Add pixi configuration

[LucaMarconato]

Solution for #2.

This PR adds a pixi configuration tested on macOS (Apple Silicon).
Trying out the PR on macOS should be as simple as running pixi run demo-local. Same for other operating systems, but first one need to add the new platform in pyproject.toml.

To visualize the data with neuroglancer I installed http-server and ran

 http-server test_meshes_output --cors --port 8080

then I used this script

##
import neuroglancer

ip = "localhost"  # or public IP of the machine for sharable display
port = 9999  # change to an unused port number
neuroglancer.set_server_bind_address(bind_address=ip, bind_port=port)

viewer = neuroglancer.Viewer()
print(viewer)

##
# host locally, for instance using http-server https://github.com/http-party/http-server
# http-server test_meshes_output -p 8080 --cors
demo_data = "precomputed://http://127.0.0.1:8080/multires"

with viewer.txn() as s:
    s.layers["meshes"] = neuroglancer.SegmentationLayer(source=demo_data)
    s.layers["meshes"].segments = [1, 2]

[davidackerman]

thanks so much! ill take a look in the near future. also take a look at igneous. igneous seems great, but many of my other repositories rely on dask, so i have been incorporating code from igneous into a new repository (with some other methods i find useful). I hope to include multires in there as well so ultimately one can go straight from segmentations to multires meshes. i will try to update once completed.