Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
100M<n<1B
Language Creators:
other
Annotations Creators:
no-annotation
Source Datasets:
original
ArXiv:
Tags:
image-text pairs
License:
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README.md CHANGED
@@ -141,26 +141,27 @@ Similar to most vision-and-language datasets, our primary goal in the data creat
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  We collected about 10 billion pairs of alt-text and image sources in HTML documents in [CommonCrawl](https://commoncrawl.org/) from Oct. 2020 to Aug. 2021. and eliminated uninformative pairs through the image and/or text level filtering process with minimal cost.
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  **Image Level**
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- * Include all image formats that Pillow library can decode
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- * Less than 5KB image size are dropped
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- * Images with an aspect ratio greater than 3.0 are dropped
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- * Images with min(width, height) < 200 are dropped
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- * Images are dropped if the score of [OpenNSFW2](https://github.com/yahoo/open_nsfw) or [GantMan/NSFW](https://github.com/GantMan/nsfw_model) is higher than 0.5
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- * Based on the image [pHash](http://www.phash.org/) value, we removed all duplicate images from external public datasets.
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- (ImageNet-1K/21K, Flickr-30K, MS-COCO, CC-3M, CC-12M)
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  **Text Level**
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- * We collected only English text using [cld3](https://github.com/google/cld3)
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- * Consecutive whitespace characters are replaced with a single whitespace and whitespace before and after the sentence are removed
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  (e.g. `"\n \n Load image into Gallery viewer, valentine&amp;#39;s day roses\n \n" → "Load image into Gallery viewer, valentine&amp;#39;s day roses"`)
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- * Any text with a length of 5 or less has been dropped
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- * Text that does not have a noun form has been dropped
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- * Text less than 3 words or more than 256 words and text over 1000 words were dropped
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- * All texts appearing more than 10 times have been dropped
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  (e.g. `“thumbnail for”, “image for”, “picture of”`)
 
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  **Image-Text Level**
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- * Based on (image_phash, text), duplicated samples have been dropped
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  (Different text may exist for the same image URL.)
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  #### Who are the source language producers?
@@ -179,9 +180,10 @@ No human annotation
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  ### Personal and Sensitive Information
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  The COYO dataset is recommended to be used for research purposes.
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- Kakao Brain tried to construct a "Safe" dataset when building the COYO dataset.
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- (See Data Filtering Section) Kakao Brain is constantly making efforts to create more "Safe" datasets.
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  However, despite these efforts, this large-scale dataset was not hand-picked by humans to avoid the risk due to its very large size (over 700M).
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  Keep in mind that the unscreened nature of the dataset means that the collected images can lead to strongly discomforting and disturbing content for humans.
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  The COYO dataset may contain some inappropriate data, and any problems resulting from such data are the full responsibility of the user who used it.
@@ -207,12 +209,22 @@ It will be described in a paper to be released soon.
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  COYO dataset was released as an open source in the hope that it will be helpful to many research institutes and startups for research purposes. We look forward to contacting us from various places who wish to cooperate with us.
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- [coyo@kakaobrain.com](mailto://coyo@kakaobrain.com)
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  ### Licensing Information
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  The COYO dataset of Kakao Brain is licensed under [CC-BY-4.0 License](https://creativecommons.org/licenses/by/4.0/).
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- The dataset includes “Image URL” and “Text” collected from various sites by analyzing Common Crawl data, an open data web crawling project. The collected data (images and text) is subject to the license to which each content belongs.
 
 
 
 
 
 
 
 
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  ### Citation Information
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  We collected about 10 billion pairs of alt-text and image sources in HTML documents in [CommonCrawl](https://commoncrawl.org/) from Oct. 2020 to Aug. 2021. and eliminated uninformative pairs through the image and/or text level filtering process with minimal cost.
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  **Image Level**
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+ * Included all image formats that [Pillow library](https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html) can decode. (JPEG, WEBP, PNG, BMP, ...)
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+ * Removed images less than 5KB image size.
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+ * Removed images with an aspect ratio greater than 3.0.
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+ * Removed images with min(width, height) < 200.
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+ * Removed images with a score of [OpenNSFW2](https://github.com/bhky/opennsfw2) or [GantMan/NSFW](https://github.com/GantMan/nsfw_model) higher than 0.5.
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+ * Removed all duplicate images based on the image [pHash](http://www.phash.org/) value from external public datasets.
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+ * ImageNet-1K/21K, Flickr-30K, MS-COCO, CC-3M, CC-12M
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  **Text Level**
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+ * Collected only English text using [cld3](https://github.com/google/cld3).
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+ * Replaced consecutive whitespace characters with a single whitespace and removed the whitespace before and after the sentence.
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  (e.g. `"\n \n Load image into Gallery viewer, valentine&amp;#39;s day roses\n \n" → "Load image into Gallery viewer, valentine&amp;#39;s day roses"`)
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+ * Removed texts with a length of 5 or less.
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+ * Removed texts that do not have a noun form.
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+ * Removed texts with less than 3 words or more than 256 words and texts over 1000 in length.
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+ * Removed texts appearing more than 10 times.
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  (e.g. `“thumbnail for”, “image for”, “picture of”`)
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+ * Removed texts containing NSFW words collected from [profanity_filter](https://github.com/rominf/profanity-filter/blob/master/profanity_filter/data/en_profane_words.txt), [better_profanity](https://github.com/snguyenthanh/better_profanity/blob/master/better_profanity/profanity_wordlist.txt), and [google_twunter_lol](https://gist.github.com/ryanlewis/a37739d710ccdb4b406d).
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  **Image-Text Level**
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+ * Removed duplicated samples based on (image_phash, text).
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  (Different text may exist for the same image URL.)
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  #### Who are the source language producers?
 
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  ### Personal and Sensitive Information
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+ #### Disclaimer & Content Warning
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+
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  The COYO dataset is recommended to be used for research purposes.
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+ Kakao Brain tried to construct a "Safe" dataset when building the COYO dataset. (See [Data Filtering](#source-data) Section) Kakao Brain is constantly making efforts to create more "Safe" datasets.
 
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  However, despite these efforts, this large-scale dataset was not hand-picked by humans to avoid the risk due to its very large size (over 700M).
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  Keep in mind that the unscreened nature of the dataset means that the collected images can lead to strongly discomforting and disturbing content for humans.
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  The COYO dataset may contain some inappropriate data, and any problems resulting from such data are the full responsibility of the user who used it.
 
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  COYO dataset was released as an open source in the hope that it will be helpful to many research institutes and startups for research purposes. We look forward to contacting us from various places who wish to cooperate with us.
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+ [coyo@kakaobrain.com](mailto:coyo@kakaobrain.com)
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  ### Licensing Information
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+ #### License
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+
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  The COYO dataset of Kakao Brain is licensed under [CC-BY-4.0 License](https://creativecommons.org/licenses/by/4.0/).
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+ The full license can be found in the [LICENSE.cc-by-4.0 file](./LICENSE.cc-by-4.0).
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+ The dataset includes “Image URL” and “Text” collected from various sites by analyzing Common Crawl data, an open data web crawling project.
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+ The collected data (images and text) is subject to the license to which each content belongs.
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+
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+ #### Obligation to use
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+
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+ While Open Source may be free to use, that does not mean it is free of obligation.
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+ To determine whether your intended use of the COYO dataset is suitable for the CC-BY-4.0 license, please consider the license guide.
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+ If you violate the license, you may be subject to legal action such as the prohibition of use or claim for damages depending on the use.
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  ### Citation Information
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