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
 # =====================

backend/image_tagger.py

@@ -0,0 +1,89 @@
+"""
+Skriv og les bib-metadata i bildefiler via EXIF UserComment (JSON).
+
+Bruker piexif + Pillow som allerede er i requirements.txt.
+Metadata lagres i Exif.UserComment som:
+  b"ASCII\x00\x00\x00" + JSON-bytes
+
+Eksempel-innhold:
+  {"bibs": ["42", "87"], "station": "finish", "confidence": 0.93, "confirmed": true}
+"""
+
+import json
+import logging
+from pathlib import Path
+from typing import Optional
+
+import piexif
+from PIL import Image
+
+logger = logging.getLogger(__name__)
+
+_ASCII_PREFIX = b"ASCII\x00\x00\x00"
+
+
+def write_bib_tags(
+    image_path: Path,
+    bibs: list[str],
+    *,
+    station: Optional[str] = None,
+    race_id: Optional[str] = None,
+    confidence: Optional[float] = None,
+    confirmed: bool = False,
+) -> None:
+    """
+    Skriv startnummer-metadata til bildefil som EXIF UserComment (JSON).
+    Bevarer all eksisterende EXIF. Feiler stille — krasjer ikke ingest-prosessen.
+    """
+    data: dict = {"bibs": bibs}
+    if station:
+        data["station"] = station
+    if race_id:
+        data["race_id"] = race_id
+    if confidence is not None:
+        data["confidence"] = round(confidence, 4)
+    if confirmed:
+        data["confirmed"] = True
+
+    json_bytes = json.dumps(data, ensure_ascii=True, separators=(",", ":")).encode("ascii")
+    comment_bytes = _ASCII_PREFIX + json_bytes
+
+    try:
+        img = Image.open(image_path)
+        raw_exif = img.info.get("exif")
+        if raw_exif:
+            exif_dict = piexif.load(raw_exif)
+        else:
+            exif_dict = {"0th": {}, "Exif": {}, "GPS": {}, "Interop": {}, "1st": {}}
+
+        exif_dict.setdefault("Exif", {})[piexif.ExifIFD.UserComment] = comment_bytes
+        new_exif = piexif.dump(exif_dict)
+
+        # Lagre til midlertidig fil, rename for atomisk skriving
+        tmp = image_path.with_suffix(".tmp" + image_path.suffix)
+        img.save(tmp, exif=new_exif)
+        tmp.replace(image_path)
+
+        logger.debug("EXIF-tags skrevet til %s: bibs=%s", image_path.name, bibs)
+    except Exception as e:
+        logger.warning("Kunne ikke skrive EXIF-tags til %s: %s", image_path, e)
+
+
+def read_bib_tags(image_path: Path) -> Optional[dict]:
+    """
+    Les startnummer-metadata fra EXIF UserComment.
+    Returnerer dict (med nøkkel 'bibs') eller None hvis ikke satt.
+    """
+    try:
+        img = Image.open(image_path)
+        raw_exif = img.info.get("exif")
+        if not raw_exif:
+            return None
+        exif_dict = piexif.load(raw_exif)
+        comment = exif_dict.get("Exif", {}).get(piexif.ExifIFD.UserComment)
+        if not comment or not comment.startswith(_ASCII_PREFIX):
+            return None
+        json_str = comment[len(_ASCII_PREFIX):].decode("ascii", errors="replace")
+        return json.loads(json_str)
+    except Exception:
+        return None

backend/ingest.py

@@ -21,7 +21,8 @@ from watchdog.events import FileSystemEventHandler, FileCreatedEvent
 from watchdog.observers import Observer
 
 from exif_parser import ExifError, parse_image
-from ocr import read_bib
+from image_tagger import write_bib_tags
+from ocr import read_all_bibs
 from passage_log import log_passage
 from profile_db import get_or_create_athlete, init_db
 
@@ -70,40 +71,52 @@ async def process_image(path: Path) -> None:
         return
 
     # --- OCR ---
-    ocr = read_bib(path)
+    bibs = read_all_bibs(path)
-    logger.debug("OCR: digits=%s conf=%.2f", ocr.digits, ocr.confidence)
+    logger.debug("OCR: %d startnumre funnet", len(bibs))
 
     # --- Flytt til processed/ ---
     dest = _destination_path(path, meta.timestamp_utc)
     shutil.move(str(path), str(dest))
     logger.info("Flyttet til: %s", dest)
 
