developmentseed/skynet-data

README.md A pipeline to simplify building a set of training data for aerial-imagery- and OpenStreetMap- based machine learning. The idea is to use OSM QA Tiles to generate “ground truth” images where each color represents some category derived from OSM features. Being map tiles, it’s then pretty easy to match these up with the desired input imagery. Install Install tippecanoe Clone this repo and npm install Use The make commands below work off the following variables (with defaults as listed): # location of image files IMAGE_TILES ?= “tilejson+https://a.tiles.mapbox.com/v4/mapbox.satellite.json?access_token=$(MapboxAccessToken)” # which osm-qa tiles extract to download; e.g. united_states_of_america QA_TILES=planet # number of images (tiles) to sample TRAIN_SIZE=1000 # define label classes output CLASSES=classes/water-roads-buildings.json Sample available tiles make data/sample.txt This just does a simple random sample of the available tiles in the…


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