kwcoco.data.grab_spacenet module

References

https://medium.com/the-downlinq/the-spacenet-7-multi-temporal-urban-development-challenge-algorithmic-baseline-4515ec9bd9fe https://arxiv.org/pdf/2102.11958.pdf https://spacenet.ai/sn7-challenge/

kwcoco.data.grab_spacenet.grab_spacenet7(data_dpath)

References

https://spacenet.ai/sn7-challenge/

Requires:

awscli

kwcoco.data.grab_spacenet.convert_spacenet_to_kwcoco(extract_dpath, coco_fpath)

Converts the raw SpaceNet7 dataset to kwcoco

Note

• The “train” directory contains 60 “videos” representing a region over time.

• Each “video” directory contains :

  • images - unmasked images

  • images_masked - images with masks applied

  • labels - geojson polys in wgs84?

  • labels_match - geojson polys in wgs84 with track ids?

  • labels_match_pix - geojson polys in pixels with track ids?

  • UDM_masks - unusable data masks (binary data corresponding with an image, may not exist)

File names appear like:

“global_monthly_2018_01_mosaic_L15-1538E-1163N_6154_3539_13”

kwcoco.data.grab_spacenet.main()