YFCC100M subset from OpenAI

Subset of YFCC100M used by OpenAI for CLIP, filtered to contain only the images that we could retrieve.

Split	train	validation
Number of samples	14,808,859	16,374
Size	1.9 TB	2.1 GB

Features:

from the original dataset: title, description, photoid, uid, unickname, datetaken, dateuploaded, capturedevice, usertags, machinetags, longitude, latitude, accuracy, pageurl, downloadurl, licensename, licenseurl, serverid, farmid, secret, secretoriginal, ext, marker, key
img: image content, can be loaded with PIL.Image.open(io.BytesIO(item['img']))
title_clean and description_clean: derived from title and description using clean_text function detailed below

def clean_text(text):
    # decode url
    text = urllib.parse.unquote_plus(text)
    # remove html tags
    text = re.sub('<[^<]+?>', '', text)
    # remove multiple spaces + "\r" + "\n" + "\t"
    text = " ".join(text.split())
    return text