fiftyone-embeddings-visualization
Embeddings Visualization in FiftyOne
Key Directives
ALWAYS follow these rules:
1. Set context first
set_context(dataset_name="my-dataset")
2. Launch FiftyOne App
Brain operators are delegated and require the app:
launch_app()
Wait 5-10 seconds for initialization.
3. Discover operators dynamically
More from voxel51/fiftyone-skills
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Finds duplicate or near-duplicate images in FiftyOne datasets using brain similarity computation. Use when deduplicating datasets, finding similar images, or removing redundant samples.
20fiftyone-dataset-import
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.
14fiftyone-model-evaluation
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.
12fiftyone-dataset-inference
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.
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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.
11fiftyone-code-style
Writes Python code following FiftyOne's official conventions. Use when contributing to FiftyOne, developing plugins, or writing code that integrates with FiftyOne's codebase.
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