open_images_labels.md

Open Images 600 labels (object detection / bounding box) in alphabetical order

Training set

Labels 0 to 59 [totals]	Labels 60 to 119 [totals]	Labels 180 to 239 [totals]	Labels 300 to 359 [totals]	Labels 360 to 419 [totals]	Labels 420 to 479 [totals]	Labels 480 to 539 [totals]	Labels 540 to 599 [totals]
Accordion [955]	Bowl [4507]	Envelope [177]	Ladybug [734]	Oven [637]	Remote control [236]	Spatula [64]	Tomato [6254]
Adhesive tape [255]	Bowling equipment [3846]	Eraser [53]	Lamp [3663]	Owl [1663]	Reptile [578]	Spice rack [131]	Tool [2075]
Aircraft [1898]	Box [5364]	Face powder [80]	Land vehicle [81108]	Oyster [1038]	Rhinoceros [724]	Spider [2033]	Toothbrush [219]
Airplane [21285]	Boy [87555]	Facial tissue holder [20]	Lantern [5429]	Paddle [6951]	Rifle [2540]	Spoon [1709]	Torch [20]
Alarm clock [169]	Brassiere [1694]	Falcon [1717]	Laptop [9327]	Palm tree [42026]	Ring binder [84]	Sports equipment [44900]	Towel [338]
Alpaca [829]	Bread [3846]	Fashion accessory [91024]	Lavender (Plant) [6472]	Pancake [775]	Rocket [918]	Sports uniform [19396]	Tower [67945]
Ambulance [447]	Briefcase [162]	Fast food [24991]	Lemon [1756]	Panda [882]	Roller skates [5476]	Squash (Plant) [375]	Toy [70963]
Animal [17442]	Broccoli [1128]	Fax [28]	Leopard [811]	Paper cutter [4]	Rose [12053]	Squid [221]	Traffic light [7426]
Ant [925]	Bronze sculpture [2748]	Fedora [3660]	Light bulb [1816]	Paper towel [210]	Rugby ball [294]	Squirrel [1940]	Traffic sign [6112]
Antelope [1568]	Brown bear [647]	Filing cabinet [374]	Light switch [97]	Parachute [2672]	Ruler [253]	Stairs [5981]	Train [13050]
Apple [3898]	Building [178634]	Fire hydrant [432]	Lighthouse [1518]	Parking meter [209]	Salad [3088]	Stapler [59]	Training bench [194]
Armadillo [56]	Bull [1736]	Fireplace [711]	Lily [2252]	Parrot [2388]	Salt and pepper shakers [180]	Starfish [639]	Treadmill [247]
Artichoke [376]	Burrito [262]	Fish [23195]	Limousine [366]	Pasta [769]	Sandal [2938]	Stationary bicycle [338]	Tree [1051344]
Auto part [13586]	Bus [11927]	Flag [29246]	Lion [1653]	Pastry [5852]	Sandwich [1157]	Stethoscope [78]	Tree house [110]
Axe [148]	Bust [1060]	Flashlight [88]	Lipstick [1343]	Peach [756]	Saucer [2819]	Stool [1254]	Tripod [1446]
Backpack [1216]	Butterfly [10127]	Flower [345296]	Lizard [2120]	Pear [923]	Saxophone [1208]	Stop sign [394]	Trombone [953]
Bagel [640]	Cabbage [435]	Flowerpot [22760]	Lobster [597]	Pen [1705]	Scale [139]	Strawberry [7944]	Trousers [8481]
Baked goods [23010]	Cabinetry [9191]	Flute [362]	Loveseat [631]	Pencil case [132]	Scarf [2303]	Street light [44697]	Truck [12135]
Balance beam [326]	Cake [5784]	Flying disc [249]	Luggage and bags [2220]	Pencil sharpener [21]	Scissors [399]	Stretcher [174]	Trumpet [1546]
