diff --git a/exfiltrate.py b/exfiltrate.py
index af0bc2e..12c5d51 100644
--- a/exfiltrate.py
+++ b/exfiltrate.py
@@ -11,7 +11,7 @@ from rasterio import Affine
 from tqdm import tqdm
 
 from pkg.image import random_file_width
-from pkg.spatial import deg2num, lonlat_to_meters
+from pkg.spatial import deg2num
 from pkg.thread import download_tile
 
 if __name__ == '__main__':
@@ -102,6 +102,7 @@ if __name__ == '__main__':
     col_bar.close()
 
     print(f'Downloaded {total_downloaded} images.')
+    print('Preparing data...')
 
     tile_size = random_file_width(tiles_output)
 
@@ -144,16 +145,12 @@ if __name__ == '__main__':
 
     with ThreadPoolExecutor(max_workers=args.tiff_threads) as executor:
         futures = {executor.submit(build_tiff_data, task) for task in tiles}
-        for future in tqdm(as_completed(futures), total=len(futures), desc='Building TIFF'):
+        for future in tqdm(as_completed(futures), total=len(futures), desc='Preparing Data'):
             pass
 
     # Transpose the image data array to the format (bands, rows, cols).
     image_data = np.transpose(image_data, (2, 0, 1))
 
-    # Convert geographic coordinates to Web Mercator coordinates. Not 100% sure this is nessesary.
-    top_left_mx, top_left_my = lonlat_to_meters(top_left_lon, top_left_lat)
-    bottom_right_mx, bottom_right_my = lonlat_to_meters(bottom_right_lon, bottom_right_lat)
-
     # Define the transformation from pixel coordinates to geographic coordinates, which is an Affine transformation that
     # maps pixel coordinates in the image to geographic coordinates on the Earth's surface.
     transform = (Affine.translation(top_left_lon, top_left_lat)  # Create a translation transformation that shifts the image and set the origin of the image to the top-left corner of the bounding box.