= ImageNet
{c}
{tag=Closed standard}
{title2=2009}
{wiki}
14 million images with more than 20k categories, typically denoting prominent objects in the image, either common daily objects, or a wild range of animals. About 1 million of them also have <bounding boxes> for the objects. The images have different sizes, they are not all standardized to a single size like <MNIST>https://stackoverflow.com/questions/36109886/what-is-the-resolution-of-an-image-in-imagenet-dataset{ref}.
Each image appears to have a single label associated to it. Care must have been taken somehow with categories, since some images contain severl possible objects, e.g. a person and some object.
In practice, the <ILSVRC> subset of <ImageNet> is the most commonly used dataset.
Official project page: https://www.image-net.org/
The data license is restrictive and forbids commercial usage: https://www.image-net.org/download.php[]. Also as a result you have to login to download the dataset. Super annoying.
How to visualize: https://datascience.stackexchange.com/questions/111756/where-can-i-view-the-imagenet-classes-as-a-hierarchy-on-wordnet
The categories are all part of <WordNet>, which means that there are several parent/child categories such as dog vs type of dog available. <ImageNet1k> only appears to have leaf nodes however (i.e. no "dog" label, just specific types of dog).
A major model that performed well on <ImageNet> starting on 2012 and became notable is <AlexNet>.
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