You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The orange dot is the polygon centroid. The teal dot is the ideal label position. Red boxes show the search space.
You can generate this visualisation yourself by cloning this repo, switching to the visualise branch, and opening the visualise.ipynb Jupyter notebook, then stepping through the cells. You can also easily visualise a Polygon of your own using the notebook.
A command-line tool is available: cargo install polylabel_cmd. This enables the polylabel command, which takes a GeoJSON file as input, as well as an optional (-t / --tolerance) tolerance value. See more at crates.io.
Using a 4-core 2.3 GHz Intel Core i5, finding a label position on a ~9k-vertex polygon (representing the Norwegian mainland) using a tolerance of 1.0 takes around 9 ms. Depending upon the dimensions of your polygon(s), you may require a higher tolerance (i.e. a smaller number). See here for some guidance on the accuracy provided by each decimal place.
CPU Optimizations
Build using the target-cpu=nativeRUSTFLAG for a ~10 % perf improvement