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stanford_filtered/scene-graph-TF-release/data_tools/README.md

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+# Dataset Preperation
+This instruction contains details about how to convert the VisualGenome dataset into a format that can be read by the framework. Alternatively,
+you may follow the instruction to download a pre-processed dataset.
+
+## Overview
+
+A dataset for the framework consists of five files:
+1. An image database in hdf5 format.
+2. An scene graph database in hdf5 format.
+3. An scene graph database metadata file in json format.
+4. An RoI proposal database in hdf5 format.
+5. An RoI distribution for normalizing the bounding boxes.
+
+**Important:** Note that (1) takes ~320GB of space. Hence we recommend creating (1) by yourself and download (2-5). If you just want to test/visualize predictions,
+you may download a subset of the processed dataset following the instructions in the next section.
+Also note that the framework does not include a regional proposal network implementation. Hence (4) is needed to run the framework.
+
+## Download pre-processed dataset.
+You may download the pre-processd full VG dataset using the following links
+1. Image database (currently unavailable, please refer to the next section on how to create an IMDB by yourself)
+2. Scene graph database: [VG-SGG.h5](http://svl.stanford.edu/projects/scene-graph/dataset/VG-SGG.h5)
+3. Scene graph database metadata: [VG-SGG-dicts.json](http://svl.stanford.edu/projects/scene-graph/dataset/VG-SGG-dicts.json)
+4. RoI proposals: [proposals.h5](http://svl.stanford.edu/projects/scene-graph/dataset/proposals.h5)
+5. RoI distribution: [bbox_distribution.npy](http://svl.stanford.edu/projects/scene-graph/dataset/bbox_distribution.npy)
+
+**mini-vg:** Alternatively, you may download a subset of the dataset (mini-vg). The dataset contains 1000 images (973 have scene graph annotations) from the test set
+of the full VG dataset and no training data. mini-vg takes around 4GB of space uncompressed. Note that you don't have to download it if you have ran the `download.sh` script.
+
+[mini-vg.zip](http://svl.stanford.edu/projects/scene-graph/dataset/mini-vg.zip)
+
+After downloading the dataset, place all files under `data/vg/`. If you use the mini-vg dataset, the directory should look like this:
+
+```
+data/vg/mini_imdb_1024.h5
+data/vg/mini_proposals.h5
+data/vg/mini_VG-SGG.h5
+data/vg/mini_VG-SGG-dicts.json
+```
+
+
+## Convert VisualGenome to desired format
+(i). To start with, download VisualGenome dataset using the following links:
+- Images [part1](https://cs.stanford.edu/people/rak248/VG_100K_2/images.zip) [part2](https://cs.stanford.edu/people/rak248/VG_100K_2/images2.zip)
+- [Image metadata](http://svl.stanford.edu/projects/scene-graph/VG/image_data.json)
+- [VG scene graph](http://svl.stanford.edu/projects/scene-graph/VG/VG-scene-graph.zip)
+
+(ii). Place all the json files under `data_tools/VG/`. Place the images under `data_tools/VG/images`
+
+(iii). Create image database by executing `./create_imdb.sh` in this directory. This script creates a hdf5 databse of images `imdb_1024.h5`. 
+The longer dimension of an image is resized to 1024 pixels and the shorter side is scaled accordingly. You may also create a image database of smaller dimension by
+editing the size argument of the script. You may skip to (vii) if you chose to downloaded (2-4).
+
+(iv). Create an ROI database and its metadata by executing `./create_roidb.sh` in this directory. The scripts creates a scene graph database file `VG-SGG.h5` and its metadata `VG-SGG-dicts.json`.
+By default, the script reads the dimensions of the images from the imdb file created in (iii). If your imdb file is of different size than 512 and 1024, you must add the size to
+the `img_long_sizes` list variable in the `vg_to_roidb.py` script.
+
+(v). Use the script provided by py-faster-rcnn to generate (4).
+
+(vi). Change line 93 of `tools/train_net.py` to `True` to generate (5).
+
+(vii). Finally, place (1-5) in `data/vg`.
+
+```
+data/vg/imdb_1024.h5
+data/vg/bbox_distribution.npy
+data/vg/proposals.h5
+data/vg/VG-SGG-dicts.json
+data/vg/VG-SGG.h5
+```

stanford_filtered/scene-graph-TF-release/data_tools/VG/object_alias.txt

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+called a forest,is called a forest
+saver,savers
+bookend,bookends
+yellow,is yellow,yellows
+gladiola,gladiolas
+four,fours
+railing,railings,of railing
+skeleton,skeletons
+trolley,trolleys
+hyssop,hyssops
+buddy,buddies
+swab,swabs
+swan,swans
+glider,gliders
+bike,bikes,bikes are
+teaspoon,teaspoons
+crossbar,crossbars
+toga,togas
+spec,specs
+shaving,shavings
+digit,digits
+ceramic,ceramics
+fishbone,fishbones
+blanket,blankets
+costume,costumes
+jack,jacks
+peripheral,peripherals
+kick,kicks
+wall white,is wall white
+em,ems
+undergarment,undergarments
+wick,wicks
+prize,prizes
+motorcyclist,motorcyclists
+shoelace,shoelaces
+venue,venues
+handout,handouts
+piling,pilings
+roadblock,roadblocks
+electric traffic,an electric traffic
+poppy,poppies
+fritter,fritters
+farmhouse,farmhouses
+paperback,paperbacks
+bicycle,bicycles,bicycle is,of bicycle
+speck,specks
+quilt,quilts
+eagle,eagles
+kitchenware,kitchenwares
+panther,panthers
+almond,almonds
+horn,horns
+nail,nails
+bannister,bannisters
+second,seconds
+street,streets
+tether,tethers
+cactus,cacti,cactuses
+panda,pandas
+monster,monsters
+blue,are blue,blue a,is blue,blues
+man on,man on a
+person ,person  is
+lampshade,lampshades
+older couple,an older couple
+conduct,conducts
+numeral,numerals
+net,nets,net is
+color yellow,is the color yellow
+crunch,crunches
+niche,niches
+hero,heroes
+dahl,dahls
+herb,herbs
+hydrangea,hydrangeas
+men,mens
+pontoon,pontoons
+here,heres,is here,here is
+herd,herd of
+preserver,preservers
+floret,florets
+path,paths
+chino,chinos
+cardboard,cardboards
+substance,substances
+luggage,luggages
+guide,guides
+credit,credits
+indentation,indentations
+eaves are on,eaves are on the
+climber,climbers
+bloomer,bloomers
+tenst,tenst are
+straw,straws
+snowcap,snowcaps
+seven,sevens
+strap,straps
+visible,is visible
+remnant,remnants
+pyramid,pyramids
+stern,sterns
+handlebar,handlebars
+unit,units
+plot,plots
+spoke,spokes
+marine,marines
+sweater,sweaters
+backrest,backrests
+foster,fosters
+call,calls
+card,cards
+spike,spikes
+type,types
+blueberry,blueberries
+calf,calves
+refection,refections,refection is
+posting,postings
+wart,warts
+under,under the
+reign,reigns
+glass,glasses,glassses,glasss,an glass
+pigmentation,pigmentations
+farmland,farmlands
+pecan,pecans
+adult,adults,an adult
+airport in,airport in the
+indent,indents
+hole,holes
+ware,wares
+scribble,scribbles
+shoot,shoots
+shamrock,shamrocks
+word,words,word of,word the
+room,of room,rooms
+mm,mms
+candelabra,candelabras
+blade,blades
+worm,worms
+roof,roofs,roof of
+waiter,waiters
+locker,lockers
+rim,rims
+wort,worts
+era,eras
+mechanic,mechanics
+elbow,an elbow,elbows
+root,roots
+pinecone,pinecones
+inscription,inscriptions
+iron gate,an iron gate
+wand,wands
+organizer,organizers
+nozzle,nozzles
+dolphin,dolphins
+taxiway,taxiways
+liter,liters
+knickknack,knickknacks
+green hose on,green hose on the
+indention,indentions
+sideline,sidelines
+end,ends,end of
+turn,turns
+dimple,dimples
+bunk,bunks
+sitting,is sitting
+feature,features
+machine,machines
+end table,an end table
+shred,shreds
+popover,popovers
+cheetah,cheetahs
+beach,beaches,beach is,beachs
+guardrail,guardrails
+pizza,pizzas,of pizza
+poker,pokers
+briefcase,briefcases
+lad,lads
+ladder,ladders,ladder is
+stroller,strollers
+lump,lumps
+diagram,diagrams
+lay,lays
+infielder,infielders
+lat,lats
+president,presidents
+law,laws
+arch,arches,an arch,archs
+pigtail,pigtails
+plier,pliers
+turd,turds
+messed up,are messed up
+croissant,croissants
+spout,spouts
+tulip,tulips
+green,greens,are green,is green,green is the
+ambulance,ambulances
+wing,wings
+wind,winds
+wine,wines
+blind,blinds
+popsicle,popsicles
+office,offices,an office
+pelican,pelicanss,pelicans
+pothole,potholes
+muffin,muffins
+plane on landing,plane on landing are
+foodstuff,foodstuffs
+oven,ovens,an oven
+keyboard,keyboards,keyboard is
+dwelling,dwellings
+caster,casters
+windshield,windshields
+surfboarder,surfboarders
+fir,firs
+forehead,foreheads
+backpack,backpacks
+avocado,avocados
+writing,writings
+plantation,plantations
+condition,conditions
+fade,fades
+savory,savories
+carton,cartons
+fin,fins
+shear,shears
+belly,bellies
+tourist,tourists
+fragment,fragments
+sitting on,sitting on the
+slate,slates
+handcuff,handcuffs
+band,bands
