claude

fiftyone-dataset-curation

End-to-end dataset curation for any FiftyOne dataset: inspect schema and media quality (blur, brightness, corruption, resolution), audit annotation quality (mistakenness, hardness, duplicate labels, IoU overlaps), analyze class distributions and imbalances, explore embedding space and data gaps, find near/exact duplicates, create curated subsets using semantic search and brain ops, build train/val/test splits, and answer natural language questions about your data. Delegates to fiftyone-find-duplicates and fiftyone-embeddings-visualization. Requires FiftyOne MCP server with @voxel51/brain and @voxel51/utils plugins.

48 on GitHubApache-2.0updated 14 days agoCuration
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Plugin fiftyone-dataset-curation from marketplace fiftyone-skills in voxel51/fiftyone-skills. Commands read from the repo's manifest — 12 days ago.

What it installs

Skills (1)

  • fiftyone-dataset-curation

    End-to-end dataset curation for FiftyOne: inspect schema and quality, audit annotations, analyze class distributions, explore embeddings, find duplicates, create curated subsets, and build train/val/test splits. Works with any computer vision dataset type.

View source on GitHub

More from voxel51/fiftyone-skills

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Build high-quality datasets and computer vision models. Visualize datasets, analyze models, find duplicates, run inference, evaluate predictions, and develop custom plugins.

19 skills · 2 commands · 1 MCP server

48

Drive the FiftyOne App via the Playwright MCP for operator/plugin verification, demo or screencast recording, and end-to-end UI automation against `fo.launch_app(...)`. Use when automating the FiftyOne App, recording an operator demo, or debugging a session that silently dies after a UI action (the `browser_navigate`-after-`reload_dataset` crash), covering launcher patterns (`remote=True`, trigger-file IPC), MUI input/dropdown gotchas, `data-cy` selectors, and scoped cleanup.

1 skill

48

Write Python code following FiftyOne's official conventions. Use when contributing to FiftyOne, developing plugins, or writing code that integrates with FiftyOne's codebase. Covers module structure, import organization, Google-style docstrings, lazy imports, guard patterns, and error handling.

1 skill

48

Creates Jupyter notebooks for FiftyOne workflows including getting-started guides, tutorials, recipes, and full ML pipelines. Use when users want to create a notebook, write a tutorial, build a demo, document a workflow, or generate a FiftyOne walkthrough covering data loading, exploration, inference, evaluation, and export. Builds notebooks cell-by-cell using NotebookEdit.

1 skill

48

Export FiftyOne datasets to standard formats (COCO, YOLO, VOC, CVAT, CSV, etc.) and Hugging Face Hub. Use when converting datasets, exporting for training, creating archives, sharing data in specific formats, or publishing datasets to Hugging Face Hub.

1 skill

48

Universal dataset import for FiftyOne supporting all media types (images, videos, point clouds, 3D scenes), all label formats (COCO, YOLO, VOC, CVAT, KITTI, etc.), multimodal grouped datasets, LeRobot v3 robot-learning episode datasets, and Hugging Face Hub datasets. Use when users want to import any dataset regardless of format or source, load datasets from Hugging Face, handle autonomous driving data with multiple cameras and LiDAR, import LeRobot robot-learning episodes, or create grouped datasets from multimodal data.

1 skill

48

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