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The Auto polygon tool allows you to boost your labeling productivity.
You create a bounding box around the object you wish to label and an AI automatically transforms this bounding box into a precise polygon around your object.
You can refine the automatically generated polygons by simply moving the target keypoint and/or adding inside keypoints and outside keypoints .
This is as simple as moving the target keypoint and/or doing a click inside or outside the created polygon.
Target keypoint. It must always be on the object you wish to label. Else move it on the object.
Outside keypoint. A click inside the polygon will add an outside keypoint and exclude this area from the polygon label.
Inside keypoint. A click outside the polygon will add an inside keypoint and include this area to the polygon label.
Click on to activate the selection mode (or press v for the shortcut)
Click on the polygon you want to edit
Select the polygon edition mode (next to the class selection menu in the top left). You can press e to switch between both edition modes.
You can now drag any points on the contour to adjust the polygon geometry
This edition mode is also illustrated in the above video.
A class is a category in which labels are classified. It helps group similar labels together, which is essential for any labeling project. A class is defined by its name and has its own color to help differentiate it from the others.
When you create a new labeling project, it comes with the default class "None". These are the simple steps you need to take to create more labels
Right-click on an existing label
Click on the search field and write the name of the new class
Press enter or click on the button that says "Create class [New_Class] "
The classes tab in your project space shows all the information about all the classes in your project. The total number of classes is also visible to help you, as well as the number of occurrences for each class. Furthermore, this screen details the keyboard shortcuts that can be used to quickly select the appropriate class.
You can change the name of a class by selecting the edit icon and giving your class a new name.
You can also delete a class and all labels associated with it will be classified as "None".
LabelFlow can accommodate complex taxonomies, allowing users to manage very specific use cases.
The use of the / to separate classes and subclasses is widely used and easily comprehensible: Class/Subclass1/Subclass2
An example schema could be: Object/Material/Defect for infrastructure inspections, or even Object/Type/Material/Defect.
Using this methodology to manage complex taxonomies and use-cases allows for the classes to be easily interpreted once exported.
There are 2 ways to import your images
There are two ways to import images and labels to your dataset.
Import Images from files. Simply Drag and drop the files in the uploader.
Simply paste the image URLs in the Image uploader
These are the simple steps you should follow to import from your database:
Press the Add images button on the top right
Select Import from a list of URLs instead button
Copy and paste the image URLs
Select Start Import
It's that easy. 🔥👌
A bounding box is the simplest type of label that is defined by just two points.
These are the simple steps you need to take to make a bounding box label:
Select the bounding box tool on the left
Click on the outermost edge of the subject of the label
Click the opposite edge of the object to create a rectangle covering the subject
Right-click on the label to select/add its class
Let us take the case that you are making an AI model that identifies rhinos from an image for wildlife protection services. You need to train your model with high-quality labeled images so you can produce an effective tool against poaching. These are the steps you can follow to get prepare the high-quality labeled images.
The first step is to gather a dataset of images containing rhinos.
Navigate to LabelFlow and you will be welcomed with this interface. Press “Start Labeling”. Click on “Create new dataset” and give your dataset a name. Now press “Start Labeling” and enter your dataset.
Press “Add images” and you drop all the images that you will label for this project. You can drag and drop the images onto the screen or paste the URL to your database. You can also drop the URL to your database if your images are on the cloud.
It will lead you to a gallery where you can see all your pictures.
Select the image you would like to label first and away we go!
Select the bounding box tool and click on the edges of the Rhinos you would like to label. Two guiding lines will be available to help you select the edges. Right-click on the bounding box to specify the class of the label. Labels are colored by class for convenience.
Select the small arrow on the drawing tool and choose the polygon tool. Draw a polygon around the rhino and adjust the vertices at the end by dragging them.
Navigate between your images by simply choosing the next image you would like to label or clicking the small arrows at the bottom left. You can also use the left and right arrow keys.
Labels can overlap, intersect or encompass other labels. Zoom in on your images by using the top right button or by using the trackpad. Create as many label classes as you need.
Once you've finished, select the export tool on the top right.
A small pop-up will appear with information about the number of labels and will prompt you to specify the export format, such as COCO.
Select your desired file type and it will download to your device.
Now you are ready to train your AI model! It’s that easy! 👌
The beginner's guide to the image labelling annotation tool LabelFlow
At LabelFlow we are on a mission to build GitHub for Visual Data. We first started building an open source image labeling platform focused on user experience. We are now working on more advanced features to manage datasets and allow you build the next big thing with AI ! You can find the code on Github here, feel free to ping us on Discord as well, there are impactful contributions to bring to the project.
After 5 years building Sterblue, an AI-powered platform for the energy space helping to identify hazards on power grids and wind turbines, LabelFlow founding team figured out that it was possible to bring AI to scale in complex use cases. It usually brings better reliability, more productivity and hence a better user experience but this has a price and there is no secret sauce: the dataset must be large, homogeneous, and accurately labeled. Machine Learning models performance mainly comes from the quality of the datasets, less from the model itself.
Head on over to Quick start and let us take a test case to see how you can leverage LabelFlow to bring your machine learning models to scale today.