+bang,bangs
+giraffe,giraffes,giraffes are,giraffess,giraffe is
+they,they are
+flotation,flotations
+silver,are silver,is silver
+bank,banks
+headboard,headboards
+old clock,an old clock
+overcast day,an overcast day
+meat,meats
+spigot,spigots
+chuck,chucks
+in the middle,is in the middle
+wooden,is of wooden
+filling,fillings
+panini,paninis
+arrow,arrows,an arrow
+side,sides,side of
+bone,bones
+gargoyle,gargoyles
+hanger,hangers
+tumbleweed,tumbleweeds
+periodical,periodicals
+palm tree on,palm tree on the
+garment,garments
+blinder,blinders
+spider,spiders
+waffle,waffles
+owner,owners
+bra,bras
+turnip,turnips
+logo,logos
+poncho,ponchos
+ward,wards
+enclosure,of enclosure,enclosures,an enclosure
+trench,trenches
+rv,rvs
+snail,snails
+marcher,marchers
+gradation,gradations
+content,contents
+sparkle,sparkles
+hanging,hangings
+washer,washers
+marigold,marigolds
+resistor,resistors
+foundation,foundations
+barrier,barriers
+soda can,is a soda can
+free,frees
+formation,formations
+regulation,regulations
+terrain in,terrain in the
+kit,kits
+lollipop,lollipops
+aisle,aisles,of the aisle
+tendril,tendrils
+equine,equines
+denture,dentures
+raisin,raisins
+louse,lice
+scruff,scruffs
+filter,filters
+sprig,sprigs
+soda,sodas
+thumbtack,thumbtacks
+breed,breeds
+shopper,shoppers
+gazelle,gazelles
+traveller,travellers
+hoop,hoops
+veggie,veggies
+buttock,buttocks
+hook,hooks
+green and leafy,is green and leafy
+chevron,chevrons
+comforter,comforters
+comic,comics
+hoof,hoofs,hooves
+hood,hoods
+sky is blue,the sky is blue
+chequer,chequers
+toy,toys,toy is
+elephant standing,an elephant standing
+hydrant,hydrant is,hydrants
+service,services
+lego,legos
+undersole,undersole of
+top,tops,top of,top of a,top is
+giraffe pen,of giraffe pen
+elevator,elevators
+blackberry,blackberries
+periwinkle,periwinkles
+tea,teas
+flagpole,flagpoles
+kid,kids
+toe,toes
+kiwi,kiwi is,kiwis
+danish,danishes
+ceiling,ceilings
+emblem,emblems,a emblem
+tool,tools
+scenery,sceneries
+task,tasks
+cereal,cereals
+tampon,tampons
+stocking,stockings
+chef,chefs
+icicle,icicles
+outlaw,outlaws
+tree,trees,tree is,of trees,of a tree,trees are,treess
+rate,rates
+project,projects
+matter,matters
+store on,store on the
+flame,flames
+iron,irons
+wheeler,wheelers
+bridge,bridges
+donkey,donkeys
+hue,hues
+runner,runners
+ram,rams
+sconce,sconces
+canvass,canvasses
+rat,rats
+seed,seeds
+pylon,pylons
+increment,increments
+dinner,dinners
+mint,mints
+spade,spades
+ray,rays
+escalator,escalators,an escalator
+necktie,neckties
+latter,latters
+thruster,thrusters
+snow,snows,of snow
+sachet,sachets
+chest,chests
+hatch,hatches
+orange with a fac,an orange with a fac
+matchstick,matchsticks
+rider,riders
+paintbrush,paintbrushes
+blouse,blouses
+unoccupied,is unoccupied
+stirrup,stirrups
+boxcar,boxcars
+object,objects,an object
+rambutan,rambutans
+sidewalk area,sidewalk area is
+y,ys
+mouth,mouths,of mouth
+letter,letters,letter a
+peppercorn,peppercorns
+coil,coils
+coin,coins
+suture,sutures
+dummy,dummies
+lifesaver,lifesavers
+grove,groves
+alarm,alarms
+partition,partitions
+metal,metals,of metal,is metal
+dog,dogs,dog is
+valance,valances
+leaflet,leaflets
+ice machine,an ice machine
+bracket,brackets
+camo,camos
+rocker,rockers
+pineapple,pineapples
+tuff,tuffs
+sunbeam,sunbeams
+dot,dots
+saying,sayings
+chariot,chariots
+bomb,bombs
+mitten,mittens
+sightseer,sightseers
+hilltop,hilltops
+visitor,visitors
+queen,queens
+flagstone,flagstones
+chandelier,chandeliers
+gauge,gauges
+cruller,crullers
+outdoor concert,an outdoor concert
+bail,bails
+recliner,recliners
+kale,kales
+caper,capers
+herbivore,herbivores
+lovebird,lovebirds
+menu,menus
+refreshment,refreshments
+sugar,sugars
+celery,celeries
+bush,bushes
+knuckle,knuckles
+branding,brandings
+tropic,tropics
+folder,folders
+forelock,forelocks
+rectangle,rectangles
+wearing,is wearing
+plate,plates
+sunglasses,sunglassess
+fossil,fossils
+de,des
+watch,watches
+fluid,fluids
+appetizer,appetizers
+pocket,pockets
+boathouse,boathouses
+watermelon,watermelons
+cushion,cushions
+report,reports
+footrest,footrests
+prune,prunes
+bat,bats
+bar,bars
+avenger,avengers
+covering,coverings
+boarder,boarders
+pretzel,pretzels
+licking,is licking
+patch,patches,patch of
+emu,emus
+bag,bags,of bag
+troop,troops
+rung,rungs
+lettering,letterings
+spool on,spool on the
+obey sticker,an obey sticker
+observer,observers
+freesia,freesias
+nut,nuts
+signage,signages
+grass hill,of the grass hill
+cattle,cattles
+christian,christians
+trivet,trivets
+nub,nubs
+hairbrush,hairbrushes
+plantation that,plantation that is
+dungaree,dungarees
+sombrero,sombreros
+scrap,scraps
+sail,sails
+gentleman,gentlemen
+mug,mugs
+score,scores
+finger,fingers
+mum,mums
+jumpsuit,jumpsuits
+cubby,cubbies
+pirate,pirates
+preserve,preserves
+warrior,warriors
+splinter,splinters
+wa,was
+component,components
+vitamin,vitamins
+lotion,lotions
+toothbrush,toothbrushes
+rime,rimes
+cut,cuts
+wear,wears
+medallion,medallions
+beautician,beauticians
+mule,mules
+roller,rollers
+kitchen,kitchens,kitchen are
+cop,cops
+frosting on,frosting on a
+cot,cots
+cow,cows,a cow,is a cow,of cow
+country,countries
+adapter,adapters
+eyeball,eyeballs
+hoofprint,hoofprints
+jelly,jellies,jellys
+all fully grown,are all fully grown
+facet,facets
+bookcase,bookcases
+empty plate,an empty plate
+cog,cogs
+photographer,photographers
+con,cons
+gable,gables
+spear,spears
+royal,royals
+hairline,hairlines
+mullion,mullions
+train color,train color is
+orange object,an orange object
+truss,trusses
+beetroot,beetroots
+redskin,redskins
+bathroom,bathrooms
+tint,tints
+seashell,seashells
+three,threes,three of
+advert,adverts
+fowl,fowls
+beer,beers
+airport employee,an airport employee
+beet,beets
+stadium,stadiums
+this person,this person is
+basin,basins
+image projector,an image projector
+idol,idols
+board,boards
+mushroom,mushrooms
+horseshoe,horseshoes
+worker,workers
+shoestring,shoestrings
+lift,lifts
+chile,chiles
+child,children,childs
+chili,chilis
+spin,spins
+teapot,teapots
+train this,train this is
+tank,tanks
+cracker,crackers
+warbler,warblers
+n,ns
+dept,dept of
+motorist,motorists
+property,properties
+armband,armbands
+anchor,anchors
+cylinder,cylinders
+cane,canes
+congratulation,congratulations
+handrail,handrails
+house in,house in the
+sticker,stickers,the stickers
+sushi,sushis
+tress,tresses
+it,its,it is a,it is
+sting,stings
+player,players,of the player,of players,player is
+tissue,tissues,of tissues
+brake,brakes
+cone,cones
+decanter,decanters
+conditioner,conditioners
+bathroom has,bathroom has a
+mouse,mouse is,mice
+id,ids
+emergency,emergencies
+nike,nikes
+journal,journals
+saw,saws
+toaster,toasters
+wound,wounds
+umbrellas in,umbrellas in the
+grass near,grass near the
+drawstring,drawstrings
+boater,boaters
+carnation,carnations
+vegetable,vegetables
+bunny,bunnies
+wheel,wheels,of a wheel
+satellite,satellites
+papaya,papayas
+smoke,smoke is,smokes
+rotor,rotors
+swell,swells
+pinstripe,pinstripes
+rail,rails
+clove,cloves
+hand,hands,an hand,hand of
+suburb,suburbs
+waterfall,waterfalls
+warden,wardens
+pantograph,pantographs
+cycle,cycles
+tassel,tassels
+whicker,whickers
+drip,drips
+ocean,oceans,an ocean
+tho,thos
+bedspread,bedspreads
+client,clients
+tombstone,tombstones
+mother,mothers
+jean,jeans
+plaque,plaques
+snowman,snowmen
+american flag,an american flag
+barge,barges
+open window,an open window
+orange umbrella,an orange umbrella
+photo,photos,of photo,photo is
+laptop,laptops,of laptop,laptop is
+bruise,bruises
+rush,rushes
+rodent,rodents
+human,humans
+campbell,campbells
+pectoral,pectorals
+transformer,transformers
+ham,hams
+sunflower,sunflowers
+palm tree,a palm tree
+kabob,kabobs
+cherry,cherries
+character,characters
+hay,hays
+collard,collards
+spread,spreads
+stallion,stallions
+teenager,teenagers
+striation,striations
+basketball,basketballs
+hat,hats
+trimming,trimmings
+teddy bears,the teddy bears
+menorah,menorahs
+elevation,elevations
+visor,visors
+confection,confections
+vulture,vultures
+cosmetic,cosmetics
+boxer,boxers
+background,background of,backgrounds
+judge,judges
+cape,capes,cape is
+shadow,shadows,shadow of,shadows of
+hatchback,hatchbacks
+flavoring,flavorings
+shoulder,shoulders
+specie,species
+gift,gifts
+cooler,coolers
+pharmacist,pharmacists
+cheeseburger on,cheeseburger on the
+manual,manuals
+50,50s
+mit,mits
+specific,specifics
+forepaw,forepaws
+pavement,pavements
+officer,officers,an officer
+eyelet,eyelets
+signal,signals
+clementine,clementines
+antique,antiques,an antique
+dean,deans
+crowd,crowds,crowd is
+people,people are,peoples
