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LVIS Dataset

The LVIS dataset is a large-scale, fine-grained vocabulary-level annotation dataset developed and released by Facebook AI Research (FAIR). It is primarily used as a research benchmark for object detection and instance segmentation with a large vocabulary of categories, aiming to drive further advancements in computer vision field.



Watch: YOLO World training workflow with LVIS dataset

LVIS Dataset example images

Key Features

  • LVIS contains 160k images and 2M instance annotations for object detection, segmentation, and captioning tasks.
  • The dataset comprises 1203 object categories, including common objects like cars, bicycles, and animals, as well as more specific categories such as umbrellas, handbags, and sports equipment.
  • Annotations include object bounding boxes, segmentation masks, and captions for each image.
  • LVIS provides standardized evaluation metrics like mean Average Precision (mAP) for object detection, and mean Average Recall (mAR) for segmentation tasks, making it suitable for comparing model performance.
  • LVIS uses exactly the same images as COCO dataset, but with different splits and different annotations.

Dataset Structure

The LVIS dataset is split into three subsets:

  1. Train: This subset contains 100k images for training object detection, segmentation, and captioning models.
  2. Val: This subset has 20k images used for validation purposes during model training.
  3. Minival: This subset is exactly the same as COCO val2017 set which has 5k images used for validation purposes during model training.
  4. Test: This subset consists of 20k images used for testing and benchmarking the trained models. Ground truth annotations for this subset are not publicly available, and the results are submitted to the LVIS evaluation server for performance evaluation.

Applications

The LVIS dataset is widely used for training and evaluating deep learning models in object detection (such as YOLO, Faster R-CNN, and SSD), instance segmentation (such as Mask R-CNN). The dataset's diverse set of object categories, large number of annotated images, and standardized evaluation metrics make it an essential resource for computer vision researchers and practitioners.

Dataset YAML

A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the LVIS dataset, the lvis.yaml file is maintained at https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/lvis.yaml.

ultralytics/cfg/datasets/lvis.yaml

# Ultralytics YOLO 🚀, AGPL-3.0 license
# LVIS dataset http://www.lvisdataset.org by Facebook AI Research.
# Documentation: https://docs.ultralytics.com/datasets/detect/lvis/
# Example usage: yolo train data=lvis.yaml
# parent
# ├── ultralytics
# └── datasets
#     └── lvis  ← downloads here (20.1 GB)

# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/lvis # dataset root dir
train: train.txt # train images (relative to 'path') 100170 images
val: val.txt # val images (relative to 'path') 19809 images
minival: minival.txt # minval images (relative to 'path') 5000 images

