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A smiling man stands in front of a pole. | [
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A policeman and his dog are working together. | [
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A person is riding a bike in snow. | [
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Five men in white clothes converse in a parking lot. | [
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A Caucasian man and a dark-skinned woman work together in a factory setting. | [
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Asian man sweeps street with broom. | [
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Two men converse with a driver and a cyclist. | [
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Two girls are playing outside. | [
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A man approaches a silver vehicle. | [
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A newlywed couple walks down the aisle. | [
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A young boy is playing a video game at a McDonald's. | [
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A white dog is playing with a red ball on the shore. | [
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A group of people are enjoying a picnic or barbecue at a park. | [
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A man and woman sit on a bench while a car passes by. | [
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A group of people enjoy food outdoors. | [
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A crowd watches a martial arts demonstration. | [
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A man is being doused by a boy. | [
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A man in a red jacket shields his face from the sun while reading. | [
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Two men and children walk down a street together. | [
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A smiling boy stands on a street with a man working on a stone wall. | [
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A black dog leaps over a fallen log. | [
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A man in a red shirt rides his bicycle. | [
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A man grills hotdogs while holding a cup. | [
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A dog is running in the snow. | [
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A man skiing past other man selling art in the snow. | [
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A group of climbers are climbing a rock. | [
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A gymnast performs on a balance beam. | [
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A young boy is pushing a toy vehicle around a pool or lawn. | [
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A woman is using a telescope to look at a bay from a viewing deck or rooftop. | [
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A brown dog is playing with a hose. | [
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A happy family poses in a supermarket. | [
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A white dog catches a yellow ball. | [
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A man sits at a table with a glass of water. | [
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A dog catches a ball in a field. | [
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Two men are hiking in the snow. | [
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A man is carrying a wooden cabinet. | [
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Two men sitting on the floor. | [
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A man reads a map while driving. | [
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A boy watches a duck from the shore near a cityscape. | [
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A couple hold an infant while sitting near a pond or lake. | [
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Three men stand near a shelter and bike parking. | [
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A black dog splashes in the water. | [
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A man drills a hole in the ice for ice fishing. | [
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Two dogs are playing on a beach. | [
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An ice climber scales an ice wall using ice picks and crampons. | [
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Two or more individuals walking together in nature. | [
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A man shovels snow on a city street. | [
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A couple is cutting a wedding cake. | [
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A black dog is carrying a blue toy while walking through the grass. | [
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A group of people is selling vegetables at a market. | [
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A punk rock band performs at a concert. | [
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A person is skateboarding at a skate park. | [
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A man and child are kayaking. | [
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A little boy sits on porch, smiling as two women laugh. | [
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Construction workers install a light post at a street construction site. | [
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Two men sit on a bench outside the airport, one wearing a yellow shirt and the other wearing a white shirt. | [
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People are holding rainbow flags during a parade. | [
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Three men watch as fish is being prepared. | [
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A woman sings karaoke in a green skirt. | [
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Four college-aged individuals sit on the steps outside of a building. | [
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A black and brown dog play with a red toy. | [
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A young boy is playing goalie at a hockey rink. | [
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A man reads a newspaper by a sculpture. | [
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End of preview. Expand in Data Studio
flickr30k-condensed
flickr30k dataset condensed to use single condensed caption for each image.
Dataset Details
Dataset Description
Flickr30k provides a dataset where a single image has multiple captions. These captions vary in their descriptiveness and the information may be too expressive or contradicting between the multiple captions. To train simpler models on this dataset, we propose to condense the multiple caption information into a single condensed caption. This is done by using the original dataset, parsing the images and captions, and using zero-shot inference with Qwen/Qwen2-1.5B-Instruct model condensing the multiple captions into a single caption. Original splits of train, validation, test have been preserved.
Dataset Sources
- Base Dataset: [robinhad/flickr30k]
- Original Paper: [From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions]
- Homepage: [From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions]
Direct Use
The dataset can be used directly using datasets.
from datasets import load_dataset
train_dataset = load_dataset("reiniscimurs/flickr30k-condensed", split="train")
validation_dataset = load_dataset("reiniscimurs/flickr30k-condensed", split="validation")
test_dataset = load_dataset("reiniscimurs/flickr30k-condensed", split="test")
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