The polygon label type is defined by several vertices, which allows the user to accurately label complex shapes.
By definition, polygon labels are closer in shape to the subject of the label than a simple bounding box.
These are the simple steps you need to take to make a polygon label:
Select the small arrow on the drawing tool on the left and select the polygon tool
Click on the outermost edge of the subject of the label
Follow the edges of the subject and select the vertices of the polygon
When you are finished click on the vertex near the pointer and the polygon will be created
Right-click on the label to select/add its class
The classification label type is the simplest and quickest way to label images. As opposed to the bounding box and polygon label types, the classification type doesn't have an associated geometry within the image. This label type simply consists of a general label for the entire image.
These are the simple steps you need to take to make a classification label:
Select the small arrow on the drawing tool on the left and select the classification tool
Click on the label box in the top left of the image or right-click on the image to select/add its class
It's that easy!
Once you have created a label for your object, you may want to change its shape, size, location, or class.
Right-click on the label and select the appropriate class from the pop-up menu.
Select and drag a vertex to move it to correct the shape and size of the label.
If the label you are editing is a polygon, it is possible to add additional vertices to it.
Simply select an edge and drag the vertex that appears on your chosen position.
Click anywhere inside the label and drag it to another position
The DEtection TRansformer (DETR) model was trained by Facebook on the COCO 2017 dataset (118,000 images) and is hosted by Hugging Face. You can find its complete description card here.
DETR - COCO AI Assistant outputs by default bounding boxes around the detected objects. If the detected object class does not exist in the dataset, the AI assistant will create it.
It is possible to transform a bounding box into a polygon by selecting the Post-process option. Note that the inference time will be slightly longer by selecting this option.
DETR - COCO AI Assistant is able to detect 90 different classes of objects (some better than others we must say...!)
person
bicycle
car
motorcycle
airplane
bus
train
truck
boat
trafficlight
firehydrant
streetsign
stopsign
parkingmeter
bench
bird
cat
dog
horse
sheep
cow
elephant
bear
zebra
giraffe
hat
backpack
umbrella
shoe
eyeglasses
handbag
tie
suitcase
frisbee
skis
snowboard
sportsball
kite
baseballbat
baseballglove
skateboard
surfboard
tennisracket
bottle
plate
wineglass
cup
fork
knife
spoon
bowl
banana
apple
sandwich
orange
broccoli
carrot
hotdog
pizza
donut
cake
chair
couch
pottedplant
bed
mirror
diningtable
window
desk
toilet
door
tv
laptop
mouse
remote
keyboard
cellphone
microwave
oven
toaster
sink
refrigerator
blender
book
clock
vase
scissors
teddybear
hairdrier
toothbrush
Online workspaces allow users to collaborate by uploading images to LabelFlow's secure servers, unlocking new levels of productivity. Sign up to use these collaborative tools for free now.
By default, LabelFlow users have one local or offline workspace, where they can label and export their datasets from their computers without ever having to sign in.
Signing in to LabelFlow allows users to create unlimited online workspaces, upload their images to LabelFlow's secure servers and collaborate with teammates. Here's a brief walkthrough of the new Workspace feature.
Choosing the right label type for your image annotation project is important. Classification tags will maximize your labeling productivity, while polygons will boost your AI performance and bounding boxes may be for some an acceptable compromise.
Good news, check the Auto polygons tool which creates a polygon by simply adding a bounding box.
LabelFlow supports the following labeling types:
Image classification
Bounding boxes
Polygons
Auto polygons (a polygon generated from a bounding box)
You can read more about the different label types on our dedicated post:
The AI Assistant tool 🥁 assists (...) you in the labelling process! Each Assistant is an AI trained on a specific task.
For now there are 2 general purpose AI Assistants (more will come, vote below!).
DETR - COCO an object detection AI Assistant trained across 80 classes. More here.
ViT - ImageNet an image classification AI Assistant trained across 1000 classes. More here.
As we are launching this new feature and we want to collect your feedbacks, every plans (Community, Starter, Pro) have access to the current AI Assistants.
If you have specific needs in terms of AI Assistants, upvote or add your own request here ⬇️
Online workspaces allow users to collaborate by uploading images to LabelFlow's secure servers, unlocking new levels of productivity. Sign up to use these collaborative tools.
Each labeling project has its own dataset which is a collection of images that are prepared to be labeled. You can view all the images in your dataset on the Images tab of your project.
You can add images to your dataset by clicking the "add images" button on the top right of the images page.
When you create a new project, you are greeted with the suggestion to add images to your dataset.
Online workspaces allow users to collaborate by uploading images to LabelFlow's secure servers, unlocking new levels of productivity. Sign up to use these collaborative tools for free now.
There are many shortcuts in LabelFlow you can take advantage of to optimize your productivity. Click on the keyboard icon on the top right to see the complete list of shortcuts
Press v to activate the selection tool
Press b to select the bounding box tool
Press p to select the polygon tool
Press k to select the classification tool
Press a to select the Auto-Polygon tool
Press i to select the AI Assistant tool and r to run the AI Assistant
Press c to change the class of the currently selected label
Press del or Backspace to delete the selected label
Press from 0 to 9 to select the corresponding class for the selected label
Press / or f to search for labels in the label class selection
Press ⬅️ Left arrow key to navigate to the previous image
Press ➡️ Right arrow key to navigate to the next image
Press Esc to cancel current action
Press ctrl + z or cmd + z to undo last action
Press ctrl + y, ctrl + shift + y, cmd + y, or cmd + shift + z to redo last action
COCO is a file format for object detections within an image. It describes the boundaries and attributes of labels inside an image which makes it perfect as an input for training AI models.