names:
  0: aerosol can/spray can
  1: air conditioner
  2: airplane/aeroplane
  3: alarm clock
  4: alcohol/alcoholic beverage
  5: alligator/gator
  6: almond
  7: ambulance
  8: amplifier
  9: anklet/ankle bracelet
  10: antenna/aerial/transmitting aerial
  11: apple
  12: applesauce
  13: apricot
  14: apron
  15: aquarium/fish tank
  16: arctic/arctic type of shoe/galosh/golosh/rubber/rubber type of shoe/gumshoe
  17: armband
  18: armchair
  19: armoire
  20: armor/armour
  21: artichoke
  22: trash can/garbage can/wastebin/dustbin/trash barrel/trash bin
  23: ashtray
  24: asparagus
  25: atomizer/atomiser/spray/sprayer/nebulizer/nebuliser
  26: avocado
  27: award/accolade
  28: awning
  29: ax/axe
  30: baboon
  31: baby buggy/baby carriage/perambulator/pram/stroller
  32: basketball backboard
  33: backpack/knapsack/packsack/rucksack/haversack
  34: handbag/purse/pocketbook
  35: suitcase/baggage/luggage
  36: bagel/beigel
  37: bagpipe
  38: baguet/baguette
  39: bait/lure
  40: ball
  41: ballet skirt/tutu
  42: balloon
  43: bamboo
  44: banana
  45: Band Aid
  46: bandage
  47: bandanna/bandana
  48: banjo
  49: banner/streamer
  50: barbell
  51: barge
  52: barrel/cask
  53: barrette
  54: barrow/garden cart/lawn cart/wheelbarrow
  55: baseball base
  56: baseball
  57: baseball bat
  58: baseball cap/jockey cap/golf cap
  59: baseball glove/baseball mitt
  60: basket/handbasket
  61: basketball
  62: bass horn/sousaphone/tuba
  63: bat/bat animal
  64: bath mat
  65: bath towel
  66: bathrobe
  67: bathtub/bathing tub
  68: batter/batter food
  69: battery
  70: beachball
  71: bead
  72: bean curd/tofu
  73: beanbag
  74: beanie/beany
  75: bear
  76: bed
  77: bedpan
  78: bedspread/bedcover/bed covering/counterpane/spread
  79: cow
  80: beef/beef food/boeuf/boeuf food
  81: beeper/pager
  82: beer bottle
  83: beer can
  84: beetle
  85: bell
  86: bell pepper/capsicum
  87: belt
  88: belt buckle
  89: bench
  90: beret
  91: bib
  92: Bible
  93: bicycle/bike/bike bicycle
  94: visor/vizor
  95: billboard
  96: binder/ring-binder
  97: binoculars/field glasses/opera glasses
  98: bird
  99: birdfeeder
  100: birdbath
  101: birdcage
  102: birdhouse
  103: birthday cake
  104: birthday card
  105: pirate flag
  106: black sheep
  107: blackberry
  108: blackboard/chalkboard
  109: blanket
  110: blazer/sport jacket/sport coat/sports jacket/sports coat
  111: blender/liquidizer/liquidiser
  112: blimp
  113: blinker/flasher
  114: blouse
  115: blueberry
  116: gameboard
  117: boat/ship/ship boat
  118: bob/bobber/bobfloat
  119: bobbin/spool/reel
  120: bobby pin/hairgrip
  121: boiled egg/coddled egg
  122: bolo tie/bolo/bola tie/bola
  123: deadbolt
  124: bolt
  125: bonnet
  126: book
  127: bookcase
  128: booklet/brochure/leaflet/pamphlet
  129: bookmark/bookmarker
  130: boom microphone/microphone boom
  131: boot
  132: bottle
  133: bottle opener
  134: bouquet
  135: bow/bow weapon
  136: bow/bow decorative ribbons
  137: bow-tie/bowtie
  138: bowl
  139: pipe bowl
  140: bowler hat/bowler/derby hat/derby/plug hat
  141: bowling ball
  142: box
  143: boxing glove
  144: suspenders
  145: bracelet/bangle
  146: brass plaque
  147: brassiere/bra/bandeau
  148: bread-bin/breadbox
  149: bread
  150: breechcloth/breechclout/loincloth
  151: bridal gown/wedding gown/wedding dress
  152: briefcase
  153: broccoli
  154: broach
  155: broom
  156: brownie
  157: brussels sprouts
  158: bubble gum
  159: bucket/pail
  160: horse buggy
  161: horned cow
  162: bulldog
  163: bulldozer/dozer
  164: bullet train
  165: bulletin board/notice board
  166: bulletproof vest
  167: bullhorn/megaphone
  168: bun/roll
  169: bunk bed
  170: buoy
  171: burrito
  172: bus/bus vehicle/autobus/charabanc/double-decker/motorbus/motorcoach
  173: business card
  174: butter
  175: butterfly
  176: button
  177: cab/cab taxi/taxi/taxicab
  178: cabana
  179: cabin car/caboose
  180: cabinet
  181: locker/storage locker
  182: cake
  183: calculator
  184: calendar
  185: calf
  186: camcorder
  187: camel
  188: camera
  189: camera lens
  190: camper/camper vehicle/camping bus/motor home
  191: can/tin can
  192: can opener/tin opener
  193: candle/candlestick
  194: candle holder
  195: candy bar
  196: candy cane
  197: walking cane
  198: canister/canister
  199: canoe
  200: cantaloup/cantaloupe
  201: canteen
  202: cap/cap headwear
  203: bottle cap/cap/cap container lid
  204: cape
  205: cappuccino/coffee cappuccino
  206: car/car automobile/auto/auto automobile/automobile
  207: railcar/railcar part of a train/railway car/railway car part of a train/railroad car/railroad car part of a train
  208: elevator car
