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データ・研究 · SKILL.md

metrics-evaluation

metrics-evaluation

Guides Waymo Open Dataset detection, tracking, motion, keypoint, and segmentation metric APIs, configs, TensorFlow ops, and submission artifacts.

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: metrics-evaluation description: "Guides Waymo Open Dataset detection, tracking, motion, keypoint, and segmentation metric APIs, configs, TensorFlow ops, and submission artifacts." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Metrics Evaluation

Use this sub-skill when a task asks for WOD detection, tracking, motion, keypoint, segmentation, AP/APH/APL, minADE/minFDE/MissRate/mAP, metric config breakdown names, py_metrics_ops, metric tensor shapes, or accuracy submission artifacts.

Read:

Run scripts/inspect_metric_config.py to verify installed metric imports and a tiny config breakdown.

Route raw Frame conversion to dataset-utils, latency timing to latency-submissions, camera segmentation optional dependency issues to camera-and-segmentation, and sim-agent challenge metrics to motion-sim-agents.

保存したスキル