Datasets:

Task Categories: image-to-text
Languages: en
Multilinguality: monolingual
Size Categories: 1M<n<10M
Licenses: unknown
Language Creators: found
Annotations Creators: found
Source Datasets: original
Dataset Preview Go to dataset viewer
image_url (image)user_id (string)caption (string)
47889917@N08
A wooden chair in the living room
29708551@N00
white horse near avebury
46339232@N07
Yellow flower surrounded by scorched black stalks - Moore Nature Reserve
69405057@N00
King Arthur's beheading rock - right on the sidewalk in the middle of town
79837140@N00
This is a shot of the Brittanic flag flying atop a farmhouse beside a field of megaliths
48341195@N04
It was taken when the season was running out and only this lonely flower was left in the field.
32887925@N07
Coma sleeping on her bed in the front bedroom (2008)
20144640@N00
Photos from a trip to a castle tower above Ljubljana.
32267947@N06
Frost in my bathroom window as seen on a cold winter day.Cabri, Saskatchewan in February 2011
39882612@N04
this was the sun and some tree branches in front of my bedroom window.. i inverted and edited.
8328184@N02
A bottle in the main door of Tiffany &amp;amp; Co.
17904502@N00
wild ducks in a big sweet water lake in Guizhou, China
43472658@N07
Asbestos is used willy-nilly in ukraine as building material. Dad and Tanya have an asbestos roof and an asbestos fence.
99746053@N00
Iris near the tri-foliate orange tree
48078717@N00
View out the window of the upstairs bedroom of Mercedes' place in Holland, MI. August 2004.
56665574@N00
bridge street in the rain ..
52848143@N00
sitting in my computer chair.
32762779@N07
You see these in orange, magenta, red and white all over Tenerife. A riot of colour.
9143581@N03
box elder bugs on one of my old 33&amp;quot; truck tires layin under the tree
12544404@N06
Kellogs in a pizza box =) (c) celine jacinto 2010. all rights reserved.
8435962@N06
A pink car on the ferris wheel in Odaiba.
9474298@N08
Me in a tree at my school in France! boy was I high up there!
7745738@N08
Area just north of hydro-electric plant near Great Fall SC. Power lines can be seen just above the tree line
32497732@N07
Dan, waiting for fish to jump in the boat so he can retake the lead from the NG
64749159@N00
Mommy, Daddy and Chase in a paddle boat on the lake at the Tarara Winery outside of Lucketts, VA.
16918641@N05
Monkeys up in the tree as seen from our river cruise along the Belize River.
27607575@N00
Chicago at night from bridge over the river
75881025@N00
bits of glass smoothed over by the waves and sand
53170558@N03
The day is over .. the big red sunball goes to sleep painting the sky in red
87547772@N00
The plate near the door almost makes it look like the CCTV camera is the logo of the hotel.
44124423673@N01
A new church in Leam with cool window reflections.
28100651@N07
A corner view of a brick building in black &amp;amp; white.
42744010@N00
darren on the corner of beach blvd &amp;amp; main st. bsl bridge in the background. soooo tired of streets torn up.
22767894@N02
Brix sitting in her rocking chair on the front porch
45813919@N07
This boat man has to pull the bamboo boat across every divider as the water does not flow across in low tide.
8188078@N04
This is a flower of a gourd plant in my backyard.
44831858@N00
A little bird built her nest underneath the roof of my veranda this spring. She hatched 4 babies.
28217619@N00
Felix in his uber cute argyle cat sweater. Too bad he HATED it...with a passion.
20794436@N00
A close look at winter stoneflies reveals mottled wings and black or brown bodies. Photo by Jason du Pont.
79204206@N00
This crazy dog was jumping up and down at the tree and running all around
46485566@N04
Out of my bedroom window at 8 o' clock in the evening
42886798@N00
Had sleeping bags and pillows in the back of the truck and a chair for Bill.
23485843@N02
Sunset red sky over Koltur
80811313@N00
A train trellis over a body of water surrounded by trees turning.
82635623@N00
Bird Running in water on beach near Monterey
35484044@N05
Cinnamon and nutmeg in tree form. Delicious! Your wall will thank you!
22976502@N05
Karipol Leipzig, Germany, abandoned factory for house und car cleaning supplies in leipzig. founded in 1897, closed in 1995.
80789365@N00
The pump house (second building in the background) and some other building next to it (in the foreground)
