spacenet-utils

Utilities for modeling and visualizing SpaceNet data.

SpaceNet data is available on aws.

spacenet-utils dependencies: numpy, pandas, osgeo, matplotlib, geomet, scikit-learn.

Example usage

Display geotiff image with building-polygon overlay.

# python3
import spacenet_utils as snu
import matplotlib.pyplot as plt

# path to csv of ground-truth polygon vertices
csv_path = 'AOI_5_Khartoum_Train/summaryData/AOI_5_Khartoum_Train_Building_Solutions.csv'
# path to geotiff image
im_path = 'AOI_5_Khartoum_Train/MUL-PanSharpen/MUL-PanSharpen_AOI_5_Khartoum_img5.tif'

fig, ax = plt.subplots()
snu.plot_image(ax,im_path,band=7)
snu.plot_gt(ax,im_path,csv_path)
plt.show()

Example usage

Label buildings using kNN on the pixel spectra.

$ python example_knn.py

performance = 0.799041
confusion matrix = 
array([[288411,  13766],
       [ 71139,  49184]])
fscore = 0.536729360026

Note

example_knn.py has only been tested on MUL-PanSharpened images from the Khartoum region.

To use on a different region or image type, be sure to set the following kwargs in spacenet_utils.py: poly_verts2mask.w, postprocess.w, get_poly_arr.im_id_prefix, plot_gt.im_id_prefix.

See these functions' docstrings for further documentation.