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)[source]¶
References
https://spacenet.ai/sn7-challenge/
- Requires:
awscli
- kwcoco.data.grab_spacenet.convert_spacenet_to_kwcoco(extract_dpath, coco_fpath)[source]¶
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”