'save_cog_with_dask' fails with numpy > 2

Hello,

With numpy <2, save_cog_with_dask fails because illegal casting.

With numpy < 2, everything works fine.
With numpy 2.0.1, I have the following error: OverflowError: Python integer 999999 out of bounds for uint8
With numpy 2.1.0, this one: TypeError: Cannot cast scalar from dtype('int64') to dtype('uint8') according to the rule 'same_kind'

This issue is based on this discussion: https://discourse.pangeo.io/t/save-cog-with-dask-cannot-convert-fill-value-999999-to-dtype-uint8/4713/9

As @maxrjones said there:

This is most likely coming from NumPy’s defaults for masked arrays - numpy.ma.default_fill_value — NumPy v2.1 Manual.

Minimal working example:

import numpy as np
import rioxarray as rxr
from odc.geo import cog, xr  # noqa
xds = rxr.open_rasterio(r"not_cog.tif", chunks=True)
nodata = 0
cog.save_cog_with_dask(
    xds.copy(data=xds.fillna(nodata).astype(np.uint8)).rio.set_nodata(
        nodata
    ),
    r"cog.tif",
).compute()

Data : not_cog.zip

I'm on Windows, maybe this doesn't help...

opendatacube / odc-geo

'save_cog_with_dask' fails with numpy > 2 #189