Fixing changed loading script

CTSpine1K.py

@@ -120,11 +120,11 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
             features = datasets.Features(
                 {
                     "image": datasets.Array3D(
-                        shape=(None, None, None),
+                        shape=(None, 512, 512),
                         dtype="float32",
                     ),
                     "segmentation": datasets.Array3D(
-                        shape=(None, None, None),
+                        shape=(None, 512, 512),
                         dtype="int32",
                     ),
                     "patient_id": datasets.Value("string"),
@@ -133,8 +133,8 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
         else:
             features = datasets.Features(
                 {
-                    "image": datasets.Array2D(shape=(None, None), dtype="float32"),
-                    "segmentation": datasets.Array2D(shape=(None, None), dtype="int32"),
+                    "image": datasets.Array2D(shape=(512, 512), dtype="float32"),
+                    "segmentation": datasets.Array2D(shape=(512, 512), dtype="int32"),
                     "patient_id": datasets.Value("string"),
                 },
             )
@@ -279,14 +279,14 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
     @staticmethod
     def _volumetric_sample(path: Path) -> np.ndarray:
         volume = nib.load(path)
-
-        return volume.get_fdata()
+        volume = volume.get_fdata()
+        return np.transpose(volume, (2, 0, 1))
 
     def _generate_examples(self, pairs: list[tuple[Path, Path]]) -> Generator:
         for volume_path, label_path in pairs:
             patient_id = Path(volume_path.stem).stem
             image = self._volumetric_sample(volume_path)
-            segmentation = self._volumetric_sample(label_path)
+            segmentation = self._volumetric_sample(label_path).astype(np.uint32)
 
             if self.config.volumetric:
                 yield {
@@ -297,7 +297,7 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
             else:
                 for idx in range(image.shape[2]):  # iterate over axial slices
                     yield {
-                        "image": image[:, :, idx],
-                        "segmentation": segmentation[:, :, idx],
+                        "image": image[idx],
+                        "segmentation": segmentation[idx],
                         "patient_id": patient_id + f"_{idx}",
                     }