Once you are finished with your labeling project, select the export tool on the top right.
A small pop-up will appear with information about the number of labels and prompts you to specify the export format. Select the COCO file type and it will download your labels in the COCO format.
As an option, you can export the images together with the COCO detection file in a zip file.
You Only Look Once, or YOLO is a widely used labeling format, where a .txt file is created for each image file in the same directory. Each .txt file contains the annotations for the corresponding image file, that is object class, object coordinates, height, and width.
Once you are finished with your labeling project, select the export tool on the top right.
A small pop-up will appear with information about the number of labels and prompts you to specify the export format. Select the YOLO file type and it will download your labels in the YOLO format.
As an option, you can export the images together with the YOLO detection file in a zip file.
Online workspaces allow users to collaborate by uploading images to LabelFlow's secure servers, unlocking new levels of productivity. Sign up to use these collaborative tools for free now.
The settings tab is where you'll be able to update your workspace's name, your plan and also delete your workspace.
You can change the name of your workspace from the settings tab. Making modifications to the name will also automatically update the Avatar, which helps to quickly identify specific workspaces.
You'll also be able to consult and update your current plan, payment methods and billing information from the settings tab to match your needs.
This is what we call the Danger Zone. You can delete a workspace along with all of its data from the settings tab. In order to delete the workspace for good, you will be prompted to type the workspace's name to avoid any potential accidents.
Simply drag and drop the image files in the image uploader
These are the simple steps you should follow to import from your computer:
Press the Add images button on the top right
Drag and drop your images and/or folders.
Select Start Labeling once the import is finished
It's that easy. 🔥👌
LabelFlow can ingest Labels in the COCO format into a dataset. For that you must drop a COCO .json file in the uploader. The COCO .json file contains the annotations of your dataset images.
Open an existing dataset or create a new one
First import your images
Press the Add images button on the top right
Drag and drop your images in the uploader
Select Start Labeling once the import is finished
Second import your annotations
Press the Add images button again
Drag and drop your annotation file in the COCO format
Select Start Labeling once the import is finished
It's that easy. 🔥👌
How to migrate a dataset to another workspace
Let's imagine you want to move a dataset from a workspace that we'll call old-workspace to new-workspace. For now you'll need to export your dataset in the COCO format and import them back into the new workspace.
Go to your old workspace https://labelflow.ai/old-workspace
Open the dataset you wish to migrate
Click on Export in the top right
Select the COCO format
In the displayed options, choose to export the annotations only, it will save a JSON file to your computer
Click on Create workspace by opening the workspace switcher (top left - or click here)
Name your workspace (it has to be unique across the entire LabelFlow community)
Sign-in if you are not already signed-in
You now have an online workspace in the workspace switcher. Select it.
new-workspaceCreate a new dataset. This dataset is hosted in your new-workspace.
Make sure you have selected your new-workspace in the workspace switcher (see above)
Click on the dataset card to open the image gallery view
Click on the Add images button
Start by uploading the images you had in your old-workspace dataset you have exported at step 1. Once done, close the import modal to come back to the image gallery view.
Click on Add images a 2nd time and drop the COCO (.json) annotation file you have exported at step 1.
That's it 🎉 . Click on your images, your annotations and the classes have been imported.
You should repeat this operation for every dataset you wish to migrate.
Vision Transformer (ViT) model was pre-trained by Google on ImageNet-21k (14 million images, 21,843 classes), and fine-tuned on ImageNet 2012 (1 million images, 1,000 classes). The model is hosted by Hugging Face and you can find its complete description card here.
ViT - ImageNet performs image classification, it add tags corresponding to the detected object onto the image. If the detected object class does not exist in the dataset, the AI assistant will create it.
ViT - ImageNet AI Assistant is able to detect 1000 different classes of objects (some better than others we must say...!).