+shirtsleeve,shirtsleeves
+crown,crowns
+sponge,sponges
+statistic,statistics
+billboard,billboards
+black tire,black tire is
+bore,bores
+marlin,marlins
+orchid,orchids
+trace,traces
+bottom,bottoms,bottom of,bottom is
+notification,notifications
+microwave,microwaves
+rhino,rhinos
+buffer,buffers
+skylight,skylights
+plantain,plantains
+skateboarder,skateboarders,of skateboarder,skateboarder is
+avatar,avatars
+cord,cords
+peek,peeks
+shaker,shakers
+khaki,khakis
+peel,peels
+corn,corns
+burn,burns
+illustration,illustrations
+cork,corks
+all the bikers,all the bikers are
+binder,binders
+aqua surf board,an aqua surf board
+yoke,yokes
+bolt,bolts
+front part,front part of the
+post,posts
+headstone,headstones
+plug,plugs
+oreo,oreos
+houseplant,houseplants
+diner,diners
+cowboy,cowboys
+latrine,latrines
+plum,plums
+o,os
+essential,essentials
+orange bear on,orange bear on a
+magazine,magazines
+tomatillo,tomatillos
+seabird,seabirds
+octopus,octopuses
+partial view,partial view of a
+mantle,of mantle
+puzzle,puzzles
+float,floats
+sol,soles
+fern,ferns
+sedan,sedans
+carafe,carafes
+furnishing,furnishings
+fuselage,of the fuselage
+carving,carvings
+wrap,wraps
+chime,chimes
+cubicle,cubicles
+wavelet,wavelets
+fabric,fabrics
+medal,medals
+support,supports
+initial,initials
+frill,frills
+sunlight,sunlights,sunlight is,of sunlight
+wildflower,wildflowers
+way,ways
+spring,springs
+icon,icons
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+open umbrella,an open umbrella
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+faucet,faucets
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+breast,breasts
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+chimney,chimneys
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+art,arts
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+barn,barns
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+fang,fangs
+movie,movies
+burner,burners
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+restaurant,restaurants
+archway,archways,an archway
+bowie,bowies
+connection,connections
+separator,separators
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+stoplight,stoplights
+lanyard,lanyards
+patty,patties
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+lev,leva
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+sweet,sweets
+whelk,whelks
+pamphlet,pamphlets
+dancer,dancers
+church,churches
+vessel,vessels
+belt,belts
+trestle,trestles
+dishtowel,dishtowels
+pt,pts
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+apostle,apostles
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+dug,dugs
+pc,pcs
+brick,bricks,of brick
+orange globe,an orange globe
+empty,an empty,is empty
+cyclist,cyclists
+flight,flights
+champion,champions
+fire,fires
+elephant walking,an elephant walking
+crack,cracks
+gas,gass,gasses
+gar,garss
+imac,an imac
+gap,gaps
+racer,racers
+gal,galss
+close together,are close together
+ornate clock,an ornate clock
+serviceman,servicemen
+furrow,furrows
+fur,furs,of fur
+look,looks
+hostess,hostesses
+juice,juices
+bill,bills
+crutch,crutches
+rope,ropes
+pace,paces
+bikini,bikinis
+parachuter,parachuters
+barricade,barricades
+honey badger,honey badger is
+blue poles,blue poles are
+outskirt,outskirts
+loop,loops
+pack,packs
+underpass,an underpass
+ducky,duckies
+moth,moths
+petal,petals
+owen,owens
+binding,bindings
+rip,rips
+decoration,decorations,of a decoration
+obstacle,obstacles
+facade,facades
+rig,rigs
+rib,ribs
+shirt,shirts,the shirt
+squiggle,squiggles
+ewe,ewes
+port,ports
+bristle,bristles,bristles of the
+9,9s
+dozen,dozens
+many waves,is many waves
+sliver,slivers
+windmill,windmills
+fatty,are fatty
+cartridge,cartridges
+dime,dimes
+scaffolding for,scaffolding for the
+restraint,restraints
+pomegranate,pomegranates
+cigar,cigars
+deformity,deformities
+m,ms
+cucumber,cucumbers
+stripe,stripes,of stripes,the stripes
+parfait,parfaits
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+stack,stacks,stack of
+bedroll,bedrolls
+lower,lowers
+noodle,noodles
+older,an older
+cheek,cheeks
+maker,makers
+person,persons,person is
+cheer,cheers
+edge,edges,an edge
+dreadlock,dreadlocks
+sweatshirt,sweatshirts
+landmark,landmarks
+entry,entries
+pepole,pepole are
+hotdog,hotdogs
+toothpaste ,toothpaste  is
+chord,chords
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+morsel,morsels
+small stick on,small stick on the
+shape,shapes
+old man drinking,an old man drinking
+goo,goos
+trees in,trees in the
+aerial view,an aerial view
+timber,timbers
+sandal,sandals
+concrete brick,is concrete brick
+goblet,goblets
+tablet,tablets
+cup,cups
+romper,rompers
+sire,sires
+cemetery,cemeteries
+fitting,fittings
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+cue,cues
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+plateau,plateaus
+ad on a bus,an ad on a bus
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+snap,snaps
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+bridal,bridals
+kumquat,kumquats
+divot,divots
+bin,bins
+australia,australias
+vendor,vendors
+outdoor image,an outdoor image
+big,big a,is big
+couple,couples
+bib,bibs
+game,games
+bit,bits
+blemish,blemishes
+d,ds,d a
+spine,spines
+pillar,pillars
+stiletto,stilettos
+glove,gloves
+snowflake,snowflakes
+nipple,nipples
+in grass,is in grass
+sequin,sequins
+gill,gills
+clipping,clippings
+google,googles
+whitecap,whitecaps
+cheerleader,cheerleaders
+back,backs,back of,back of the
+yolk,yolks
+oval,an oval,ovals
+palm,palms
+blue and white,is blue and white
+mirror,mirrors
+underbelly,underbellies
+candle,candles
+server,servers
+saucer,saucers
+scale,scales
+vacationer,vacationers
+cutlet,cutlets
+pet,pets
+pew,pews
+orange cone,an orange cone
+prop,props
+pen,pens
+slash,slashes
+colorful sail in,colorful sail in the
+peg,pegs
+pea,peas
+t,ts
+eyeglass,eyeglasses
+cameraman,cameramen
+run,runs
+ba,bas
+booklet,booklets
+rug,are rug,rugs
+stem,stems
+zombie,zombies
+step,steps,steps of
+garnishment,garnishments
+santa,santas
+lounger,loungers
+ache,aches
+accoutrement,accoutrements
+raspberry,raspberries
+rut,ruts
+projector,projectors
+open door,an open door
+gnome,gnomes
+building is made,building is made of
+goody,goodies
+smoothy,smoothies
+hinge,hinges
+range,ranges
+bridle,bridles
+jogger,joggers
+block,blocks,is a block
+repair,repairs
+jimmy,jimmies
+noddle,noddles
+rollerblade,rollerblades
+signature,signatures
+vehicles are on,vehicles are on the
+holster,holsters
+lesson,lessons
+pentagon,pentagons
+canal,canals
+appendage,appendages
+jockey,jockeys
+span,spans
+arcade,arcades
+white  clouds,white  clouds are
+sock,socks
+cuticle,cuticles
+splat,splats
+crag,crags
+oyster,oysters
+suit,suits
+forward,forwards
+athlete,an athlete,athletes
+lemmon,lemmons
+poster,posters
+plinth,plinths
+large and green,are large and green
+cloth,cloths
+reed,reeds
+ling,lings
+crane,cranes
+reel,reels
+penguin,penguins
+lifeguard,lifeguards
+clydesdale,clydesdales
+ringlet,ringlets
+apricot,apricots
+up,are up
+barring,barrings
+planet,planets
+growth,growths
+highlight,highlights
+groove,grooves
+doohickey,doohickeys
+bell,bells
+sort,sorts
+flop,flops
+forest,forests
+cattail,cattails
+white curtains,white curtains are
+cleat,cleats
+dark shelf,a dark shelf
+chap,chaps
+curb,curbs
+curl,curls
+work,works
+gecko,geckos
+shades of green,are shades of green
+rainbow,rainbows
+lemon,lemons
+polygon,polygons
+peach,peaches
+tuft,tufts
+fixing,fixings
+peace,peaces
+scrape,scrapes
+nick,nicks
+parakeet,parakeets
+swirl,swirls
+tarp,tarps
+tart,tarts
+padding,paddings
+draw,draws
+trouser,trousers
+scrub,scrubs
+kiosk,kiosks
+printing,printings
+cannister,cannisters
+stipe,stipes
+lens,lenses
+cobblestone,cobblestones
+insect,an insect,insects
+competitor,competitors
+wrinkle,wrinkles
+desert,deserts
+structure,structures
+wonton,wontons
+lane,lanes
+land,lands
+e,an e,es
+lead,leads
+wafer,wafers
+cooker,cookers
+dvd,dvds
+ledge,ledges
+ton,tons
+crease,creases
+circuit,circuits
+beverage,beverages
+crinkle,crinkles
+walker,walkers
+buffalo,buffalos,buffaloes
+scroll,scrolls
+rabbit,rabbits
+scratch,scratches
+lowland,lowlands
+alien,aliens
+baby,babies,babys
+moon,moons
+reactor,reactors
+handgrip,handgrips
+peanut,peanuts
+description,descriptions
+sky is clear,the sky is clear
+rudder,rudders
+shack,shacks
+geranium,geraniums
+stable,stables
+suite,suites
+gravel,gravels
+ingredient,ingredients
+rag,rags
+probe,probes
+toenail,toenails
+fishnet,fishnets
+dessert,desserts
+kitty,kitties
+wave,waves,waves of
+spool,spools
+spoon,spoons
+thermos,thermoses
+trough,troughs
+tricycle,tricycles
+tutu,tutus
+wipe,wipes
