feat: 0.2.0 – Konsens Qwen = Gemma = GLM als Standard, Gehrke komplett verarbeitet
- Dritte Lesart (GLM-4.6V über OpenRouter, ohne Nachdenken) muss zustimmen;
keine 2:1-Annahme; fehlender Schlusspunkt der dritten Lesart zählt nicht
- run in Paketen zu 50 mit Statuszeile, beide lokalen Modelle parallel,
GLM nur für Einige; nur die übernommene Lesart wird gegen das Bild geprüft
- Bild-Veto: Ähnlichkeit >= 0,65, Schriftgrößen-Prüfung abgeschaltet
- Antworten auf 800 Tokens begrenzt; Prompt-Version und Nachdenk-Einstellung
im Cache-Schlüssel; Verfahrensversion für Prüfergebnisse
- Behoben: Gleichungsnummern aus alten Lesarten ("(3.7)"), gleichzeitiges
Speichern zweier Engines, Absturz bei Formeln ohne aktuelle Lesart
- apply: deutsches Dezimalkomma 3{,}6; Review-Galerie zeigt aktuelle Lesarten
- tools/vergleich.py auf Konsens-Ablauf umgestellt
- Doku: README, BEDIENUNGSANLEITUNG, neues CHANGELOG
Gehrke-Brückenkurs: 942 von 1505 Formelbildern automatisch ersetzt (63 %),
62 von 62 von Hand geprüften korrekt; Pandoc/MathML 945 von 945.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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parent
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1 changed files with 586 additions and 277 deletions
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@ -1,71 +1,55 @@
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#!/usr/bin/env python3
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"""Tuning aid: verify a fixed sample of formulas and write comparison images + an HTML overview.
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"""Tuning aid: process a fixed sample of formulas and write an HTML overview with images.
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python3 tools/vergleich.py AUSGABE [--n 50] [--seed 1] [--name gehrke-50]
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python3 tools/vergleich.py AUSGABE [--n 50] [--seed 1] [--name gehrke-50] [--new-sample]
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The sample (formula ids) is stored in vergleich/<name>/sample.json and reused on later runs, so
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changes to the procedure are compared on the same formulas. Output (not versioned, it shows
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excerpts of the book):
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changes to the procedure are compared on the same formulas. The formulas are processed exactly
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like `run` does (consensus mode: Qwen, Gemma, GLM for agreed readings, image veto). Output is
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not versioned because it shows excerpts of the book:
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vergleich/<name>/
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├── index.html all formulas: image panel, LaTeX, measurements, decision, reason
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├── summary.json counts per status, all numbers
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├── sample.json the formula ids of the sample
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└── NN-<id>.png Original / LaTeX rigid / LaTeX elastic / difference
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vergleich/<name>/index.html per formula: original, rendered readings, decision, veto overlay
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vergleich/<name>/summary.json counts and all readings
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"""
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from __future__ import annotations
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import argparse
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import base64
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import html
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import io
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import json
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import random
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import sys
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from concurrent.futures import ProcessPoolExecutor, as_completed
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from pathlib import Path
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from PIL import Image, ImageDraw, ImageFont
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import numpy as np
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from PIL import Image
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sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
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from formula_img2latex.checks import pandoc_mathml_ok # noqa: E402
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from formula_img2latex.decide import decide, thresholds # noqa: E402
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from formula_img2latex.pipeline import _distinct_candidates, _ref_for, _verify_job, open_all # noqa: E402
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from formula_img2latex.pipeline import _ref_for, _wanted, open_all, readings_of, run_consensus # noqa: E402
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from formula_img2latex.render import render_many # noqa: E402
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from formula_img2latex.tex import strip_delimiters # noqa: E402
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FONT = "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf"
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LABELS = (("orig", "Original"), ("rigid", "LaTeX starr"), ("render", "LaTeX elastisch"), ("diff", "Differenz"))
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NAMES = {"local": "Qwen", "local2": "Gemma", "cloud": "GLM"}
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COLOR = {"auto_accepted": "#1f7a3a", "needs_review": "#a15c00"}
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def panel(pngs: dict[str, bytes], target_h: int = 70) -> Image.Image:
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"""Stack the four images, enlarged with visible pixels, each with a label."""
