214
+ Irish_setter
215
+ Gordon_setter
216
+ Brittany_spaniel
217
+ clumber
218
+ English_springer
219
+ Welsh_springer_spaniel
220
+ cocker_spaniel
221
+ Sussex_spaniel
222
+ Irish_water_spaniel
223
+ kuvasz
224
+ schipperke
225
+ groenendael
226
+ malinois
227
+ briard
228
+ kelpie
229
+ komondor
230
+ Old_English_sheepdog
231
+ Shetland_sheepdog
232
+ collie
233
+ Border_collie
234
+ Bouvier_des_Flandres
235
+ Rottweiler
236
+ German_shepherd
237
+ Doberman
238
+ miniature_pinscher
239
+ Greater_Swiss_Mountain_dog
240
+ Bernese_mountain_dog
241
+ Appenzeller
242
+ EntleBucher
243
+ boxer
244
+ bull_mastiff
245
+ Tibetan_mastiff
246
+ French_bulldog
247
+ Great_Dane
248
+ Saint_Bernard
249
+ Eskimo_dog
250
+ malamute
251
+ Siberian_husky
252
+ dalmatian
253
+ affenpinscher
254
+ basenji
255
+ pug
256
+ Leonberg
257
+ Newfoundland
258
+ Great_Pyrenees
259
+ Samoyed
260
+ Pomeranian
261
+ chow
262
+ keeshond
263
+ Brabancon_griffon
264
+ Pembroke
265
+ Cardigan
266
+ toy_poodle
267
+ miniature_poodle
268
+ standard_poodle
269
+ Mexican_hairless
270
+ timber_wolf
271
+ white_wolf
272
+ red_wolf
273
+ coyote
274
+ dingo
275
+ dhole
276
+ African_hunting_dog
277
+ hyena
278
+ red_fox
279
+ kit_fox
280
+ Arctic_fox
281
+ grey_fox
282
+ tabby
283
+ tiger_cat
284
+ Persian_cat
285
+ Siamese_cat
286
+ Egyptian_cat
287
+ cougar
288
+ lynx
289
+ leopard
290
+ snow_leopard
291
+ jaguar
292
+ lion
293
+ tiger
294
+ cheetah
295
+ brown_bear
296
+ American_black_bear
297
+ ice_bear
298
+ sloth_bear
299
+ mongoose
300
+ meerkat
301
+ tiger_beetle
302
+ ladybug
303
+ ground_beetle
304
+ long-horned_beetle
305
+ leaf_beetle
306
+ dung_beetle
307
+ rhinoceros_beetle
308
+ weevil
309
+ fly
310
+ bee
311
+ ant
312
+ grasshopper
313
+ cricket
314
+ walking_stick
315
+ cockroach
316
+ mantis
317
+ cicada
318
+ leafhopper
319
+ lacewing
320
+ dragonfly
321
+ damselfly
322
+ admiral
323
+ ringlet
324
+ monarch
325
+ cabbage_butterfly
326
+ sulphur_butterfly
327
+ lycaenid
328
+ starfish
329
+ sea_urchin
330
+ sea_cucumber
331
+ wood_rabbit
332
+ hare
333
+ Angora
334
+ hamster
335
+ porcupine
336
+ fox_squirrel
337
+ marmot
338
+ beaver
339
+ guinea_pig
340
+ sorrel
341
+ zebra
342
+ hog
343
+ wild_boar
344
+ warthog
345
+ hippopotamus
346
+ ox
347
+ water_buffalo
348
+ bison
349
+ ram
350
+ bighorn
351
+ ibex
352
+ hartebeest
353
+ impala
354
+ gazelle
355
+ Arabian_camel
356
+ llama
357
+ weasel
358
+ mink
359
+ polecat
360
+ black-footed_ferret
361
+ otter
362
+ skunk
363
+ badger
364
+ armadillo
365
+ three-toed_sloth
366
+ orangutan
367
+ gorilla
368
+ chimpanzee
369
+ gibbon
370
+ siamang
371
+ guenon
372
+ patas
373
+ baboon
374
+ macaque
375
+ langur
376
+ colobus
377
+ proboscis_monkey
378
+ marmoset
379
+ capuchin
380
+ howler_monkey
381
+ titi
382
+ spider_monkey
383
+ squirrel_monkey
384
+ Madagascar_cat
385
+ indri
386
+ Indian_elephant
387
+ African_elephant
388
+ lesser_panda
389
+ giant_panda
390
+ barracouta
391
+ eel
392
+ coho
393
+ rock_beauty
394
+ anemone_fish
395
+ sturgeon
396
+ gar
397
+ lionfish
398
+ puffer
399
+ abacus
400
+ abaya
401
+ academic_gown
402
+ accordion
403