+footmark,footmarks
+knight,knights
+button,buttons,button the,button a
+shock,shocks
+kansa,kansas
+this,this is,this is a
+race,races
+ornamentation,ornamentations
+subwoofer,subwoofers
+rack,racks,rackss
+booty,booties
+pleat,pleats
+crow,crows
+scientist,scientists
+mural,murals
+jump,jumps
+fold,folds
+video,videos
+booth,booths
+folk,folks
+sausage,sausages
+font,fonts
+speckle,speckles
+showcase,showcases
+sunny day,sunny day is
+top shelf,of the top shelf
+paddle,paddles
+elephants trunk,an elephants trunk
+attire,attires
+bird,birds
+body,bodies,bodys
+toast,toasts
+led,leds
+cozy,cozies
+leg,legs,legs of,legs are,leg of
+lei,leis
+indicator,indicators
+gravel that,gravel that is
+let,lets
+sink,sinks,of sink,sink is,of the sink
+pancake,pancakes
+engraving,engravings
+barb,barbs
+leaving,leavings
+mussel,mussels
+implement,implements
+hexagon,hexagons
+ruin,ruins
+pajama,pajamas
+wig,wigs
+shovel,shovels
+apple,apples,an apple
+clark,clarks
+overpass,an overpass
+duct,ducts
+win,wins
+talon,talons
+performer,performers
+bust,busts
+motor,motors
+duck,ducks
+limb,limbs
+hedgerow,hedgerows
+lima,limas
+white sign,the white sign
+staple,staples
+cloud,clouds
+lime,limes
+standing,standings,is standing
+road with no zone,a road with no zone
+fee,fees
+figure,figures
+certificate,certificates
+doodle,doodles
+frog,frogs
+capri,capris
+camera,cameras
+crab,crabs
+vehicle,vehicles,vehicles are,of vehicle
+timing,timings
+stage,stages
+possession,possessions
+pencil,pencils
+speaker that,speaker that is
+porch,porches
+tennis,tenniss
+musician,musicians
+tangerine,tangerines
+sister,sisters
+missile,missiles
+trail,trails
+train,trains,of train,of the train
+escape,escapes
+brochure,brochures
+customer,customers
+sample,samples
+account,accounts
+salad,salads
+heard,heard of
+tunnel,tunnels
+ride,rides
+cornucopia,cornucopias
+villain,villains
+donut,donuts
+carrot,carrots
+stabilizer,stabilizers
+smear,smears
+pouf,poufs
+control,controls
+wedge,wedges
+tap,taps
+bent,bents
+patron,patrons
+carabao,carabaos
+lock,locks
+loch,lochs
+dripping,drippings
+open space,an open space
+slit,slits
+tag,tags
+streamer,streamers
+tab,tabs
+earmuff,earmuffs
+shrimp,shrimps
+skirt,skirts
+hangar,hangars
+lamb,lambs
+sitting down on,sitting down on the
+legging,leggings
+briar,briars
+tom,toms
+arrangement,arrangements
+lamp,lamps
+attachment,attachments
+animal,animals,an animal
+toddler,toddlers
+establishment,establishments
+filament,filaments
+airline,airlines
+profile,profiles
+egret,egrets
+cupboard,cupboards
+halter,halters
+farm,of farm,farms
+stop,stops
+collection,collection of
+tack,tacks
+wrist,wrists
+bluff,bluffs
+taco,tacos
+tier,tiers
+cabbage,cabbages
+hawk,hawks
+berg,bergs
+concession,concessions
+physic,physics
+tomato,tomatoes,tomatos
+drape,drapes
+bluebell,bluebells
+bine,bines
+light,lights,is light,lights are
+counter,counters
+platypus,platypuses
+liner,liners
+element,elements
+linen,linens
+hiawatha,hiawathas
+necklace,necklaces
+martini,martinis
+colonnade,colonnades
+maintained well,is maintained well
+flapper,flappers
+antelope,antelopes
+thigh,thighs
+minnow,minnows
+move,moves
+meter,meters
+spatula,spatulas
+motorcycle,motorcycles,motorcycle is,of motorcycle
+quake,quakes
+denim,denims
+bunch,bunches
+orange peach,an orange peach
+le,less
+galosh,galoshes
+banner,banners
+broom,brooms
+imperfection,imperfections
+pawpaw,pawpaws
+walnut,walnuts
+decal,decals
+knothole,knotholes
+paperclip,paperclips
+insulator,insulators
+orange,oranges,an orange,is orange
+holiday,holidays
+old brick road,an old brick road
+pixel,pixels
+greeting,greetings
+contrail,contrails
+sapling,saplings
+seatbelt,seatbelts
+sword,swords
+tailfin,tailfins
+huff,huffs
+frond,fronds
+material,materials
+dock,docks
+cutting,cuttings
+snake,snakes
+kiss,kisses
+fingerprint,fingerprints
+front,fronts,front of
+cage,cages
+day,days
+easel,an easel,easels
+footstool,footstools
+tram,trams
+wooden desk,of a wooden desk
+testicle,testicles
+white plate,of a white plate
+slide,slide is,slides
+trap,traps
+condominium,condominiums
+boat that,boat that is
+stock,stocks
+tray,trays,of tray
+glasses,glassess
+sunburn,sunburns
+fare,fares
+moped,mopeds
+lilac,lilacs
+bump,bumps
+chunk,chunks
+goalpost,goalposts
+bedstead,bedsteads
+drop of liquid,a drop of liquid
+antique tuck,an antique tuck
+one shoe,one shoe is
+special,specials
+out,is out
+matt,matts
+giant,giants
+staircase,staircases
+boutique,boutiques
+valve,valves
+sticking up,is sticking up
+stub,stubs
+stud,studs
+peeling,peelings
+open collar,an open collar
+burka,burkas
+yankee,yankees
+red,is red,red a
+young boy,young boy is
+umbrella,umbrellas,an umbrella
+this picture,of this picture
+tully,tullys
+utensil,utensils
+ipod,ipods
+tiger,tigers
+orange beak,an orange beak
+pendant,pendants
+dumpster,dumpsters
+thrust,thrusts
+van,vans
+philip,philips
+princess,princesses
+ramekin,ramekins
+retriever,retrievers
+chilli,chillis
+river,of river,rivers,of the river
+yard,yards
+g,gs
+spill,spills
+grassy,grassy are
+route,routes
+skateboard,skateboards
+wrapping,wrappings
+yarn,yarns
+chicken,chickens
+notebook,notebooks
+blotch,blotches
+fatigue,fatigues
+ossicle,ossicles
+scarf,scarves,scarfs
+windsock,windsocks
+ski trails,ski trails are
+bouquet,bouquets
+signboard,signboards
+sack,sacks
+spiral,spirals
+safety ring,safety ring is
+hurdle,hurdles
+drinker,drinkers
+stump,stumps
+horseman,horsemen
+bracer,bracers
+fella,fellas
+stencil,stencils
+monkey,monkeys
+terrier,terriers
+accent,accents
+system,systems
+wrapper,wrappers
+potty,potties
+autograph,autographs
+plane is white,the plane is white
+ankle,ankles
+prong,prongs
+cabin,cabins
+beard,beards
+tidbit,tidbits
+shell,shells
+stomach,stomachs
+gear,gears
+shallot,shallots
+shelf,shelves,shelfs,shelf is
+shallow,shallows
+adaptor,adaptors
+confectioner,confectioners
+what this,what this is
+manhole,manholes
+vas,vases
+newlywed,newlyweds
+outline,outlines
+photograph,photographs
+slack,slacks
+split,splits
+shampoo,shampoos
+cheekbone,cheekbones
+bed,beds,bed is
+bee,bees
+firework,fireworks
+dowel,dowels
+bind,binds
+sculpture,sculptures
+steer,steers
+exhibit,exhibits
+hairstyle,hairstyles
+thistle,thistles
+clip,clips
+crack on,crack on the
+viewer,viewers
+splatter,splatters
+tide,tides
+tender,tenders
+enforcer,enforcers
+quiche,quiches
+two lane road,of a two lane road
+border,borders
+screw,screws
+microphone,microphones
+angle,angles
+sprinkler,sprinklers
+scone,scones
+there is a letter,there is a letter a
+hammer,hammers
+bough,boughs
+mechanism,mechanisms
+gunner,gunners
+bagel,bagels
+action photo,an action photo
+lily,lilies
+soap,soaps
+vegetation,vegetations
+deposit,deposits
+raindrop,raindrops
+camper,campers
+white counter,white counter is
+kickstand,kickstands,kickstand of
+baseboard,baseboards
+sb,sbs
+device,devices
+blue frisbee in,blue frisbee in the
+segment,segments
+clasp,clasps
+cellphone,cellphones
+placement,placements
+burn area near,burn area near the
+crew,crews
+hot dog,an hot dog
+urn,urns
+thunderbird,thunderbirds
+face,face is,faces,face of
+pipe,pipes
+enclosed area,an enclosed area
+snapshot,snapshots
+mustache,mustaches
+collectable,collectables
+holstein,holsteins
+painting,paintings
+fact,facts
+son,sons
+impression,impressions
+backyard,backyards
+feline,felines
+white bus,of the white bus
+kite,kites,kite is,kites are,kite is a
+text,texts
+stove,stoves
+rosebush,rosebushes
+crate,crates
+violator,violators
+bookshelf,bookshelves,bookshelf is
+serving,servings
+seaweed,seaweeds
+bedroom,bedrooms
+ottoman,ottomen,an ottoman,ottomans
+floodlight,floodlights
+thicket,thickets
+supporter,supporters
+samosa,samosas
+ear,ears,ear of the,an ear,ear of
+planter,planters
+tire,tires,tire of
+outbuilding,outbuildings
+attractive girl,an attractive girl
+jaw,jaws
+jar,jars
+terminal,terminals
+jam,jams
+tape,tapes
+employee,employees
+riding,is riding
+local,locals
+sweetener,sweeteners
+cube,cubes
+handle,handles,handle of
+starch,starches
+beat,beats
+canyon,canyons
+overall,overalls
+yellow lines,yellow lines are
+bear,bears,bear is,the bears
+equid,equids
+joint,joints
+bean,beans
+occupant,occupants
+beak,beaks
+bead,beads
+cutout,cutouts
+gray,is gray
+graz,grazes
+designer on,designer on the
+organ,organs
+motorboat,motorboats
+eyebrow,eyebrows
+ire,ireses
+stuff,stuffs
+she,she is
+rein,reins
+graf,graves
+widow,widows
+buzzer,buzzers
+gravestone,gravestones
+shedding,sheddings
+official,officials
+bucket,buckets,the bucket
+puddle,puddles
+shake,shakes
+packet,packets
+freeze,freezes
+apple is on,an apple is on the
+computer,computers
+graph,graphs