-    # --- Bestem konfidens og review-flagg ---
-    confidence = ocr.confidence
-    needs_review = False
-    review_note = None
-    id_method = "bib_ocr"
-
-    if ocr.digits is None or confidence < MIN_AUTO_CONFIDENCE:
-        needs_review = True
-        review_note = "number_unreadable" if ocr.digits is None else "low_confidence"
-        id_method = "bib_ocr_uncertain"
-
-    # --- Koble mot profil-DB ---
-    profile_id = None
-    bib_number = ocr.digits
-
     async with aiosqlite.connect(DB_PATH) as db:
         db.row_factory = aiosqlite.Row
         await init_db(db)
 
-        if bib_number and not needs_review:
+        if not bibs:
-            profile_id = await get_or_create_athlete(db, bib_number)
+            # Ingen bib funnet — legg til manuell gjennomgang
+            await log_passage(
+                db,
+                profile_id=None,
+                bib_number=None,
+                station=meta.station or "unknown",
+                timestamp_utc=meta.timestamp_utc,
+                gps_lat=meta.gps_lat,
+                gps_lon=meta.gps_lon,
+                gps_alt=meta.gps_alt,
+                confidence=0.0,
+                proximity_score=0.0,
+                id_method="bib_ocr_uncertain",
+                source_image=str(dest),
+                needs_review=True,
+                review_note="number_unreadable",
+            )
+            logger.info("Passering logget (ingen bib): station=%s", meta.station)
+        else:
+            for ocr in bibs:
+                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:
+                    profile_id = await get_or_create_athlete(db, ocr.digits)
 
                 await log_passage(
                     db,
                     profile_id=profile_id,
-            bib_number=bib_number,
+                    bib_number=ocr.digits,
                     station=meta.station or "unknown",
                     timestamp_utc=meta.timestamp_utc,
                     gps_lat=meta.gps_lat,
@@ -118,9 +131,14 @@ async def process_image(path: Path) -> None:
                 )
                 logger.info(
                     "Passering logget: bib=%s station=%s needs_review=%s",
-            bib_number, meta.station, needs_review,
+                    ocr.digits, meta.station, needs_review,
                 )
 
+        # Skriv alle funne bibs til EXIF-metadata i filen
+        found_bibs = [ocr.digits for ocr in bibs if ocr.digits]
+        if found_bibs:
+            write_bib_tags(dest, found_bibs, station=meta.station or "unknown")
+
 
 async def process_image_with_override(
     path: Path,
@@ -148,16 +166,35 @@ async def process_image_with_override(
     except ExifError:
         timestamp = datetime.now(timezone.utc)
 
-    ocr = read_bib(path)
+    bibs = read_all_bibs(path)
     dest = _destination_path(path, timestamp)
     shutil.move(str(path), str(dest))
 
-    confidence = ocr.confidence
+    if not bibs:
-    needs_review = ocr.digits is None or confidence < MIN_AUTO_CONFIDENCE
+        await log_passage(
-    id_method = "bib_ocr" if not needs_review else "bib_ocr_uncertain"
+            db,
-    review_note = None if not needs_review else (
+            race_id=race_id,
-        "number_unreadable" if ocr.digits is None else "low_confidence"
+            profile_id=None,
+            bib_number=None,
+            station=station_name,
+            timestamp_utc=timestamp,
+            gps_lat=gps_lat or 0.0,
+            gps_lon=gps_lon or 0.0,
+            gps_alt=gps_alt,
+            confidence=0.0,
+            proximity_score=0.0,
+            id_method="bib_ocr_uncertain",
+            source_image=str(dest),
+            needs_review=True,
+            review_note="number_unreadable",
         )
+        logger.info("Passering logget (ingen bib): station=%s", station_name)
+    else:
+        for ocr in bibs:
+            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:
@@ -182,6 +219,11 @@ async def process_image_with_override(
             )
             logger.info("Passering logget: bib=%s station=%s", ocr.digits, station_name)
 
+        # Skriv alle funne bibs til EXIF-metadata i filen
+        found_bibs = [ocr.digits for ocr in bibs if ocr.digits]
+        if found_bibs:
+            write_bib_tags(dest, found_bibs, station=station_name, race_id=race_id)
+
 
 async def process_existing() -> None:
     """Behandle bilder som allerede ligger i depot/ ved oppstart."""

