BenediktAlkin/ImageNetSubsetGenerator

Creates subsets of ImageNet (e.g. ImageNet100)

27
/ 100
Experimental

This helps machine learning researchers or practitioners working with large image datasets. It takes a full ImageNet1K dataset as input and produces a smaller, curated subset of images. This is useful for training and testing computer vision models more efficiently, especially when experimenting with different data scales or specific research benchmarks.

No commits in the last 6 months.

Use this if you need to quickly create a smaller, standardized subset from the massive ImageNet1K dataset for your machine learning experiments or model development.

Not ideal if you need to generate custom image subsets based on criteria not already pre-defined (e.g., specific object counts per class or non-ImageNet datasets).

computer-vision machine-learning deep-learning image-recognition dataset-preparation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

13

Forks

1

Language

Python

License

MIT

Last pushed

Feb 28, 2024

Commits (30d)

0

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