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To get enormous amount of Apple Maps tile with ease

Project description


DOI

Purpose

This manually brute forces apple-map. It Then scraps all the tiles (image and road mask pair) as given by the parameters provided by the user. This uses an API-key generated at the time of browsing the map.

The api accessKey token is automatically fetched if you have Google Chrome or Chromium installed using chromedriver-autoinstaller. Otherwise, you'll have to fetch it manually and set the ac_key parameter (which can be found out by selecting one tile from Apple Map, through chrome/firefox by going Developer->Network, looking at the assets, and finding the part of the link beginning with &accessKey= until the next &) every 10-15 mins.

Some of the example images downloaded at different scales

YouTube video

If you are confused with the documentation, please see this video, to see the scraping in action Apple Maps API to get enormous amount of satellite data for free using Python3.

Installation

sudo pip install jimutmap

Sample of the images downloaded

<center> img of sat dat </center>

Download the whole dataset https://drive.google.com/u/3/uc?id=1-2LeYNZquto5vZlDnyuIxXhTzBh2EjRp.

Need for scraping satellite data

Well it's good (best in the world) satellite images, we just need to give the coordinates (Lat,Lon, and zoom) to get your dataset of high resolution satellite images! Create your own dataset and apply ML algorithms :')

The scraping API is present, call it and download it.

>>from jimutmap import api

>>download_obj = api(min_lat_deg = 10,
                      max_lat_deg = 10.01,
                      min_lon_deg = 10.1,
                      max_lon_deg = 10.11,
                      zoom = 19,
                      verbose = False,
                      threads_ = 5, 
                      container_dir = "myOutputFolder")

# If you don't have Chrome and can't take advantage of the auto access key fetch, set
# a.ac_key = ACCESS_KEY_STRING
# here

>>download_obj.download(getMasks = True)

100%|██████████████████████████████████████████████████████████████                     | 1000/10000000 [00:02<00:00, 3913.19it/s

Perks

Well I'm not that bad. This is done through parallel proccessing, so this will take all the thread in your CPU, change the code to your own requirements! This is done so that you could download about 40K images in 30 mins! (That's too fast!!!)

If you want to re-fetch tiles, remember to delete/move tiles after every fetch request done! Else you won't get the updated information (tiles) of satellite data after that tile. It is calculated automatically so that all the progress remains saved!

TODOs

Check TODO

Additional Note

This also uses multithreading, which may overload your computer, so set the parameters in the API, minimise the pool else your PC may hang! This is created for educational and research purposes only! The authors are not liable for any damage to private property.

Contribution

Please see Contributing.md

LICENSE

 GNU GENERAL PUBLIC LICENSE
                       Version 3, 29 June 2007

 Copyright (C) 2019-20 Jimut Bahan Pal, <https://jimut123.github.io/>
 Everyone is permitted to copy and distribute verbatim copies
 of this license document, but changing it is not allowed.

BibTeX and citations

@misc{jimutmap_2019,
  author = {Jimut Bahan Pal},
  title = {jimutmap},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/Jimut123/jimutmap}},
}

Project details


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Files for jimutmap, version 1.3.9
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Filename, size jimutmap-1.3.9-py3-none-any.whl (20.8 kB) File type Wheel Python version py3 Upload date Hashes View

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