Datasets:

---

Sabbir12345

/

Pabna-Urban-Tree-Phase9-S2Val

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
s2_scene_date: timestamp[s]
s2_cloud_pct: double
sd_scene_date: timestamp[s]
sd_cloud_pct: double
ndvi_threshold: double
ndre_threshold: double
n_inside_samples: int64
n_outside_samples: int64
acc_ndvi_only: double
acc_ndvi_ndre: double
f1_tree_ndvi: double
f1_tree_both: double
precision_tree: double
recall_tree: double
s2_ndvi_mean_inside: double
s2_ndvi_mean_outside: double
ndvi_bias_s2_vs_sd: double
s2_tree_area_ha: double
sd_tree_area_ha: double
area_diff_ha: double
s2_canopy_pct: double
total_aoi_ha: double
canopy_cover_pct: double
scene_id: string
cloud_cover_pct: double
n_bands: int64
tree_area_ha: double
scene_date: timestamp[s]
to
{'scene_id': Value('string'), 'scene_date': Value('timestamp[s]'), 'cloud_cover_pct': Value('float64'), 'n_bands': Value('int64'), 'ndvi_threshold': Value('float64'), 'ndre_threshold': Value('float64'), 'tree_area_ha': Value('float64'), 'canopy_cover_pct': Value('float64')}
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
              s2_scene_date: timestamp[s]
              s2_cloud_pct: double
              sd_scene_date: timestamp[s]
              sd_cloud_pct: double
              ndvi_threshold: double
              ndre_threshold: double
              n_inside_samples: int64
              n_outside_samples: int64
              acc_ndvi_only: double
              acc_ndvi_ndre: double
              f1_tree_ndvi: double
              f1_tree_both: double
              precision_tree: double
              recall_tree: double
              s2_ndvi_mean_inside: double
              s2_ndvi_mean_outside: double
              ndvi_bias_s2_vs_sd: double
              s2_tree_area_ha: double
              sd_tree_area_ha: double
              area_diff_ha: double
              s2_canopy_pct: double
              total_aoi_ha: double
              canopy_cover_pct: double
              scene_id: string
              cloud_cover_pct: double
              n_bands: int64
              tree_area_ha: double
              scene_date: timestamp[s]
              to
              {'scene_id': Value('string'), 'scene_date': Value('timestamp[s]'), 'cloud_cover_pct': Value('float64'), 'n_bands': Value('int64'), 'ndvi_threshold': Value('float64'), 'ndre_threshold': Value('float64'), 'tree_area_ha': Value('float64'), 'canopy_cover_pct': Value('float64')}
              because column names don't match