clarification
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README.md
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README.md
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@ -35,13 +35,17 @@ python3 exfiltrate.py \
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--threads 30
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```
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Building the GeoTIFF will take dozens of gigs of memory for any significant extent! For example, a 21 mile extent
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required about 400GB of memory. You can use swap for this, but don't expect it to be very quick if you go this route.
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Building the GeoTIFF will take dozens of gigs of memory for any significant extent! For example, a 336 square mile
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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
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route.
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Be careful not to go overboard with your spatial extent. Use only what you need to avoid unnecessary processing time or
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else you will end up with a situation where it will take a week to download all the tiles and build a TIFF.
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### ArcGIS
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TODO
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### Credits
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### Inspiration
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https://jimmyutterstrom.com/blog/2019/06/05/map-tiles-to-geotiff/
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@ -114,7 +114,7 @@ if __name__ == '__main__':
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print(f' {num_cols}x{num_rows}')
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# Create an empty array to store the image data
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print(f'Allocating an array with the shape {num_rows * tile_size, num_cols * tile_size} and dimension 3...')
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print(f'Allocating an array with shape {num_rows * tile_size, num_cols * tile_size} and dimension 3...')
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image_data = np.empty((num_rows * tile_size, num_cols * tile_size, 3), dtype=np.uint8)
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@ -149,8 +149,10 @@ if __name__ == '__main__':
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with ThreadPoolExecutor(max_workers=args.tiff_threads) as executor:
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futures = {executor.submit(build_tiff_data, task) for task in tiles}
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for future in tqdm(as_completed(futures), total=len(futures), desc='Building TIFF'):
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pass
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bar = tqdm(total=len(futures), desc='Building TIFF', postfix='There may be a lengthy startup time, please be patient!')
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for future in as_completed(futures):
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bar.set_postfix()
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bar.update()
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# Transpose the image data array to the format (bands, rows, cols).
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print('Transposing...')
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