Image data ≠Structured data
Working with image libraries at scale is not the same as working with large sets of structured data.
And this means that statistical tools used to process structured data are inadequate.

How can you find a representative ‘average image’? Or a ‘particularly weird’ one?

But there are visual ways.
How it works
Visually explore large image databases
Gain an intuitive understanding of what images are present in your dataset by browsing 3-dimensional point clouds
Visually explore large image databases
Gain an intuitive understanding of what images are present in your dataset by browsing 3-dimensional point clouds
Visually explore large image databases
Gain an intuitive understanding of what images are present in your dataset by browsing 3-dimensional point clouds
Discover untapped potential
Find images that have the most explanatory power in your data, by identifying unique and unexpected samples
Discover untapped potential
Find images that have the most explanatory power in your data, by identifying unique and unexpected samples
Visually explore large image databases
Gain an intuitive understanding of what images are present in your dataset by browsing 3-dimensional point clouds
Identify bias
Use visual exploration to quickly understand whether your labels or datasets are biased towards certain characteristics
Identify bias
Use visual exploration to quickly understand whether your labels or datasets are biased towards certain characteristics
Identify bias
Use visual exploration to quickly understand whether your labels or datasets are biased towards certain characteristics
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