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Cyberes 2023-11-03 02:06:46 -06:00
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16
README.md
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# wmts-scraper # wmts-exfiltrator
Scrape tiles from WMTS servers. _Scrape tiles from WMTS servers._
You know what I hate? Those godforsaken WMTS servers, perched on their digital thrones, acting like they're the TILE TYRANTS of the universe. They think they can just LOCK UP their precious little tiles and keep me from doing my THING? HA!
No more will these WMTS servers shroud their CRAPPY-ASS tiles in mystery. I'm coming for your DATA, you binary BASTARDS, and there's not a SINGLE 1 or 0 you can throw at me that will stop my CHARGE.
You think your firewalls and security mumbo-jumbo can keep me at bay? THINK AGAIN. I'll slice through your defenses like a HOT PIZZA through COLD BUTTER. I'll have your DATA, and there's absolutely NOTHING, I repeat, NOTHING you can do to STOP ME.
So, buckle up, WMTS servers. Your reign of TILE TERROR is about to CRASH AND BURN. I'm coming for your DATA, and I'm bringing a whole lot of CHAOS with me.
### ArcGIS ### ArcGIS
- If your raster is a teal square in ArcGIS, open Symbology and set `Stretch type` to `Esri`, which is the only stretch type that works with the background mask. - Set `Stretch type` to `Esri`, which is the only stretch type that works with the background mask.
### Thank Yous ### Credits
https://jimmyutterstrom.com/blog/2019/06/05/map-tiles-to-geotiff/ https://jimmyutterstrom.com/blog/2019/06/05/map-tiles-to-geotiff/

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exfiltrate.py
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@ -93,7 +93,7 @@ if __name__ == '__main__':
# Replace white pixels with NODATA # Replace white pixels with NODATA
tile_data[np.all(tile_data == [255, 255, 255], axis=-1)] = [0, 0, 0] tile_data[np.all(tile_data == [255, 255, 255], axis=-1)] = [0, 0, 0]
# ArcGIS does not like pixels that have zeros in them, eg (255, 0, 0). We need to convert these to (255, 1, 1). # ArcGIS does not like pixels that have zeros in them, eg. (255, 0, 0). We need to convert the zeros to ones, eg. (255, 1, 1).
mask = np.any(tile_data == 0, axis=-1) & np.any(tile_data != 0, axis=-1) # Identify pixels where not all bands are zero and at least one band is zero. mask = np.any(tile_data == 0, axis=-1) & np.any(tile_data != 0, axis=-1) # Identify pixels where not all bands are zero and at least one band is zero.
for i in range(3): # Iterate over each band. for i in range(3): # Iterate over each band.
# For these pixels, set zero bands to one. # For these pixels, set zero bands to one.