OpenStreetMap

RoboSat v1.1.0 — fine-tuning models, training and prediction improvements

Posted by daniel-j-h on 27 September 2018 in English (English)

I'm happy to announce the RoboSat v1.1.0 release — our open source end-to-end pipeline for feature extraction from aerial and satellite imagery.

This release is powered by major community contributions from features like fine-tuning trained models, to training and prediction speedups, and bug fixes! Thank you to our contributors!

Here is an overview of what you will find in the v1.1.0 release

You can find automatically built Docker images at https://hub.docker.com/r/mapbox/robosat/


For our next release we already have a couple amazing community contributions

Here's why you should be excited for the Lovasz loss: the following shows a preview

Left to right: image / label / cross entropy / miou / lovasz

In contrast to the current default cross entropy loss the Lovasz loss will be an amazing default for robosat's binary models and greatly improve common feature extraction use-cases!

Again, thanks for these amazing community contributions!


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

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