backend/ocr.py

@@ -64,33 +64,11 @@ def _bbox_area(bbox) -> float:
     return (max(xs) - min(xs)) * (max(ys) - min(ys))
 
 
-def _extract_bib_number(texts: list[tuple]) -> tuple[Optional[str], float, bool, float]:
+def read_all_bibs(image_path: Path) -> list["OcrResult"]:
     """
-    Finn beste siffersekvens blant OCR-treff.
+    Les alle startnumre fra bildet.
-    Returnerer (sifre, konfidens, partial, proximity_score).
+    Returnerer én OcrResult per unikt startnummer funnet (minst 2 sifre).
-    proximity_score = areal av bounding box i piksler² (større = nærmere kamera).
+    Tom liste hvis ingen funnet eller ved feil.
-    """
-    candidates = []
-    for (bbox, text, conf) in texts:
-        digits = re.sub(r"[^0-9]", "", text)
-        if digits:
-            candidates.append((digits, float(conf), _bbox_area(bbox)))
-
-    if not candidates:
-        return None, 0.0, False, 0.0
-
-    # Velg kandidat med høyest konfidens
-    best_digits, best_conf, best_area = max(candidates, key=lambda x: x[1])
-
-    partial = len(best_digits) < 2
-
-    return best_digits, best_conf, partial, best_area
-
-
-def read_bib(image_path: Path) -> OcrResult:
-    """
-    Les startnummer fra bildet.
-    Returnerer OcrResult. Aldri exception — fallback til konfidens 0 ved feil.
     """
     try:
         processed = _preprocess(image_path)
@@ -98,19 +76,59 @@ def read_bib(image_path: Path) -> OcrResult:
         results = reader.readtext(processed, detail=1, paragraph=False)
 
         raw_texts = [text for (_, text, _) in results]
-        digits, confidence, partial, proximity_score = _extract_bib_number(results)
 
-        return OcrResult(
+        # Best konfidens + areal per unikt siffersekvens (minst 2 sifre)
+        best: dict[str, tuple[float, float]] = {}  # digits -> (conf, area)
+        for (bbox, text, conf) in results:
+            digits = re.sub(r"[^0-9]", "", text)
+            if len(digits) < 2:
+                continue
+            area = _bbox_area(bbox)
+            if digits not in best or float(conf) > best[digits][0]:
+                best[digits] = (float(conf), area)
+
+        return [
+            OcrResult(
                 digits=digits,
-            confidence=confidence,
+                confidence=conf,
-            partial=partial,
+                partial=False,
-            proximity_score=proximity_score,
+                proximity_score=area,
                 raw_texts=raw_texts,
             )
+            for digits, (conf, area) in best.items()
+        ]
     except Exception as e:
+        return [OcrResult(digits=None, confidence=0.0, partial=False, raw_texts=[f"ERROR: {e}"])]
+
+
+def read_bib(image_path: Path) -> OcrResult:
+    """
+    Les beste startnummer fra bildet (bakoverkompatibel).
+    Returnerer OcrResult. Aldri exception — fallback til konfidens 0 ved feil.
+    """
+    bibs = read_all_bibs(image_path)
+    if not bibs or bibs[0].digits is None:
+        # Sjekk også enkle sifre (partial) for bakoverkompatibilitet
+        try:
+            processed = _preprocess(image_path)
+            reader = _get_reader()
+            results = reader.readtext(processed, detail=1, paragraph=False)
+            raw_texts = [text for (_, text, _) in results]
+            candidates = []
+            for (bbox, text, conf) in results:
+                digits = re.sub(r"[^0-9]", "", text)
+                if digits:
+                    candidates.append((digits, float(conf), _bbox_area(bbox)))
+            if candidates:
+                best_digits, best_conf, best_area = max(candidates, key=lambda x: x[1])
                 return OcrResult(
-            digits=None,
+                    digits=best_digits,
-            confidence=0.0,
+                    confidence=best_conf,
-            partial=False,
+                    partial=len(best_digits) < 2,
-            raw_texts=[f"ERROR: {e}"],
+                    proximity_score=best_area,
+                    raw_texts=raw_texts,
                 )
+        except Exception:
+            pass
+        return OcrResult(digits=None, confidence=0.0, partial=False)
+    return max(bibs, key=lambda r: r.confidence)

backend/race_db.py

@@ -16,6 +16,7 @@ async def init_race_tables(db: aiosqlite.Connection) -> None:
             date               TEXT,
             description        TEXT,
             is_active          INTEGER NOT NULL DEFAULT 0,
+            bib_filter_enabled INTEGER NOT NULL DEFAULT 0,
             created_at         TEXT NOT NULL DEFAULT (datetime('now'))
         );
 
