Update app.py

app.py

@@ -180,8 +180,8 @@ if uploaded_file is not None:
         collection = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED").filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', max_cloud_cover)).filter(ee.Filter.date(start_date, end_date)).select(['B4', 'B8'])
 
         # Get Zonal NDVI based on collection and geometries (Original KML and Buffered KML)
-        df_geom = get_zonal_ndvi(collection, geom_ee_object)
-        df_buffered_geom = get_zonal_ndvi(collection, buffered_ee_object)
+        df_geom = get_zonal_ndvi(collection.filterBounds(geom_ee_object), geom_ee_object)
+        df_buffered_geom = get_zonal_ndvi(collection.filterBounds(buffered_ee_object), buffered_ee_object)
 
         # Merge both Zonalstats and create resultant dataframe
         resultant_df = pd.merge(df_geom, df_buffered_geom, on='Date', how='inner')