I’m happy to release RoboSat v1.2.0 — RoboSat is an open source end-to-end pipeline for feature extraction from aerial and satellite imagery seamlessly integrating with OpenStreetMap for automated dataset creation.

This release is powered by major community contributions: state of the art Lovasz pixel-wise segmentation loss, better metrics, a road extraction dataset creation handler, and bug fixes! Thank you to our contributors!

v1.2.0 is also the first release shifting from a Mapbox sponsored development process to a community owned development process (after I quit Mapbox end of last year). New features, bug fixes, training and prediction all happens on my personal GPU rig now.

6 x GTX 1080 TI. Yes, the LEDs are necessary - they make it go fast

Here is an overview of what you will find in the v1.2.0 release

• rs train: state of the art losses and metrics. Lovasz loss as default, many many more small features and fixes in training and related tools. Thanks https://github.com/ocourtin

• rs extract: fully automatated road training dataset creation Thanks https://github.com/DragonEmperorG

• rs extract: batch feature extraction for datasets too big for memory Thanks http://github.com/daniel-j-h

• rs rasterize: batch rasterization for datasets too big for memory Thanks http://github.com/daniel-j-h

• Infrastructure: improved docker images, pre-trained weights in images, upgrades to CUDA 10.1, cudnn 7, and pytorch 1.1. Thanks http://github.com/daniel-j-h

The pre-built docker images are now the recommended way of using robosat:

• https://github.com/mapbox/robosat#installation

• https://hub.docker.com/r/mapbox/robosat/

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Here is an example for a model trained on an automatically generated road dataset

Here is an example for the new Lovasz loss after the first few epochs already; 80cm / z17 aerial imagery for Bavaria, Germany

And an example of where we fall short. For the following location OpenStreetMap contains buildings robosat did not detect in the aerial imagery because they are construction sites. Should robosat flag construction sites as buildings, too? Should OpenStreetMap not map construction sites as buildings? Or is the imagery outdated? These questions are defining our boundaries of what we can detect.

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Here is a preview of what I am currently playing around with for potential future releaes

• Squeeze and Excitation modules (scSE) for improvements in segmentation at (almost) no cost https://github.com/mapbox/robosat/pull/161

• Topology-aware loss function which not only takes pixel-wise loss into account but e.g. how roads are connected (think: trees occluding roads for a couple of meters; topology loss will help continue the roads in these cases) https://github.com/mapbox/robosat/pull/135

• Feature Pyramid Attention (FPA) for context aware segmentation https://github.com/mapbox/robosat/pull/168

• Feature Pyramid Network (FPN) to potentially replace our existing encoder-decoder architecture https://github.com/mapbox/robosat/pull/75

These features all need to be benchmarked wrt. segmentation improvements, but also model complexity, training and prediction runtime, and similar trade-offs. Stay tuned!

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As usual hit me up for feedback be it at OSM hack weekends, on tickets, IRC, or the OSMUS Slack. Also check out previous diary posts about robosat:

• https://www.openstreetmap.org/user/daniel-j-h/diary/44145

• https://www.openstreetmap.org/user/daniel-j-h/diary/44321

• https://www.openstreetmap.org/user/daniel-j-h/diary/45042