Fixing changed loading script

CTSpine1K.py

@@ -1,7 +1,6 @@
 """Wrapper to load the actual data using Python."""
 
 from collections.abc import Generator
-from functools import lru_cache
 from pathlib import Path
 from typing import ClassVar
 
@@ -98,23 +97,6 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
         ),
     ]
 
-    @property
-    def volumetric(self) -> bool:
-        """Mode indicating whether we use 3D or 2D data."""
-        return self.config.volumetric
-
-    def __len__(self) -> int:
-        """Length attribute of the class.
-
-        Returns:
-            Return the amount of samples based on mode.
-
-        """
-        if self.config.volumetric:
-            return len(self._lookup)
-
-        return sum(elem[2] for elem in self._lookup.values())
-
     def _info(self) -> datasets.DatasetInfo:
         if self.config.volumetric:
             features = datasets.Features(
@@ -128,6 +110,7 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
                         dtype="int32",
                     ),
                     "patient_id": datasets.Value("string"),
+                    "index": datasets.Value("int32"),
                 },
             )
         else:
@@ -136,6 +119,8 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
                     "image": datasets.Array2D(shape=(512, 512), dtype="float32"),
                     "segmentation": datasets.Array2D(shape=(512, 512), dtype="int32"),
                     "patient_id": datasets.Value("string"),
+                    "index": datasets.Value("int32"),
+                    "slice_index": datasets.Value("int32"),
                 },
             )
 
@@ -263,10 +248,6 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
 
         return lookup
 
-    @lru_cache(maxsize=1)  # since it does not change  # noqa: B019
-    def _sorted_lookup(self) -> list[Path]:
-        return sorted(self._lookup.keys())
-
     @staticmethod
     def _get_sample_length(file_path: Path) -> int:
         expected_ndim = 3
@@ -283,21 +264,30 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
         return np.transpose(volume, (2, 0, 1))
 
     def _generate_examples(self, pairs: list[tuple[Path, Path]]) -> Generator:
-        for volume_path, label_path in pairs:
+        for pair_idx, (volume_path, label_path) in enumerate(pairs):
             patient_id = Path(volume_path.stem).stem
             image = self._volumetric_sample(volume_path)
             segmentation = self._volumetric_sample(label_path).astype(np.uint32)
 
             if self.config.volumetric:
-                yield {
-                    "image": image,
-                    "segmentation": segmentation,
-                    "patient_id": patient_id,
-                }
+                yield (
+                    patient_id,
+                    {
+                        "image": image,
+                        "segmentation": segmentation,
+                        "patient_id": patient_id,
+                        "index": pair_idx,
+                    },
+                )
             else:
                 for idx in range(image.shape[2]):  # iterate over axial slices
-                    yield {
-                        "image": image[idx],
-                        "segmentation": segmentation[idx],
-                        "patient_id": patient_id + f"_{idx}",
-                    }
+                    yield (
+                        patient_id + f"_{idx}",
+                        {
+                            "image": image[idx],
+                            "segmentation": segmentation[idx],
+                            "patient_id": patient_id,
+                            "index": pair_idx,
+                            "slice_index": idx,
+                        },
+                    )