kit fox, Vulpes macrotis
English setter
Australian terrier
grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus
lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens
Egyptian cat
ibex, Capra ibex
Persian cat
cougar, puma, catamount, mountain lion, painter, panther, Felis concolor
gazelle
porcupine, hedgehog
sea lion
badger
Great Dane
Scottish deerhound, deerhound
killer whale, killer, orca, grampus, sea wolf, Orcinus orca
mink
African elephant, Loxodonta africana
red wolf, maned wolf, Canis rufus, Canis niger
jaguar, panther, Panthera onca, Felis onca
hyena, hyaena
titi, titi monkey
three-toed sloth, ai, Bradypus tridactylus
sorrel
black-footed ferret, ferret, Mustela nigripes
dalmatian, coach dog, carriage dog
Staffordshire bullterrier, Staffordshire bull terrier
Bouvier des Flandres, Bouviers des Flandres
weasel
miniature poodle
bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis
fox squirrel, eastern fox squirrel, Sciurus niger
colobus, colobus monkey
tiger cat
impala, Aepyceros melampus
coyote, prairie wolf, brush wolf, Canis latrans
Yorkshire terrier
Newfoundland, Newfoundland dog
red fox, Vulpes vulpes
hartebeest
grey fox, gray fox, Urocyon cinereoargenteus
Pekinese, Pekingese, Peke
guenon, guenon monkey
mongoose
indri, indris, Indri indri, Indri brevicaudatus
tiger, Panthera tigris
wild boar, boar, Sus scrofa
zebra
ram, tup
orangutan, orang, orangutang, Pongo pygmaeus
basenji
leopard, Panthera pardus
vizsla, Hungarian pointer
squirrel monkey, Saimiri sciureus
Siamese cat, Siamese
chimpanzee, chimp, Pan troglodytes
komondor
proboscis monkey, Nasalis larvatus
guinea pig, Cavia cobaya
white wolf, Arctic wolf, Canis lupus tundrarum
ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus
gorilla, Gorilla gorilla
ox
Tibetan mastiff
spider monkey, Ateles geoffroyi
Doberman, Doberman pinscher
warthog
Arabian camel, dromedary, Camelus dromedarius
siamang, Hylobates syndactylus, Symphalangus syndactylus
golden retriever
Border collie
hare
boxer
patas, hussar monkey, Erythrocebus patas
baboon
macaque
capuchin, ringtail, Cebus capucinus
flat-coated retriever
hog, pig, grunter, squealer, Sus scrofa
Eskimo dog, husky
Brittany spaniel
dial telephone, dial phone
maze, labyrinth
Gordon setter
dingo, warrigal, warragal, Canis dingo
hamster
Arctic fox, white fox, Alopex lagopus
water buffalo, water ox, Asiatic buffalo, Bubalus bubalis
American black bear, black bear, Ursus americanus, Euarctos americanus
Angora, Angora rabbit
bison
howler monkey, howler
hippopotamus, hippo, river horse, Hippopotamus amphibius
giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca
tabby, tabby cat
marmoset
Saint Bernard, St Bernard
armadillo
redbone
polecat, fitch, foulmart, foumart, Mustela putorius
marmot
gibbon, Hylobates lar
llama
wood rabbit, cottontail, cottontail rabbit
lion, king of beasts, Panthera leo
Irish setter, red setter
dugong, Dugong dugon
Indian elephant, Elephas maximus
beaver
Madagascar cat, ring-tailed lemur, Lemur catta
Rhodesian ridgeback
lynx, catamount
African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus
langur
timber wolf, grey wolf, gray wolf, Canis lupus
cheetah, chetah, Acinonyx jubatus
sloth bear, Melursus ursinus, Ursus ursinus
German shepherd, German shepherd dog, German police dog, alsatian
otter
koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus
tusker
echidna, spiny anteater, anteater
wallaby, brush kangaroo
platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus
wombat
revolver, six-gun, six-shooter
umbrella
schooner
soccer ball
accordion, piano accordion, squeeze box
ant, emmet, pismire
starfish, sea star
chambered nautilus, pearly nautilus, nautilus
grand piano, grand
laptop, laptop computer
strawberry
airliner
warplane, military plane
airship, dirigible
balloon
space shuttle
fireboat
gondola
speedboat
lifeboat
canoe
yawl
catamaran
trimaran
container ship, containership, container vessel
liner, ocean liner
pirate, pirate ship
aircraft carrier, carrier, flattop, attack aircraft carrier
submarine, pigboat, sub, U-boat
wreck
half track
tank, army tank, armored combat vehicle, armoured combat vehicle
missile
bobsled, bobsleigh, bob
dogsled, dog sled, dog sleigh
bicycle-built-for-two, tandem bicycle, tandem
mountain bike, all-terrain bike, off-roader
freight car
passenger car, coach, carriage
barrow, garden cart, lawn cart, wheelbarrow
shopping cart
motor scooter, scooter
forklift
electric locomotive
steam locomotive
amphibian, amphibious vehicle
ambulance
beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon
cab, hack, taxi, taxicab
convertible
jeep, landrover
limousine, limo
minivan
Model T
racer, race car, racing car
sports car, sport car
go-kart
golfcart, golf cart
moped
snowplow, snowplough
fire engine, fire truck
garbage truck, dustcart
pickup, pickup truck
tow truck, tow car, wrecker
trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi
moving van
police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria
recreational vehicle, RV, R.V.