@@ -34,6 +35,14 @@ async def init_race_tables(db: aiosqlite.Connection) -> None:
 
         CREATE INDEX IF NOT EXISTS idx_stations_race ON stations(race_id, station_order);
     """)
+    # Migrering: legg til kolonne for eksisterende databaser
+    try:
+        await db.execute(
+            "ALTER TABLE races ADD COLUMN bib_filter_enabled INTEGER NOT NULL DEFAULT 0"
+        )
+        await db.commit()
+    except Exception:
+        pass  # Kolonnen finnes allerede
     await db.commit()
 
 
@@ -44,11 +53,12 @@ async def create_race(
     name: str,
     date: Optional[str] = None,
     description: Optional[str] = None,
+    bib_filter_enabled: bool = False,
 ) -> dict:
     race_id = str(uuid.uuid4())
     await db.execute(
-        "INSERT INTO races (race_id, name, date, description) VALUES (?, ?, ?, ?)",
+        "INSERT INTO races (race_id, name, date, description, bib_filter_enabled) VALUES (?, ?, ?, ?, ?)",
-        (race_id, name, date, description),
+        (race_id, name, date, description, int(bib_filter_enabled)),
     )
     # Sett som aktivt hvis det er første løpet
     async with db.execute("SELECT COUNT(*) FROM races") as cur:
@@ -86,10 +96,11 @@ async def update_race(
     name: str,
     date: Optional[str],
     description: Optional[str],
+    bib_filter_enabled: bool = False,
 ) -> bool:
     cur = await db.execute(
-        "UPDATE races SET name = ?, date = ?, description = ? WHERE race_id = ?",
+        "UPDATE races SET name = ?, date = ?, description = ?, bib_filter_enabled = ? WHERE race_id = ?",
-        (name, date, description, race_id),
+        (name, date, description, int(bib_filter_enabled), race_id),
     )
     await db.commit()
     return cur.rowcount > 0

frontend/src/api.js

@@ -51,6 +51,7 @@ export const api = {
     body: JSON.stringify(body),
   }),
   deletePassage: (id) => request(`/passages/${id}`, { method: 'DELETE' }),
+  reanalyzePassage: (id) => request(`/passages/${id}/reanalyze`, { method: 'POST' }),
 
   // Resultater
   getResults: (raceId) => request(`/results${qs({ race_id: raceId })}`),

frontend/src/pages/RacePage.jsx

@@ -63,6 +63,18 @@ function RaceCard({ race, isActive, onActivated, onDeleted, onUpdated }) {
   const [expanded, setExpanded] = useState(false)
   const [newStation, setNewStation] = useState({ display_name: '', name: '' })
   const [adding, setAdding] = useState(false)
+  const [bibFilter, setBibFilter] = useState(!!race.bib_filter_enabled)
+
+  const handleBibFilterToggle = async (enabled) => {
+    setBibFilter(enabled)
+    await api.updateRace(race.race_id, {
+      name: race.name,
+      date: race.date || null,
+      description: race.description || null,
+      bib_filter_enabled: enabled,
+    })
+    onUpdated()
+  }
 
   const loadStations = async () => {
     const s = await api.getStations(race.race_id)
@@ -99,6 +111,10 @@ function RaceCard({ race, isActive, onActivated, onDeleted, onUpdated }) {
           {race.date && <span style={{ marginLeft: 8, color: '#888', fontSize: '0.85rem' }}>{race.date}</span>}
           {isActive && <span className="badge badge-success" style={{ marginLeft: 8 }}>Aktivt</span>}
           {race.description && <p style={{ fontSize: '0.85rem', color: '#666', marginTop: 4 }}>{race.description}</p>}
+          <label style={{ display: 'inline-flex', alignItems: 'center', gap: 6, marginTop: 4, fontSize: '0.82rem', color: '#555', cursor: 'pointer' }}>
+            <input type="checkbox" checked={bibFilter} onChange={e => handleBibFilterToggle(e.target.checked)} />
+            Filtrer OCR mot startliste
+          </label>
         </div>
         <div style={{ display: 'flex', gap: 6 }}>
           {!isActive && (

frontend/src/pages/ReviewPage.jsx

@@ -1,6 +1,68 @@
-import { useEffect, useState } from 'react'
+import { useEffect, useRef, useState } from 'react'
 import { api } from '../api.js'
 