Ball [6845]	Cake stand [337]	Food [88422]	Lynx [237]	Penguin [4197]	Scoreboard [517]	Studio couch [1889]	Turkey [734]
Balloon [13505]	Calculator [210]	Food processor [192]	Magpie [145]	Perfume [363]	Scorpion [204]	Submarine [81]	Turtle [205]
Banana [1612]	Camel [1340]	Football [5097]	Mammal [156154]	Person [1034721]	Screwdriver [85]	Submarine sandwich [273]	Umbrella [7204]
Band-aid [36]	Camera [6404]	Football helmet [11705]	Man [1418594]	Personal care [409]	Sculpture [34533]	Suit [110848]	Unicycle [194]
Banjo [264]	Can opener [7]	Footwear [744474]	Mango [429]	Personal flotation device [3678]	Sea lion [1823]	Suitcase [630]	Van [7720]
Barge [983]	Canary [387]	Fork [1687]	Maple [4923]	Piano [1374]	Sea turtle [1132]	Sun hat [6979]	Vase [2468]
Barrel [2086]	Candle [5886]	Fountain [3691]	Maracas [10]	Picnic basket [425]	Seafood [3063]	Sunglasses [23996]	Vegetable [18621]
Baseball bat [1228]	Candy [2261]	Fox [565]	Marine invertebrates [9112]	Picture frame [11957]	Seahorse [314]	Surfboard [2594]	Vehicle [50959]
Baseball glove [2529]	Cannon [1087]	French fries [2114]	Marine mammal [1746]	Pig [1613]	Seat belt [461]	Sushi [2088]	Vehicle registration plate [7852]
Bat (Animal) [655]	Canoe [4543]	French horn [1239]	Measuring cup [74]	Pillow [3508]	Segway [565]	Swan [4523]	Violin [2828]
Bathroom accessory [2678]	Cantaloupe [166]	Frog [1608]	Mechanical fan [681]	Pineapple [660]	Serving tray [118]	Swim cap [615]	Volleyball (Ball) [661]
Bathroom cabinet [358]	Car [248075]	Fruit [26236]	Medical equipment [2060]	Pitcher (Container) [347]	Sewing machine [453]	Swimming pool [3881]	Waffle [710]
Bathtub [545]	Carnivore [3501]	Frying pan [377]	Microphone [27272]	Pizza [2008]	Shark [625]	Swimwear [10079]	Waffle iron [31]
Beaker [168]	Carrot [1456]	Furniture [38527]	Microwave oven [485]	Pizza cutter [20]	Sheep [3438]	Sword [567]	Wall clock [1067]
Bear [427]	Cart [2755]	Garden Asparagus [387]	Milk [214]	Plant [267913]	Shelf [22899]	Syringe [127]	Wardrobe [238]
Bed [3563]	Cassette deck [74]	Gas stove [526]	Miniskirt [954]	Plastic bag [986]	Shellfish [1287]	Table [85691]	Washing machine [655]
Bee [11401]	Castle [4310]	Giraffe [1431]	Mirror [1572]	Plate [5416]	Shirt [7465]	Table tennis racket [849]	Waste container [1807]
Beehive [511]	Cat [15183]	Girl [197155]	Missile [603]	Platter [3462]	Shorts [16981]	Tablet computer [975]	Watch [1903]
Beer [9565]	Cat furniture [208]	Glasses [57946]	Mixer [216]	Plumbing fixture [481]	Shotgun [580]	Tableware [41086]	Watercraft [5202]
Beetle [3523]	Caterpillar [884]	Glove [1198]	Mixing bowl [1005]	Polar bear [664]	Shower [235]	Taco [677]	Watermelon [844]
Bell pepper [802]	Cattle [11603]	Goat [2075]	Mobile phone [6365]	Pomegranate [677]	Shrimp [1856]	Tank [1716]	Weapon [2960]
Belt [422]	Ceiling fan [478]	Goggles [9636]	Monkey [3026]	Popcorn [362]	Sink [1648]	Tap [1695]	Whale [1014]