+violet,violets
+racket,rackets
+afterburner,afterburners
+wire,wires
+closet,closets
+wisp,wisps
+pattern,patterns
+favor,favors
+state,states
+hammock,hammocks
+panty,panties
+tyre,tyres
+lug,lugs
+piston,pistons
+antler,antlers
+gemstone,gemstones
+email,emails
+tent,tents
+blinker,blinkers
+blue wench,blue wench is
+cauliflower,cauliflowers
+opening,an opening,openings
+keg,kegs
+standing up,are standing up
+key,keys
+blackbird,blackbirds
+group,groups,group of
+jeweller,jewellers
+mailbox,mailboxes
+sketch,sketches
+molehill in grass,a molehill in grass
+thumb,thumbs
+drum,drums
+barrette,barrettes
+lentil,lentils
+lifeboat,lifeboats
+shingle,shingles
+ramp,ramps
+aircraft,an aircraft,aircrafts
+white frisbee in,white frisbee in the
+doorway,doorways
+grain,grains
+puff,puffs
+canopy,canopies,canopys
+fry,fries,frys
+jersey,jerseys
+comment,comments
+vent,vents
+subtitle,subtitles
+author,authors
+saddlebag,saddlebags
+ca,cas
+cd,cds
+orange lifeboat,an orange lifeboat
+palate,palates
+crowsnest ,crowsnest  is
+table,tables,of table,of the table,table is a
+cv,cvs
+sari,saris
+motorbike,motorbikes
+swimmer,swimmers
+addition,additions
+cent,cents
+yam,yams
+treat,treats
+eraser,erasers
+rump,rumps
+curtain,curtains,curtains are
+feather,feathers
+waste,wastes
+hyacinth,hyacinths
+emirate,emirates
+parker,parkers
+nickel,nickels
+turban,turbans
+commuter,commuters
+deer,deers
+headlamp,headlamps
+spaniel,spaniels
+controller,controllers
+crevice,crevices
+shuttlecock,shuttlecocks
+mannequin,mannequins
+axle,axles
+bull,bulls,bull is
+bulb,bulbs
+watcher,watchers
+present,presents
+volunteer,volunteers
+sibling,siblings
+plain,plains
+runway,of the runway,runways,of runway
+sawhorse,sawhorses
+value,values
+chalk,chalks
+fingertip,fingertips
+hole in,hole in the
+also yellow,is also yellow
+dad,dads
+layer,layers
+motif,motives,motifs
+resident,residents
+surface,surfaces
+rooster,roosters
+adornment,adornments
+whorl,whorls
+partner,partners
+orange light,the orange light,orange light of the,an orange light
+tattoo,tattoos
+grinder,grinders
+matchbook,matchbooks
+highlighter,highlighters
+tweezer,tweezers
+balloon,balloons
+headlight,headlights
+cross,crosses
+camp,camps
+member,members
+speaker,speakers
+tumbler,tumblers
+shuttle,shuttles
+powerboat,powerboats
+stamen,stamens
+succulent,succulents
+ball,balls
+joist,joists
+fireman,firemen
+bale,bales
+drink,drinks
+effect,effects
+beast,beasts
+grandstand,grandstands
+student,students
+pedal,pedals
+cornice,cornices
+collar,collars
+crosstie,crossties
+gutter,gutters
+reflection,reflections,reflection of the,reflection of
+weapon,weapons
+left side,left side of
+command,commands
+spectator,spectators
+awning,awnings
+position,positions
+breaker,breakers
+drawing,drawings
+lightbulb,lightbulbs
+coaster,coasters
+outrigger,an outrigger
+camel,camels
+half,halves,halfs
+old man,an old man
+bongo,bongos
+flier,fliers
+keypad,keypads
+skill,skills
+dais,daises
+white box,white box is
+clipper,clippers
+rapid,rapids
+wee,wees
+empty dish,an empty dish
+snicker,snickers
+supply,supplies
+sky,skies,skys,sky is
+lake,lake is,lakes
+bench,benches,of a bench,bench is
+backpacker,backpackers
+add,adds
+oat,oats
+poll,polls
+citizen,citizens
+crossroad,crossroads
+ski,skis,of skis
+persimmon,persimmons
+match,matches
+knob,knobs
+rafter,rafters
+railcar,railcars
+molding,moldings
+dryer,dryers
+five,fives
+know,knows
+knot,knots
+desk,desks,desk is,of the desk
+propeller,propellers
+doughnut,doughnuts
+intersection,intersections,an intersection
+pier,piers
+muscle,muscles
+insert,inserts
+flamingo,flamingos,flamingoes
+crisp,crisps
+onion,onions
+scallop,scallops
+sofa,sofas
+matte,mattess
+candy,candies
+garage,garages
+journalist,journalists
+bane,banes
+chick,chicks
+page,pages
+heel,heels
+shed,sheds
+because,because of
+glare,glares
+habitat,habitats
+tumble,tumbles
+hair,hairs
+husk,husks
+warmer,warmers
+sepal,sepals
+home,homes,home is
+drizzle,drizzles
+leaf,leaves,leafs,leaves are,leavess
+shrub,shrubs
+jalapeno,jalapenos
+leak,leaks
+bedding,beddings
+kettle,kettles
+lean,leans
+muff,muffs
+duckling,ducklings
+truffle,truffles
+leader,leaders
+stairway,stairways
+pepper,peppers
+hose,hoses
+pear,pears
+mitt,mitts
+crossing,crossings
+pasta,pastas
+topiary,topiaries
+crust,crusts
+panel,panels
+beaker,beakers
+iris,irises
+throng,throngs
+socket,sockets
+extension,extensions,an extension
+saddle,saddles
+column,columns,columnss
+biscuit,biscuits
+location,locations
+flake,flakes
+carrier,carriers
+sweat,sweats
+cranberry,cranberries,cranberrys
+udder,udders
+tomb,tombs
+good for you,are good for you
+owl,owls
+artefact,artefacts
+man wears,man wears a
+headphone,headphones
+chestnut,chestnuts
+guard,guards
+receptor,receptors
+brush,brushes,brushes are
+female,females
+eyelid,eyelids
+utility,utilities
+behind,behinds
+angler,anglers
+numbers on,numbers on the
+ridge,ridges
+chrysanthemum,chrysanthemums
+buckle,buckles
+firefighter,firefighters
+tine,tines
+poinsettia,poinsettias are,poinsettias
+watchman,watchmen
+drumstick,drumsticks
+gut,guts
+globe,globes
+vat,vats
+rocks in,rocks in the
+function,functions
+semicircle,semicircles
+tennis racket,a tennis racket
+storehouse,storehouses
+bus,buses,busses,of the bus,bus is,buss
+coke,cokes
+sweatband,sweatbands
+x on a sign,an x on a sign
+volume,volumes
+bun,buns
+liquor,liquors
+granny,grannys
+grate,grates
+sprinkling,sprinklings
+ha,has
+bug,bugs
+bud,buds
+he,hes,he is
+hitter,hitters
+grommet,grommets
+daffodil,daffodils
+particle,particles
+leaves on,leaves on the
+pansy,pansies
+record,records
+carriage,carriages
+limit,limits
+key on,key on a
+cake,cakes
+piece,pieces
+condiment,condiments
+display,displays
+sponsor,sponsors
+bearing,bearings
+coverall,coveralls
+orange vest,an orange vest
+pin,pins
+curve,curves
+penny,pence,pennies
+pie,pies
+pig,pigs
+twist,twists
+sky is visible,the sky is visible
+replica,replicas
+pip,pips
+pit,pits
+ew,ews
+balcony,balconies,of balcony,balconys
+planting,plantings
+diplomat,diplomats
+cashew,cashews
+boot,boots
+detail,details
+book,books,books are
+oar,oars,an oar
+branch,branches,branches of the
+boob,boobs
+ponytail,ponytails
+dresser,dressers
+tollbooth,tollbooths
+frisbee,frisbees
+star,stars
+plexiglas,plexiglass
+earplug,earplugs
+bundle,bundles
+building on,building on the
+breadcrumb,breadcrumbs
+grille,grilles
+vein,veins
+cliff,cliffs
+ghost,ghosts
+droplet,droplets
+this wall,this wall is
+baker,bakers,of the baker,baker is
+jewel,jewels
+rule,rules
+blog,blogs
+hiker,hikers
+portion,portions
+craft,crafts
+stirrer,stirrers
+pupil,pupils
+cookbook,cookbooks
+simpson,simpsons
+buoy,buoys

stanford_filtered/scene-graph-TF-release/data_tools/VG/object_list.txt

@@ -0,0 +1,150 @@
+roof
+kite
+pant
+bowl
+laptop
+paper
+shoe
+railing
+chair
+windshield
+ear
+tire
+cup
+bench
+tail
+bike
+board
+orange
+hat
+finger
+plate
+woman
+handle
+branch
+food
+elephant
+bear
+wave
+tile
+giraffe
+desk
+lady
+towel
+glove
+bag
+nose
+rock
+tower
+motorcycle
+sneaker
+fence
+people
+house
+sign
+hair
+street
+zebra
+racket
+logo
+girl
+arm
+wire
+leaf
+clock
+hill
+bird
+umbrella
+leg
+screen
+men
+sink
+trunk
+post
+sidewalk
+box
+boy
+cow
+skateboard
+plane
+stand
+pillow
+toilet
+pot
+number
+pole
+table
+boat
+sheep
+horse
+eye
+sock
+window
+vehicle
+curtain
+man
+banana
+fork
+head
+door
+shelf
+cabinet
+glass
+flag
+train
+child
+seat
+neck
+room
+player
+ski
+cap
+tree
+bed
+cat
+light
+skier
+engine
+drawer
+guy
+airplane
+car
+mountain
+shirt
+paw
+boot
+snow
+lamp
+book
+flower
+animal
+bus
+vegetable
+tie
+beach
+pizza
+wheel
+plant
+helmet
+track
+hand
+fruit
+mouth
+letter
+vase
+kid
+building
+short
+surfboard
+phone
+coat
+counter
+dog
+face
+jacket
+person
+truck
+bottle
+basket
+jean
+wing

stanford_filtered/scene-graph-TF-release/data_tools/VG/predicate_list.txt

@@ -0,0 +1,50 @@
+and
+says
+belonging to
+over
+parked on
+growing on
+standing on
+made of
+attached to
+at
+in
+hanging from
+in front of
+from
+for
+lying on
+to
+behind
+flying in
+looking at
+on back of
+holding
+under
+laying on
+riding
+has
+across
+wearing
+walking on
+eating
+wears
+watching
+walking in
+sitting on
+between
+covered in
+carrying
+using
+along
+on
+with
+above
+part of
+covering
+of
+against
+playing
+near
+painted on
+mounted on

stanford_filtered/scene-graph-TF-release/data_tools/create_imdb.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+
+python vg_to_imdb.py \
+    --imh5_dir . \
+    --image_size 1024 \

stanford_filtered/scene-graph-TF-release/data_tools/create_roidb.sh

@@ -0,0 +1,21 @@
+#!/bin/bash
+set -x
+set -e
+
+OUT_PATH="."