+function ZoomOverlay({ src, onClose }) {
+  const [scale, setScale] = useState(1)
+  const [offset, setOffset] = useState({ x: 0, y: 0 })
+  const [dragging, setDragging] = useState(false)
+  const dragStart = useRef(null)
+
+  const handleWheel = (e) => {
+    e.preventDefault()
+    setScale(s => Math.min(8, Math.max(1, s - e.deltaY * 0.005)))
+  }
+
+  const handleMouseDown = (e) => {
+    setDragging(true)
+    dragStart.current = { x: e.clientX - offset.x, y: e.clientY - offset.y }
+  }
+
+  const handleMouseMove = (e) => {
+    if (!dragging || !dragStart.current) return
+    setOffset({ x: e.clientX - dragStart.current.x, y: e.clientY - dragStart.current.y })
+  }
+
+  const handleMouseUp = () => setDragging(false)
+
+  return (
+    <div
+      onClick={onClose}
+      style={{
+        position: 'fixed', inset: 0, background: 'rgba(0,0,0,0.88)',
+        zIndex: 1000, display: 'flex', alignItems: 'center', justifyContent: 'center',
+      }}
+    >
+      <div
+        onClick={e => e.stopPropagation()}
+        onWheel={handleWheel}
+        onMouseDown={handleMouseDown}
+        onMouseMove={handleMouseMove}
+        onMouseUp={handleMouseUp}
+        onMouseLeave={handleMouseUp}
+        style={{ overflow: 'hidden', cursor: dragging ? 'grabbing' : 'grab', maxWidth: '95vw', maxHeight: '95vh' }}
+      >
+        <img
+          src={src}
+          alt="Zoomet bilde"
+          style={{
+            transform: `scale(${scale}) translate(${offset.x / scale}px, ${offset.y / scale}px)`,
+            transformOrigin: 'center',
+            display: 'block',
+            maxWidth: '90vw',
+            maxHeight: '90vh',
+            userSelect: 'none',
+            transition: dragging ? 'none' : 'transform 0.1s',
+          }}
+          draggable={false}
+        />
+      </div>
+      <div style={{ position: 'absolute', top: 16, right: 20, color: '#fff', fontSize: '0.8rem', opacity: 0.7 }}>
+        Rull for zoom · Dra for å flytte · Klikk utenfor for å lukke
+      </div>
+    </div>
+  )
+}
+
 function fmtTs(ts) {
   if (!ts) return '—'
   return new Date(ts).toLocaleString('no-NO', { timeZone: 'UTC', hour12: false })
@@ -14,31 +76,48 @@ function imgSrc(path) {
 function ImageSlider({ passageId, currentImage }) {
   const [images, setImages] = useState([])
   const [index, setIndex] = useState(0)
+  const [zoomSrc, setZoomSrc] = useState(null)
 
   useEffect(() => {
     api.getPassageImages(passageId).then(imgs => {
       setImages(imgs)
-      // Start på siste bilde (passeringstidspunktet)
       setIndex(imgs.length > 0 ? imgs.length - 1 : 0)
     })
   }, [passageId])
 
   if (images.length === 0) {
     const src = imgSrc(currentImage)
-    return src
+    return src ? (
-      ? <img src={src} alt="Passeringsbilde" className="image-preview" />
+      <>
-      : <div className="empty-state" style={{ border: '1px dashed #ddd', borderRadius: 6 }}>Bilde ikke tilgjengelig</div>
+        <img
+          src={src}
+          alt="Passeringsbilde"
+          className="image-preview"
+          onClick={() => setZoomSrc(src)}
+          style={{ cursor: 'zoom-in' }}
+          title="Klikk for å zoome"
+        />
+        {zoomSrc && <ZoomOverlay src={zoomSrc} onClose={() => setZoomSrc(null)} />}
+      </>
+    ) : (
+      <div className="empty-state" style={{ border: '1px dashed #ddd', borderRadius: 6 }}>Bilde ikke tilgjengelig</div>
+    )
   }
 