14090498@N04
The best picture of Maybree in this cake box was taken by Lorna or her mom with Lorna's camera.
15737284@N06
This box has two spearmint plants in it and a chocolate mint plant which smells really awesome.
35781259@N00
A cozy street cafe with a canopy and the colorful reflection in a modern glass building
30607051@N00
fire boat at the dock's under the bay bridge just after dawn - embarcadero, san francisco, california
66798295@N00
Cool tower at the top of the mountain in the rainforest
89612536@N00
not a cloud in the sky (marin trail)
9186480@N05
Glass knobs in Stone Glass design for furniture knobs, dresser knobs, bathroom knobs, kitchen knobs and more. Custom sizes available by Uneek Glass Fusions.
33932135@N08
This train car is parked permanently in a yard in Royal, Nebraska.
35813754@N05
over the door shoe organizer
90554698@N00
mr. and mrs. wright and mr. and mrs. van der hyde. not a bird in sight....
82088782@N00
Looking at the new bridge construction with the Kate Shelley Bridge in the background. There is a coal train going by.
7255679@N04
some with glass, some only have a white glaze....these will have glass added at earthenware temperature. Some will have lustres added in a seperate firing
7399465@N06
The empty lot next door shot from computer room window. Usualy there are Mallards swimming in the temporary ponds.
24643141@N00
sand castle on Copacabana beach in Rio de Janeiro
33896471@N06
Pine tree and the sky above the San Juan National Forest in Colorado
17129636@N00
pedestrian over bridge with leaping girl
57822052@N00
Camera is sitting on a hotel towel on the air-conditioner with the lense closed in the sliding window.
21868470@N03
Tomato plant in the ground
92891603@N00
where they replaced the squishy floor in the second bathroom
21510583@N04
I found this old farm house at the base of the Alps near Castle Neuschwanstein.
8226961@N05
Minor road in Trivandrum, East Fort, viewed from roof top restaurant China Town
11888997@N00
Tunnel with the walking path near my house with trees
60642416@N00
An alkaline and hypersaline lake in California, United States that is a critical nesting habitat for several bird species.
39313606@N07
Somewhere in this house there's a magic mirror, a talking candle stick, and a glowing rose underneath a bell jar
29670082@N04
Another shot of the building next to the sixth floor museum in Dallas
8282860@N02
Dnieper river under dramatic sky
9902927@N05
Site 14 outside Tecate Mexico building a house by the TKA students.
12635387@N04
followed into the bathroom by a boy
30147402@N08
A very surly looking black cat in a very hot Italian village.
99657969@N00
Mabel and Daisy enjoying the yummy green grass in the hayfield, while their summer home is being fenced off and built.
96822366@N00
Spider rock dominates the landscape at canyon de chelly in northern arizona
25254880@N07
Gorgeous wedding dress detailed in black and white.
46438192@N00
found in a vending machine in a train station in switzerland
22786607@N00
a tropical forest in the train station! how cool is that!
22702863@N06
kid at table 032307. todd in chair 053006.
29818212@N03
Caurosel horse with Eiffel tower in background
10950249@N07
Mallard duck in in the river Stour in Canterbury
51670120@N08
Yet another tree stump in the truck
40617004@N00
out of the oven and fruit mixed in
59417938@N00
This is a glass ceiling in the lobby of an office building.
71362151@N00
Not the best idea to roll around on my floor wearing white
58771608@N06
girl in the strange red sunglasses
14914520@N06
le hast le hill in le pink le shirt
62697203@N00
fork in red velvet cake
14524113@N08
A view of the warning track through the fence in the left field bleachers--April 9, 2007
42744010@N00
new twin span bridge goign over lake pontchartrain
53964109@N04
Accessible check-out window in a doctor's office waiting room.
17959488@N04
Conrail SD50 No. 6749 leads a westbound TV train approaching the Route 53 bridge near Cresson, PA.
11534815@N06
US mail box found in the middle of the street
74128918@N00
red sky over london
42040949@N03
my sister's dog Diva in the car
12162840@N04
baby magic candle in blue
End of preview (truncated to 100 rows)

Dataset Card for SBU Captioned Photo Dataset

Dataset Summary

SBU Captioned Photo Dataset is a collection of associated captions and images from Flickr.