  209: car battery/automobile battery
  210: identity card
  211: card
  212: cardigan
  213: cargo ship/cargo vessel
  214: carnation
  215: horse carriage
  216: carrot
  217: tote bag
  218: cart
  219: carton
  220: cash register/register/register for cash transactions
  221: casserole
  222: cassette
  223: cast/plaster cast/plaster bandage
  224: cat
  225: cauliflower
  226: cayenne/cayenne spice/cayenne pepper/cayenne pepper spice/red pepper/red pepper spice
  227: CD player
  228: celery
  229: cellular telephone/cellular phone/cellphone/mobile phone/smart phone
  230: chain mail/ring mail/chain armor/chain armour/ring armor/ring armour
  231: chair
  232: chaise longue/chaise/daybed
  233: chalice
  234: chandelier
  235: chap
  236: checkbook/chequebook
  237: checkerboard
  238: cherry
  239: chessboard
  240: chicken/chicken animal
  241: chickpea/garbanzo
  242: chili/chili vegetable/chili pepper/chili pepper vegetable/chilli/chilli vegetable/chilly/chilly vegetable/chile/chile vegetable
  243: chime/gong
  244: chinaware
  245: crisp/crisp potato chip/potato chip
  246: poker chip
  247: chocolate bar
  248: chocolate cake
  249: chocolate milk
  250: chocolate mousse
  251: choker/collar/neckband
  252: chopping board/cutting board/chopping block
  253: chopstick
  254: Christmas tree
  255: slide
  256: cider/cyder
  257: cigar box
  258: cigarette
  259: cigarette case/cigarette pack
  260: cistern/water tank
  261: clarinet
  262: clasp
  263: cleansing agent/cleanser/cleaner
  264: cleat/cleat for securing rope
  265: clementine
  266: clip
  267: clipboard
  268: clippers/clippers for plants
  269: cloak
  270: clock/timepiece/timekeeper
  271: clock tower
  272: clothes hamper/laundry basket/clothes basket
  273: clothespin/clothes peg
  274: clutch bag
  275: coaster
  276: coat
  277: coat hanger/clothes hanger/dress hanger
  278: coatrack/hatrack
  279: cock/rooster
  280: cockroach
  281: cocoa/cocoa beverage/hot chocolate/hot chocolate beverage/drinking chocolate
  282: coconut/cocoanut
  283: coffee maker/coffee machine
  284: coffee table/cocktail table
  285: coffeepot
  286: coil
  287: coin
  288: colander/cullender
  289: coleslaw/slaw
  290: coloring material/colouring material
  291: combination lock
  292: pacifier/teething ring
  293: comic book
  294: compass
  295: computer keyboard/keyboard/keyboard computer
  296: condiment
  297: cone/traffic cone
  298: control/controller
  299: convertible/convertible automobile
  300: sofa bed
  301: cooker
  302: cookie/cooky/biscuit/biscuit cookie
  303: cooking utensil
  304: cooler/cooler for food/ice chest
  305: cork/cork bottle plug/bottle cork
  306: corkboard
  307: corkscrew/bottle screw
  308: edible corn/corn/maize
  309: cornbread
  310: cornet/horn/trumpet
  311: cornice/valance/valance board/pelmet
  312: cornmeal
  313: corset/girdle
  314: costume
  315: cougar/puma/catamount/mountain lion/panther
  316: coverall
  317: cowbell
  318: cowboy hat/ten-gallon hat
  319: crab/crab animal
  320: crabmeat
  321: cracker
  322: crape/crepe/French pancake
  323: crate
  324: crayon/wax crayon
  325: cream pitcher
  326: crescent roll/croissant
  327: crib/cot
  328: crock pot/earthenware jar
  329: crossbar
  330: crouton
  331: crow
  332: crowbar/wrecking bar/pry bar
  333: crown
  334: crucifix
  335: cruise ship/cruise liner
  336: police cruiser/patrol car/police car/squad car
  337: crumb
  338: crutch
  339: cub/cub animal
  340: cube/square block
  341: cucumber/cuke
  342: cufflink
  343: cup
  344: trophy cup
  345: cupboard/closet
  346: cupcake
  347: hair curler/hair roller/hair crimper
  348: curling iron
  349: curtain/drapery
  350: cushion
  351: cylinder
  352: cymbal
  353: dagger
  354: dalmatian
  355: dartboard
  356: date/date fruit
  357: deck chair/beach chair
  358: deer/cervid
  359: dental floss/floss
  360: desk
  361: detergent
  362: diaper
  363: diary/journal
  364: die/dice
  365: dinghy/dory/rowboat
  366: dining table
  367: tux/tuxedo
  368: dish
  369: dish antenna
  370: dishrag/dishcloth
  371: dishtowel/tea towel
  372: dishwasher/dishwashing machine
  373: dishwasher detergent/dishwashing detergent/dishwashing liquid/dishsoap
  374: dispenser
  375: diving board
  376: Dixie cup/paper cup
  377: dog
  378: dog collar
  379: doll
  380: dollar/dollar bill/one dollar bill
  381: dollhouse/doll's house
  382: dolphin
  383: domestic ass/donkey
  384: doorknob/doorhandle
  385: doormat/welcome mat
  386: doughnut/donut
  387: dove
  388: dragonfly
  389: drawer
  390: underdrawers/boxers/boxershorts
  391: dress/frock
  392: dress hat/high hat/opera hat/silk hat/top hat
  393: dress suit
  394: dresser
  395: drill