+ acoustic_guitar
404
+ aircraft_carrier
405
+ airliner
406
+ airship
407
+ altar
408
+ ambulance
409
+ amphibian
410
+ analog_clock
411
+ apiary
412
+ apron
413
+ ashcan
414
+ assault_rifle
415
+ backpack
416
+ bakery
417
+ balance_beam
418
+ balloon
419
+ ballpoint
420
+ Band_Aid
421
+ banjo
422
+ bannister
423
+ barbell
424
+ barber_chair
425
+ barbershop
426
+ barn
427
+ barometer
428
+ barrel
429
+ barrow
430
+ baseball
431
+ basketball
432
+ bassinet
433
+ bassoon
434
+ bathing_cap
435
+ bath_towel
436
+ bathtub
437
+ beach_wagon
438
+ beacon
439
+ beaker
440
+ bearskin
441
+ beer_bottle
442
+ beer_glass
443
+ bell_cote
444
+ bib
445
+ bicycle-built-for-two
446
+ bikini
447
+ binder
448
+ binoculars
449
+ birdhouse
450
+ boathouse
451
+ bobsled
452
+ bolo_tie
453
+ bonnet
454
+ bookcase
455
+ bookshop
456
+ bottlecap
457
+ bow
458
+ bow_tie
459
+ brass
460
+ brassiere
461
+ breakwater
462
+ breastplate
463
+ broom
464
+ bucket
465
+ buckle
466
+ bulletproof_vest
467
+ bullet_train
468
+ butcher_shop
469
+ cab
470
+ caldron
471
+ candle
472
+ cannon
473
+ canoe
474
+ can_opener
475
+ cardigan
476
+ car_mirror
477
+ carousel
478
+ carpenters_kit
479
+ carton
480
+ car_wheel
481
+ cash_machine
482
+ cassette
483
+ cassette_player
484
+ castle
485
+ catamaran
486
+ CD_player
487
+ cello
488
+ cellular_telephone
489
+ chain
490
+ chainlink_fence
491
+ chain_mail
492
+ chain_saw
493
+ chest
494
+ chiffonier
495
+ chime
496
+ china_cabinet
497
+ Christmas_stocking
498
+ church
499
+ cinema
500
+ cleaver
501
+ cliff_dwelling
502
+ cloak
503
+ clog
504
+ cocktail_shaker
505
+ coffee_mug
506
+ coffeepot
507
+ coil
508
+ combination_lock
509
+ computer_keyboard
510
+ confectionery
511
+ container_ship
512
+ convertible
513
+ corkscrew
514
+ cornet
515
+ cowboy_boot
516
+ cowboy_hat
517
+ cradle
518
+ crane
519
+ crash_helmet
520
+ crate
521
+ crib
522
+ Crock_Pot
523
+ croquet_ball
524
+ crutch
525
+ cuirass
526
+ dam
527
+ desk
528
+ desktop_computer
529
+ dial_telephone
530
+ diaper
531
+ digital_clock
532
+ digital_watch
533
+ dining_table
534
+ dishrag
535
+ dishwasher
536
+ disk_brake
537
+ dock
538
+ dogsled
539
+ dome
540
+ doormat
541
+ drilling_platform
542
+ drum
543
+ drumstick
544
+ dumbbell
545
+ Dutch_oven
546
+ electric_fan
547
+ electric_guitar
548
+ electric_locomotive
549
+ entertainment_center
550
+ envelope
551
+ espresso_maker
552
+ face_powder
553
+ feather_boa
554
+ file
555
+ fireboat
556
+ fire_engine
557
+ fire_screen
558
+ flagpole
559
+ flute
560
+ folding_chair
561
+ football_helmet
562
+ forklift
563
+ fountain
564
+ fountain_pen
565
+ four-poster
566
+ freight_car
567
+ French_horn
568
+ frying_pan
569
+ fur_coat
570
+ garbage_truck
571
+ gasmask
572
+ gas_pump
573
+ goblet
574
+ go-kart
575
+ golf_ball
576
+ golfcart
577
+ gondola
578
+ gong
579
+ gown
580
+ grand_piano
581
+ greenhouse
582
+ grille
583
+ grocery_store
584
+ guillotine
585
+ hair_slide
586
+ hair_spray
587
+ half_track
588
+ hammer
589
+ hamper
590
+ hand_blower
591
+ hand-held_computer
592
+ handkerchief
593
+ hard_disc
594
+ harmonica
595
+ harp
596
+ harvester
597
+ hatchet
