[verified] add docling auto-map package wrapper
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#!/usr/bin/env python3
"""
finalize.py — produce the final corpus output bundle under results/final/.
Runs the full pipeline (via the real module CLIs, so the bundle is reproducible) across the corpus:
* geometry papers (image-only / OCR-path): structured + furniture + bands + page_roles + template
+ validate + overlays (template human-review view for ALL pages, rich debug for sample pages).
* born-digital fast-path papers: structured + validate (no geometry -> no overlays).
Writes per-paper report.md, a human INDEX.md, and a machine catalog.json.
Usage:
python finalize.py [--no-overlays] # --no-overlays = JSON pipeline only (fast)
"""
import os, sys, glob, json, subprocess, argparse, datetime
FINAL = "results/final"
PY = sys.executable
# ------------------------------------------------------------------ corpus manifest
GEOMETRY = [
dict(slug="aqa-physics-8463-imageonly", title="AQA GCSE Physics 8463/1H (image-only)",
board="aqa", level="GCSE", path="image-only (RapidOCR margin-pass)",
pdf="samples/AQA-Physics-Paper-1H-2022-with-qr.pdf",
docling="results/E_tess_full.json", rapid="results/rapid_pages/p*.json",
extract=["--docling", "results/E_tess_full.json", "--rapid", "results/rapid_pages/p*.json",
"--granite", "cached"]),
dict(slug="aqa-physics-7408-ocr", title="AQA A-level Physics 7408/1 (rasterised OCR)",
board="aqa", level="A-level", path="OCR (RapidOCR margin-pass + Section-B MCQ)",
pdf="samples/extra/aqa-alevel-physics-7408-1-jun22-qp.pdf",
docling="results/rapid_7408/merged.json", rapid="results/rapid_7408/p*.json",
gt="results/gt_extra/aqa-alevel-physics-7408-1-jun22-qp.txt",
extract=["--docling", "results/rapid_7408/merged.json", "--rapid", "results/rapid_7408/p*.json",
"--board", "aqa"]),
dict(slug="aqa-biology-8461-ocr", title="AQA GCSE Biology 8461/1H (rasterised OCR)",
board="aqa", level="GCSE", path="OCR (RapidOCR margin-pass)",
pdf="samples/extra/aqa-gcse-biology-8461-1h-jun22-qp.pdf",
docling="results/rapid_8461/merged.json", rapid="results/rapid_8461/p*.json",
gt="results/gt_extra/aqa-gcse-biology-8461-1h-jun22-qp.txt",
extract=["--docling", "results/rapid_8461/merged.json", "--rapid", "results/rapid_8461/p*.json",
"--board", "aqa"]),
dict(slug="edexcel-maths-1ma1-1h-ocr", title="Edexcel GCSE Maths 1MA1/1H (rasterised OCR)",
board="edexcel", level="GCSE-H", path="OCR + gemma marks gap-fill",
pdf="samples/extra/edexcel-gcse-maths-1ma1-1h-jun22-qp.pdf",
docling="results/genreport/edexcel1h/ocr.json", rapid=None,
gt="results/gt_extra/edexcel-gcse-maths-1ma1-1h-jun22-qp.txt",
extract=["--docling", "results/genreport/edexcel1h/ocr.json", "--board", "edexcel",
"--marks-fill", "results/genreport/edexcel1h/marks_fill.json"]),
dict(slug="edexcel-maths-1ma1-1f-ocr", title="Edexcel GCSE Maths 1MA1/1F (rasterised OCR)",
board="edexcel", level="GCSE-F", path="OCR + gemma marks gap-fill",
pdf="samples/extra/edexcel-gcse-maths-1ma1-1f-jun22-qp.pdf",
docling="results/genreport/edexcel1f/ocr.json", rapid=None,
extract=["--docling", "results/genreport/edexcel1f/ocr.json", "--board", "edexcel",
"--marks-fill", "results/genreport/edexcel1f/marks_fill.json"]),
dict(slug="ocr-physics-h556-ocr", title="OCR A-level Physics H556/3 (rasterised OCR)",
board="ocr", level="A-level", path="OCR + gemma marks gap-fill",
pdf="samples/extra/ocr-alevel-physics-h556-3-jun22-qp.pdf",
docling="results/genreport/ocrh556/ocr.json", rapid=None,
gt="results/gt_extra/ocr-alevel-physics-h556-3-jun22-qp.txt",
extract=["--docling", "results/genreport/ocrh556/ocr.json", "--board", "ocr",
"--marks-fill", "results/genreport/ocrh556/marks_fill.json"]),
]
FAST = [
dict(slug="aqa-physics-7408-fast", title="AQA A-level Physics 7408/1 (born-digital)", board="aqa",
level="A-level", pdf="samples/extra/aqa-alevel-physics-7408-1-jun22-qp.pdf",
gt="results/gt_extra/aqa-alevel-physics-7408-1-jun22-qp.txt"),
dict(slug="aqa-biology-8461-fast", title="AQA GCSE Biology 8461/1H (born-digital)", board="aqa",
level="GCSE", pdf="samples/extra/aqa-gcse-biology-8461-1h-jun22-qp.pdf",