  396: drone
  397: dropper/eye dropper
  398: drum/drum musical instrument
  399: drumstick
  400: duck
  401: duckling
  402: duct tape
  403: duffel bag/duffle bag/duffel/duffle
  404: dumbbell
  405: dumpster
  406: dustpan
  407: eagle
  408: earphone/earpiece/headphone
  409: earplug
  410: earring
  411: easel
  412: eclair
  413: eel
  414: egg/eggs
  415: egg roll/spring roll
  416: egg yolk/yolk/yolk egg
  417: eggbeater/eggwhisk
  418: eggplant/aubergine
  419: electric chair
  420: refrigerator
  421: elephant
  422: elk/moose
  423: envelope
  424: eraser
  425: escargot
  426: eyepatch
  427: falcon
  428: fan
  429: faucet/spigot/tap
  430: fedora
  431: ferret
  432: Ferris wheel
  433: ferry/ferryboat
  434: fig/fig fruit
  435: fighter jet/fighter aircraft/attack aircraft
  436: figurine
  437: file cabinet/filing cabinet
  438: file/file tool
  439: fire alarm/smoke alarm
  440: fire engine/fire truck
  441: fire extinguisher/extinguisher
  442: fire hose
  443: fireplace
  444: fireplug/fire hydrant/hydrant
  445: first-aid kit
  446: fish
  447: fish/fish food
  448: fishbowl/goldfish bowl
  449: fishing rod/fishing pole
  450: flag
  451: flagpole/flagstaff
  452: flamingo
  453: flannel
  454: flap
  455: flash/flashbulb
  456: flashlight/torch
  457: fleece
  458: flip-flop/flip-flop sandal
  459: flipper/flipper footwear/fin/fin footwear
  460: flower arrangement/floral arrangement
  461: flute glass/champagne flute
  462: foal
  463: folding chair
  464: food processor
  465: football/football American
  466: football helmet
  467: footstool/footrest
  468: fork
  469: forklift
  470: freight car
  471: French toast
  472: freshener/air freshener
  473: frisbee
  474: frog/toad/toad frog
  475: fruit juice
  476: frying pan/frypan/skillet
  477: fudge
  478: funnel
  479: futon
  480: gag/muzzle
  481: garbage
  482: garbage truck
  483: garden hose
  484: gargle/mouthwash
  485: gargoyle
  486: garlic/ail
  487: gasmask/respirator/gas helmet
  488: gazelle
  489: gelatin/jelly
  490: gemstone
  491: generator
  492: giant panda/panda/panda bear
  493: gift wrap
  494: ginger/gingerroot
  495: giraffe
  496: cincture/sash/waistband/waistcloth
  497: glass/glass drink container/drinking glass
  498: globe
  499: glove
  500: goat
  501: goggles
  502: goldfish
  503: golf club/golf-club
  504: golfcart
  505: gondola/gondola boat
  506: goose
  507: gorilla
  508: gourd
  509: grape
  510: grater
  511: gravestone/headstone/tombstone
  512: gravy boat/gravy holder
  513: green bean
  514: green onion/spring onion/scallion
  515: griddle
  516: grill/grille/grillwork/radiator grille
  517: grits/hominy grits
  518: grizzly/grizzly bear
  519: grocery bag
  520: guitar
  521: gull/seagull
  522: gun
  523: hairbrush
  524: hairnet
  525: hairpin
  526: halter top
  527: ham/jambon/gammon
  528: hamburger/beefburger/burger
  529: hammer
  530: hammock
  531: hamper
  532: hamster
  533: hair dryer
  534: hand glass/hand mirror
  535: hand towel/face towel
  536: handcart/pushcart/hand truck
  537: handcuff
  538: handkerchief
  539: handle/grip/handgrip
  540: handsaw/carpenter's saw
  541: hardback book/hardcover book
  542: harmonium/organ/organ musical instrument/reed organ/reed organ musical instrument
  543: hat
  544: hatbox
  545: veil
  546: headband
  547: headboard
  548: headlight/headlamp
  549: headscarf
  550: headset
  551: headstall/headstall for horses/headpiece/headpiece for horses
  552: heart
  553: heater/warmer
  554: helicopter
  555: helmet
  556: heron
  557: highchair/feeding chair
  558: hinge
  559: hippopotamus
  560: hockey stick
  561: hog/pig
  562: home plate/home plate baseball/home base/home base baseball
  563: honey
  564: fume hood/exhaust hood
  565: hook
  566: hookah/narghile/nargileh/sheesha/shisha/water pipe
  567: hornet
  568: horse
  569: hose/hosepipe
  570: hot-air balloon
  571: hotplate
  572: hot sauce
  573: hourglass
  574: houseboat
  575: hummingbird
  576: hummus/humus/hommos/hoummos/humous
  577: polar bear
  578: icecream
  579: popsicle
  580: ice maker
  581: ice pack/ice bag
  582: ice skate
  583: igniter/ignitor/lighter
  584: inhaler/inhalator
  585: iPod
  586: iron/iron for clothing/smoothing iron/smoothing iron for clothing
  587: ironing board
  588: jacket
  589: jam
  590: jar
  591: jean/blue jean/denim
  592: jeep/landrover
  593: jelly bean/jelly egg
  594: jersey/T-shirt/tee shirt
  595: jet plane/jet-propelled plane
  596: jewel/gem/precious stone
  597: jewelry/jewellery
  598: joystick
  599: jumpsuit
  600: kayak
  601: keg
  602: kennel/doghouse
  603: kettle/boiler
  604: key
  605: keycard
  606: kilt
  607: kimono
  608: kitchen sink