598
+ holster
599
+ home_theater
600
+ honeycomb
601
+ hook
602
+ hoopskirt
603
+ horizontal_bar
604
+ horse_cart
605
+ hourglass
606
+ iPod
607
+ iron
608
+ jack-o-lantern
609
+ jean
610
+ jeep
611
+ jersey
612
+ jigsaw_puzzle
613
+ jinrikisha
614
+ joystick
615
+ kimono
616
+ knee_pad
617
+ knot
618
+ lab_coat
619
+ ladle
620
+ lampshade
621
+ laptop
622
+ lawn_mower
623
+ lens_cap
624
+ letter_opener
625
+ library
626
+ lifeboat
627
+ lighter
628
+ limousine
629
+ liner
630
+ lipstick
631
+ Loafer
632
+ lotion
633
+ loudspeaker
634
+ loupe
635
+ lumbermill
636
+ magnetic_compass
637
+ mailbag
638
+ mailbox
639
+ maillot
640
+ maillot
641
+ manhole_cover
642
+ maraca
643
+ marimba
644
+ mask
645
+ matchstick
646
+ maypole
647
+ maze
648
+ measuring_cup
649
+ medicine_chest
650
+ megalith
651
+ microphone
652
+ microwave
653
+ military_uniform
654
+ milk_can
655
+ minibus
656
+ miniskirt
657
+ minivan
658
+ missile
659
+ mitten
660
+ mixing_bowl
661
+ mobile_home
662
+ Model_T
663
+ modem
664
+ monastery
665
+ monitor
666
+ moped
667
+ mortar
668
+ mortarboard
669
+ mosque
670
+ mosquito_net
671
+ motor_scooter
672
+ mountain_bike
673
+ mountain_tent
674
+ mouse
675
+ mousetrap
676
+ moving_van
677
+ muzzle
678
+ nail
679
+ neck_brace
680
+ necklace
681
+ nipple
682
+ notebook
683
+ obelisk
684
+ oboe
685
+ ocarina
686
+ odometer
687
+ oil_filter
688
+ organ
689
+ oscilloscope
690
+ overskirt
691
+ oxcart
692
+ oxygen_mask
693
+ packet
694
+ paddle
695
+ paddlewheel
696
+ padlock
697
+ paintbrush
698
+ pajama
699
+ palace
700
+ panpipe
701
+ paper_towel
702
+ parachute
703
+ parallel_bars
704
+ park_bench
705
+ parking_meter
706
+ passenger_car
707
+ patio
708
+ pay-phone
709
+ pedestal
710
+ pencil_box
711
+ pencil_sharpener
712
+ perfume
713
+ Petri_dish
714
+ photocopier
715
+ pick
716
+ pickelhaube
717
+ picket_fence
718
+ pickup
719
+ pier
720
+ piggy_bank
721
+ pill_bottle
722
+ pillow
723
+ ping-pong_ball
724
+ pinwheel
725
+ pirate
726
+ pitcher
727
+ plane
728
+ planetarium
729
+ plastic_bag
730
+ plate_rack
731
+ plow
732
+ plunger
733
+ Polaroid_camera
734
+ pole
735
+ police_van
736
+ poncho
737
+ pool_table
738
+ pop_bottle
739
+ pot
740
+ potters_wheel
741
+ power_drill
742
+ prayer_rug
743
+ printer
744
+ prison
745
+ projectile
746
+ projector
747
+ puck
748
+ punching_bag
749
+ purse
750
+ quill
751
+ quilt
752
+ racer
753
+ racket
754
+ radiator
755
+ radio
756
+ radio_telescope
757
+ rain_barrel
758
+ recreational_vehicle
759
+ reel
760
+ reflex_camera
761
+ refrigerator
762
+ remote_control
763
+ restaurant
764
+ revolver
765
+ rifle
766
+ rocking_chair
767
+ rotisserie
768
+ rubber_eraser
769
+ rugby_ball
770
+ rule
771
+ running_shoe
772
+ safe
773
+ safety_pin
774
+ saltshaker
775
+ sandal
776
+ sarong
777
+ sax
778
+ scabbard
779
+ scale
780
+ school_bus
781
+ schooner
782
+ scoreboard
783
+ screen
784
+ screw
785
+ screwdriver
786
+ seat_belt
787
+ sewing_machine
788
+ shield
789
+ shoe_shop
790
+ shoji
791
+ shopping_basket
792
+ shopping_cart
793
+ shovel
794
+ shower_cap
795
+ shower_curtain
796
+ ski
797
+ ski_mask
798
+ sleeping_bag
799
+ slide_rule
