Datasets:

---

hourouu

/

Unet_Poumons_3D

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
patient: string
n_noeuds: int64
n_tetraedres: int64
v_surfacique_mL: double
v_tetraedrique_mL: double
erreur_relative_pct: double
valide_shen2019: bool
vol_tet_min_mm3: double
vol_tet_max_mm3: double
vol_tet_mean_mm3: double
temps_tetrahedrisation_s: double
fichier_vtk: string
fichier_mesh_gmsh: string
reference_algorithme: string
reference_validation: string
reference_vtk: string
reference_gmsh: string
qem_faces_avant: int64
temps_qem_s: double
qem_faces_apres: int64
compression_glb_pct: double
temps_pipeline_total_s: double
n_vertices_apres_qem: int64
taille_glb_apres_MB: double
HD95_mm: double
temps_mc_clean_s: double
volume_mL_avant_qem: double
qem_reduction_pct: double
temps_inference_unet_s: double
temps_taubin_s: double
surface_cm2_avant_qem: double
qem_temps_s: double
volume_mL_apres_qem: double
surface_cm2_apres_qem: double
n_faces_apres_qem: int64
n_faces_avant_qem: int64
HD100_mm: double
taille_glb_avant_MB: double
temps_mc_brut_s: double
preservation_volume_pct: double
n_vertices_avant_qem: int64
watertight_avant_qem: bool
MSD_mm: double
watertight_apres_qem: bool
to
{'n_vertices_avant_qem': Value('int64'), 'n_faces_avant_qem': Value('int64'), 'watertight_avant_qem': Value('bool'), 'volume_mL_avant_qem': Value('float64'), 'surface_cm2_avant_qem': Value('float64'), 'n_vertices_apres_qem': Value('int64'), 'n_faces_apres_qem': Value('int64'), 'watertight_apres_qem': Value('bool'), 'volume_mL_apres_qem': Value('float64'), 'surface_cm2_apres_qem': Value('float64'), 'preservation_volume_pct': Value('float64'), 'qem_faces_avant': Value('int64'), 'qem_faces_apres': Value('int64'), 'qem_reduction_pct': Value('float64'), 'qem_temps_s': Value('float64'), 'HD95_mm': Value('float64'), 'MSD_mm': Value('float64'), 'HD100_mm': Value('float64'), 'taille_glb_avant_MB': Value('float64'), 'taille_glb_apres_MB': Value('float64'), 'compression_glb_pct': Value('float64'), 'temps_inference_unet_s': Value('float64'), 'temps_mc_brut_s': Value('float64'), 'temps_mc_clean_s': Value('float64'), 'temps_taubin_s': Value('float64'), 'temps_qem_s': Value('float64'), 'temps_pipeline_total_s': Value('float64'), 'patient': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              patient: string
              n_noeuds: int64
              n_tetraedres: int64
              v_surfacique_mL: double
              v_tetraedrique_mL: double
              erreur_relative_pct: double
              valide_shen2019: bool
              vol_tet_min_mm3: double
              vol_tet_max_mm3: double
              vol_tet_mean_mm3: double
              temps_tetrahedrisation_s: double
              fichier_vtk: string
              fichier_mesh_gmsh: string
              reference_algorithme: string
              reference_validation: string
              reference_vtk: string
              reference_gmsh: string
              qem_faces_avant: int64
              temps_qem_s: double
              qem_faces_apres: int64
              compression_glb_pct: double
              temps_pipeline_total_s: double
              n_vertices_apres_qem: int64
              taille_glb_apres_MB: double
              HD95_mm: double
              temps_mc_clean_s: double
              volume_mL_avant_qem: double
              qem_reduction_pct: double
              temps_inference_unet_s: double
              temps_taubin_s: double
              surface_cm2_avant_qem: double
              qem_temps_s: double
              volume_mL_apres_qem: double
              surface_cm2_apres_qem: double
              n_faces_apres_qem: int64
              n_faces_avant_qem: int64
              HD100_mm: double
              taille_glb_avant_MB: double
              temps_mc_brut_s: double
              preservation_volume_pct: double
              n_vertices_avant_qem: int64
              watertight_avant_qem: bool
              MSD_mm: double
              watertight_apres_qem: bool
              to
              {'n_vertices_avant_qem': Value('int64'), 'n_faces_avant_qem': Value('int64'), 'watertight_avant_qem': Value('bool'), 'volume_mL_avant_qem': Value('float64'), 'surface_cm2_avant_qem': Value('float64'), 'n_vertices_apres_qem': Value('int64'), 'n_faces_apres_qem': Value('int64'), 'watertight_apres_qem': Value('bool'), 'volume_mL_apres_qem': Value('float64'), 'surface_cm2_apres_qem': Value('float64'), 'preservation_volume_pct': Value('float64'), 'qem_faces_avant': Value('int64'), 'qem_faces_apres': Value('int64'), 'qem_reduction_pct': Value('float64'), 'qem_temps_s': Value('float64'), 'HD95_mm': Value('float64'), 'MSD_mm': Value('float64'), 'HD100_mm': Value('float64'), 'taille_glb_avant_MB': Value('float64'), 'taille_glb_apres_MB': Value('float64'), 'compression_glb_pct': Value('float64'), 'temps_inference_unet_s': Value('float64'), 'temps_mc_brut_s': Value('float64'), 'temps_mc_clean_s': Value('float64'), 'temps_taubin_s': Value('float64'), 'temps_qem_s': Value('float64'), 'temps_pipeline_total_s': Value('float64'), 'patient': Value('string')}
              because column names don't match