Dataset Preprocessing

This dataset doesn't download the images locally by default. Instead, it exposes URLs to the images. To fetch the images, use the following code:

from concurrent.futures import ThreadPoolExecutor
from functools import partial
import io
import urllib

import PIL.Image

from datasets import load_dataset
from datasets.utils.file_utils import get_datasets_user_agent


USER_AGENT = get_datasets_user_agent()


def fetch_single_image(image_url, timeout=None, retries=0):
    for _ in range(retries + 1):
        try:
            request = urllib.request.Request(
                image_url,
                data=None,
                headers={"user-agent": USER_AGENT},
            )
            with urllib.request.urlopen(request, timeout=timeout) as req:
                image = PIL.Image.open(io.BytesIO(req.read()))
            break
        except Exception:
            image = None
    return image


def fetch_images(batch, num_threads, timeout=None, retries=0):
    fetch_single_image_with_args = partial(fetch_single_image, timeout=timeout, retries=retries)
    with ThreadPoolExecutor(max_workers=num_threads) as executor:
        batch["image"] = list(executor.map(fetch_single_image_with_args, batch["image_url"]))
    return batch


num_threads = 20
dset = load_dataset("sbu_captions")
dset = dset.map(fetch_images, batched=True, batch_size=100, fn_kwargs={"num_threads": num_threads})

Supported Tasks and Leaderboards

  • image-to-text: This dataset can be used to train a model for Image Captioning where the goal is to predict a caption given the image.

Languages

All captions are in English.

Dataset Structure

Data Instances

Each instance in SBU Captioned Photo Dataset represents a single image with a caption and a user_id:

{
  'img_url': 'http://static.flickr.com/2723/4385058960_b0f291553e.jpg', 
  'user_id': '47889917@N08', 
  'caption': 'A wooden chair in the living room'
}

Data Fields

  • image_url: Static URL for downloading the image associated with the post.
  • caption: Textual description of the image.
  • user_id: Author of caption.

Data Splits

All the data is contained in training split. The training set has 1M instances.

Dataset Creation

Curation Rationale

From the paper:

One contribution is our technique for the automatic collection of this new dataset – performing a huge number of Flickr queries and then filtering the noisy results down to 1 million images with associated visually relevant captions. Such a collection allows us to approach the extremely challenging problem of description generation using relatively simple non-parametric methods and produces surprisingly effective results.

Source Data

The source images come from Flickr.

Initial Data Collection and Normalization

One key contribution of our paper is a novel web-scale database of photographs with associated descriptive text. To enable effective captioning of novel images, this database must be good in two ways: 1) It must be large so that image based matches to a query are reasonably similar, 2) The captions associated with the data base photographs must be visually relevant so that transferring captions between pictures is useful. To achieve the first requirement we query Flickr using a huge number of pairs of query terms (objects, attributes, actions, stuff, and scenes). This produces a very large, but noisy initial set of photographs with associated text.

Who are the source language producers?

The Flickr users.

Annotations

Annotation process

Text descriptions associated with the images are inherited as annotations/captions.

Who are the annotators?

The Flickr users.

Personal and Sensitive Information

Considerations for Using the Data

Social Impact of Dataset

Discussion of Biases

Other Known Limitations

Additional Information

Dataset Curators

Vicente Ordonez, Girish Kulkarni and Tamara L. Berg.

Licensing Information

Not specified.

Citation Information

@inproceedings{NIPS2011_5dd9db5e,
 author = {Ordonez, Vicente and Kulkarni, Girish and Berg, Tamara},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {J. Shawe-Taylor and R. Zemel and P. Bartlett and F. Pereira and K.Q. Weinberger},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Im2Text: Describing Images Using 1 Million Captioned Photographs},
 url = {https://proceedings.neurips.cc/paper/2011/file/5dd9db5e033da9c6fb5ba83c7a7ebea9-Paper.pdf},
 volume = {24},
 year = {2011}
}

Contributions

Thanks to @thomasw21 for adding this dataset.

Update on GitHub
Papers with Code