fiftyone

Get help with FiftyOne skills, understand available workflows, and troubleshoot setup issues

Guided quickstart for FiftyOne - choose between user workflows (import, inference, visualization) or developer workflows (plugin development)

Writes Python code following FiftyOne's official conventions. Use when contributing to FiftyOne, developing plugins, or writing code that integrates with FiftyOne's codebase.

Creates Jupyter notebooks for FiftyOne workflows including getting-started guides, tutorials, recipes, and full ML pipelines. Use when creating notebooks, writing tutorials, building demos, or generating FiftyOne walkthroughs covering data loading, exploration, inference, evaluation, and export.

Exports 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.

Imports datasets into FiftyOne with automatic format detection. Supports all media types (images, videos, point clouds), label formats (COCO, YOLO, VOC, KITTI), multimodal grouped datasets, and Hugging Face Hub datasets. Use when importing datasets from local files or Hugging Face, loading autonomous driving data, or creating grouped datasets.

Run ML model inference on FiftyOne datasets. Use when running models for detection, classification, segmentation, or embeddings. Discovers available models dynamically from the Zoo, plugin operators, or custom sources — never assumes a fixed model list.

Develops custom FiftyOne plugins (operators and panels) from scratch. Use when creating plugins, extending FiftyOne with custom operators, building interactive panels, or integrating external APIs.

Visualizes datasets in 2D using embeddings with UMAP or t-SNE dimensionality reduction. Use when exploring dataset structure, finding clusters, identifying outliers, or understanding data distribution.

Finds duplicate or near-duplicate images in FiftyOne datasets using brain similarity computation. Use when deduplicating datasets, finding similar images, or removing redundant samples.

Triages FiftyOne GitHub issues by categorizing as fixed, won't fix, not reproducible, or still valid. Use when reviewing GitHub issues, triaging bugs, or closing stale issues in the voxel51/fiftyone repository.

Evaluate model predictions against ground truth using COCO, Open Images, or custom protocols. Use when computing mAP, precision, recall, confusion matrices, or analyzing TP/FP/FN examples for detection, classification, segmentation, or regression tasks.

Diagnose and fix common FiftyOne issues automatically. Use when a dataset disappeared, the App won't open, changes aren't saving, MongoDB errors occur, video codecs fail, notebook connectivity breaks, operators are missing, or any recurring FiftyOne pain point needs solving.

Build FiftyOne UIs using VOODO (Voxel Official Design Ontology), the official React component library. Use when building plugin panels, creating interactive UIs, or styling FiftyOne applications. Fetches current documentation dynamically from llms.txt.