Pass the polygon data to self._viewer.add_shapes() in a more efficient way

[LucaMarconato]

Right now we have the polygons data inside a geodataframe object, and we convert this to a list of list of floats to pass it to self._viewer.add_shapes() with this code

coordinates = polygons.geometry.apply(lambda x: np.array(x.exterior.coords).tolist()).tolist()

which takes 4 seconds for 160K polygons.

We have to check:

• if there is a better way to access this information within the GeoDataFrame object (maybe some buffer). I don't think this is possible
• if there is a better way to pass this data to napari, maybe the ragged array representation.
• if we can parallelize the conversion of this data.

[melonora]

Would you think of using async?

[LucaMarconato]

Yes, this could be an option. But in general even remaining single-threaded I think that there must be a more performant way to pass the data to napari without having to change data type and create a lot of new list objects.