You know I worked a lot with pathfinding. In academia, the MovingAI benchmark created by the MovingAI Lab of the University of Denver is a must for benchmarking pathfinding algorithms. It includes synthetic maps and maps from commercial videogames.

Parsing the benchmark data, the maps, creating the map data structure and more, is one of the most boring thing I needed to do for testing my algorithms. For this reason, I think a common library for working with the maps specifications it is a must.

The MovingAI Benchmark Database is one of the most famous collections of maps for benchmark on pathfinding algorithms. I use it a lot during my work, it is useful to test an algorithm over a lot of real-world game maps. The consequence is that I developed a lot of tools to work with the map format of the MovingAI database.

The last of these tools is a straightforward Python script to convert images into maps in the MovingAI format. It is useful when you want to quickly develop some test maps.