Adding debug to loading script

CTSpine1K.py

@@ -157,20 +157,20 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
 
         training, validation, test = self._load_split(downloaded_files[split_file_idx])
 
-        self._validate_check(downloaded_files)
+        lookup = self._validate_check(downloaded_files)
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={"stems": training},
+                gen_kwargs={"pairs": [lookup[stem] for stem in training]},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
-                gen_kwargs={"stems": validation},
+                gen_kwargs={"pairs": [lookup[stem] for stem in validation]},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
-                gen_kwargs={"stems": test},
+                gen_kwargs={"pairs": [lookup[stem] for stem in test]},
             ),
         ]
 
@@ -201,21 +201,15 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
         return training, validation, test
 
     def _validate_check(self, files: list[str]) -> dict:
-        stems = [file.split(".nii.gz")[0] for file in files]
+        ffiles = sorted(file for file in files if "nii.gz" in file)
 
-        print("stems ", stems)
-        print("files ", files)
-
-        data_candidates = [
-            file
-            for file in sorted(cache_dir.rglob("rawdata/volumes/*/*"))
-            if "nii.gz" in file.as_uri().lower()
-        ]
-        label_candidates = [
-            file
-            for file in sorted(cache_dir.rglob("rawdata/labels/*/*"))
-            if "nii.gz" in file.as_uri().lower()
-        ]
+        data_candidates = []
+        label_candidates = []
+        for file in ffiles:
+            if "labels" in file:
+                label_candidates.append(file)
+            else:
+                data_candidates.append(file)
 
         if len(data_candidates) != len(label_candidates):
             msg = (
@@ -224,29 +218,14 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
             )
             raise RuntimeError(msg)
 
-        pairs = zip(data_candidates, label_candidates, strict=True)
-        pairs_lookup = {pair[0].name.split(".")[0]: pair for pair in pairs}
-
-        print("pairs", pairs_lookup)
-        print("stems", stems)
-        samples = {}
-
-        for stem in stems:
-            file_path, segmentation_path = pairs_lookup[stem]
-
-            if stem not in segmentation_path.name:
-                msg = (
-                    "Naming convention seems invalid or violated. ",
-                    "Ensure all data was downloaded successfully.",
-                )
-                raise RuntimeError(msg)
-
-            if not ((file_path).is_file() and (segmentation_path).is_file()):
-                msg = (
-                    "Data is not a file. Ensure all data was downloaded successfully."
-                    f"Failed for {file_path} and {segmentation_path}."
-                )
-                raise RuntimeError(msg)
+        pairs: list[tuple[str, str]] = zip(
+            data_candidates,
+            label_candidates,
+            strict=True,
+        )
+        lookup = {}
+        for input_, label in pairs:
+            file_path, segmentation_path = Path(input_), Path(label)
 
             image_slices = self._get_sample_length(file_path)
             segmentation_slices = self._get_sample_length(segmentation_path)
@@ -258,9 +237,15 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
                 )
                 raise ValueError(msg)
 
-            samples[stem] = (file_path, segmentation_path, image_slices)
+            # convert 'some/path/to/file/dummy_123.nii.gz' to dummy_123.nii.gz
+            stem = file_path.name
+            if stem.removesuffix("nii.gz") not in segmentation_path:
+                msg = f"Mismatch in sorted pairs. {input_} vs. {label}"
+                raise ValueError(msg)
+
+            lookup[stem] = (file_path, segmentation_path)
 
-        return samples
+        return lookup
 
     @lru_cache(maxsize=1)  # since it does not change  # noqa: B019
     def _sorted_lookup(self) -> list[Path]:
@@ -296,8 +281,8 @@ class CTSpine1K(datasets.GeneratorBasedBuilder):
 
         return volume.get_fdata()
 
-    def _generate_examples(self, stems: list[str]) -> Generator:
-        print("stems: ", stems)
+    def _generate_examples(self, pairs: list[tuple[Path, Path]]) -> Generator:
+        print("pairs: ", pairs)
         for idx in range(len(self)):
             image, segmentation, patient_id = self[idx]
             yield {