Datasets:
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imagewidth (px) 1
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Lube |
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Spencerian |
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accommodatingly |
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CARPENTER |
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REGURGITATING |
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savannas |
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unfix |
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CAGOULES |
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TRANSITS |
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looped |
|
cowmen |
|
SYSTEMICALLY |
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Offstages |
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Enquirers |
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pluck |
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FURLONG |
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Toked |
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Brawl |
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lancets |
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awarded |
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vaxes |
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CRANIUMS |
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UNBROKEN |
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REIT |
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Jarrod |
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UNFEIGNED |
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REGULATE |
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COLT |
|
snooping |
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Marquise |
|
SHELF |
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untasted |
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overusing |
|
adaption |
|
MENES |
|
SILTIEST |
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KNURLING |
|
SHOPFITTING |
|
Ideas |
|
outwitted |
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BIOL |
|
Penmanship |
|
SUSTAINED |
|
HISTORICALLY |
|
BORGLUM |
|
PLAZAS |
|
Contentment |
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callas |
|
Banyan |
|
randomized |
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populace |
|
DEPORT |
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docked |
|
GRASSROOTS |
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turbaned |
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Attired |
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Latches |
|
Leisureliness |
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quenchless |
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frontbenches |
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Graffito |
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panderer |
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ENRICHED |
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CONQUERING |
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REINSPECTS |
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stickies |
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PRIVIEST |
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FEEDBAGS |
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DEMONETIZING |
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Stamina |
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libretto |
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Turtledove |
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Tongued |
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semitones |
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DEPRECATION |
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monopolizes |
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Temptingly |
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futon |
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PROVERB |
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Gu |
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floss |
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Mamacitas |
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Wisecracking |
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Fleece |
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Stupors |
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centavos |
|
haunch |
|
Realest |
|
Reforests |
|
fainted |
|
Pests |
|
detector |
|
cup |
|
Tojo |
|
schwinn |
|
SERIALIZE |
|
Mckenzie |
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ANTIABORTION |
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trustworthy |
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DOGGED |
Dataset Card for "MJSynth_text_recognition"
This is the MJSynth dataset for text recognition on document images, synthetically generated, covering 90K English words. It includes training, validation and test splits. Source of the dataset: https://www.robots.ox.ac.uk/~vgg/data/text/
Use dataset streaming functionality to try out the dataset quickly without downloading the entire dataset (refer: https://huggingface.co/docs/datasets/stream)
Citation details provided on the source website (if you use the data please cite):
@InProceedings{Jaderberg14c, author = "Max Jaderberg and Karen Simonyan and Andrea Vedaldi and Andrew Zisserman", title = "Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition", booktitle = "Workshop on Deep Learning, NIPS", year = "2014", }
@Article{Jaderberg16, author = "Max Jaderberg and Karen Simonyan and Andrea Vedaldi and Andrew Zisserman", title = "Reading Text in the Wild with Convolutional Neural Networks", journal = "International Journal of Computer Vision", number = "1", volume = "116", pages = "1--20", month = "jan", year = "2016", }
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