Wine Label Detection Computer Vision Project

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This is a project on training the machine to read and pickup wine label information, specifically there are several class labels I look at from each of the wine labels, in each class, specific class attributes (such as under the wine type different attributes: Cabernet Sauvignion or Riesling or Merlot) can be assigned to provide more detailed information:

(1)Maker/Name of the vineyard or producer
(2)Vintage/Year of the wine produced
(3)Whether being sustainable or sustainably farmed
(4)Whether being organic or not
(5)Alcohol level
(6)Appellation Quality in terms of common AVA ratings
(7)Established Year of the vineyard
(8)Whether having any appelation AOC DOC AVA name
(9)Whether Country of the origin can be identified
(10)Whether type of the wine can be identified
(11)Whether there is distinct picture or brand logo
(12) Whether there is indication of sweetness level

I hope we all can help train the machine to be better at reading the wine label and be smarter and make more quality inference rather than just reading and picking up information as it which would be just like an OCR

-Yilong "Eric" Zheng

Cite this Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ wine-label-detection_dataset,
    title = { Wine Label Detection Dataset },
    type = { Open Source Dataset },
    author = { Wine Label },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { oct },
    note = { visited on 2022-12-04 },


Wine Label

Last Updated

2 months ago

Project Type

Object Detection




AlcoholPercentage, Appellation AOC DOC AVARegion, Appellation QualityLevel, CountryCountry, Distinct Logo, Established YearYear, Maker-Name, Organic, Sustainable, Sweetness-Brut-SecSweetness-Brut-Sec, TypeWine Type, VintageYear


CC BY 4.0