streetcar, tram, tramcar, trolley, trolley car
snowmobile
tractor
mobile home, manufactured home
tricycle, trike, velocipede
unicycle, monocycle
horse cart, horse-cart
mosquito net
oxcart
bassinet
cradle
crib, cot
four-poster
bookcase
china cabinet, china closet
medicine chest, medicine cabinet
chiffonier, commode
table lamp
file, file cabinet, filing cabinet
pay-phone, pay-station
park bench
barber chair
throne
folding chair
rocking chair, rocker
studio couch, day bed
toilet seat
desk
pool table, billiard table, snooker table
dining table, board
entertainment center
wardrobe, closet, press
Granny Smith
orange
lemon
fig
pineapple, ananas
banana
jackfruit, jak, jack
custard apple
pomegranate
acorn
hip, rose hip, rosehip
ear, spike, capitulum
rapeseed
corn
buckeye, horse chestnut, conker
organ, pipe organ
upright, upright piano
chime, bell, gong
drum, membranophone, tympan
gong, tam-tam
maraca
marimba, xylophone
steel drum
banjo
cello, violoncello
lampshade, lamp shade
harp
acoustic guitar
electric guitar
cornet, horn, trumpet, trump
French horn, horn
trombone
harmonica, mouth organ, harp, mouth harp
ocarina, sweet potato
panpipe, pandean pipe, syrinx
bassoon
sax, saxophone
flute, transverse flute
daisy
yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum
cliff, drop, drop-off
valley, vale
alp
volcano
promontory, headland, head, foreland
sandbar, sand bar
coral reef
lakeside, lakeshore
seashore, coast, seacoast, sea-coast
geyser
hatchet
cleaver, meat cleaver, chopper
letter opener, paper knife, paperknife
plane, carpenter's plane, woodworking plane
power drill
lawn mower, mower
hammer
corkscrew, bottle screw
can opener, tin opener
plunger, plumber's helper
screwdriver
shovel
plow, plough
chain saw, chainsaw
cock
hen
ostrich, Struthio camelus
brambling, Fringilla montifringilla
goldfinch, Carduelis carduelis
house finch, linnet, Carpodacus mexicanus
junco, snowbird
indigo bunting, indigo finch, indigo bird, Passerina cyanea
robin, American robin, Turdus migratorius
bulbul
jay
magpie
chickadee
water ouzel, dipper
kite
bald eagle, American eagle, Haliaeetus leucocephalus
vulture
great grey owl, great gray owl, Strix nebulosa
black grouse
ptarmigan
ruffed grouse, partridge, Bonasa umbellus
prairie chicken, prairie grouse, prairie fowl
peacock
quail
partridge
African grey, African gray, Psittacus erithacus
macaw
sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita
lorikeet
coucal
bee eater
hornbill
hummingbird
jacamar
toucan
drake
red-breasted merganser, Mergus serrator
goose
black swan, Cygnus atratus
white stork, Ciconia ciconia
black stork, Ciconia nigra
spoonbill
flamingo
American egret, great white heron, Egretta albus
little blue heron, Egretta caerulea
bittern
crane
limpkin, Aramus pictus
American coot, marsh hen, mud hen, water hen, Fulica americana
bustard
ruddy turnstone, Arenaria interpres
red-backed sandpiper, dunlin, Erolia alpina
redshank, Tringa totanus
dowitcher
oystercatcher, oyster catcher
European gallinule, Porphyrio porphyrio
pelican
king penguin, Aptenodytes patagonica
albatross, mollymawk
great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias
tiger shark, Galeocerdo cuvieri
hammerhead, hammerhead shark
electric ray, crampfish, numbfish, torpedo
stingray
barracouta, snoek
coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch
tench, Tinca tinca
goldfish, Carassius auratus
eel
rock beauty, Holocanthus tricolor
anemone fish
lionfish
puffer, pufferfish, blowfish, globefish
sturgeon
gar, garfish, garpike, billfish, Lepisosteus osseus
loggerhead, loggerhead turtle, Caretta caretta
mud turtle
terrapin
box turtle, box tortoise
banded gecko
common iguana, iguana, Iguana iguana
American chameleon, anole, Anolis carolinensis
whiptail, whiptail lizard
agama
frilled lizard, Chlamydosaurus kingi
alligator lizard
Gila monster, Heloderma suspectum
green lizard, Lacerta viridis
African chameleon, Chamaeleo chamaeleon
Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis
triceratops
African crocodile, Nile crocodile, Crocodylus niloticus
American alligator, Alligator mississipiensis
thunder snake, worm snake, Carphophis amoenus
ringneck snake, ring-necked snake, ring snake
hognose snake, puff adder, sand viper
green snake, grass snake
king snake, kingsnake
garter snake, grass snake
water snake
vine snake
night snake, Hypsiglena torquata
boa constrictor, Constrictor constrictor
rock python, rock snake, Python sebae
Indian cobra, Naja naja
green mamba
sea snake
horned viper, cerastes, sand viper, horned asp, Cerastes cornutus
stone wall
sidewinder, horned rattlesnake, Crotalus cerastes
European fire salamander, Salamandra salamandra
common newt, Triturus vulgaris
eft
spotted salamander, Ambystoma maculatum
axolotl, mud puppy, Ambystoma mexicanum
bullfrog, Rana catesbeiana
tree frog, tree-frog
tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui
whistle
wing
paintbrush
oxygen mask
snorkel
loudspeaker, speaker, speaker unit, loudspeaker system, speaker system