gt="results/gt_extra/aqa-gcse-biology-8461-1h-jun22-qp.txt"),
dict(slug="edexcel-maths-1ma1-1h-fast", title="Edexcel GCSE Maths 1MA1/1H (born-digital)",
board="edexcel", level="GCSE-H", pdf="samples/extra/edexcel-gcse-maths-1ma1-1h-jun22-qp.pdf",
gt="results/gt_extra/edexcel-gcse-maths-1ma1-1h-jun22-qp.txt"),
dict(slug="edexcel-maths-1ma1-1f-fast", title="Edexcel GCSE Maths 1MA1/1F (born-digital)",
board="edexcel", level="GCSE-F", pdf="samples/extra/edexcel-gcse-maths-1ma1-1f-jun22-qp.pdf"),
dict(slug="ocr-physics-h556-fast", title="OCR A-level Physics H556/3 (born-digital)", board="ocr",
level="A-level", pdf="samples/extra/ocr-alevel-physics-h556-3-jun22-qp.pdf",
gt="results/gt_extra/ocr-alevel-physics-h556-3-jun22-qp.txt"),
dict(slug="aqa-chemistry-8462-fast", title="AQA GCSE Chemistry 8462/1H (born-digital)", board="aqa",
level="GCSE", pdf="samples/chemistry-p1h-2023-qp.pdf"),
dict(slug="aqa-physics-8463-twin-fast", title="AQA GCSE Physics 8463/1H born-digital twin",
board="aqa", level="GCSE", pdf="samples/physics-p1h-2022-qp.pdf"),
]
def run(cmd):
r = subprocess.run([PY] + cmd, capture_output=True, text=True)
if r.returncode != 0:
print(f" ! FAILED: {' '.join(cmd)}\n{r.stderr[-400:]}")
return r.returncode == 0
def jload(p):
try:
return json.load(open(p))
except Exception:
return {}
def stats_from(struct, val):
st = struct.get("stats", {}) or {}
mc = st.get("marks_check") or {}
cov = struct.get("coverage", {}) or {}
return {
"board": struct.get("board"), "paper_code": struct.get("paper_code"),
"n_questions": st.get("n_questions"), "n_parts": st.get("n_parts"),
"marks_sum": mc.get("sum"), "official_max": mc.get("expected_max"),
"marks_pct": mc.get("pct"),
"coverage_pct": cov.get("coverage_pct"), "coverage_missed": cov.get("missed", []),
"validate_verdict": (val.get("summary") or {}).get("worst_severity"),
"validate_flags": val.get("flags", []),
"questions_expected": (val.get("summary") or {}).get("questions_expected"),
"questions_recovered": (val.get("summary") or {}).get("questions_recovered"),
"second_pass_slots": [q["label"] for q in val.get("question_sequence", []) if not q["recovered"]],
}
def do_geometry(p, overlays):
d = os.path.join(FINAL, p["slug"]); os.makedirs(d, exist_ok=True)
S, F, B, R, T, V = (os.path.join(d, f) for f in
("structured.json", "furniture.json", "bands.json", "page_roles.json",
"template.json", "validate.json"))
ex = ["extract.py"] + p["extract"] + ["--out", S]
if p.get("gt"):
ex += ["--gt", p["gt"]]
run(ex)
run(["furniture.py", p["docling"], "--out", F])
bands = ["bands.py", S, "--docling", p["docling"], "--out", B]
if p.get("rapid"):
bands += ["--rapid", p["rapid"]]
run(bands)
run(["page_roles.py", p["docling"], "--bands", B, "--out", R])
run(["template.py", "--structured", S, "--bands", B, "--furniture", F,
"--page-roles", R, "--pdf", p["pdf"], "--out", T])
run(["validate.py", S, "--out", V])
if overlays:
otpl = os.path.join(d, "overlays", "template")
run(["scripts/overlay.py", S, p["pdf"], "--template", T, "--dpi", "120", "--out", otpl])
# rich debug view on the first few pages (cover + early questions)
odbg = os.path.join(d, "overlays", "debug")
run(["scripts/overlay.py", S, p["pdf"], "--docling", p["docling"], "--bands", B,
"--furniture", F, "--pages", "1,2,3,4,5", "--dpi", "120", "--out", odbg])
return stats_from(jload(S), jload(V)), d
def do_fast(p):
d = os.path.join(FINAL, p["slug"]); os.makedirs(d, exist_ok=True)
S = os.path.join(d, "structured.json"); V = os.path.join(d, "validate.json")
ex = ["extract.py", "--text", p["pdf"], "--out", S]
if p.get("gt"):
ex += ["--gt", p["gt"]]
run(ex)
run(["validate.py", S, "--out", V])
return stats_from(jload(S), jload(V)), d
def per_paper_report(p, s, d, kind):
n_imgs = len(glob.glob(os.path.join(d, "overlays", "**", "*.png"), recursive=True))
lines = [f"# {p['title']}", "",
f"- **slug:** `{p['slug']}` · **board:** {p['board']} · **level:** {p['level']} "
f"· **path:** {kind}",
f"- **questions/parts:** {s['n_questions']} / {s['n_parts']}",
f"- **marks:** {s['marks_sum']}/{s['official_max']}"
+ (f" ({s['marks_pct']}% of official max)" if s['marks_pct'] is not None else ""),
