lmcinnes / lmcinnes/umap

Pre-trained models for the real-world images

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Dominant language
Python
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Merged PRs (30d)
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Description

would it be possible to add a simple code example for dimension reduction on images with some pre-trained model for real-world images?

P.S. Leland, many thanks for your work on UMAP, it is a brilliant thing!

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

The issue names no files, tests, or entry points. Start by locating the repository's existing examples and image-related UMAP usage, then clarify the pretrained model, image data, reduction workflow, and completion criteria with maintainers before implementing or testing the example.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
25/100

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