  609: kitchen table
  610: kite
  611: kitten/kitty
  612: kiwi fruit
  613: knee pad
  614: knife
  615: knitting needle
  616: knob
  617: knocker/knocker on a door/doorknocker
  618: koala/koala bear
  619: lab coat/laboratory coat
  620: ladder
  621: ladle
  622: ladybug/ladybeetle/ladybird beetle
  623: lamb/lamb animal
  624: lamb-chop/lambchop
  625: lamp
  626: lamppost
  627: lampshade
  628: lantern
  629: lanyard/laniard
  630: laptop computer/notebook computer
  631: lasagna/lasagne
  632: latch
  633: lawn mower
  634: leather
  635: legging/legging clothing/leging/leging clothing/leg covering
  636: Lego/Lego set
  637: legume
  638: lemon
  639: lemonade
  640: lettuce
  641: license plate/numberplate
  642: life buoy/lifesaver/life belt/life ring
  643: life jacket/life vest
  644: lightbulb
  645: lightning rod/lightning conductor
  646: lime
  647: limousine
  648: lion
  649: lip balm
  650: liquor/spirits/hard liquor/liqueur/cordial
  651: lizard
  652: log
  653: lollipop
  654: speaker/speaker stereo equipment
  655: loveseat
  656: machine gun
  657: magazine
  658: magnet
  659: mail slot
  660: mailbox/mailbox at home/letter box/letter box at home
  661: mallard
  662: mallet
  663: mammoth
  664: manatee
  665: mandarin orange
  666: manager/through
  667: manhole
  668: map
  669: marker
  670: martini
  671: mascot
  672: mashed potato
  673: masher
  674: mask/facemask
  675: mast
  676: mat/mat gym equipment/gym mat
  677: matchbox
  678: mattress
  679: measuring cup
  680: measuring stick/ruler/ruler measuring stick/measuring rod
  681: meatball
  682: medicine
  683: melon
  684: microphone
  685: microscope
  686: microwave oven
  687: milestone/milepost
  688: milk
  689: milk can
  690: milkshake
  691: minivan
  692: mint candy
  693: mirror
  694: mitten
  695: mixer/mixer kitchen tool/stand mixer
  696: money
  697: monitor/monitor computer equipment
  698: monkey
  699: motor
  700: motor scooter/scooter
  701: motor vehicle/automotive vehicle
  702: motorcycle
  703: mound/mound baseball/pitcher's mound
  704: mouse/mouse computer equipment/computer mouse
  705: mousepad
  706: muffin
  707: mug
  708: mushroom
  709: music stool/piano stool
  710: musical instrument/instrument/instrument musical
  711: nailfile
  712: napkin/table napkin/serviette
  713: neckerchief
  714: necklace
  715: necktie/tie/tie necktie
  716: needle
  717: nest
  718: newspaper/paper/paper newspaper
  719: newsstand
  720: nightshirt/nightwear/sleepwear/nightclothes
  721: nosebag/nosebag for animals/feedbag
  722: noseband/noseband for animals/nosepiece/nosepiece for animals
  723: notebook
  724: notepad
  725: nut
  726: nutcracker
  727: oar
  728: octopus/octopus food
  729: octopus/octopus animal
  730: oil lamp/kerosene lamp/kerosine lamp
  731: olive oil
  732: omelet/omelette
  733: onion
  734: orange/orange fruit
  735: orange juice
  736: ostrich
  737: ottoman/pouf/pouffe/hassock
  738: oven
  739: overalls/overalls clothing
  740: owl
  741: packet
  742: inkpad/inking pad/stamp pad
  743: pad
  744: paddle/boat paddle
  745: padlock
  746: paintbrush
  747: painting
  748: pajamas/pyjamas
  749: palette/pallet
  750: pan/pan for cooking/cooking pan
  751: pan/pan metal container
  752: pancake
  753: pantyhose
  754: papaya
  755: paper plate
  756: paper towel
  757: paperback book/paper-back book/softback book/soft-cover book
  758: paperweight
  759: parachute
  760: parakeet/parrakeet/parroket/paraquet/paroquet/parroquet
  761: parasail/parasail sports
  762: parasol/sunshade
  763: parchment
  764: parka/anorak
  765: parking meter
  766: parrot
  767: passenger car/passenger car part of a train/coach/coach part of a train
  768: passenger ship
  769: passport
  770: pastry
  771: patty/patty food
  772: pea/pea food
  773: peach
  774: peanut butter
  775: pear
  776: peeler/peeler tool for fruit and vegetables
  777: wooden leg/pegleg
  778: pegboard
  779: pelican
  780: pen
  781: pencil
  782: pencil box/pencil case
  783: pencil sharpener
  784: pendulum
  785: penguin
  786: pennant
  787: penny/penny coin
  788: pepper/peppercorn
  789: pepper mill/pepper grinder
  790: perfume
  791: persimmon
  792: person/baby/child/boy/girl/man/woman/human
  793: pet
  794: pew/pew church bench/church bench
  795: phonebook/telephone book/telephone directory
  796: phonograph record/phonograph recording/record/record phonograph recording
  797: piano
  798: pickle
  799: pickup truck
  800: pie
  801: pigeon
  802: piggy bank/penny bank
  803: pillow
  804: pin/pin non jewelry
  805: pineapple
  806: pinecone
  807: ping-pong ball
  808: pinwheel
  809: tobacco pipe
  810: pipe/piping
  811: pistol/handgun