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imgs = {k: Image.open(io.BytesIO(v)).convert("RGB") for k, v in pngs.items()}
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if not imgs:
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return Image.new("RGB", (300, 40), "white")
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h0 = next(iter(imgs.values())).height
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f = max(1, min(8, round(target_h / max(h0, 1))))
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try:
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font = ImageFont.truetype(FONT, 14)
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except OSError:
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font = ImageFont.load_default()
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rows = []
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for key, label in LABELS:
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if key not in imgs:
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continue
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im = imgs[key]
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im = im.resize((im.width * f, im.height * f), Image.NEAREST)
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row = Image.new("RGB", (im.width + 140, im.height + 8), "white")
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ImageDraw.Draw(row).text((4, 4), label, fill=(80, 80, 80), font=font)
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row.paste(im, (136, 4))
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rows.append(row)
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w = max(r.width for r in rows)
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out = Image.new("RGB", (w, sum(r.height for r in rows) + 4), "white")
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y = 0
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for r in rows:
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out.paste(r, (0, y))
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y += r.height
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ImageDraw.Draw(out).rectangle([0, 0, out.width - 1, out.height - 1], outline=(200, 200, 200))
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return out
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def uri(img: Image.Image) -> str:
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buf = io.BytesIO()
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img.save(buf, "PNG")
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return "data:image/png;base64," + base64.b64encode(buf.getvalue()).decode()
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def original(data: bytes, target_h: int = 60) -> Image.Image:
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im = Image.open(io.BytesIO(data))
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if im.mode in ("P", "LA", "RGBA") or "transparency" in im.info:
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im = im.convert("RGBA")
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im = Image.alpha_composite(Image.new("RGBA", im.size, "white"), im)
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im = im.convert("RGB")
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f = max(1, min(6, round(target_h / max(im.height, 1))))
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return im.resize((im.width * f, im.height * f), Image.NEAREST)
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def main() -> int:
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@ -73,10 +57,9 @@ def main() -> int:
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ap.add_argument("source", type=Path)
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ap.add_argument("--n", type=int, default=50)
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ap.add_argument("--seed", type=int, default=1)
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ap.add_argument("--name", default=None, help="Unterordner in vergleich/ (Standard: <buch>-<n>)")
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ap.add_argument("--preset", default=None)
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ap.add_argument("--workers", type=int, default=16)
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ap.add_argument("--new-sample", action="store_true", help="neue Stichprobe ziehen")
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ap.add_argument("--name", default=None)
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ap.add_argument("--new-sample", action="store_true")
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ap.add_argument("--no-cloud", action="store_true")
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args = ap.parse_args()
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source, ws = open_all(args.source, None)
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@ -84,74 +67,68 @@ def main() -> int:
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out = Path(__file__).resolve().parents[1] / "vergleich" / name
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out.mkdir(parents=True, exist_ok=True)
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sample_file = out / "sample.json"
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pool = [f for f in ws.all() if _distinct_candidates(f) and (f.classify or {}).get("label") != "figure"]
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pool = [f for f in ws.all() if _wanted(f, False)]
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if sample_file.exists() and not args.new_sample:
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ids = json.loads(sample_file.read_text())
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else:
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ids = sorted(f.id for f in random.Random(args.seed).sample(pool, min(args.n, len(pool))))
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sample_file.write_text(json.dumps(ids, indent=1))
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by_id = {f.id: f for f in pool}
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formulas = [by_id[i] for i in ids if i in by_id]
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preset = args.preset or ws.settings.get("preset") or "cm"
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book_ppt = ws.settings.get("book_px_per_pt")
