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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

## 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 🚀 AGPL-3.0 License - https://ultralytics.com/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: 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 # minival 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 pathlib import Path

      from ultralytics.utils.downloads import download

      # Download labels
      dir = Path(yaml["path"])  # dataset root dir
      url = "https://github.com/ultralytics/assets/releases/download/v0.0.0/"
      urls = [f"{url}lvis-labels-segments.zip"]
      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

Python CLI

    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:

- 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:

BibTeX

    @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

Python CLI

    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:

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 1 year ago ✏️ Updated 6 months ago

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