microphone, mike
screen, CRT screen
mouse, computer mouse
electric fan, blower
oil filter
strainer
space heater
stove
guillotine
barometer
rule, ruler
odometer, hodometer, mileometer, milometer
scale, weighing machine
analog clock
digital clock
wall clock
hourglass
sundial
parking meter
stopwatch, stop watch
digital watch
stethoscope
syringe
magnetic compass
binoculars, field glasses, opera glasses
projector
sunglasses, dark glasses, shades
loupe, jeweler's loupe
radio telescope, radio reflector
bow
cannon
assault rifle, assault gun
rifle
projectile, missile
computer keyboard, keypad
typewriter keyboard
crane
lighter, light, igniter, ignitor
abacus
cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM
slide rule, slipstick
desktop computer
hand-held computer, hand-held microcomputer
notebook, notebook computer
padlock
harvester, reaper
thresher, thrasher, threshing machine
printer
slot, one-armed bandit
vending machine
sewing machine
joystick
switch, electric switch, electrical switch
hook, claw
car wheel
paddlewheel, paddle wheel
pinwheel
potter's wheel
gas pump, gasoline pump, petrol pump, island dispenser
carousel, carrousel, merry-go-round, roundabout, whirligig
swing
reel
radiator
puck, hockey puck
hard disc, hard disk, fixed disk
sunglass
pick, plectrum, plectron
car mirror
solar dish, solar collector, solar furnace
remote control, remote
disk brake, disc brake
buckle
hair slide
knot
combination lock
web site, website, internet site, site
nail
safety pin
screw
muzzle
seat belt, seatbelt
ski
candle, taper, wax light
jack-o'-lantern
spotlight, spot
torch
neck brace
pier
tripod
maypole
hand blower, blow dryer, blow drier, hair dryer, hair drier
mousetrap
spider web, spider's web
trilobite
harvestman, daddy longlegs, Phalangium opilio
scorpion
black and gold garden spider, Argiope aurantia
barn spider, Araneus cavaticus
garden spider, Aranea diademata
black widow, Latrodectus mactans
tarantula
wolf spider, hunting spider
tick
centipede
isopod
Dungeness crab, Cancer magister
rock crab, Cancer irroratus
fiddler crab
king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica
American lobster, Northern lobster, Maine lobster, Homarus americanus
spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish
crayfish, crawfish, crawdad, crawdaddy
hermit crab
tiger beetle
ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle
ground beetle, carabid beetle
long-horned beetle, longicorn, longicorn beetle
leaf beetle, chrysomelid
dung beetle
rhinoceros beetle
weevil
fly
bee
grasshopper, hopper
cricket
walking stick, walkingstick, stick insect
cockroach, roach
mantis, mantid
cicada, cicala
leafhopper
lacewing, lacewing fly
dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk
damselfly
admiral
ringlet, ringlet butterfly
monarch, monarch butterfly, milkweed butterfly, Danaus plexippus
cabbage butterfly
sulphur butterfly, sulfur butterfly
lycaenid, lycaenid butterfly
jellyfish
sea anemone, anemone
brain coral
flatworm, platyhelminth
nematode, nematode worm, roundworm
conch
snail
slug
sea slug, nudibranch
chiton, coat-of-mail shell, sea cradle, polyplacophore
sea urchin
sea cucumber, holothurian
iron, smoothing iron
espresso maker
microwave, microwave oven
Dutch oven
rotisserie
toaster
waffle iron
vacuum, vacuum cleaner
dishwasher, dish washer, dishwashing machine
refrigerator, icebox
washer, automatic washer, washing machine
Crock Pot
frying pan, frypan, skillet
wok
caldron, cauldron
coffeepot
teapot
spatula
altar
triumphal arch
patio, terrace
steel arch bridge
suspension bridge
viaduct
barn
greenhouse, nursery, glasshouse
palace
monastery
library
apiary, bee house
boathouse
church, church building
mosque
stupa, tope
planetarium
restaurant, eating house, eating place, eatery
cinema, movie theater, movie theatre, movie house, picture palace
home theater, home theatre
lumbermill, sawmill
coil, spiral, volute, whorl, helix
obelisk
totem pole
castle
prison, prison house
grocery store, grocery, food market, market
bakery, bakeshop, bakehouse
barbershop
bookshop, bookstore, bookstall
butcher shop, meat market
confectionery, confectionary, candy store
shoe shop, shoe-shop, shoe store
tobacco shop, tobacconist shop, tobacconist
toyshop
fountain
cliff dwelling
yurt
dock, dockage, docking facility
brass, memorial tablet, plaque
megalith, megalithic structure
bannister, banister, balustrade, balusters, handrail
breakwater, groin, groyne, mole, bulwark, seawall, jetty
dam, dike, dyke
chainlink fence
picket fence, paling
worm fence, snake fence, snake-rail fence, Virginia fence
diamondback, diamondback rattlesnake, Crotalus adamanteus
grille, radiator grille
sliding door
turnstile
mountain tent
scoreboard
honeycomb
plate rack
pedestal, plinth, footstall
beacon, lighthouse, beacon light, pharos
leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea
mashed potato
bell pepper
head cabbage
broccoli
cauliflower
zucchini, courgette
spaghetti squash
acorn squash
butternut squash
cucumber, cuke
artichoke, globe artichoke
