Generates maps from satellite images.
The generated maps classify regions of the satellite image as Buildings, Roads, Water and Other.
Each region is color-coded a different shade of grey to differentiate them in the map.
data_collection/ Folder to extract data from Google Maps API. We can filter the map image generation by State in the getmapimages.py
model_generation/ Scripts used to generate training data and using training model. We used Weka to generate decforests2.model which is a Random Forest implementation. To generate prediction images, load map_data/ with satellite data of 800x800 satellite images(containing "satellite" in the filename), and then run python train_test.py. The map generation images from the model will be generated in the map_data/ folder. To change the model being used we have to use weka to generate a model and change the model location string in predict.java and recompile the class. Then re-run python train_test.py.
mapgen_results/ Results of test map generation runs from initial phase of model testing and evaluation. There are 3 runs displayed here.
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Automated Map Generation Project Paper
