I’ve taken Lesson 3 CamVID image segmentation, and Planet’s image classification lesson, to create an image segmentation to detect building footprints from satellite images.
There is a lot of training data (tens of Gb of high-resolution images) from the Spacenet competition, but mostly I wanted to do one project on my own, so I took ~6k chips of images in Rio de Janeiro.
The hardest part was to convert the .geojson footprints into images (I used parallel rio rasterize), and then fiddle to avoid running out of memory. Overall I’m quite happy, here is the notebook, and the results:
left ground truth, right prediction.
