How do I track dataset changes for vision models?

ML Forum
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Datasets evolve often. What’s the best way to version and monitor updates for computer vision training sets?

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Use dataset versioning tools like DVC, Git-LFS, or platforms such as Labelbox and Roboflow. They track labeling changes, metadata, image additions, and dataset lineage, ensuring experiments remain reproducible when retraining models.

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Maintain strict data pipelines - store hashes for each file, track annotation revisions, and automate audit logs. Clear version control prevents model regression and supports compliance in regulated environments.