  812: pita/pita bread/pocket bread
  813: pitcher/pitcher vessel for liquid/ewer
  814: pitchfork
  815: pizza
  816: place mat
  817: plate
  818: platter
  819: playpen
  820: pliers/plyers
  821: plow/plow farm equipment/plough/plough farm equipment
  822: plume
  823: pocket watch
  824: pocketknife
  825: poker/poker fire stirring tool/stove poker/fire hook
  826: pole/post
  827: polo shirt/sport shirt
  828: poncho
  829: pony
  830: pool table/billiard table/snooker table
  831: pop/pop soda/soda/soda pop/tonic/soft drink
  832: postbox/postbox public/mailbox/mailbox public
  833: postcard/postal card/mailing-card
  834: poster/placard
  835: pot
  836: flowerpot
  837: potato
  838: potholder
  839: pottery/clayware
  840: pouch
  841: power shovel/excavator/digger
  842: prawn/shrimp
  843: pretzel
  844: printer/printing machine
  845: projectile/projectile weapon/missile
  846: projector
  847: propeller/propellor
  848: prune
  849: pudding
  850: puffer/puffer fish/pufferfish/blowfish/globefish
  851: puffin
  852: pug-dog
  853: pumpkin
  854: puncher
  855: puppet/marionette
  856: puppy
  857: quesadilla
  858: quiche
  859: quilt/comforter
  860: rabbit
  861: race car/racing car
  862: racket/racquet
  863: radar
  864: radiator
  865: radio receiver/radio set/radio/tuner/tuner radio
  866: radish/daikon
  867: raft
  868: rag doll
  869: raincoat/waterproof jacket
  870: ram/ram animal
  871: raspberry
  872: rat
  873: razorblade
  874: reamer/reamer juicer/juicer/juice reamer
  875: rearview mirror
  876: receipt
  877: recliner/reclining chair/lounger/lounger chair
  878: record player/phonograph/phonograph record player/turntable
  879: reflector
  880: remote control
  881: rhinoceros
  882: rib/rib food
  883: rifle
  884: ring
  885: river boat
  886: road map
  887: robe
  888: rocking chair
  889: rodent
  890: roller skate
  891: Rollerblade
  892: rolling pin
  893: root beer
  894: router/router computer equipment
  895: rubber band/elastic band
  896: runner/runner carpet
  897: plastic bag/paper bag
  898: saddle/saddle on an animal
  899: saddle blanket/saddlecloth/horse blanket
  900: saddlebag
  901: safety pin
  902: sail
  903: salad
  904: salad plate/salad bowl
  905: salami
  906: salmon/salmon fish
  907: salmon/salmon food
  908: salsa
  909: saltshaker
  910: sandal/sandal type of shoe
  911: sandwich
  912: satchel
  913: saucepan
  914: saucer
  915: sausage
  916: sawhorse/sawbuck
  917: saxophone
  918: scale/scale measuring instrument
  919: scarecrow/strawman
  920: scarf
  921: school bus
  922: scissors
  923: scoreboard
  924: scraper
  925: screwdriver
  926: scrubbing brush
  927: sculpture
  928: seabird/seafowl
  929: seahorse
  930: seaplane/hydroplane
  931: seashell
  932: sewing machine
  933: shaker
  934: shampoo
  935: shark
  936: sharpener
  937: Sharpie
  938: shaver/shaver electric/electric shaver/electric razor
  939: shaving cream/shaving soap
  940: shawl
  941: shears
  942: sheep
  943: shepherd dog/sheepdog
  944: sherbert/sherbet
  945: shield
  946: shirt
  947: shoe/sneaker/sneaker type of shoe/tennis shoe
  948: shopping bag
  949: shopping cart
  950: short pants/shorts/shorts clothing/trunks/trunks clothing
  951: shot glass
  952: shoulder bag
  953: shovel
  954: shower head
  955: shower cap
  956: shower curtain
  957: shredder/shredder for paper
  958: signboard
  959: silo
  960: sink
  961: skateboard
  962: skewer
  963: ski
  964: ski boot
  965: ski parka/ski jacket
  966: ski pole
  967: skirt
  968: skullcap
  969: sled/sledge/sleigh
  970: sleeping bag
  971: sling/sling bandage/triangular bandage
  972: slipper/slipper footwear/carpet slipper/carpet slipper footwear
  973: smoothie
  974: snake/serpent
  975: snowboard
  976: snowman
  977: snowmobile
  978: soap
  979: soccer ball
  980: sock
  981: sofa/couch/lounge
  982: softball
  983: solar array/solar battery/solar panel
  984: sombrero
  985: soup
  986: soup bowl
  987: soupspoon
  988: sour cream/soured cream
  989: soya milk/soybean milk/soymilk
  990: space shuttle
  991: sparkler/sparkler fireworks
  992: spatula
  993: spear/lance
  994: spectacles/specs/eyeglasses/glasses
  995: spice rack
  996: spider
  997: crawfish/crayfish
  998: sponge
  999: spoon
  1000: sportswear/athletic wear/activewear
  1001: spotlight
  1002: squid/squid food/calamari/calamary
  1003: squirrel
  1004: stagecoach
  1005: stapler/stapler stapling machine
  1006: starfish/sea star
  1007: statue/statue sculpture
  1008: steak/steak food
  1009: steak knife
  1010: steering wheel
  1011: stepladder
  1012: step stool
  1013: stereo/stereo sound system
  1014: stew
  1015: stirrer
  1016: stirrup
