category.py 20 KB

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  1. # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. from __future__ import absolute_import
  15. from __future__ import division
  16. from __future__ import print_function
  17. import os
  18. from paddlex.ppdet.data.source.voc import pascalvoc_label
  19. from paddlex.ppdet.data.source.widerface import widerface_label
  20. from paddlex.ppdet.utils.logger import setup_logger
  21. logger = setup_logger(__name__)
  22. __all__ = ['get_categories']
  23. def get_categories(metric_type, anno_file=None, arch=None):
  24. """
  25. Get class id to category id map and category id
  26. to category name map from annotation file.
  27. Args:
  28. metric_type (str): metric type, currently support 'coco', 'voc', 'oid'
  29. and 'widerface'.
  30. anno_file (str): annotation file path
  31. """
  32. if arch == 'keypoint_arch':
  33. return (None, {'id': 'keypoint'})
  34. if metric_type.lower() == 'coco':
  35. if anno_file and os.path.isfile(anno_file):
  36. # lazy import pycocotools here
  37. from pycocotools.coco import COCO
  38. coco = COCO(anno_file)
  39. cats = coco.loadCats(coco.getCatIds())
  40. clsid2catid = {i: cat['id'] for i, cat in enumerate(cats)}
  41. catid2name = {cat['id']: cat['name'] for cat in cats}
  42. return clsid2catid, catid2name
  43. # anno file not exist, load default categories of COCO17
  44. else:
  45. return _coco17_category()
  46. elif metric_type.lower() == 'voc':
  47. if anno_file and os.path.isfile(anno_file):
  48. cats = []
  49. with open(anno_file) as f:
  50. for line in f.readlines():
  51. cats.append(line.strip())
  52. if cats[0] == 'background':
  53. cats = cats[1:]
  54. clsid2catid = {i: i for i in range(len(cats))}
  55. catid2name = {i: name for i, name in enumerate(cats)}
  56. return clsid2catid, catid2name
  57. # anno file not exist, load default categories of
  58. # VOC all 20 categories
  59. else:
  60. return _vocall_category()
  61. elif metric_type.lower() == 'oid':
  62. if anno_file and os.path.isfile(anno_file):
  63. logger.warn("only default categories support for OID19")
  64. return _oid19_category()
  65. elif metric_type.lower() == 'widerface':
  66. return _widerface_category()
  67. elif metric_type.lower() == 'keypointtopdowncocoeval':
  68. return (None, {'id': 'keypoint'})
  69. elif metric_type.lower() in ['mot', 'motdet', 'reid']:
  70. return _mot_category()
  71. else:
  72. raise ValueError("unknown metric type {}".format(metric_type))
  73. def _mot_category():
  74. """
  75. Get class id to category id map and category id
  76. to category name map of mot dataset
  77. """
  78. label_map = {'person': 0}
  79. label_map = sorted(label_map.items(), key=lambda x: x[1])
  80. cats = [l[0] for l in label_map]
  81. clsid2catid = {i: i for i in range(len(cats))}
  82. catid2name = {i: name for i, name in enumerate(cats)}
  83. return clsid2catid, catid2name
  84. def _coco17_category():
  85. """
  86. Get class id to category id map and category id
  87. to category name map of COCO2017 dataset
  88. """
  89. clsid2catid = {
  90. 1: 1,
  91. 2: 2,
