added reprojection to WGS84

inference_tab/inference_logic.py

@@ -707,6 +707,14 @@ def fuzzyMatch(score_th, tile_dict):
         crs="EPSG:3857"
     )
 
+    # Add lat lon to the blobs
+    # Reproject temporarily to WGS84 for coordinates
+    gdf_ll = gdf.to_crs(epsg=4326)
+
+    # Add longitude/latitude columns to the original gdf
+    gdf['lon'] = gdf_ll.geometry.x
+    gdf['lat'] = gdf_ll.geometry.y
+
     OSM_PATH = os.path.join(OUTPUT_DIR, "osm_extract.geojson")
     osm_gdf = gpd.read_file(OSM_PATH, dtype={"name": "str"})
     osm_gdf["name"] = osm_gdf["name"].str.replace("strasse", "", case=False, regex=False)
@@ -736,8 +744,8 @@ def fuzzyMatch(score_th, tile_dict):
 
         results.append({
             "blob_id": row.blob_id,
-            "x": row.x,
-            "y": row.y,
+            "lon": row.lon,
+            "lat": row.lat,
             "blob_name": row.pred_text,
             "best_osm_match": match[0] if match else None,
             "osm_match_score": match[1] if match else 0,
@@ -756,6 +764,7 @@ def fuzzyMatch(score_th, tile_dict):
     results_df.to_csv(RES_PATH, index=False)
 
     # Export OSM layer as CSV
+    osm_gdf = osm_gdf.to_crs(epsg=4326)
     OSM_CSV_PATH = os.path.join(OUTPUT_DIR, f"osm_extract_tile{tile_number}.csv")
     osm_export_df = osm_gdf[["name", "geometry"]].copy()
     osm_export_df["geometry"] = osm_export_df["geometry"].apply(lambda g: g.wkt)