  1017: stool
  1018: stop sign
  1019: brake light
  1020: stove/kitchen stove/range/range kitchen appliance/kitchen range/cooking stove
  1021: strainer
  1022: strap
  1023: straw/straw for drinking/drinking straw
  1024: strawberry
  1025: street sign
  1026: streetlight/street lamp
  1027: string cheese
  1028: stylus
  1029: subwoofer
  1030: sugar bowl
  1031: sugarcane/sugarcane plant
  1032: suit/suit clothing
  1033: sunflower
  1034: sunglasses
  1035: sunhat
  1036: surfboard
  1037: sushi
  1038: mop
  1039: sweat pants
  1040: sweatband
  1041: sweater
  1042: sweatshirt
  1043: sweet potato
  1044: swimsuit/swimwear/bathing suit/swimming costume/bathing costume/swimming trunks/bathing trunks
  1045: sword
  1046: syringe
  1047: Tabasco sauce
  1048: table-tennis table/ping-pong table
  1049: table
  1050: table lamp
  1051: tablecloth
  1052: tachometer
  1053: taco
  1054: tag
  1055: taillight/rear light
  1056: tambourine
  1057: army tank/armored combat vehicle/armoured combat vehicle
  1058: tank/tank storage vessel/storage tank
  1059: tank top/tank top clothing
  1060: tape/tape sticky cloth or paper
  1061: tape measure/measuring tape
  1062: tapestry
  1063: tarp
  1064: tartan/plaid
  1065: tassel
  1066: tea bag
  1067: teacup
  1068: teakettle
  1069: teapot
  1070: teddy bear
  1071: telephone/phone/telephone set
  1072: telephone booth/phone booth/call box/telephone box/telephone kiosk
  1073: telephone pole/telegraph pole/telegraph post
  1074: telephoto lens/zoom lens
  1075: television camera/tv camera
  1076: television set/tv/tv set
  1077: tennis ball
  1078: tennis racket
  1079: tequila
  1080: thermometer
  1081: thermos bottle
  1082: thermostat
  1083: thimble
  1084: thread/yarn
  1085: thumbtack/drawing pin/pushpin
  1086: tiara
  1087: tiger
  1088: tights/tights clothing/leotards
  1089: timer/stopwatch
  1090: tinfoil
  1091: tinsel
  1092: tissue paper
  1093: toast/toast food
  1094: toaster
  1095: toaster oven
  1096: toilet
  1097: toilet tissue/toilet paper/bathroom tissue
  1098: tomato
  1099: tongs
  1100: toolbox
  1101: toothbrush
  1102: toothpaste
  1103: toothpick
  1104: cover
  1105: tortilla
  1106: tow truck
  1107: towel
  1108: towel rack/towel rail/towel bar
  1109: toy
  1110: tractor/tractor farm equipment
  1111: traffic light
  1112: dirt bike
  1113: trailer truck/tractor trailer/trucking rig/articulated lorry/semi truck
  1114: train/train railroad vehicle/railroad train
  1115: trampoline
  1116: tray
  1117: trench coat
  1118: triangle/triangle musical instrument
  1119: tricycle
  1120: tripod
  1121: trousers/pants/pants clothing
  1122: truck
  1123: truffle/truffle chocolate/chocolate truffle
  1124: trunk
  1125: vat
  1126: turban
  1127: turkey/turkey food
  1128: turnip
  1129: turtle
  1130: turtleneck/turtleneck clothing/polo-neck
  1131: typewriter
  1132: umbrella
  1133: underwear/underclothes/underclothing/underpants
  1134: unicycle
  1135: urinal
  1136: urn
  1137: vacuum cleaner
  1138: vase
  1139: vending machine
  1140: vent/blowhole/air vent
  1141: vest/waistcoat
  1142: videotape
  1143: vinegar
  1144: violin/fiddle
  1145: vodka
  1146: volleyball
  1147: vulture
  1148: waffle
  1149: waffle iron
  1150: wagon
  1151: wagon wheel
  1152: walking stick
  1153: wall clock
  1154: wall socket/wall plug/electric outlet/electrical outlet/outlet/electric receptacle
  1155: wallet/billfold
  1156: walrus
  1157: wardrobe
  1158: washbasin/basin/basin for washing/washbowl/washstand/handbasin
  1159: automatic washer/washing machine
  1160: watch/wristwatch
  1161: water bottle
  1162: water cooler
  1163: water faucet/water tap/tap/tap water faucet
  1164: water heater/hot-water heater
  1165: water jug
  1166: water gun/squirt gun
  1167: water scooter/sea scooter/jet ski
  1168: water ski
  1169: water tower
  1170: watering can
  1171: watermelon
  1172: weathervane/vane/vane weathervane/wind vane
  1173: webcam
  1174: wedding cake/bridecake
  1175: wedding ring/wedding band
  1176: wet suit
  1177: wheel
  1178: wheelchair
  1179: whipped cream
  1180: whistle
  1181: wig
  1182: wind chime
  1183: windmill
  1184: window box/window box for plants
  1185: windshield wiper/windscreen wiper/wiper/wiper for windshield or screen
  1186: windsock/air sock/air-sleeve/wind sleeve/wind cone
  1187: wine bottle
  1188: wine bucket/wine cooler
  1189: wineglass
  1190: blinder/blinder for horses
  1191: wok
  1192: wolf
  1193: wooden spoon
  1194: wreath
  1195: wrench/spanner
  1196: wristband
  1197: wristlet/wrist band
  1198: yacht
  1199: yogurt/yoghurt/yoghourt
  1200: yoke/yoke animal equipment
  1201: zebra
  1202: zucchini/courgette

