Støtte for flere bibs per bilde, EXIF-metadata og zoom i gjennomgang

- OCR: ny read_all_bibs() returnerer alle unike startnumre (≥2 sifre) per bilde
- Ingest: oppretter én passering per bib (ikke bare beste), ingen bib → needs_review
- image_tagger.py: skriv/les bib-metadata som JSON i EXIF UserComment (piexif)
- Ingest + resolve: tagger bildefilen med bibs automatisk og ved manuell bekreftelse
- API: POST /api/passages/{id}/reanalyze — re-kjør OCR på eksisterende bilde
- API: POST /api/passages/{id}/resolve oppdaterer nå EXIF med bekreftet bib
- races: ny kolonne bib_filter_enabled (med automatisk migrering) + per-løp toggle
- ReviewPage: Re-analyser-knapp og klikk-for-zoom med scroll/drag

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/api.py

@@ -68,6 +68,7 @@ class RaceRequest(BaseModel):
     name: str
     date: Optional[str] = None
     description: Optional[str] = None
+    bib_filter_enabled: bool = False
 
 
 @app.get("/api/races")
@@ -83,12 +84,12 @@ async def active_race(db=Depends(get_connection)):
 
 @app.post("/api/races")
 async def create_race_endpoint(body: RaceRequest, db=Depends(get_connection)):
-    return await create_race(db, body.name, body.date, body.description)
+    return await create_race(db, body.name, body.date, body.description, body.bib_filter_enabled)
 
 
 @app.put("/api/races/{race_id}")
 async def update_race_endpoint(race_id: str, body: RaceRequest, db=Depends(get_connection)):
-    ok = await update_race(db, race_id, body.name, body.date, body.description)
+    ok = await update_race(db, race_id, body.name, body.date, body.description, body.bib_filter_enabled)
     if not ok:
         raise HTTPException(404, "Løp ikke funnet")
     return await get_race(db, race_id)
@@ -223,6 +224,30 @@ async def resolve(passage_id: str, body: ResolveRequest, db=Depends(get_connecti
                                review_note=body.review_note)
     if not ok:
         raise HTTPException(404, "Passering ikke funnet")
+
+    # Oppdater EXIF-metadata med bekreftet startnummer
+    if body.bib_number:
+        from image_tagger import write_bib_tags, read_bib_tags
+        async with db.execute(
+            "SELECT source_image, station, race_id FROM passages WHERE passage_id = ?",
+            (passage_id,),
+        ) as cur:
+            row = await cur.fetchone()
+        if row:
+            img_path = Path(row["source_image"])
+            if img_path.exists():
+                # Behold allerede taggede bibs, legg til bekreftet
+                existing = read_bib_tags(img_path)
+                all_bibs = list(dict.fromkeys(
+                    (existing or {}).get("bibs", []) + [body.bib_number]
+                ))
+                write_bib_tags(
+                    img_path, all_bibs,
+                    station=row["station"],
+                    race_id=row["race_id"],
+                    confirmed=True,
+                )
+
     return {"ok": True}
 
 
@@ -239,6 +264,82 @@ async def remove_passage(passage_id: str, db=Depends(get_connection)):
     return {"ok": True}
 
 
+@app.post("/api/passages/{passage_id}/reanalyze")
+async def reanalyze_passage(passage_id: str, db=Depends(get_connection)):
+    """
+    Kjør OCR på nytt på passeringens kildebilde.
+    Oppretter nye passeringer for eventuelle startnumre som ikke allerede er logget fra dette bildet.
+    Returnerer alle funne startnumre og eventuelle nye passage_id-er.
+    """
+    from datetime import timezone as _tz
+    from ocr import read_all_bibs
+    from ingest import MIN_AUTO_CONFIDENCE
+    from profile_db import get_athlete_by_bib
+
+    async with db.execute("SELECT * FROM passages WHERE passage_id = ?", (passage_id,)) as cur:
+        row = await cur.fetchone()
+    if not row:
+        raise HTTPException(404, "Passering ikke funnet")
+
+    passage = dict(row)
+    image_path = Path(passage["source_image"])
+    if not image_path.exists():
+        raise HTTPException(404, "Kildebilde ikke funnet på disk")
+
+    bibs = read_all_bibs(image_path)
+
+    # Finn bib-numre som allerede er logget fra dette bildet
+    async with db.execute(
+        "SELECT bib_number FROM passages WHERE source_image = ?", (passage["source_image"],)
+    ) as cur:
+        existing_bibs = {r["bib_number"] for r in await cur.fetchall()}
+
+    new_passages = []
+    ts_str = passage["timestamp_utc"]
+    ts = datetime.fromisoformat(ts_str)
+    if ts.tzinfo is None:
+        ts = ts.replace(tzinfo=_tz.utc)
+
+    for ocr in bibs:
+        if ocr.digits in existing_bibs:
+            continue
+
+        confidence = ocr.confidence
+        needs_review = confidence < MIN_AUTO_CONFIDENCE
+        id_method = "bib_ocr" if not needs_review else "bib_ocr_uncertain"
+        review_note = "low_confidence" if needs_review else None
+
+        profile_id = None
+        if ocr.digits and not needs_review:
+            athlete = await get_athlete_by_bib(db, ocr.digits)
+            if athlete:
+                profile_id = athlete["profile_id"]
+
+        new_id = await log_passage(
+            db,
+            race_id=passage["race_id"],
+            profile_id=profile_id,
+            bib_number=ocr.digits,
+            station=passage["station"],
+            timestamp_utc=ts,
+            gps_lat=passage["gps_lat"],
+            gps_lon=passage["gps_lon"],
+            gps_alt=passage["gps_alt"],
+            confidence=confidence,
+            proximity_score=ocr.proximity_score,
+            id_method=id_method,
+            source_image=passage["source_image"],
+            needs_review=needs_review,
+            review_note=review_note,
+        )
+        new_passages.append({"passage_id": new_id, "bib_number": ocr.digits, "confidence": confidence})
+
+    return {
+        "found_bibs": [ocr.digits for ocr in bibs],
+        "new_passages": new_passages,
+    }
+
+
 # =====================
 # Resultater
 # =====================