القائمة
Push uncertain or misclassified images to CVAT for human annotation review after training analysis.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
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.
استنادا إلى تصنيف SOC المهني
| name | cvat-push |
| description | Push uncertain or misclassified images to CVAT for human annotation review after training analysis. |
After training analysis identifies uncertain images, push them to CVAT for human annotation or correction.
yolo-analyze has been run (check for uncertain_images.txt or analysis output)yolo-project.yamlCVAT_ACCESS_TOKEN env var is setRead the analysis output:
cat reports/uncertain_images.txt
Or check experiments/analysis.md for the list of uncertain predictions.
Organize images into review batches:
# From analysis file (auto-batches into tasks of 50)
yolo-cvat push --from-analysis reports/uncertain_images.txt
# Or manually specify images
yolo-cvat push --images <path_to_images> --labels <path_to_labels> --task-name "Review: False Negatives"
Write experiments/cvat_push_report.md:
## CVAT Upload Report
- Date: YYYY-MM-DD
- Tasks created: N
- Total images: N
- False negatives: N (Task ID: X)
- Uncertain: N (Task ID: Y)
- CVAT URL: http://localhost:8080/tasks/<id>
More than 100 images?
├── Yes → Split into batches of 50, create multiple tasks
└── No → Single task
Has existing YOLO labels for these images?
├── Yes → Upload as pre-annotations (saves annotator time)
└── No → Push images only for fresh annotation
False negatives found?
├── Yes → Create separate high-priority task labeled "URGENT: False Negatives"
└── No → Single "Review: Uncertain" task