# Download script/URL (optional)
download: |
  from ultralytics.utils.downloads import download
  from pathlib import Path

  # Download labels
  dir = Path(yaml['path'])  # dataset root dir
  url = 'https://github.com/ultralytics/assets/releases/download/v0.0.0/'
  urls = [url + 'lvis-labels-segments.zip']  # labels
  download(urls, dir=dir.parent)
  # Download data
  urls = ['http://images.cocodataset.org/zips/train2017.zip',  # 19G, 118k images
          'http://images.cocodataset.org/zips/val2017.zip',  # 1G, 5k images
          'http://images.cocodataset.org/zips/test2017.zip']  # 7G, 41k images (optional)
  download(urls, dir=dir / 'images', threads=3)

Usage

To train a YOLO11n model on the LVIS dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model Training page.

Train Example

from ultralytics import YOLO

# Load a model
model = YOLO("yolo11n.pt")  # load a pretrained model (recommended for training)

# Train the model
results = model.train(data="lvis.yaml", epochs=100, imgsz=640)
# Start training from a pretrained *.pt model
yolo detect train data=lvis.yaml model=yolo11n.pt epochs=100 imgsz=640

Sample Images and Annotations

The LVIS dataset contains a diverse set of images with various object categories and complex scenes. Here are some examples of images from the dataset, along with their corresponding annotations:

LVIS Dataset sample image

  • Mosaiced Image: This image demonstrates a training batch composed of mosaiced dataset images. Mosaicing is a technique used during training that combines multiple images into a single image to increase the variety of objects and scenes within each training batch. This helps improve the model's ability to generalize to different object sizes, aspect ratios, and contexts.

The example showcases the variety and complexity of the images in the LVIS dataset and the benefits of using mosaicing during the training process.

Citations and Acknowledgments

If you use the LVIS dataset in your research or development work, please cite the following paper:

@inproceedings{gupta2019lvis,
  title={LVIS: A Dataset for Large Vocabulary Instance Segmentation},
  author={Gupta, Agrim and Dollar, Piotr and Girshick, Ross},
  booktitle={Proceedings of the {IEEE} Conference on Computer Vision and Pattern Recognition},
  year={2019}
}

We would like to acknowledge the LVIS Consortium for creating and maintaining this valuable resource for the computer vision community. For more information about the LVIS dataset and its creators, visit the LVIS dataset website.

FAQ

What is the LVIS dataset, and how is it used in computer vision?

The LVIS dataset is a large-scale dataset with fine-grained vocabulary-level annotations developed by Facebook AI Research (FAIR). It is primarily used for object detection and instance segmentation, featuring over 1203 object categories and 2 million instance annotations. Researchers and practitioners use it to train and benchmark models like Ultralytics YOLO for advanced computer vision tasks. The dataset's extensive size and diversity make it an essential resource for pushing the boundaries of model performance in detection and segmentation.

How can I train a YOLO11n model using the LVIS dataset?

To train a YOLO11n model on the LVIS dataset for 100 epochs with an image size of 640, follow the example below. This process utilizes Ultralytics' framework, which offers comprehensive training features.

Train Example

from ultralytics import YOLO

# Load a model
model = YOLO("yolo11n.pt")  # load a pretrained model (recommended for training)

# Train the model
results = model.train(data="lvis.yaml", epochs=100, imgsz=640)
# Start training from a pretrained *.pt model
yolo detect train data=lvis.yaml model=yolo11n.pt epochs=100 imgsz=640

For detailed training configurations, refer to the Training documentation.

How does the LVIS dataset differ from the COCO dataset?

The images in the LVIS dataset are the same as those in the COCO dataset, but the two differ in terms of splitting and annotations. LVIS provides a larger and more detailed vocabulary with 1203 object categories compared to COCO's 80 categories. Additionally, LVIS focuses on annotation completeness and diversity, aiming to push the limits of object detection and instance segmentation models by offering more nuanced and comprehensive data.

Why should I use Ultralytics YOLO for training on the LVIS dataset?

Ultralytics YOLO models, including the latest YOLO11, are optimized for real-time object detection with state-of-the-art accuracy and speed. They support a wide range of annotations, such as the fine-grained ones provided by the LVIS dataset, making them ideal for advanced computer vision applications. Moreover, Ultralytics offers seamless integration with various training, validation, and prediction modes, ensuring efficient model development and deployment.

Can I see some sample annotations from the LVIS dataset?

Yes, the LVIS dataset includes a variety of images with diverse object categories and complex scenes. Here is an example of a sample image along with its annotations:

LVIS Dataset sample image

This mosaiced image demonstrates a training batch composed of multiple dataset images combined into one. Mosaicing increases the variety of objects and scenes within each training batch, enhancing the model's ability to generalize across different contexts. For more details on the LVIS dataset, explore the LVIS dataset documentation.

📅 Created 7 months ago ✏️ Updated 1 month ago

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