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name: validation-evaluation description: "Run and interpret YOLOv3 validation, mAP metrics, val.py tasks, COCO JSON output, and evaluation artifacts." disable-model-invocation: true metadata: disco-role: operating license: AGPL 3.0

Validation and Evaluation Sub-skill

Read this for val.py, model mAP, precision/recall, COCO JSON output, text predictions, speed/study tasks, validation dataloaders, or post-training evaluation.

Use

• Read references/workflows.md for validation commands, output interpretation, and task modes.
• Use scripts/yolov3_eval_command_builder.py to build validation commands and JSON plans safely.
• Read references/troubleshooting.md for metric, class-count, and dataset failures.

Important facts

• Main entry point: python val.py.
• Key flags: --data, --weights, --batch-size, --imgsz, --task, --device, --save-txt, --save-conf, --save-json, --half, and --dnn.
• --task accepts train, val, test, speed, or study.
• --save-json is automatically enabled for coco.yaml; pycocotools is optional but needed for official COCO JSON metrics.