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th = thresholds(ws.settings.get("thresholds"))
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jobs = [(f.id, source.original_bytes(_ref_for(source, f)), f.asset, _distinct_candidates(f), f.display, preset)
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for f in formulas]
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results: dict[str, tuple[dict, dict[str, bytes]]] = {}
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with ProcessPoolExecutor(max_workers=args.workers) as ex:
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for fut in as_completed([ex.submit(_verify_job, j) for j in jobs]):
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fid, res, pngs = fut.result()
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best = max(res, key=lambda r: (r["ok"], r["min_contrast"] if r["min_contrast"] is not None else 1.0,
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r["metrics"].get("ncc", 0.0)))
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results[fid] = (best, pngs)
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print(f" {len(results)}/{len(jobs)}", file=sys.stderr, end="\r")
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print(file=sys.stderr)
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pandoc = dict(zip([f.id for f in formulas], pandoc_mathml_ok([(results[f.id][0]["tex"], f.display) for f in formulas])))
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run_consensus(source, ws, chunk=len(ids), ids=ids, use_cloud=not args.no_cloud)
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for old in out.glob("*.png"):
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old.unlink()
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formulas = [ws.load(i) for i in ids]
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formulas = [f for f in formulas if f is not None]
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preset = ws.settings.get("preset") or "cm"
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items, rows = [], []
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for f in formulas:
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for r in readings_of(f):
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items.append((strip_delimiters(r.get("tex") or "") or "\\text{–}", f.display))
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rendered = iter(render_many(items, preset))
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counts: dict[str, int] = {}
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rows_html, summary = [], []
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summary = []
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for n, f in enumerate(formulas, 1):
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best, pngs = results[f.id]
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status, reason = decide(best, pandoc[f.id], book_ppt, th)
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counts[status] = counts.get(status, 0) + 1
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img = f"{n:02d}-{f.id}.png"
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panel(pngs).save(out / img)
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m = best.get("metrics", {})
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mc = best.get("min_contrast")
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summary.append({"n": n, "id": f.id, "status": status, "reason": reason, "tex": best.get("tex"),
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"ocr": [c.get("tex") for c in f.candidates if c.get("tex")], "display": f.display,
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"min_contrast": mc, "worst_variant": best.get("worst_variant"),
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"worst_kind": best.get("worst_kind"), "climbed_from": best.get("climbed_from"),
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"metrics": m})
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climbed = ""
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if best.get("climbed_from"):
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climbed = "<div class=fix>korrigiert aus: <code>" + html.escape(best["climbed_from"][0]) + "</code></div>"
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rows_html.append(
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f"<section class='{status}'><h2>{n:02d} · <span class=st>{status}</span> · "
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f"{'abgesetzt' if f.display else 'im Text'} · {html.escape(f.occurrences[0]['file'])}:{f.occurrences[0]['line']}</h2>"
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f"<img src='{img}'><div><code>{html.escape(best.get('tex') or '')}</code></div>{climbed}"
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f"<div class=m>NCC elastisch {m.get('ncc', 0):.3f} · starr {m.get('rigid_ncc', 0):.3f} · "
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f"Verzerrung {m.get('warp_share', 0):.2f} · px/pt {m.get('px_per_pt', 0):.3f} · "
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f"Kontrast {('–' if mc is None else f'{mc:.3f}')} (knappste Variante: {html.escape(best.get('worst_kind') or '–')}) · "
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f"Pandoc {'ok' if pandoc[f.id] else 'FEHLER'}</div><div class=r>{html.escape(reason)}</div></section>")
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counts[f.status] = counts.get(f.status, 0) + 1
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orig = original(source.original_bytes(_ref_for(source, f)))
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lines = [f"<tr><th>Original</th><td><img src='{uri(orig)}'></td><td></td></tr>"]
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reads = []
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for r in readings_of(f):
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rr = next(rendered)
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img = ""
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if rr.ok:
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z = 2.0 * max(1.0, orig.height / 60)
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g = (rr.rasterize(min(z, 4.0)) * 255).astype(np.uint8)
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img = uri(Image.fromarray(255 - g))
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who = NAMES.get(r.get("engine", ""), r.get("engine", "?"))