   const current = images[index]
+  const src = imgSrc(current.image_path)
 
   return (
     <div>
       <img
-        src={imgSrc(current.image_path)}
+        src={src}
         alt={`Bilde ${index + 1} av ${images.length}`}
         className="image-preview"
+        onClick={() => setZoomSrc(src)}
+        style={{ cursor: 'zoom-in' }}
+        title="Klikk for å zoome"
       />
+      {zoomSrc && <ZoomOverlay src={zoomSrc} onClose={() => setZoomSrc(null)} />}
       {images.length > 1 && (
         <div style={{ marginTop: '0.5rem' }}>
           <input
@@ -63,10 +142,12 @@ function ImageSlider({ passageId, currentImage }) {
   )
 }
 
-function ReviewCard({ passage, athletes, onResolved, onDeleted }) {
+function ReviewCard({ passage, athletes, onResolved, onDeleted, onReanalyzed }) {
   const [bib, setBib] = useState(passage.bib_number || '')
   const [note, setNote] = useState('')
   const [saving, setSaving] = useState(false)
+  const [reanalyzing, setReanalyzing] = useState(false)
+  const [reanalyzeResult, setReanalyzeResult] = useState(null)
 
   const matchedAthlete = athletes.find(a => a.bib_number === bib)
 
@@ -90,6 +171,22 @@ function ReviewCard({ passage, athletes, onResolved, onDeleted }) {
     onDeleted()
   }
 
+  const handleReanalyze = async () => {
+    setReanalyzing(true)
+    setReanalyzeResult(null)
+    try {
+      const result = await api.reanalyzePassage(passage.passage_id)
+      setReanalyzeResult(result)
+      if (result.new_passages.length > 0) {
+        onReanalyzed()
+      }
+    } catch (e) {
+      setReanalyzeResult({ error: e.message })
+    } finally {
+      setReanalyzing(false)
+    }
+  }
+
   return (
     <div className="card">
       <div style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: '1.5rem' }}>
@@ -137,12 +234,34 @@ function ReviewCard({ passage, athletes, onResolved, onDeleted }) {
             />
           </div>
 
-          <div style={{ display: 'flex', gap: '0.5rem' }}>
+          <div style={{ display: 'flex', gap: '0.5rem', flexWrap: 'wrap' }}>
             <button className="btn-success" onClick={handleResolve} disabled={saving}>
               {saving ? 'Lagrer...' : 'Bekreft'}
             </button>
+            <button onClick={handleReanalyze} disabled={reanalyzing} style={{ background: '#8e44ad', color: '#fff', border: 'none', borderRadius: 4, padding: '0.4rem 0.9rem', cursor: 'pointer' }}>
+              {reanalyzing ? 'Analyserer...' : 'Re-analyser bilde'}
+            </button>
             <button className="btn-danger" onClick={handleDelete}>Slett</button>
           </div>
+
+          {reanalyzeResult && (
+            <div style={{ marginTop: '0.75rem', fontSize: '0.85rem', padding: '0.5rem 0.75rem', background: '#f5f5f5', borderRadius: 4 }}>
+              {reanalyzeResult.error ? (
+                <span style={{ color: '#e74c3c' }}>Feil: {reanalyzeResult.error}</span>
+              ) : (
+                <>
+                  <div>Funne bibs: {reanalyzeResult.found_bibs.length > 0 ? reanalyzeResult.found_bibs.join(', ') : 'ingen'}</div>
+                  {reanalyzeResult.new_passages.length > 0 ? (
+                    <div style={{ color: '#27ae60', marginTop: 2 }}>
+                      {reanalyzeResult.new_passages.length} ny(e) passering(er) opprettet: {reanalyzeResult.new_passages.map(p => p.bib_number).join(', ')}
+                    </div>
+                  ) : (
+                    <div style={{ color: '#888', marginTop: 2 }}>Ingen nye bibs funnet.</div>
+                  )}
+                </>
+              )}
+            </div>
+          )}
         </div>
       </div>
     </div>
@@ -188,6 +307,7 @@ export default function ReviewPage({ activeRace }) {
               athletes={athletes}
               onResolved={() => removeFromQueue(p.passage_id)}
               onDeleted={() => removeFromQueue(p.passage_id)}
+              onReanalyzed={load}
             />
           ))}
         </>