How to Cluster Images

• fiftyone

  21 6,712 10.0 Python

  The open-source tool for building high-quality datasets and computer vision models

  

With all that background out of the way, let’s turn theory into practice and learn how to use clustering to structure our unstructured data. We’ll be leveraging two open-source machine learning libraries: scikit-learn, which comes pre-packaged with implementations of most common clustering algorithms, and fiftyone, which streamlines the management and visualization of unstructured data:

• clustering-runs-plugin

  1 4 - Python

  Discontinued Compute clustering on your data in a visual, intuitive way with FiftyOne and Sklearn! [Moved to: https://github.com/jacobmarks/clustering-plugin]

The FiftyOne Clustering Plugin makes our lives even easier.  It provides the connective tissue between scikit-learn’s clustering algorithms and our images and wraps all of this in a simple UI within the FiftyOne App. We can install the plugin from the CLI:

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• clustering-plugin

  1 5 6.4 Python

  Compute clustering on your data in a visual, intuitive way with FiftyOne and Sklearn!

fiftyone plugins download https://github.com/jacobmarks/clustering-plugin

• CLIP

  104 22,316 1.2 Jupyter Notebook

  CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  

We will also need two more libraries: OpenAI’s CLIP GitHub repo, enabling us to generate image features with the CLIP model, and the umap-learn library, which will let us apply a dimensionality reduction technique called Uniform Manifold Approximation and Projection (UMAP) to those features to visualize them in 2D:

• fiftyone-image-captioning-plugin

  1 5 5.3 Python

  Caption images across your datasets with state of the art models from Hugging Face and Replicate!

Concept Modeling Techniques: the built-in concept modeling technique in this walkthrough uses GPT-4V and some light prompting to identify each cluster's core concept. This is but one way to approach an open-ended problem. Try using image captioning and topic modeling, or create your own technique!

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