800
+ sliding_door
801
+ slot
802
+ snorkel
803
+ snowmobile
804
+ snowplow
805
+ soap_dispenser
806
+ soccer_ball
807
+ sock
808
+ solar_dish
809
+ sombrero
810
+ soup_bowl
811
+ space_bar
812
+ space_heater
813
+ space_shuttle
814
+ spatula
815
+ speedboat
816
+ spider_web
817
+ spindle
818
+ sports_car
819
+ spotlight
820
+ stage
821
+ steam_locomotive
822
+ steel_arch_bridge
823
+ steel_drum
824
+ stethoscope
825
+ stole
826
+ stone_wall
827
+ stopwatch
828
+ stove
829
+ strainer
830
+ streetcar
831
+ stretcher
832
+ studio_couch
833
+ stupa
834
+ submarine
835
+ suit
836
+ sundial
837
+ sunglass
838
+ sunglasses
839
+ sunscreen
840
+ suspension_bridge
841
+ swab
842
+ sweatshirt
843
+ swimming_trunks
844
+ swing
845
+ switch
846
+ syringe
847
+ table_lamp
848
+ tank
849
+ tape_player
850
+ teapot
851
+ teddy
852
+ television
853
+ tennis_ball
854
+ thatch
855
+ theater_curtain
856
+ thimble
857
+ thresher
858
+ throne
859
+ tile_roof
860
+ toaster
861
+ tobacco_shop
862
+ toilet_seat
863
+ torch
864
+ totem_pole
865
+ tow_truck
866
+ toyshop
867
+ tractor
868
+ trailer_truck
869
+ tray
870
+ trench_coat
871
+ tricycle
872
+ trimaran
873
+ tripod
874
+ triumphal_arch
875
+ trolleybus
876
+ trombone
877
+ tub
878
+ turnstile
879
+ typewriter_keyboard
880
+ umbrella
881
+ unicycle
882
+ upright
883
+ vacuum
884
+ vase
885
+ vault
886
+ velvet
887
+ vending_machine
888
+ vestment
889
+ viaduct
890
+ violin
891
+ volleyball
892
+ waffle_iron
893
+ wall_clock
894
+ wallet
895
+ wardrobe
896
+ warplane
897
+ washbasin
898
+ washer
899
+ water_bottle
900
+ water_jug
901
+ water_tower
902
+ whiskey_jug
903
+ whistle
904
+ wig
905
+ window_screen
906
+ window_shade
907
+ Windsor_tie
908
+ wine_bottle
909
+ wing
910
+ wok
911
+ wooden_spoon
912
+ wool
913
+ worm_fence
914
+ wreck
915
+ yawl
916
+ yurt
917
+ web_site
918
+ comic_book
919
+ crossword_puzzle
920
+ street_sign
921
+ traffic_light
922
+ book_jacket
923
+ menu
924
+ plate
925
+ guacamole
926
+ consomme
927
+ hot_pot
928
+ trifle
929
+ ice_cream
930
+ ice_lolly
931
+ French_loaf
932
+ bagel
933
+ pretzel
934
+ cheeseburger
935
+ hotdog
936
+ mashed_potato
937
+ head_cabbage
938
+ broccoli
939
+ cauliflower
940
+ zucchini
941
+ spaghetti_squash
942
+ acorn_squash
943
+ butternut_squash
944
+ cucumber
945
+ artichoke
946
+ bell_pepper
947
+ cardoon
948
+ mushroom
949
+ Granny_Smith
950
+ strawberry
951
+ orange
952
+ lemon
953
+ fig
954
+ pineapple
955
+ banana
956
+ jackfruit
957
+ custard_apple
958
+ pomegranate
959
+ hay
960
+ carbonara
961
+ chocolate_sauce
962
+ dough
963
+ meat_loaf
964
+ pizza
965
+ potpie
966
+ burrito
967
+ red_wine
968
+ espresso
969
+ cup
970
+ eggnog
971
+ alp
972
+ bubble
973
+ cliff
974
+ coral_reef
975
+ geyser
976
+ lakeside
977
+ promontory
978
+ sandbar
979
+ seashore
980
+ valley
981
+ volcano
982
+ ballplayer
983
+ groom
984
+ scuba_diver
985
+ rapeseed
986
+ daisy
987
+ yellow_ladys_slipper
988
+ corn
989
+ acorn
990
+ hip
991
+ buckeye
992
+ coral_fungus
993
+ agaric
994
+ gyromitra
995
+ stinkhorn
996
+ earthstar
997
+ hen-of-the-woods
998
+ bolete
999
+ ear
1000
+ toilet_tissue