few minor changes

README.md

@@ -35,8 +35,8 @@ python3 exfiltrate.py \
   --threads 30
 ```
 
-Building the GeoTIFF will take dozens of gigs of memory for any significant extent! For example, a 336 square mile
-extent required about 400GB of memory. You can use swap for this, but don't expect it to be very quick if you go this
+Building the GeoTIFF will take dozens of gigs of memory for any significant extent! For example, a ??? square mile
+extent required about 280GB of memory. You can use swap for this, but don't expect it to be very quick if you go this
 route.
 
 Be careful not to go overboard with your spatial extent. Use only what you need to avoid unnecessary processing time or
@@ -48,4 +48,4 @@ TODO
 
 ### Inspiration
 
-https://jimmyutterstrom.com/blog/2019/06/05/map-tiles-to-geotiff/
+https://jimmyutterstrom.com/blog/2019/06/05/map-tiles-to-geotiff/

exfiltrate.py

@@ -11,11 +11,13 @@ from PIL import Image
 from rasterio import Affine
 from tqdm import tqdm
 
+from pkg.helpers import convert_seconds
 from pkg.image import random_file_width
 from pkg.spatial import deg2num
 from pkg.thread import download_tile
 
 if __name__ == '__main__':
+    main_start_time = time.time()
     parser = argparse.ArgumentParser(description='Exfiltrate data from WMS servers.')
     parser.add_argument('base_url', help='The base URL for the WMS server. Example: https://wmts.nlsc.gov.tw/wmts/nURBAN/default/EPSG:3857/')
     parser.add_argument('--zoom', type=int, required=True, help='The zoom level to use.')
@@ -168,8 +170,9 @@ if __name__ == '__main__':
                  * Affine.scale((bottom_right_lon - top_left_lon) / image_data.shape[2], (bottom_right_lat - top_left_lat) / image_data.shape[1]))
 
     # Write the image data to a GeoTIFF file
-    print('Saving to:', output_tiff)
-    start = time.time()
+    print('Writing TIFF to:', output_tiff)
+    start_write_tiff = time.time()
     with rasterio.open(output_tiff, "w", driver="GTiff", height=num_rows * tile_size, width=num_cols * tile_size, count=3, dtype=str(image_data.dtype), crs='EPSG:4326', transform=transform, compress="DEFLATE", nodata=0) as dst:
         dst.write(image_data, indexes=[1, 2, 3])
-    print(f'Saved in {int(time.time() - start)} seconds.')
+    now = time.time()
+    print(f'Time to write TIFF: {convert_seconds(int(now - start_write_tiff))} seconds. Total run time: {convert_seconds(int(now - main_start_time))}')

pkg/helpers.py

@@ -0,0 +1,6 @@
+def convert_seconds(seconds):
+    hours = seconds // 3600
+    seconds %= 3600
+    minutes = seconds // 60
+    seconds %= 60
+    return "%d:%02d:%02d" % (hours, minutes, seconds)