Describe the annoyance
It'd be nice if boolean tensors could be logged (and show up as black and white masks in Rerun).
To Reproduce
import numpy as np
import rerun as rr
import rerun.experimental as rr2
rr.init("mask", spawn=True)
mask = np.random.rand(100, 100) > 0.5
rr2.log("mask", rr2.Tensor(mask))
gives
AssertionError: Failed to find <class 'numpy.bool_'> in f{<class 'numpy.uint8'>: 'U8', <class 'numpy.uint16'>: 'U16', <class 'numpy.uint32'>: 'U32', <class 'numpy.uint64'>: 'U64', <class 'numpy.int8'>: 'I8', <class 'numpy.int16'>: 'I16', <class 'numpy.int32'>: 'I32', <class 'numpy.int64'>: 'I64', <class 'numpy.float16'>: 'F16', <class 'numpy.float32'>: 'F32', <class 'numpy.float64'>: 'F64'}
Expected behavior
Show a black and white mask in the Rerun viewer.
Desktop (please complete the following information):
Rerun version
rerun_py 0.9.0-alpha.4 [rustc 1.72.0 (5680fa18f 2023-08-23), LLVM 16.0.5] x86_64-unknown-linux-gnu 7db7b54, built 2023-09-12T08:50:21Z
Describe the annoyance
It'd be nice if boolean tensors could be logged (and show up as black and white masks in Rerun).
To Reproduce
gives
Expected behavior
Show a black and white mask in the Rerun viewer.
Desktop (please complete the following information):
Rerun version