  92. 3: 3,
  93. 4: 4,
  94. 5: 5,
  95. 6: 6,
  96. 7: 7,
  97. 8: 8,
  98. 9: 9,
  99. 10: 10,
  100. 11: 11,
  101. 12: 13,
  102. 13: 14,
  103. 14: 15,
  104. 15: 16,
  105. 16: 17,
  106. 17: 18,
  107. 18: 19,
  108. 19: 20,
  109. 20: 21,
  110. 21: 22,
  111. 22: 23,
  112. 23: 24,
  113. 24: 25,
  114. 25: 27,
  115. 26: 28,
  116. 27: 31,
  117. 28: 32,
  118. 29: 33,
  119. 30: 34,
  120. 31: 35,
  121. 32: 36,
  122. 33: 37,
  123. 34: 38,
  124. 35: 39,
  125. 36: 40,
  126. 37: 41,
  127. 38: 42,
  128. 39: 43,
  129. 40: 44,
  130. 41: 46,
  131. 42: 47,
  132. 43: 48,
  133. 44: 49,
  134. 45: 50,
  135. 46: 51,
  136. 47: 52,
  137. 48: 53,
  138. 49: 54,
  139. 50: 55,
  140. 51: 56,
  141. 52: 57,
  142. 53: 58,
  143. 54: 59,
  144. 55: 60,
  145. 56: 61,
  146. 57: 62,
  147. 58: 63,
  148. 59: 64,
  149. 60: 65,
  150. 61: 67,
  151. 62: 70,
  152. 63: 72,
  153. 64: 73,
  154. 65: 74,
  155. 66: 75,
  156. 67: 76,
  157. 68: 77,
  158. 69: 78,
  159. 70: 79,
  160. 71: 80,
  161. 72: 81,
  162. 73: 82,
  163. 74: 84,
  164. 75: 85,
  165. 76: 86,
  166. 77: 87,
  167. 78: 88,
  168. 79: 89,
  169. 80: 90
  170. }
  171. catid2name = {
  172. 0: 'background',
  173. 1: 'person',
  174. 2: 'bicycle',
  175. 3: 'car',
  176. 4: 'motorcycle',
  177. 5: 'airplane',
  178. 6: 'bus',
  179. 7: 'train',
  180. 8: 'truck',
  181. 9: 'boat',
  182. 10: 'traffic light',
  183. 11: 'fire hydrant',
  184. 13: 'stop sign',
  185. 14: 'parking meter',
  186. 15: 'bench',
  187. 16: 'bird',
  188. 17: 'cat',
  189. 18: 'dog',
  190. 19: 'horse',
  191. 20: 'sheep',
  192. 21: 'cow',
  193. 22: 'elephant',
  194. 23: 'bear',
  195. 24: 'zebra',
  196. 25: 'giraffe',
  197. 27: 'backpack',
  198. 28: 'umbrella',
  199. 31: 'handbag',
  200. 32: 'tie',
  201. 33: 'suitcase',
  202. 34: 'frisbee',
  203. 35: 'skis',
  204. 36: 'snowboard',
  205. 37: 'sports ball',
  206. 38: 'kite',
  207. 39: 'baseball bat',
  208. 40: 'baseball glove',
  209. 41: 'skateboard',
  210. 42: 'surfboard',
  211. 43: 'tennis racket',
  212. 44: 'bottle',
  213. 46: 'wine glass',
  214. 47: 'cup',
  215. 48: 'fork',
  216. 49: 'knife',
  217. 50: 'spoon',
  218. 51: 'bowl',
  219. 52: 'banana',
  220. 53: 'apple',
  221. 54: 'sandwich',
  222. 55: 'orange',
  223. 56: 'broccoli',
  224. 57: 'carrot',
  225. 58: 'hot dog',
  226. 59: 'pizza',
  227. 60: 'donut',
  228. 61: 'cake',
  229. 62: 'chair',
  230. 63: 'couch',
  231. 64: 'potted plant',
  232. 65: 'bed',
  233. 67: 'dining table',
  234. 70: 'toilet',
  235. 72: 'tv',
  236. 73: 'laptop',
  237. 74: 'mouse',
  238. 75: 'remote',
  239. 76: 'keyboard',
  240. 77: 'cell phone',
  241. 78: 'microwave',
  242. 79: 'oven',
  243. 80: 'toaster',
  244. 81: 'sink',
  245. 82: 'refrigerator',
  246. 84: 'book',
  247. 85: 'clock',
  248. 86: 'vase',
  249. 87: 'scissors',
  250. 88: 'teddy bear',
  251. 89: 'hair drier',
  252. 90: 'toothbrush'
  253. }
  254. clsid2catid = {k - 1: v for k, v in clsid2catid.items()}
  255. catid2name.pop(0)
  256. return clsid2catid, catid2name
  257. def _vocall_category():
  258. """
  259. Get class id to category id map and category id
