Why to convert to image points?

[nithinme3]

Hi,

Thanks for the example.

I was wondering if we can do hausdorff distance calculation on lat long values (or at least on corresponding utm values) directly instead on image points.
My plan was to do the clustering in lat-long/utm coordinates and plot using folium.

Infact I tried hausdorff distance calculation on both utm and lat long but am getting following error,

(rapids) [root@nithin-rapids cuspatial]# python ./python/cuspatial/demos/hausdorff_clustering_test_toy.py
Traceback (most recent call last):
File "/share/adas_coe_159/nithin/cuspatial/./python/cuspatial/demos/hausdorff_clustering_test_toy.py", line 39, in
distance = cuspatial.directed_hausdorff_distance(pnt_x, pnt_y, cnt)
File "/opt/conda/envs/rapids/lib/python3.10/site-packages/cuspatial/core/spatial/distance.py", line 97, in directed_hausdorff_distance
return DataFrame(result)
File "/opt/conda/envs/rapids/lib/python3.10/contextlib.py", line 79, in inner
return func(*args, **kwds)
File "/opt/conda/envs/rapids/lib/python3.10/site-packages/cudf/core/dataframe.py", line 679, in init
new_df = self._from_arrays(data, index=index, columns=columns)
File "/opt/conda/envs/rapids/lib/python3.10/contextlib.py", line 79, in inner
return func(*args, **kwds)
File "/opt/conda/envs/rapids/lib/python3.10/site-packages/cudf/core/dataframe.py", line 5404, in _from_arrays
df._data[k] = column.as_column(
File "/opt/conda/envs/rapids/lib/python3.10/site-packages/cudf/core/column/column.py", line 1887, in as_column
arbitrary = cupy.ascontiguousarray(arbitrary)
File "/opt/conda/envs/rapids/lib/python3.10/site-packages/cupy/_creation/from_data.py", line 107, in ascontiguousarray
return _core.ascontiguousarray(a, dtype)
File "cupy/_core/core.pyx", line 2673, in cupy._core.core.ascontiguousarray
File "cupy/_core/core.pyx", line 2689, in cupy._core.core.ascontiguousarray
File "cupy/_core/core.pyx", line 136, in cupy._core.core.ndarray.new
File "cupy/_core/core.pyx", line 224, in cupy._core.core._ndarray_base._init
File "cupy/cuda/memory.pyx", line 742, in cupy.cuda.memory.alloc
File "/opt/conda/envs/rapids/lib/python3.10/site-packages/rmm/rmm.py", line 230, in rmm_cupy_allocator
buf = librmm.device_buffer.DeviceBuffer(size=nbytes, stream=stream)
File "device_buffer.pyx", line 85, in rmm._lib.device_buffer.DeviceBuffer.cinit
MemoryError: std::bad_alloc: CUDA error at: /opt/conda/envs/rapids/include/rmm/mr/device/cuda_memory_resource.hpp
(rapids) [root@nithin-rapids cuspatial]# python ./python/cuspatial/demos/hausdorff_clustering_test_toy.py

What could be the issue?