+
+N_OBJ=150 # number of object categories
+N_REL=50 # number of relationship categories
+
+H5=VG-SGG.h5
+JSON=VG-SGG-dicts.json
+FRAC=1
+IMDB=imdb_1024.h5
+
+python vg_to_roidb.py \
+    --imdb $IMDB \
+    --json_file $OUT_PATH/$JSON \
+    --h5_file $OUT_PATH/$H5 \
+    --load_frac $FRAC \
+    --num_objects $N_OBJ \
+    --num_predicates $N_REL \

stanford_filtered/scene-graph-TF-release/data_tools/vg_to_imdb.py

@@ -0,0 +1,128 @@
+# coding=utf8
+
+import argparse, os, json, string
+from Queue import Queue
+from threading import Thread, Lock
+
+import h5py
+import numpy as np
+from scipy.misc import imread, imresize
+
+def build_filename_dict(data):
+    # First make sure all basenames are unique
+    basenames_list = [os.path.basename(img['image_path']) for img in data]
+    assert len(basenames_list) == len(set(basenames_list))
+
+    next_idx = 1
+    filename_to_idx, idx_to_filename = {}, {}
+    for img in data:
+        filename = os.path.basename(img['image_path'])
+        filename_to_idx[filename] = next_idx
+        idx_to_filename[next_idx] = filename
+        next_idx += 1
+    return filename_to_idx, idx_to_filename
+
+
+def encode_filenames(data, filename_to_idx):
+    filename_idxs = []
+    for img in data:
+        filename = os.path.basename(img['image_path'])
+        idx = filename_to_idx[filename]
+        filename_idxs.append(idx)
+    return np.asarray(filename_idxs, dtype=np.int32)
+
+
+def add_images(im_data, h5_file, args):
+    fns = []; ids = []; idx = []
+    corrupted_ims = ['1592.jpg', '1722.jpg', '4616.jpg', '4617.jpg']
+    for i, img in enumerate(im_data):
+        basename =  str(img['image_id']) + '.jpg'
+        if basename in corrupted_ims:
+            continue
+            
+        filename = os.path.join(args.image_dir, basename)
+        if os.path.exists(filename):
+            fns.append(filename)
+            ids.append(img['image_id'])
+            idx.append(i)
+
+    ids = np.array(ids, dtype=np.int32)
+    idx = np.array(idx, dtype=np.int32)
+    h5_file.create_dataset('image_ids', data=ids)
+    h5_file.create_dataset('valid_idx', data=idx)
+
+    num_images = len(fns)
+
+    shape = (num_images, 3, args.image_size, args.image_size)
+    image_dset = h5_file.create_dataset('images', shape, dtype=np.uint8)
+    original_heights = np.zeros(num_images, dtype=np.int32)
+    original_widths = np.zeros(num_images, dtype=np.int32)
+    image_heights = np.zeros(num_images, dtype=np.int32)
+    image_widths = np.zeros(num_images, dtype=np.int32)
+
+    lock = Lock()
+    q = Queue()
+    for i, fn in enumerate(fns):
+        q.put((i, fn))
+
+    def worker():
+        while True:
+            i, filename = q.get()
+
+            if i % 10000 == 0:
+                print('processing %i images...' % i)
+            img = imread(filename)
+            # handle grayscale
+            if img.ndim == 2:
+                img = img[:, :, None][:, :, [0, 0, 0]]
+            H0, W0 = img.shape[0], img.shape[1]
+            img = imresize(img, float(args.image_size) / max(H0, W0))
+            H, W = img.shape[0], img.shape[1]
+            # swap rgb to bgr. This can't be the best way right? #fail
+            r = img[:,:,0].copy()
+            img[:,:,0] = img[:,:,2]
+            img[:,:,2] = r
+
+            lock.acquire()
+            original_heights[i] = H0
+            original_widths[i] = W0
+            image_heights[i] = H
+            image_widths[i] = W
+            image_dset[i, :, :H, :W] = img.transpose(2, 0, 1)
+            lock.release()
+            q.task_done()
+
+    for i in range(args.num_workers):
+        t = Thread(target=worker)
+        t.daemon = True
+        t.start()
+
+    q.join()
+
+    h5_file.create_dataset('image_heights', data=image_heights)
+    h5_file.create_dataset('image_widths', data=image_widths)
+    h5_file.create_dataset('original_heights', data=original_heights)
+    h5_file.create_dataset('original_widths', data=original_widths)
+
+    return fns
+
+
+def main(args):
+    im_metadata = json.load(open(args.metadata_input))
+    h5_fn = 'imdb_' + str(args.image_size) + '.h5'
+    # write the h5 file
+    h5_file = os.path.join(args.imh5_dir, h5_fn)
+    f = h5py.File(h5_file, 'w')
+    # load images
+    im_fns = add_images(im_metadata, f, args)
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--image_dir', default='VG/images')
+    parser.add_argument('--image_size', default=1024, type=int)
+    parser.add_argument('--imh5_dir', default='.')
+    parser.add_argument('--num_workers', default=20, type=int)
+    parser.add_argument('--metadata_input', default='VG/image_data.json', type=str)
+
+    args = parser.parse_args()
+    main(args)

stanford_filtered/scene-graph-TF-release/data_tools/vg_to_roidb.py

@@ -0,0 +1,639 @@
+# coding=utf8
+# --------------------------------------------------------
+# Scene Graph Generation by Iterative Message Passing
+# Licensed under The MIT License [see LICENSE for details]
+# Written by Danfei Xu
+# --------------------------------------------------------
+
+import argparse, json, string
+from collections import Counter
+import math
+
+from math import floor
+import h5py as h5
+import numpy as np
+import pprint
+
+"""
+A script for generating an hdf5 ROIDB from the VisualGenome dataset
+"""
+
+def preprocess_object_labels(data, alias_dict={}):
+    for img in data:
+        for obj in img['objects']:
+            obj['ids'] = [obj['object_id']]
+            names = []
+            for name in obj['names']:
+                label = sentence_preprocess(name)
+                if label in alias_dict:
+                    label = alias_dict[label]
+                names.append(label)
+            obj['names'] = names
+
+
+def preprocess_predicates(data, alias_dict={}):
+    for img in data:
+        for relation in img['relationships']:
+            predicate = sentence_preprocess(relation['predicate'])
+            if predicate in alias_dict:
+                predicate = alias_dict[predicate]
+            relation['predicate'] = predicate
+
+
+def extract_object_token(data, num_tokens, obj_list=[], verbose=True):
+    """ Builds a set that contains the object names. Filters infrequent tokens. """
+    token_counter = Counter()
+    for img in data:
+        for region in img['objects']:
+            for name in region['names']:
+                if not obj_list or name in obj_list:
+                    token_counter.update([name])
+    tokens = set()
+    # pick top N tokens
+    token_counter_return = {}
+    for token, count in token_counter.most_common():
+        tokens.add(token)
+        token_counter_return[token] = count
+        if len(tokens) == num_tokens:
+            break
+    if verbose:
+        print(('Keeping %d / %d objects'
+                  % (len(tokens), len(token_counter))))
+    return tokens, token_counter_return
+
+
+def extract_predicate_token(data, num_tokens, pred_list=[], verbose=True):
+    """ Builds a set that contains the relationship predicates. Filters infrequent tokens. """
+    token_counter = Counter()
+    total = 0
+    for img in data:
+        for relation in img['relationships']:
+            predicate = relation['predicate']
+            if not pred_list or predicate in pred_list:
+                token_counter.update([predicate])
+            total += 1
+    tokens = set()
+    token_counter_return = {}
+    for token, count in token_counter.most_common():
+        tokens.add(token)
+        token_counter_return[token] = count
+        if len(tokens) == num_tokens:
+            break
+    if verbose:
+        print(('Keeping %d / %d predicates with enough instances'
+                  % (len(tokens), len(token_counter))))
+    return tokens, token_counter_return
+
+
+def merge_duplicate_boxes(data):
+    def IoU(b1, b2):
+        if b1[2] <= b2[0] or \
+            b1[3] <= b2[1] or \
+            b1[0] >= b2[2] or \
+            b1[1] >= b2[3]:
+            return 0
+
+        b1b2 = np.vstack([b1,b2])
+        minc = np.min(b1b2, 0)
+        maxc = np.max(b1b2, 0)
+        union_area = (maxc[2]-minc[0])*(maxc[3]-minc[1])
+        int_area = (minc[2]-maxc[0])*(minc[3]-maxc[1])
+        return float(int_area)/float(union_area)
+
+    def to_x1y1x2y2(obj):
+        x1 = obj['x']
+        y1 = obj['y']
+        x2 = obj['x'] + obj['w']
+        y2 = obj['y'] + obj['h']
+        return np.array([x1, y1, x2, y2], dtype=np.int32)
+
+    def inside(b1, b2):
+        return b1[0] >= b2[0] and b1[1] >= b2[1] \
+            and b1[2] <= b2[2] and b1[3] <= b2[3]
+
+    def overlap(obj1, obj2):
+        b1 = to_x1y1x2y2(obj1)
+        b2 = to_x1y1x2y2(obj2)
+        iou = IoU(b1, b2)
+        if all(b1 == b2) or iou > 0.9: # consider as the same box
+            return 1
+        elif (inside(b1, b2) or inside(b2, b1))\
+            and obj1['names'][0] == obj2['names'][0]: # same object inside the other
+            return 2
+        elif iou > 0.6 and obj1['names'][0] == obj2['names'][0]: # multiple overlapping same object
+            return 3
+        else:
+            return 0  # no overlap
+
+    num_merged = {1:0, 2:0, 3:0}
+    print('merging boxes..')