cardoon
mushroom
shower curtain
jean, blue jean, denim
carton
handkerchief, hankie, hanky, hankey
sandal
ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin
safe
plate
necklace
croquet ball
fur coat
thimble
pajama, pyjama, pj's, jammies
running shoe
oboe, hautboy, hautbois
cocktail shaker
chest
manhole cover
modem
tub, vat
tray
balance beam, beam
bagel, beigel
violin, fiddle
prayer rug, prayer mat
kimono
hot pot, hotpot
whiskey jug
knee pad
book jacket, dust cover, dust jacket, dust wrapper
spindle
ski mask
beer bottle
crash helmet
bottlecap
tile roof
mask
maillot
Petri dish
football helmet
bathing cap, swimming cap
teddy, teddy bear
holster
pop bottle, soda bottle
photocopier
vestment
crossword puzzle, crossword
golf ball
trifle
suit, suit of clothes
water tower
feather boa, boa
cloak
red wine
drumstick
shield, buckler
Christmas stocking
hoopskirt, crinoline
menu
stage
bonnet, poke bonnet
meat loaf, meatloaf
baseball
face powder
scabbard
sunscreen, sunblock, sun blocker
beer glass
hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa
guacamole
wool, woolen, woollen
hay
bow tie, bow-tie, bowtie
mailbag, postbag
water jug
bucket, pail
dishrag, dishcloth
soup bowl
eggnog
mortar
trench coat
paddle, boat paddle
chain
swab, swob, mop
mixing bowl
potpie
wine bottle
shoji
bulletproof vest
drilling platform, offshore rig
binder, ring-binder
cardigan
sweatshirt
pot, flowerpot
birdhouse
jinrikisha, ricksha, rickshaw
hamper
ping-pong ball
pencil box, pencil case
consomme
apron
punching bag, punch bag, punching ball, punchball
backpack, back pack, knapsack, packsack, rucksack, haversack
groom, bridegroom
bearskin, busby, shako
pencil sharpener
broom
abaya
mortarboard
poncho
crutch
Polaroid camera, Polaroid Land camera
space bar
cup
racket, racquet
traffic light, traffic signal, stoplight
quill, quill pen
radio, wireless
snow leopard, ounce, Panthera uncia
dough
cuirass
military uniform
lipstick, lip rouge
shower cap
monitor
oscilloscope, scope, cathode-ray oscilloscope, CRO
mitten
brassiere, bra, bandeau
French loaf
vase
milk can
rugby ball
paper towel
earthstar
envelope
miniskirt, mini
cowboy hat, ten-gallon hat
trolleybus, trolley coach, trackless trolley
perfume, essence
bathtub, bathing tub, bath, tub
hotdog, hot dog, red hot
coral fungus
bullet train, bullet
pillow
toilet tissue, toilet paper, bathroom tissue
cassette
carpenter's kit, tool kit
ladle
stinkhorn, carrion fungus
lotion
hair spray
academic gown, academic robe, judge's robe
dome
crate
wig
burrito
pill bottle
chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour
theater curtain, theatre curtain
window shade
barrel, cask
washbasin, handbasin, washbowl, lavabo, wash-hand basin
ballpoint, ballpoint pen, ballpen, Biro
basketball
bath towel
cowboy boot
gown
window screen
agaric
standard poodle
cellular telephone, cellular phone, cellphone, cell, mobile phone
nipple
barbell
mailbox, letter box
lab coat, laboratory coat
fire screen, fireguard
minibus
packet
brown bear, bruin, Ursus arctos
pole
horizontal bar, high bar
sombrero
pickelhaube
rain barrel
wallet, billfold, notecase, pocketbook
cassette player
comic book
piggy bank, penny bank
street sign
bell cote, bell cot
fountain pen
Windsor tie
volleyball
overskirt
sarong
purse
bolo tie, bolo, bola tie, bola
bib
parachute, chute
sleeping bag
television, television system
swimming trunks, bathing trunks
measuring cup
espresso
pizza, pizza pie
breastplate, aegis, egis
shopping basket
wooden spoon
saltshaker, salt shaker
chocolate sauce, chocolate syrup
ballplayer, baseball player
goblet
gyromitra
stretcher
water bottle
skunk, polecat, wood pussy
soap dispenser
jersey, T-shirt, tee shirt
school bus
jigsaw puzzle
plastic bag
reflex camera
diaper, nappy, napkin
Band Aid
ice lolly, lolly, lollipop, popsicle
velvet
tennis ball
gasmask, respirator, gas helmet
doormat, welcome mat
Loafer
ice cream, icecream
pretzel
quilt, comforter, comfort, puff
maillot, tank suit
tape player
clog, geta, patten, sabot
iPod
bolete
meerkat, mierkat
scuba diver
pitcher, ewer
matchstick
bikini, two-piece
sock
CD player
lens cap, lens cover
thatch, thatched roof
vault
beaker
bubble
cheeseburger
parallel bars, bars
flagpole, flagstaff
coffee mug
rubber eraser, rubber, pencil eraser
stole
carbonara
dumbbell
English springer, English springer spaniel
malamute, malemute, Alaskan malamute
Walker hound, Walker foxhound
Welsh springer spaniel
whippet
Weimaraner
soft-coated wheaten terrier
Dandie Dinmont, Dandie Dinmont terrier
Old English sheepdog, bobtail
otterhound, otter hound
bloodhound, sleuthhound
Airedale, Airedale terrier
giant schnauzer
black-and-tan coonhound
papillon
Mexican hairless
Cardigan, Cardigan Welsh corgi
malinois
Lhasa, Lhasa apso
Norwegian elkhound, elkhound
Rottweiler
Saluki, gazelle hound
schipperke
Brabancon griffon
West Highland white terrier
Sealyham terrier, Sealyham
Irish wolfhound
EntleBucher
French bulldog
Bernese mountain dog
Maltese dog, Maltese terrier, Maltese