  260. to category name map of mixup voc dataset
  261. """
  262. label_map = pascalvoc_label()
  263. label_map = sorted(label_map.items(), key=lambda x: x[1])
  264. cats = [l[0] for l in label_map]
  265. clsid2catid = {i: i for i in range(len(cats))}
  266. catid2name = {i: name for i, name in enumerate(cats)}
  267. return clsid2catid, catid2name
  268. def _widerface_category():
  269. label_map = widerface_label()
  270. label_map = sorted(label_map.items(), key=lambda x: x[1])
  271. cats = [l[0] for l in label_map]
  272. clsid2catid = {i: i for i in range(len(cats))}
  273. catid2name = {i: name for i, name in enumerate(cats)}
  274. return clsid2catid, catid2name
  275. def _oid19_category():
  276. clsid2catid = {k: k + 1 for k in range(500)}
  277. catid2name = {
  278. 0: "background",
  279. 1: "Infant bed",
  280. 2: "Rose",
  281. 3: "Flag",
  282. 4: "Flashlight",
  283. 5: "Sea turtle",
  284. 6: "Camera",
  285. 7: "Animal",
  286. 8: "Glove",
  287. 9: "Crocodile",
  288. 10: "Cattle",
  289. 11: "House",
  290. 12: "Guacamole",
  291. 13: "Penguin",
  292. 14: "Vehicle registration plate",
  293. 15: "Bench",
  294. 16: "Ladybug",
  295. 17: "Human nose",
  296. 18: "Watermelon",
  297. 19: "Flute",
  298. 20: "Butterfly",
  299. 21: "Washing machine",
  300. 22: "Raccoon",
  301. 23: "Segway",
  302. 24: "Taco",
  303. 25: "Jellyfish",
  304. 26: "Cake",
  305. 27: "Pen",
  306. 28: "Cannon",
  307. 29: "Bread",
  308. 30: "Tree",
  309. 31: "Shellfish",
  310. 32: "Bed",
  311. 33: "Hamster",
  312. 34: "Hat",
  313. 35: "Toaster",
  314. 36: "Sombrero",
  315. 37: "Tiara",
  316. 38: "Bowl",
  317. 39: "Dragonfly",
  318. 40: "Moths and butterflies",
  319. 41: "Antelope",
  320. 42: "Vegetable",
  321. 43: "Torch",
  322. 44: "Building",
  323. 45: "Power plugs and sockets",
  324. 46: "Blender",
  325. 47: "Billiard table",
  326. 48: "Cutting board",
  327. 49: "Bronze sculpture",
  328. 50: "Turtle",
  329. 51: "Broccoli",
  330. 52: "Tiger",
  331. 53: "Mirror",
  332. 54: "Bear",
  333. 55: "Zucchini",
  334. 56: "Dress",
  335. 57: "Volleyball",
  336. 58: "Guitar",
  337. 59: "Reptile",
  338. 60: "Golf cart",
  339. 61: "Tart",
  340. 62: "Fedora",
  341. 63: "Carnivore",
  342. 64: "Car",
  343. 65: "Lighthouse",
  344. 66: "Coffeemaker",
  345. 67: "Food processor",
  346. 68: "Truck",
  347. 69: "Bookcase",
  348. 70: "Surfboard",
  349. 71: "Footwear",
  350. 72: "Bench",
  351. 73: "Necklace",
  352. 74: "Flower",
  353. 75: "Radish",
  354. 76: "Marine mammal",
  355. 77: "Frying pan",
  356. 78: "Tap",
  357. 79: "Peach",
  358. 80: "Knife",
  359. 81: "Handbag",
  360. 82: "Laptop",
  361. 83: "Tent",
  362. 84: "Ambulance",
  363. 85: "Christmas tree",
  364. 86: "Eagle",
  365. 87: "Limousine",
  366. 88: "Kitchen & dining room table",
  367. 89: "Polar bear",
  368. 90: "Tower",
  369. 91: "Football",
  370. 92: "Willow",
  371. 93: "Human head",
  372. 94: "Stop sign",
  373. 95: "Banana",
  374. 96: "Mixer",
  375. 97: "Binoculars",
  376. 98: "Dessert",
  377. 99: "Bee",
  378. 100: "Chair",
  379. 101: "Wood-burning stove",
  380. 102: "Flowerpot",
  381. 103: "Beaker",
