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.
Quickly install fiftyone-model-evaluation AI skill to your development environment via command line
Source: voxel51/fiftyone-skills.
Verify the dataset has both prediction and ground truth fields of compatible types.
Ask user for evaluation parameters Always confirm with the user:
| Label Type | Evaluation Method | Supported Methods |
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. Source: voxel51/fiftyone-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/voxel51/fiftyone-skills --skill fiftyone-model-evaluationEvaluate 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. Source: voxel51/fiftyone-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/voxel51/fiftyone-skills --skill fiftyone-model-evaluation Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/voxel51/fiftyone-skills