Hello,
first of all thank you for this great contribution.
I am trying to run the eval.py with the pretrained model on our own data. I converted out las files to ply using cloudcompare and added scalar fields for semantic_seg and treeID (both set to 0) . It runs up to 100% and then exits with two errors.
forainet/.venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 87, in _wrapreduction
return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
numpy.AxisError: axis 1 is out of bounds for array of dimension 0
and
/forainet/.venv/lib/python3.9/site-packages/hydra/_internal/utils.py", line 237, in run_and_report
assert mdl is not None
AssertionError
Any ideas about this? It works with the ForINStance pointclouds. So it has to do with data structure I suppose
Thanks alot!!
Hello,
first of all thank you for this great contribution.
I am trying to run the eval.py with the pretrained model on our own data. I converted out las files to ply using cloudcompare and added scalar fields for semantic_seg and treeID (both set to 0) . It runs up to 100% and then exits with two errors.
forainet/.venv/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 87, in _wrapreduction
return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
numpy.AxisError: axis 1 is out of bounds for array of dimension 0
and
/forainet/.venv/lib/python3.9/site-packages/hydra/_internal/utils.py", line 237, in run_and_report
assert mdl is not None
AssertionError
Any ideas about this? It works with the ForINStance pointclouds. So it has to do with data structure I suppose
Thanks alot!!