  382. 104: "Oyster",
  383. 105: "Woodpecker",
  384. 106: "Harp",
  385. 107: "Bathtub",
  386. 108: "Wall clock",
  387. 109: "Sports uniform",
  388. 110: "Rhinoceros",
  389. 111: "Beehive",
  390. 112: "Cupboard",
  391. 113: "Chicken",
  392. 114: "Man",
  393. 115: "Blue jay",
  394. 116: "Cucumber",
  395. 117: "Balloon",
  396. 118: "Kite",
  397. 119: "Fireplace",
  398. 120: "Lantern",
  399. 121: "Missile",
  400. 122: "Book",
  401. 123: "Spoon",
  402. 124: "Grapefruit",
  403. 125: "Squirrel",
  404. 126: "Orange",
  405. 127: "Coat",
  406. 128: "Punching bag",
  407. 129: "Zebra",
  408. 130: "Billboard",
  409. 131: "Bicycle",
  410. 132: "Door handle",
  411. 133: "Mechanical fan",
  412. 134: "Ring binder",
  413. 135: "Table",
  414. 136: "Parrot",
  415. 137: "Sock",
  416. 138: "Vase",
  417. 139: "Weapon",
  418. 140: "Shotgun",
  419. 141: "Glasses",
  420. 142: "Seahorse",
  421. 143: "Belt",
  422. 144: "Watercraft",
  423. 145: "Window",
  424. 146: "Giraffe",
  425. 147: "Lion",
  426. 148: "Tire",
  427. 149: "Vehicle",
  428. 150: "Canoe",
  429. 151: "Tie",
  430. 152: "Shelf",
  431. 153: "Picture frame",
  432. 154: "Printer",
  433. 155: "Human leg",
  434. 156: "Boat",
  435. 157: "Slow cooker",
  436. 158: "Croissant",
  437. 159: "Candle",
  438. 160: "Pancake",
  439. 161: "Pillow",
  440. 162: "Coin",
  441. 163: "Stretcher",
  442. 164: "Sandal",
  443. 165: "Woman",
  444. 166: "Stairs",
  445. 167: "Harpsichord",
  446. 168: "Stool",
  447. 169: "Bus",
  448. 170: "Suitcase",
  449. 171: "Human mouth",
  450. 172: "Juice",
  451. 173: "Skull",
  452. 174: "Door",
  453. 175: "Violin",
  454. 176: "Chopsticks",
  455. 177: "Digital clock",
  456. 178: "Sunflower",
  457. 179: "Leopard",
  458. 180: "Bell pepper",
  459. 181: "Harbor seal",
  460. 182: "Snake",
  461. 183: "Sewing machine",
  462. 184: "Goose",
  463. 185: "Helicopter",
  464. 186: "Seat belt",
  465. 187: "Coffee cup",
  466. 188: "Microwave oven",
  467. 189: "Hot dog",
  468. 190: "Countertop",
  469. 191: "Serving tray",
  470. 192: "Dog bed",
  471. 193: "Beer",
  472. 194: "Sunglasses",
  473. 195: "Golf ball",
  474. 196: "Waffle",
  475. 197: "Palm tree",
  476. 198: "Trumpet",
  477. 199: "Ruler",
  478. 200: "Helmet",
  479. 201: "Ladder",
  480. 202: "Office building",
  481. 203: "Tablet computer",
  482. 204: "Toilet paper",
  483. 205: "Pomegranate",
  484. 206: "Skirt",
  485. 207: "Gas stove",
  486. 208: "Cookie",
  487. 209: "Cart",
  488. 210: "Raven",
  489. 211: "Egg",
  490. 212: "Burrito",
  491. 213: "Goat",
  492. 214: "Kitchen knife",
  493. 215: "Skateboard",
  494. 216: "Salt and pepper shakers",
  495. 217: "Lynx",
  496. 218: "Boot",
  497. 219: "Platter",
  498. 220: "Ski",
  499. 221: "Swimwear",
  500. 222: "Swimming pool",
  501. 223: "Drinking straw",
  502. 224: "Wrench",
  503. 225: "Drum",
  504. 226: "Ant",
  505. 227: "Human ear",
  506. 228: "Headphones",
  507. 229: "Fountain",
  508. 230: "Bird",
  509. 231: "Jeans",
  510. 232: "Television",
  511. 233: "Crab",
  512. 234: "Microphone",
  513. 235: "Home appliance",
  514. 236: "Snowplow",
  515. 237: "Beetle",