f"- **coverage vs GT:** {s['coverage_pct']}%"
+ (f" (missed {s['coverage_missed'][:8]})" if s.get('coverage_missed') else "")
if s['coverage_pct'] is not None else "- **coverage vs GT:** n/a",
f"- **G6 verdict:** {s['validate_verdict']}",
]
if s["validate_flags"]:
lines += ["", "**Flags (human-review hints):**"] + [f"- {f}" for f in s["validate_flags"]]
lines += ["", "**Artifacts:** `structured.json`, `validate.json`"
+ (", `furniture.json`, `bands.json`, `page_roles.json`, `template.json`, "
f"`overlays/` ({n_imgs} images)" if kind != "born-digital fast-path"
else " (born-digital: no page geometry → no overlays)")]
open(os.path.join(d, "report.md"), "w").write("\n".join(lines) + "\n")
return n_imgs
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--no-overlays", action="store_true")
a = ap.parse_args()
os.makedirs(FINAL, exist_ok=True)
catalog = {"generated_at": datetime.datetime.now().isoformat(timespec="seconds"),
"papers": []}
total_imgs = 0
for p in GEOMETRY:
print(f"[geometry] {p['slug']}")
s, d = do_geometry(p, not a.no_overlays)
n = per_paper_report(p, s, d, p["path"])
total_imgs += n
catalog["papers"].append({**{k: p[k] for k in ("slug", "title", "board", "level")},
"kind": "geometry", "path": p["path"], "dir": d,
"overlay_images": n, **s})
for p in FAST:
print(f"[fast] {p['slug']}")
s, d = do_fast(p)
per_paper_report(p, s, d, "born-digital fast-path")
catalog["papers"].append({**{k: p[k] for k in ("slug", "title", "board", "level")},
"kind": "fast", "path": "born-digital fast-path", "dir": d, **s})
json.dump(catalog, open(os.path.join(FINAL, "catalog.json"), "w"), indent=2)
write_index(catalog, total_imgs)
print(f"\n-> {len(catalog['papers'])} papers, {total_imgs} overlay images -> {FINAL}/")
def write_index(catalog, total_imgs):
g = [p for p in catalog["papers"] if p["kind"] == "geometry"]
f = [p for p in catalog["papers"] if p["kind"] == "fast"]
L = ["# Final corpus output — exam-extraction spike", "",
f"Generated {catalog['generated_at']}. {len(catalog['papers'])} paper-runs across "
f"3 boards × 2 levels, both pipeline paths; {total_imgs} overlay debug images.", "",
"Each `<slug>/` holds the machine artifacts (JSON) + `report.md`; geometry papers also have "
"`overlays/template/` (human-review view, all pages) and `overlays/debug/` (raw-detection view).",
"Machine catalog: `catalog.json`.", "",
"## Image-only / OCR-path (with geometry + overlays)", "",
"| Paper | Board / level | Q/parts | Marks/max | Coverage | G6 | Images |",
"|---|---|---|---|---|---|---|"]
for p in g:
cov = f"{p['coverage_pct']}%" if p['coverage_pct'] is not None else "n/a"
L.append(f"| [{p['title']}]({p['slug']}/report.md) | {p['board']} {p['level']} | "
f"{p['n_questions']}/{p['n_parts']} | {p['marks_sum']}/{p['official_max']} "
f"({p['marks_pct']}%) | {cov} | {p['validate_verdict']} | "
f"{p['overlay_images']} |")
L += ["", "## Born-digital fast-path (CPU, no geometry)", "",
"| Paper | Board / level | Q/parts | Marks/max | Coverage | G6 |",
"|---|---|---|---|---|---|"]
for p in f:
L.append(f"| [{p['title']}]({p['slug']}/report.md) | {p['board']} {p['level']} | "
f"{p['n_questions']}/{p['n_parts']} | {p['marks_sum']}/{p['official_max']} "
f"({p['marks_pct']}%) | {p['coverage_pct'] if p['coverage_pct'] is not None else 'n/a'}% | "
f"{p['validate_verdict']} |")
L += ["", "## Per-paper directory layout", "```",
"<slug>/",
" structured.json extract.py output (questions->parts->marks/bbox/regions)",
" validate.json G6 consistency judge (confidence + flags)",
" furniture.json recurring-furniture mask + content margins [geometry only]",
" bands.json main + part y-bands [geometry only]",
" page_roles.json per-page role + margin override [geometry only]",
" template.json editable first-pass template (source/confirmed) [geometry only]",
" overlays/template/ human-review view, all pages [geometry only]",
" overlays/debug/ raw-detection view, sample pages [geometry only]",
" report.md per-paper human summary", "```"]
open(os.path.join(FINAL, "INDEX.md"), "w").write("\n".join(L) + "\n")
if __name__ == "__main__":
main()