+    for img in data:
+        # mark objects to be merged and save their ids
+        objs = img['objects']
+        num_obj = len(objs)
+        for i in range(num_obj):
+            if 'M_TYPE' in objs[i]:  # has been merged
+                continue
+            merged_objs = [] # circular refs, but fine
+            for j in range(i+1, num_obj):
+                if 'M_TYPE' in objs[j]:  # has been merged
+                    continue
+                overlap_type = overlap(objs[i], objs[j])
+                if overlap_type > 0:
+                    objs[j]['M_TYPE'] = overlap_type
+                    merged_objs.append(objs[j])
+            objs[i]['mobjs'] = merged_objs
+
+        # merge boxes
+        filtered_objs = []
+        merged_num_obj = 0
+        for obj in objs:
+            if 'M_TYPE' not in obj:
+                ids = [obj['object_id']]
+                dims = [to_x1y1x2y2(obj)]
+                prominent_type = 1
+                for mo in obj['mobjs']:
+                    ids.append(mo['object_id'])
+                    obj['names'].extend(mo['names'])
+                    dims.append(to_x1y1x2y2(mo))
+                    if mo['M_TYPE'] > prominent_type:
+                        prominent_type = mo['M_TYPE']
+                merged_num_obj += len(ids)
+                obj['ids'] = ids
+                mdims = np.zeros(4)
+                if prominent_type > 1: # use extreme
+                    mdims[:2] = np.min(np.vstack(dims)[:,:2], 0)
+                    mdims[2:] = np.max(np.vstack(dims)[:,2:], 0)
+                else:  # use mean
+                    mdims = np.mean(np.vstack(dims), 0)
+                obj['x'] = int(mdims[0])
+                obj['y'] = int(mdims[1])
+                obj['w'] = int(mdims[2] - mdims[0])
+                obj['h'] = int(mdims[3] - mdims[1])
+
+                num_merged[prominent_type] += len(obj['mobjs'])
+
+                obj['mobjs'] = None
+                obj['names'] = list(set(obj['names']))  # remove duplicates
+
+                filtered_objs.append(obj)
+            else:
+                assert 'mobjs' not in obj
+
+        img['objects'] = filtered_objs
+        assert(merged_num_obj == num_obj)
+
+    print('# merged boxes per merging type:')
+    print(num_merged)
+
+
+def build_token_dict(vocab):
+    """ build bi-directional mapping between index and token"""
+    token_to_idx, idx_to_token = {}, {}
+    next_idx = 1
+    vocab_sorted = sorted(list(vocab)) # make sure it's the same order everytime
+    for token in vocab_sorted:
+        token_to_idx[token] = next_idx
+        idx_to_token[next_idx] = token
+        next_idx = next_idx + 1
+
+    return token_to_idx, idx_to_token
+
+
+def encode_box(region, org_h, org_w, im_long_size):
+    x = region['x']
+    y = region['y']
+    w = region['w']
+    h = region['h']
+    scale = float(im_long_size) / max(org_h, org_w)
+    image_size = im_long_size
+    # recall: x,y are 1-indexed
+    x, y = math.floor(scale*(region['x']-1)), math.floor(scale*(region['y']-1))
+    w, h = math.ceil(scale*region['w']), math.ceil(scale*region['h'])
+
+    # clamp to image
+    if x < 0: x = 0
+    if y < 0: y = 0
+
+    # box should be at least 2 by 2
+    if x > image_size - 2:
+        x = image_size - 2
+    if y > image_size - 2:
+        y = image_size - 2
+    if x + w >= image_size:
+        w = image_size - x
+    if y + h >= image_size:
+        h = image_size - y
+
+    # also convert to center-coord oriented
+    box = np.asarray([x+floor(w/2), y+floor(h/2), w, h], dtype=np.int32)
+    assert box[2] > 0  # width height should be positive numbers
+    assert box[3] > 0
+    return box
+
+
+def encode_objects(obj_data, token_to_idx, token_counter, org_h, org_w, im_long_sizes):
+    encoded_labels = []
+    encoded_boxes  = {}
+    for size in im_long_sizes:
+        encoded_boxes[size] = []
+    im_to_first_obj = np.zeros(len(obj_data), dtype=np.int32)
+    im_to_last_obj = np.zeros(len(obj_data), dtype=np.int32)
+    obj_counter = 0
+
+    for i, img in enumerate(obj_data):
+        im_to_first_obj[i] = obj_counter
+        img['id_to_idx'] = {}  # object id to region idx
+        for obj in img['objects']:
+           # pick a label for the object
+            max_occur = 0
+            obj_label = None
+            for name in obj['names']:
+                # pick the name that has maximum occurance
+                if name in token_to_idx and token_counter[name] > max_occur:
+                    obj_label = name
+                    max_occur = token_counter[obj_label]
+
+            if obj_label is not None:
+                # encode region
+                for size in im_long_sizes:
+                    encoded_boxes[size].append(encode_box(obj, org_h[i], org_w[i], size))
+
+                encoded_labels.append(token_to_idx[obj_label])
+
+                for obj_id in obj['ids']: # assign same index for merged ids
+                    img['id_to_idx'][obj_id] = obj_counter
+
+                obj_counter += 1
+
+
+        if im_to_first_obj[i] == obj_counter:
+            im_to_first_obj[i] = -1
+            im_to_last_obj[i] = -1
+        else:
+            im_to_last_obj[i] = obj_counter - 1
+
+    for k, boxes in encoded_boxes.items():
+        encoded_boxes[k] = np.vstack(boxes)
+    return np.vstack(encoded_labels), encoded_boxes, im_to_first_obj, im_to_last_obj
+
+
+def encode_relationship(sub_id, obj_id, id_to_idx):
+    # builds a tuple of the index of object and subject in the object list
+    sub_idx = id_to_idx[sub_id]
+    obj_idx = id_to_idx[obj_id]
+    return np.asarray([sub_idx, obj_idx], dtype=np.int32)
+
+
+def encode_relationships(rel_data, token_to_idx, obj_data):
+    """MUST BE CALLED AFTER encode_objects!!!"""
+    encoded_pred = []  # encoded predicates
+    encoded_rel = []  # encoded relationship tuple
+    im_to_first_rel = np.zeros(len(rel_data), dtype=np.int32)
+    im_to_last_rel = np.zeros(len(rel_data), dtype=np.int32)
+    rel_idx_counter = 0
+
+    no_rel_counter = 0
+    obj_filtered = 0
+    predicate_filtered = 0
+    duplicate_filtered = 0
+    for i, img in enumerate(rel_data):
+        im_to_first_rel[i] = rel_idx_counter
+        id_to_idx = obj_data[i]['id_to_idx']  # object id to object list idx
+        for relation in img['relationships']:
+            subj = relation['subject']
+            obj = relation['object']
+            predicate = relation['predicate']
+            if subj['object_id'] not in id_to_idx or obj['object_id'] not in id_to_idx:
+                obj_filtered += 1
+                continue
+            elif predicate not in token_to_idx:
+                predicate_filtered += 1
+                continue
+            elif id_to_idx[subj['object_id']] == id_to_idx[obj['object_id']]: # sub and obj can't be the same box
+                duplicate_filtered += 1
+                continue
+            else:
+                encoded_pred.append(token_to_idx[predicate])
+                encoded_rel.append(
+                    encode_relationship(subj['object_id'],
+                                        obj['object_id'],
+                                        id_to_idx
+                                        ))
+                rel_idx_counter += 1  # accumulate counter
+
+        if im_to_first_rel[i] == rel_idx_counter:
+            # if no qualifying relationship
+            im_to_first_rel[i] = -1
+            im_to_last_rel[i] = -1
+            no_rel_counter += 1
+        else:
+            im_to_last_rel[i] = rel_idx_counter - 1
+    print('%i rel is filtered by object' % obj_filtered)
+    print('%i rel is filtered by predicate' % predicate_filtered)
+    print('%i rel is filtered by duplicate' % duplicate_filtered)
+    print('%i rel remains ' % len(encoded_pred))
+
+    print('%i out of %i valid images have relationships' % (len(rel_data)-no_rel_counter, len(rel_data)))
+    return np.vstack(encoded_pred), np.vstack(encoded_rel), im_to_first_rel, im_to_last_rel
+
+
+def sentence_preprocess(phrase):
+    """ preprocess a sentence: lowercase, clean up weird chars, remove punctuation """
+    replacements = {
+      '½': 'half',
+      '—' : '-',
+      '™': '',
+      '¢': 'cent',
+      'ç': 'c',
+      'û': 'u',
+      'é': 'e',
+      '°': ' degree',
+      'è': 'e',
+      '…': '',
+    }
+    phrase = phrase.encode('utf-8')
+    phrase = phrase.lstrip(' ').rstrip(' ')
+    for k, v in replacements.iteritems():
+        phrase = phrase.replace(k, v)
+    return str(phrase).lower().translate(None, string.punctuation).decode('utf-8', 'ignore')
+
+
+def encode_splits(obj_data, opt=None):
+    if opt is not None:
+        val_begin_idx = opt['val_begin_idx']
+        test_begin_idx = opt['test_begin_idx']
+    split = np.zeros(len(obj_data), dtype=np.int32)
+    for i, info in enumerate(obj_data):
+        splitix = 0
+        if opt is None: # use encode from input file
+            s = info['split']
+            if s == 'val': splitix = 1
+            if s == 'test': splitix = 2
+        else: # use portion split
+            if i >= val_begin_idx: splitix = 1
+            if i >= test_begin_idx: splitix = 2
+        split[i] = splitix
+    if opt is not None and opt['shuffle']:
+        np.random.shuffle(split)
+
+    print(('assigned %d/%d/%d to train/val/test split' % (np.sum(split==0), np.sum(split==1), np.sum(split==2))))
+    return split
+
+
+def make_alias_dict(dict_file):
+    """create an alias dictionary from a file"""
+    out_dict = {}
+    vocab = []
+    for line in open(dict_file, 'r'):
+        alias = line.strip('\n').strip('\r').split(',')
+        alias_target = alias[0] if alias[0] not in out_dict else out_dict[alias[0]]
+        for a in alias:
+            out_dict[a] = alias_target  # use the first term as the aliasing target
+        vocab.append(alias_target)
+    return out_dict, vocab
+
+
+def make_list(list_file):
+    """create a blacklist list from a file"""
+    return [line.strip('\n').strip('\r') for line in open(list_file)]
+
+
+def filter_object_boxes(data, heights, widths, area_frac_thresh):
+    """
+    filter boxes by a box area-image area ratio threshold
+    """
+    thresh_count = 0
+    all_count = 0
+    for i, img in enumerate(data):
+        filtered_obj = []
+        area = float(heights[i]*widths[i])
+        for obj in img['objects']:
+            if float(obj['h'] * obj['w']) > area * area_frac_thresh:
+                filtered_obj.append(obj)
+                thresh_count += 1
+            all_count += 1
+        img['objects'] = filtered_obj
+    print('box threshod: keeping %i/%i boxes' % (thresh_count, all_count))
+
+
+def filter_by_idx(data, valid_list):
+    return [data[i] for i in valid_list]
+
+
+def obj_rel_cross_check(obj_data, rel_data, verbose=False):
+    """
+    make sure all objects that are in relationship dataset
+    are in object dataset
+    """
+    num_img = len(obj_data)
+    num_correct = 0
+    total_rel = 0
+    for i in xrange(num_img):
+        assert(obj_data[i]['image_id'] == rel_data[i]['image_id'])
+        objs = obj_data[i]['objects']
+        rels = rel_data[i]['relationships']
+        ids = [obj['object_id'] for obj in objs]
+        for rel in rels:
+            if rel['subject']['object_id'] in ids \
+                and rel['object']['object_id'] in ids:
+                num_correct += 1
+            elif verbose:
+                if rel['subject']['object_id'] not in ids:
+                    print(str(rel['subject']['object_id']) + 'cannot be found in ' + str(i))
+                if rel['object']['object_id'] not in ids:
+                    print(str(rel['object']['object_id']) + 'cannot be found in ' + str(i))
+            total_rel += 1
+    print('cross check: %i/%i relationship are correct' % (num_correct, total_rel))
+
+
+def sync_objects(obj_data, rel_data):
+    num_img = len(obj_data)
+    for i in xrange(num_img):
+        assert(obj_data[i]['image_id'] == rel_data[i]['image_id'])
+        objs = obj_data[i]['objects']
+        rels = rel_data[i]['relationships']
+
+        ids = [obj['object_id'] for obj in objs]
+        for rel in rels:
+            if rel['subject']['object_id'] not in ids:
+                rel_obj = rel['subject']
+                rel_obj['names'] = [rel_obj['name']]
+                objs.append(rel_obj)
+            if rel['object']['object_id'] not in ids:
+                rel_obj = rel['object']
+                rel_obj['names'] = [rel_obj['name']]
+                objs.append(rel_obj)
+
+        obj_data[i]['objects'] = objs
+
+
+def main(args):
+    print('start')
+    pprint.pprint(args)
+
+    obj_alias_dict = {}
+    if len(args.object_alias) > 0:
+        print('using object alias from %s' % (args.object_alias))
+        obj_alias_dict, obj_vocab_list = make_alias_dict(args.object_alias)
+
+    pred_alias_dict = {}
+    if len(args.pred_alias) > 0:
+        print('using predicate alias from %s' % (args.pred_alias))
+        pred_alias_dict, pred_vocab_list = make_alias_dict(args.pred_alias)
+
+    obj_list = []
+    if len(args.object_list) > 0:
+        print('using object list from %s' % (args.object_list))
+        obj_list = make_list(args.object_list)
+        assert(len(obj_list) >= args.num_objects)
+
+    pred_list = []
+    if len(args.pred_list) > 0:
+        print('using predicate list from %s' % (args.pred_list))
+        pred_list = make_list(args.pred_list)
+        assert(len(obj_list) >= args.num_predicates)
+
+    # read in the annotation data
+    print('loading json files..')
+    obj_data = json.load(open(args.object_input))
+    rel_data = json.load(open(args.relationship_input))
+    img_data = json.load(open(args.metadata_input))
+    assert(len(rel_data) == len(obj_data) and
+           len(obj_data) == len(img_data))
+
+    print('read image db from %s' % args.imdb)
+    imdb = h5.File(args.imdb, 'r')
+    num_im, _, _, _ = imdb['images'].shape
+    img_long_sizes = [512, 1024]
+    valid_im_idx = imdb['valid_idx'][:] # valid image indices
+    img_ids = imdb['image_ids'][:]
+    obj_data = filter_by_idx(obj_data, valid_im_idx)
+    rel_data = filter_by_idx(rel_data, valid_im_idx)
+    img_data = filter_by_idx(img_data, valid_im_idx)
+
+    # sanity check
+    for i in xrange(num_im):
+        assert(obj_data[i]['image_id'] \
+               == rel_data[i]['image_id'] \
+               == img_data[i]['image_id'] \
+               == img_ids[i]
+               )
+
+    # may only load a fraction of the data
+    if args.load_frac < 1:
+        num_im = int(num_im*args.load_frac)
+        obj_data = obj_data[:num_im]
+        rel_data = rel_data[:num_im]
+    print('processing %i images' % num_im)
+
+    # sync objects from rel to obj_data
+    sync_objects(obj_data, rel_data)
+
+    obj_rel_cross_check(obj_data, rel_data)
+
+    # preprocess label data
+    preprocess_object_labels(obj_data, alias_dict=obj_alias_dict)
+    preprocess_predicates(rel_data, alias_dict=pred_alias_dict)
+
+    heights, widths = imdb['original_heights'][:], imdb['original_widths'][:]
+    if args.min_box_area_frac > 0:
+        # filter out invalid small boxes
+        print('threshold bounding box by %f area fraction' % args.min_box_area_frac)
+        filter_object_boxes(obj_data, heights, widths, args.min_box_area_frac) # filter by box dimensions
+
+    merge_duplicate_boxes(obj_data)
+
+    # build vocabulary
+    object_tokens, object_token_counter = extract_object_token(obj_data, args.num_objects,
+                                                               obj_list)
+
+    label_to_idx, idx_to_label = build_token_dict(object_tokens)
+
+    predicate_tokens, predicate_token_counter = extract_predicate_token(rel_data,
+                                                                        args.num_predicates,
+                                                                        pred_list)
+    predicate_to_idx, idx_to_predicate = build_token_dict(predicate_tokens)
+
+    # print out vocabulary
+    print('objects: ')
+    print(object_token_counter)
+    print('relationships: ')
+    print(predicate_token_counter)
+
+    # write the h5 file
+    f = h5.File(args.h5_file, 'w')
+
+    # encode object
+    encoded_label, encoded_boxes, im_to_first_obj, im_to_last_obj = \
+    encode_objects(obj_data, label_to_idx, object_token_counter, \
+                   heights, widths, img_long_sizes)
+
+    f.create_dataset('labels', data=encoded_label)
+    for k, boxes in encoded_boxes.items():
+        f.create_dataset('boxes_%i' % k, data=boxes)
+    f.create_dataset('img_to_first_box', data=im_to_first_obj)
+    f.create_dataset('img_to_last_box', data=im_to_last_obj)
+
+    encoded_predicate, encoded_rel, im_to_first_rel, im_to_last_rel = \
+    encode_relationships(rel_data, predicate_to_idx, obj_data)
+
+    f.create_dataset('predicates', data=encoded_predicate)
+    f.create_dataset('relationships', data=encoded_rel)
+    f.create_dataset('img_to_first_rel', data=im_to_first_rel)
+    f.create_dataset('img_to_last_rel', data=im_to_last_rel)
+
+   # build train/val/test splits
+
+    print('num objects = %i' % encoded_label.shape[0])
+    print('num relationships = %i' % encoded_predicate.shape[0])
+
+
+    opt = None
+    if not args.use_input_split:
+        opt = {}
+        opt['val_begin_idx'] = int(len(obj_data) * args.train_frac)
+        opt['test_begin_idx'] = int(len(obj_data) * args.val_frac)
+        opt['shuffle'] = args.shuffle
+    split = encode_splits(obj_data, opt)
+
+    if split is not None:
+        f.create_dataset('split', data=split) # 1 = test, 0 = train
+
+    # and write the additional json file
+    json_struct = {
+        'label_to_idx': label_to_idx,
+        'idx_to_label': idx_to_label,
+        'predicate_to_idx': predicate_to_idx,
+        'idx_to_predicate': idx_to_predicate,
+        'predicate_count': predicate_token_counter,
+        'object_count': object_token_counter
+    }
+
+    with open(args.json_file, 'w') as f:
+        json.dump(json_struct, f)
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--imdb', default='VG/imdb_1024.h5', type=str)
+    parser.add_argument('--object_input', default='VG/objects.json', type=str)
+    parser.add_argument('--relationship_input', default='VG/relationships.json', type=str)
+    parser.add_argument('--metadata_input', default='VG/image_data.json', type=str)
+    parser.add_argument('--object_alias', default='VG/object_alias.txt', type=str)
+    parser.add_argument('--pred_alias', default='VG/predicate_alias.txt', type=str)
+    parser.add_argument('--object_list', default='VG/object_list.txt', type=str)
+    parser.add_argument('--pred_list', default='VG/predicate_list.txt', type=str)
+    parser.add_argument('--num_objects', default=150, type=int, help="set to 0 to disable filtering")
+    parser.add_argument('--num_predicates', default=50, type=int, help="set to 0 to disable filtering")
+    parser.add_argument('--min_box_area_frac', default=0.002, type=float)
+    parser.add_argument('--json_file', default='VG-dicts.json')
+    parser.add_argument('--h5_file', default='VG.h5')
+    parser.add_argument('--load_frac', default=1, type=float)
+    parser.add_argument('--use_input_split', default=False, type=bool)
+    parser.add_argument('--train_frac', default=0.7, type=float)
+    parser.add_argument('--val_frac', default=0.7, type=float)
+    parser.add_argument('--shuffle', default=False, type=bool)
+
+    args = parser.parse_args()
+    main(args)