计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
train-eval【效率与协作】Routes AdelaiDet config selection, training, evaluation, Detectron2 launch flags, checkpoints, and model-family run workflows.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill when a task asks how to train, evaluate, resume, benchmark, debug a config, or launch an AdelaiDet model family through the repository's Detectron2-style training workflow.
--eval-only, --resume, distributed launch flags, or checkpoint-backed evaluation.MODEL.WEIGHTS behavior.../setup-build/SKILL.md first.../text-spotting/SKILL.md.../data-prep/SKILL.md.../demo-visualize/SKILL.md.../export-convert/SKILL.md.references/config-selection.md to choose a model/config family.references/train-eval-workflows.md for launch patterns, flags, and outputs.../../references/model-overview.md for package-wide model routing.../../references/api-reference.md for verified config and registry surfaces.scripts/run_train_eval.py — validates common paths and builds/runs an AdelaiDet training or evaluation command. Use --dry-run before expensive jobs.Confirm setup:
python ../../scripts/check_install.py --cuda-ops
Choose the config family and config YAML.
Confirm datasets are registered and available; switch to data-prep if not.
Dry-run the launch:
python scripts/run_train_eval.py --repo-root /path/to/AdelaiDet \
--config configs/FCOS-Detection/R_50_1x.yaml --num-gpus 1 --dry-run
Add --eval-only --model-weights /path/to/model.pth for evaluation-only runs, or --resume for continuation.
Inspect OUTPUT_DIR, logs, metrics, checkpoints, and evaluator output.
text-spotting before finalizing training flags.data-prep before launch.export-convert for conversion utilities.No object named ... in registry appears, verify setup/import first, then check config family/key spelling.