  516. 238: "Artichoke",
  517. 239: "Jet ski",
  518. 240: "Stationary bicycle",
  519. 241: "Human hair",
  520. 242: "Brown bear",
  521. 243: "Starfish",
  522. 244: "Fork",
  523. 245: "Lobster",
  524. 246: "Corded phone",
  525. 247: "Drink",
  526. 248: "Saucer",
  527. 249: "Carrot",
  528. 250: "Insect",
  529. 251: "Clock",
  530. 252: "Castle",
  531. 253: "Tennis racket",
  532. 254: "Ceiling fan",
  533. 255: "Asparagus",
  534. 256: "Jaguar",
  535. 257: "Musical instrument",
  536. 258: "Train",
  537. 259: "Cat",
  538. 260: "Rifle",
  539. 261: "Dumbbell",
  540. 262: "Mobile phone",
  541. 263: "Taxi",
  542. 264: "Shower",
  543. 265: "Pitcher",
  544. 266: "Lemon",
  545. 267: "Invertebrate",
  546. 268: "Turkey",
  547. 269: "High heels",
  548. 270: "Bust",
  549. 271: "Elephant",
  550. 272: "Scarf",
  551. 273: "Barrel",
  552. 274: "Trombone",
  553. 275: "Pumpkin",
  554. 276: "Box",
  555. 277: "Tomato",
  556. 278: "Frog",
  557. 279: "Bidet",
  558. 280: "Human face",
  559. 281: "Houseplant",
  560. 282: "Van",
  561. 283: "Shark",
  562. 284: "Ice cream",
  563. 285: "Swim cap",
  564. 286: "Falcon",
  565. 287: "Ostrich",
  566. 288: "Handgun",
  567. 289: "Whiteboard",
  568. 290: "Lizard",
  569. 291: "Pasta",
  570. 292: "Snowmobile",
  571. 293: "Light bulb",
  572. 294: "Window blind",
  573. 295: "Muffin",
  574. 296: "Pretzel",
  575. 297: "Computer monitor",
  576. 298: "Horn",
  577. 299: "Furniture",
  578. 300: "Sandwich",
  579. 301: "Fox",
  580. 302: "Convenience store",
  581. 303: "Fish",
  582. 304: "Fruit",
  583. 305: "Earrings",
  584. 306: "Curtain",
  585. 307: "Grape",
  586. 308: "Sofa bed",
  587. 309: "Horse",
  588. 310: "Luggage and bags",
  589. 311: "Desk",
  590. 312: "Crutch",
  591. 313: "Bicycle helmet",
  592. 314: "Tick",
  593. 315: "Airplane",
  594. 316: "Canary",
  595. 317: "Spatula",
  596. 318: "Watch",
  597. 319: "Lily",
  598. 320: "Kitchen appliance",
  599. 321: "Filing cabinet",
  600. 322: "Aircraft",
  601. 323: "Cake stand",
  602. 324: "Candy",
  603. 325: "Sink",
  604. 326: "Mouse",
  605. 327: "Wine",
  606. 328: "Wheelchair",
  607. 329: "Goldfish",
  608. 330: "Refrigerator",
  609. 331: "French fries",
  610. 332: "Drawer",
  611. 333: "Treadmill",
  612. 334: "Picnic basket",
  613. 335: "Dice",
  614. 336: "Cabbage",
  615. 337: "Football helmet",
  616. 338: "Pig",
  617. 339: "Person",
  618. 340: "Shorts",
  619. 341: "Gondola",
  620. 342: "Honeycomb",
  621. 343: "Doughnut",
  622. 344: "Chest of drawers",
  623. 345: "Land vehicle",
  624. 346: "Bat",
  625. 347: "Monkey",
  626. 348: "Dagger",
  627. 349: "Tableware",
  628. 350: "Human foot",
  629. 351: "Mug",
  630. 352: "Alarm clock",
  631. 353: "Pressure cooker",
  632. 354: "Human hand",
  633. 355: "Tortoise",
  634. 356: "Baseball glove",
  635. 357: "Sword",
  636. 358: "Pear",
  637. 359: "Miniskirt",
  638. 360: "Traffic sign",
  639. 361: "Girl",
  640. 362: "Roller skates",
  641. 363: "Dinosaur",
  642. 364: "Porch",
  643. 365: "Human beard",
  644. 366: "Submarine sandwich",
  645. 367: "Screwdriver",
  646. 368: "Strawberry",
  647. 369: "Wine glass",
