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feat(core): load L1-L3 train weights into structure pipeline (#104) - #105

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loootte merged 1 commit into
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feature/104-learned-l1l3
Aug 2, 2026
Merged

loootte merged 1 commit into
mainfrom
feature/104-learned-l1l3

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@loootte

@loootte loootte commented Aug 2, 2026

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Summary

Wire learned L2+L3 weights into the structure pipeline while keeping rule default and fallback (#104).

Features

  • ENPU_STRUCTURE_L1L3_ENGINE=rule|learned + weights/device/fallback settings
  • core/app/pipeline/structure/learned/: model (mirrors train LayoutNet), loader, postprocess, adapter, infer
  • L1 remains hybrid (rule page regions); L2+L3 from heatmaps; L4–L5 unchanged
  • scripts/eval_l1l3_engines.py rule vs learned line-level metrics
  • Docs: docs/train/core-inference.md
  • Tests: load weights, rule path, fallback, optional full learned run

Not in default installer

torch is optional; CI/slim package stay rule-only.

Closes #104

Add structure/learned loader+infer, ENPU_STRUCTURE_L1L3_ENGINE switch with
rule fallback, eval_l1l3_engines comparison script, and core-inference docs.

Closes #104
@loootte
loootte merged commit e488735 into main Aug 2, 2026
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@loootte
loootte deleted the feature/104-learned-l1l3 branch August 2, 2026 10:36
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feat(core): 加载 L1–L3 训练权重并接入 structure 推理

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