Bench [7229]	Cello [2004]	Goldfish [2204]	Moths and butterflies [1857]	Porch [3854]	Skateboard [1810]	Tart [973]	Wheel [340639]
Bicycle [40161]	Centipede [280]	Golf ball [434]	Motorcycle [13382]	Porcupine [229]	Ski [3505]	Taxi [4199]	Wheelchair [1464]
Bicycle helmet [15952]	Chainsaw [130]	Golf cart [595]	Mouse [857]	Poster [23566]	Skirt [1259]	Tea [1342]	Whisk [180]
Bicycle wheel [59521]	Chair [132483]	Gondola [1868]	Muffin [4608]	Potato [599]	Skull [2661]	Teapot [632]	Whiteboard [1003]
Bidet [440]	Cheese [1560]	Goose [8436]	Mug [2272]	Power plugs and sockets [290]	Skunk [56]	Teddy bear [1587]	Willow [735]
Billboard [9823]	Cheetah [715]	Grape [2787]	Mule [1117]	Pressure cooker [14]	Skyscraper [81261]	Telephone [274]	Window [503467]
Billiard table [912]	Chest of drawers [1526]	Grapefruit [1283]	Mushroom [4497]	Pretzel [294]	Slow cooker [125]	Television [3789]	Window blind [570]
Binoculars [123]	Chicken [3059]	Grinder [14]	Musical instrument [16503]	Printer [263]	Snack [37374]	Tennis ball [502]	Wine [15400]
Bird [47921]	Chime [41]	Guacamole [224]	Musical keyboard [1771]	Pumpkin [6150]	Snail [943]	Tennis racket [985]	Wine glass [12934]
Blender [235]	Chisel [33]	Guitar [25896]	Nail (Construction) [491]	Punching bag [336]	Snake [1378]	Tent [6907]	Wine rack [254]
Blue jay [259]	Chopsticks [617]	Hair dryer [27]	Necklace [2735]	Rabbit [1641]	Snowboard [944]	Tiara [411]	Winter melon [43]
Boat [79113]	Christmas tree [4243]	Hair spray [10]	Nightstand [1125]	Raccoon [381]	Snowman [770]	Tick [143]	Wok [730]
Bomb [8]	Clock [1222]	Hamburger [1486]	Oboe [162]	Racket [281]	Snowmobile [366]	Tie [10545]	Woman [767337]
Book [41280]	Closet [661]	Hammer [139]	Office building [4986]	Radish [688]	Snowplow [300]	Tiger [1260]	Wood-burning stove [300]
Bookcase [5307]	Clothing [1438128]	Hamster [546]	Office supplies [6198]	Ratchet (Device) [327]	Soap dispenser [78]	Tin can [2988]	Woodpecker [515]
Boot [3132]	Coat [6523]	Hand dryer [70]	Orange [6195]	Raven [567]	Sock [1425]	Tire [122615]	Worm [270]
Bottle [40188]	Cocktail [4458]	Handbag [2495]	Organ (Musical Instrument) [398]	Rays and skates [485]	Sofa bed [1501]	Toaster [73]	Wrench [204]
Bottle opener [21]	Cocktail shaker [27]	Handgun [727]	Ostrich [640]	Red panda [423]	Sombrero [651]	Toilet [1099]	Zebra [1120]
Bow and arrow [594]	Coconut [874]	Harbor seal [2084]	Otter [752]	Refrigerator [592]	Sparrow [1651]	Toilet paper [377]	Zucchini [1098]

Train your own model by following the steps on this notebook.

As some classes don't have a lot of samples available (e.g. "Cocktail shaker" has only 27, not sure why you would want a object detector trained on this, but I'm not here to judge :D), you may need to augment your dataset. One easy option is to use colab_utils augment_dataset. You can find a usage example on this notebook.