  648. 370: "Seafood",
  649. 371: "Racket",
  650. 372: "Wheel",
  651. 373: "Sea lion",
  652. 374: "Toy",
  653. 375: "Tea",
  654. 376: "Tennis ball",
  655. 377: "Waste container",
  656. 378: "Mule",
  657. 379: "Cricket ball",
  658. 380: "Pineapple",
  659. 381: "Coconut",
  660. 382: "Doll",
  661. 383: "Coffee table",
  662. 384: "Snowman",
  663. 385: "Lavender",
  664. 386: "Shrimp",
  665. 387: "Maple",
  666. 388: "Cowboy hat",
  667. 389: "Goggles",
  668. 390: "Rugby ball",
  669. 391: "Caterpillar",
  670. 392: "Poster",
  671. 393: "Rocket",
  672. 394: "Organ",
  673. 395: "Saxophone",
  674. 396: "Traffic light",
  675. 397: "Cocktail",
  676. 398: "Plastic bag",
  677. 399: "Squash",
  678. 400: "Mushroom",
  679. 401: "Hamburger",
  680. 402: "Light switch",
  681. 403: "Parachute",
  682. 404: "Teddy bear",
  683. 405: "Winter melon",
  684. 406: "Deer",
  685. 407: "Musical keyboard",
  686. 408: "Plumbing fixture",
  687. 409: "Scoreboard",
  688. 410: "Baseball bat",
  689. 411: "Envelope",
  690. 412: "Adhesive tape",
  691. 413: "Briefcase",
  692. 414: "Paddle",
  693. 415: "Bow and arrow",
  694. 416: "Telephone",
  695. 417: "Sheep",
  696. 418: "Jacket",
  697. 419: "Boy",
  698. 420: "Pizza",
  699. 421: "Otter",
  700. 422: "Office supplies",
  701. 423: "Couch",
  702. 424: "Cello",
  703. 425: "Bull",
  704. 426: "Camel",
  705. 427: "Ball",
  706. 428: "Duck",
  707. 429: "Whale",
  708. 430: "Shirt",
  709. 431: "Tank",
  710. 432: "Motorcycle",
  711. 433: "Accordion",
  712. 434: "Owl",
  713. 435: "Porcupine",
  714. 436: "Sun hat",
  715. 437: "Nail",
  716. 438: "Scissors",
  717. 439: "Swan",
  718. 440: "Lamp",
  719. 441: "Crown",
  720. 442: "Piano",
  721. 443: "Sculpture",
  722. 444: "Cheetah",
  723. 445: "Oboe",
  724. 446: "Tin can",
  725. 447: "Mango",
  726. 448: "Tripod",
  727. 449: "Oven",
  728. 450: "Mouse",
  729. 451: "Barge",
  730. 452: "Coffee",
  731. 453: "Snowboard",
  732. 454: "Common fig",
  733. 455: "Salad",
  734. 456: "Marine invertebrates",
  735. 457: "Umbrella",
  736. 458: "Kangaroo",
  737. 459: "Human arm",
  738. 460: "Measuring cup",
  739. 461: "Snail",
  740. 462: "Loveseat",
  741. 463: "Suit",
  742. 464: "Teapot",
  743. 465: "Bottle",
  744. 466: "Alpaca",
  745. 467: "Kettle",
  746. 468: "Trousers",
  747. 469: "Popcorn",
  748. 470: "Centipede",
  749. 471: "Spider",
  750. 472: "Sparrow",
  751. 473: "Plate",
  752. 474: "Bagel",
  753. 475: "Personal care",
  754. 476: "Apple",
  755. 477: "Brassiere",
  756. 478: "Bathroom cabinet",
  757. 479: "studio couch",
  758. 480: "Computer keyboard",
  759. 481: "Table tennis racket",
  760. 482: "Sushi",
  761. 483: "Cabinetry",
  762. 484: "Street light",
  763. 485: "Towel",
  764. 486: "Nightstand",
  765. 487: "Rabbit",
  766. 488: "Dolphin",
  767. 489: "Dog",
  768. 490: "Jug",
  769. 491: "Wok",
  770. 492: "Fire hydrant",
  771. 493: "Human eye",
  772. 494: "Skyscraper",
  773. 495: "Backpack",
  774. 496: "Potato",
  775. 497: "Paper towel",
  776. 498: "Lifejacket",
  777. 499: "Bicycle wheel",
  778. 500: "Toilet",
  779. }
  780. return clsid2catid, catid2name