feat: map view with GPS extraction fix

Adds a new Map sidebar entry that plots photos by their EXIF GPS
coordinates on a clustered Leaflet map. While wiring this up, the
metadata extractor was reading unprefixed GPS keys that never exist
in `exiftool -G -j` output AND assumed coordinates were already
floats — every photo silently lost its GPS. The new extract_gps
helper handles Composite/EXIF group prefixes and parses DMS strings,
and lat/lon are stored as first-class indexed columns so the map
can query them without parsing exif_json on every request.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

backend/app/tasks/scan.py

@@ -456,16 +456,44 @@ def watch_folders():
 async def handle_file_deletion(filepath: str):
     """Handle deletion of a file from the filesystem"""
     from sqlalchemy import select
-    
+
     async with AsyncSessionLocal() as session:
         result = await session.execute(
             select(Photo).where(Photo.filepath == filepath)
         )
         photo = result.scalar_one_or_none()
-        
+
         if photo:
             # Mark as missing or delete from database
             photo.is_discarded = True
             photo.discarded_at = datetime.utcnow()
             await session.commit()
-            logger.info(f"Marked photo as discarded: {filepath}")
+            logger.info(f"Marked photo as discarded: {filepath}")
+
+
+@shared_task(name='backfill_gps')
+def backfill_gps():
+    """Re-run metadata extraction on every non-discarded photo that is
+    missing latitude/longitude. Used both as a one-shot kick-off after the
+    GPS columns are added on an existing install (see app/database.py) and
+    as a manual trigger from POST /api/v1/library/backfill-gps. Each
+    extract_metadata call is itself a Celery task, so this just enqueues —
+    it does not block on extraction completing."""
+    return asyncio.run(_backfill_gps_async())
+
+
+async def _backfill_gps_async():
+    async with AsyncSessionLocal() as session:
+        result = await session.execute(
+            select(Photo.id).where(
+                Photo.latitude.is_(None),
+                Photo.is_discarded.is_(False),
+            )
+        )
+        photo_ids = [row[0] for row in result.all()]
+
+    for pid in photo_ids:
+        extract_metadata.delay(pid)
+
+    logger.info(f"backfill_gps: queued extract_metadata for {len(photo_ids)} photos")
+    return {'queued': len(photo_ids)}