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Overall, most machine tags are related to food and drink, events, camera and application metadata, as well as locations.
In terms of locations, the photos and videos in the dataset have been taken all over the world.
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Fw-300 #ya-qn-sort h2 /* Breadcrumb */ #ya-question-breadcrumb #ya-question-breadcrumb i #ya-question-breadcrumb a #bc .ya-q-full-text, .ya-q-text #ya-question-detail h1 html[lang="zh-Hant-TW"] .ya-q-full-text, html[lang="zh-Hant-TW"] .ya-q-text, html[lang="zh-Hant-HK"] .ya-q-full-text, html[lang="zh-Hant-HK"] .ya-q-text html[lang="zh-Hant-TW"] #ya-question-detail h1, html[lang="zh-Hant-HK"] #ya-question-detail h1 #Stencil . There’s a diverse collection of visual concepts present in the photos and videos, ranging from indoor to outdoor images, faces to food, nature to automobiles.There are 68,971,123 photos and videos in the set that have user-annotated tags.Each of the 100 million photos and videos is associated with a Creative Commons license that indicates how it may be used by others.The table below shows the complete breakdown of licenses in our dataset.