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 
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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

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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

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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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