Script and models for clustering LAION-400m CLIP embeddings.

Last update: Oct 4, 2022

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Overview

clustering-laion400m

Script and models for clustering LAION-400m CLIP embeddings.

Models were fit on the first million or so image embeddings. A subjective description of what the labels appear to be is included in cluster-labels.txt along with counts for the first million or so embeddings (aka the first file).

Precomputed labels are here: https://archive.org/details/laion400m-64-clustering-labels.tar

Run Fit Clusters.ipynb to reproduce the labels or create your own clusters / models. This requires the CLIP embeddings from the LAION 400m open dataset, which can be found here: https://laion.ai/laion-400-open-dataset/

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Comments

Reasoning behind FastICA/PCA vectors for GMM

Just out of curiosity, I was wondering what the reasoning was behind using a combined PCA and FastICA vectors for Gaussian Mixture Models. I wasn't able to find this kind of approach anywhere else. Does it offer some specific benefits regarding CLIP feature vectors?

Thanks!

opened by njanakiev 3

Owner

Peter Baylies

GitHub

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Script and models for clustering LAION-400m CLIP embeddings.

Related tags

Overview

clustering-laion400m

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Reasoning behind FastICA/PCA vectors for GMM

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