Norfolk terrier
toy terrier
cairn, cairn terrier
groenendael
clumber, clumber spaniel
Afghan hound, Afghan
Japanese spaniel
borzoi, Russian wolfhound
toy poodle
Kerry blue terrier
Scotch terrier, Scottish terrier, Scottie
Boston bull, Boston terrier
Greater Swiss Mountain dog
Appenzeller
Shih-Tzu
Irish water spaniel
Pomeranian
Bedlington terrier
miniature schnauzer
collie
Irish terrier
affenpinscher, monkey pinscher, monkey dog
silky terrier, Sydney silky
beagle
Leonberg
German short-haired pointer
dhole, Cuon alpinus
Chesapeake Bay retriever
bull mastiff
kuvasz
pug, pug-dog
curly-coated retriever
Norwich terrier
keeshond
Lakeland terrier
standard schnauzer
Tibetan terrier, chrysanthemum dog
wire-haired fox terrier
basset, basset hound
chow, chow chow
American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier
Shetland sheepdog, Shetland sheep dog, Shetland
Great Pyrenees
Chihuahua
Labrador retriever
Samoyed, Samoyede
bluetick
kelpie
miniature pinscher
Italian greyhound
cocker spaniel, English cocker spaniel, cocker
Sussex spaniel
Pembroke, Pembroke Welsh corgi
Blenheim spaniel
Ibizan hound, Ibizan Podenco
English foxhound
briard
Border terrier
LabelFlow GraphQL playground is the best way to get started with the API. Just connect to https://labelflow.ai/graphiql using any modern web browser, and get started. The interface should look like something like this.
As the images on LabelFlow are stored locally only, there is no authentication needed. All queries and mutations will be done on a database stored locally in your browser.
Let’s write a graphQL query which asks for the ids, names, and dataset id of the first 10 images you have access to:
query images {
images(first:10){
id
datasetId
name
}
}You can now run the query by pressing the ▶️“Run Query Button” in the top left of the screen. You should see the response appear on the right side of the screen.
Our Graph API is self-documented. You can access all the documentation in the GraphQL playground. There are several ways to benefit from the documentation:
Automatic autocompletion of your queries
Manual autocompletion of your queries, triggered by pressing CTRL-SPACE when writing a query in the query area
Schema documentation, using the “Schema” Button on the right side of the screen.
Here is a screenshot showcasing both Autocompletion (on the left side, in the query area), and the schema documentation (on the right side, in the sidebar). Our API is based on the principle of OpenCrud (https://github.com/opencrud/opencrud).
Yes! You need to sign-in, create an online workspace and invite your team to the newly created workspace.
Please do! You can ask or upvote a specific feature here:
Yes! You can see the features/Bugs that are planned or that we are working on here:
Online workspaces allow users to collaborate by uploading images to LabelFlow's secure servers, unlocking new levels of productivity. Sign up to use these collaborative tools for free now.
Online Workspaces can be shared with teammates, unlocking new levels of productivity through collaboration.
Simply enter your teammates' email addresses to add them to the workspace.
For now, all invitees are given the Owner role, giving them the ability to edit & delete datasets as well as update the plan, payment methods and billing information. More roles will be added in the near future.
Head over to our feedback page to let us know what roles you'd like to see on LabelFlow, and vote on other new features.
The CSV export format lists the labels contained in your dataset. Note that the polygon and classification labels are exported as bounding boxes.
You'll find several columns for every label:
imageId: a unique identifier for every image
imageName: speaks for itself...!
width: width of the image in pixel
height: height of the image in pixel
class: name of the label class
xmin, ymin, xmax, ymax: bounding box coordinates in pixel of its top left corner and bottom right corner
imageURL: link to the image stored in LabelFlow
Discover our discord server! The place where you can interact with the LabelFlow community and its developers.
The LabelFlow Graph API is available at the following URL: https://labelflow.ai/graphiql. It allows front-end applications to access all LabelFlow back-end services in a unified way. The Graph API is a gateway to LabelFlow services.
The Graph API uses the GraphQL query language, at modern, open specification initiated by Facebook but now used by a large part of the Web, as a successor to REST APIs. The specification and documentation for GraphQL can be found at https://graphql.org/.The Graph API is implemented over HTTPS, in practice, most tools made for REST APIs are compatible with GraphQL APIs out of the box.
The API is available as a GraphQL API over HTTPS. All communications with the API are encrypted and secured using state-of-the-art standards. The API is used by LabelFlow's own applications. It is open to integration with customers' IT systems.