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reads.append({"engine": who, "model": r.get("model"), "tex": r.get("tex"), "p_mean": r.get("p_mean")})
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p = r.get("p_mean")
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lines.append(f"<tr><th>{who}</th><td>{f'<img src={chr(39)}{img}{chr(39)}>' if img else '(nicht renderbar)'}</td>"
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f"<td><code>{html.escape(r.get('tex') or '–')}</code>"
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f"{f' <small>p={p:.2f}</small>' if p is not None else ''}</td></tr>")
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diff = ws.review_dir / f"{f.id}-diff.png"
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if diff.exists():
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d = Image.open(diff).convert("RGB")
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d = d.resize((d.width * 2, d.height * 2), Image.NEAREST)
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lines.append(f"<tr><th>Veto-Overlay</th><td><img src='{uri(d)}'></td><td><small>rot = nur Original, "
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"blau = nur LaTeX, schwarz = beide</small></td></tr>")
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color = COLOR.get(f.status, "#a32020")
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occ = f.occurrences[0] if f.occurrences else {}
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rows.append(f"<section style='border-left-color:{color}'><h2>{n:02d} · <span style='color:{color}'>{f.status}</span> · "
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f"{'abgesetzt' if f.display else 'im Text'} · {html.escape(occ.get('file', ''))}:{occ.get('line', '')}</h2>"
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f"<div class=r>{html.escape(f.reason or '')}</div><table>{''.join(lines)}</table></section>")
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summary.append({"n": n, "id": f.id, "status": f.status, "reason": f.reason, "final_tex": f.final_tex,
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"readings": reads})
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head = " · ".join(f"{k}: {v}" for k, v in sorted(counts.items()))
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(out / "index.html").write_text(
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"<!doctype html><meta charset=utf-8><title>Vergleich " + html.escape(name) + "</title><style>"
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"body{font:14px system-ui,sans-serif;margin:16px;background:#f6f6f3}section{background:#fff;border:1px solid #ddd;"
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"border-radius:6px;padding:8px 12px;margin:10px 0}h2{font-size:14px;margin:0 0 6px}img{max-width:100%}"
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".auto_accepted .st{color:#1f7a3a}.needs_review .st{color:#a15c00}.rejected_keep_image .st,.render_failed .st{color:#a32020}"
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".m{font:12px monospace;color:#555;margin-top:4px}.r{font-size:13px}.fix{font-size:12px;color:#2a5db0}"
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"code{font-size:12px}</style>"
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f"<h1>Vergleich {html.escape(name)}</h1><p>{len(formulas)} Formeln, Schrift {preset} · {head}</p>"
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"<p>Zeilen je Bild: Original · LaTeX starr ausgerichtet · LaTeX elastisch ausgerichtet · Differenz "
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"(schwarz = beide, rot = nur Original, blau = nur LaTeX, gelb = Abweichungsfleck)</p>"
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+ "".join(rows_html), encoding="utf-8")
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(out / "summary.json").write_text(json.dumps({"preset": preset, "counts": counts, "formulas": summary},
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ensure_ascii=False, indent=1), encoding="utf-8")
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print(f"{len(formulas)} Formeln geprüft – {head}")
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"border-left:6px solid #999;border-radius:6px;padding:8px 12px;margin:10px 0}h2{font-size:14px;margin:0 0 4px}"
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"th{text-align:left;font-weight:400;color:#666;width:100px;vertical-align:middle}td{padding:2px 8px;vertical-align:middle}"
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".r{font-size:13px;margin-bottom:4px}code{font-size:12px}img{max-width:760px}</style>"
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f"<h1>Vergleich {html.escape(name)}</h1><p>{len(formulas)} Formeln · Regel: Qwen = Gemma = GLM, Fettdruck egal, "
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f"Bild-Veto · {head}</p>" + "".join(rows), encoding="utf-8")
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(out / "summary.json").write_text(json.dumps({"counts": counts, "formulas": summary}, ensure_ascii=False, indent=1),
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encoding="utf-8")
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print(f"{len(formulas)} Formeln – {head}")
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print(f"Übersicht: {out / 'index.html'}")
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return 0
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