Menu
Claude visually inspects images and corrects/creates YOLO bounding box annotations using multimodal vision.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
Set up autonomous training monitoring — creates cron jobs to track long-running training, auto-continue pipeline when training completes.
Audit YOLO dataset quality — class distribution, annotation quality, image stats, and improvement suggestions.
Orchestrate the full active learning loop: train, analyze, push to CVAT, wait for review, pull, merge, retrain.
Analyze YOLO training runs — compares to baseline/best, checks per-class regression, analyzes training dynamics and tune convergence, writes actionable recommendations.
Run autonomous YOLO training experiments — reads training-plan.md, assesses bottlenecks, acts strategically, and delegates HP optimization to model.tune().
Profile YOLO model inference speed, FPS, and size across image sizes and export formats.
| name | annotate |
| description | Claude visually inspects images and corrects/creates YOLO bounding box annotations using multimodal vision. |
Claude vision annotation correction using multi-pass refinement.
STATUS: EXPERIMENTAL
yolo-project.yaml for class namespython scripts/draw_annotations.py
b. Claude reads annotated image
c. Evaluate: keep / correct / remove / add
d. Write corrected YOLO label