added resize parameter

SPIDER.py

@@ -36,10 +36,18 @@ def import_csv_data(filepath: str) -> List[Dict[str, str]]:
             results.append(line)
     return results
 
+def standardize_3D_image(image: np.ndarray) -> np.ndarray:
+    """TODO"""
+    if image.shape[0] < image.shape[2]:
+        image = np.transpose(image, axes=[1, 2, 0])
+    return image
+
 # Define constants
 N_PATIENTS = 218
 MIN_IVD = 0
 MAX_IVD = 9
+DEFAULT_SCAN_TYPES = ['t1', 't2', 't2_SPACE']
+DEFAULT_RESIZE = (512, 512, 30)
 
 # TODO: Add BibTeX citation
 # Find for instance the citation on arxiv or on the dataset repo/website
@@ -82,10 +90,12 @@ class CustomBuilderConfig(datasets.BuilderConfig):
         data_dir: Optional[str] = None,
         data_files: Optional[Union[str, Sequence, Mapping]] = None,
         description: Optional[str] = None,
-        scan_types: List[str] = ['t1', 't2', 't2_SPACE'],
+        scan_types: List[str] = DEFAULT_SCAN_TYPES,
+        resize_dims: Tuple[int, int, int] = DEFAULT_RESIZE,
     ):
         super().__init__(name, version, data_dir, data_files, description)
         self.scan_types = scan_types
+        self.resize_dims = resize_dims
 
 
 class SPIDER(datasets.GeneratorBasedBuilder):
@@ -95,34 +105,49 @@ class SPIDER(datasets.GeneratorBasedBuilder):
 
     BUILDER_CONFIG_CLASS = CustomBuilderConfig
 
-    BUILDER_CONFIGS = [
-        CustomBuilderConfig(
-            name="all_scan_types",
-            version=VERSION,
-            description="Use images of all scan types (t1, t2, t2 SPACE)",
-            scan_types=['t1', 't2', 't2_SPACE'],
-        ),
-        CustomBuilderConfig(
-            name="t1_scan_types",
-            version=VERSION,
-            description="Use images of t1 scan types only",
-            scan_types=['t1'],
-        ),
-        CustomBuilderConfig(
-            name="t2_scan_types",
-            version=VERSION,
-            description="Use images of t2 scan types only",
-            scan_types=['t2'],
-        ),
-        CustomBuilderConfig(
-            name="t2_SPACE_scan_types",
-            version=VERSION,
-            description="Use images of t2 SPACE scan types only",
-            scan_types=['t2_SPACE'],
-        ),
-    ]
-
-    DEFAULT_CONFIG_NAME = "all_scan_types"
+    # BUILDER_CONFIGS = [
+    #     CustomBuilderConfig(
+    #         name="all_scan_types",
+    #         version=VERSION,
+    #         description="Use images of all scan types (t1, t2, t2 SPACE)",
+    #         scan_types=['t1', 't2', 't2_SPACE'],
+    #         resize_dims=DEFAULT_RESIZE,
+    #     ),
+    #     CustomBuilderConfig(
+    #         name="t1_scan_types",
+    #         version=VERSION,
+    #         description="Use images of t1 scan types only",
+    #         scan_types=['t1'],
+    #         resize_dims=DEFAULT_RESIZE,
+    #     ),
+    #     CustomBuilderConfig(
+    #         name="t2_scan_types",
+    #         version=VERSION,
+    #         description="Use images of t2 scan types only",
+    #         scan_types=['t2'],
+    #         resize_dims=DEFAULT_RESIZE,
+    #     ),
+    #     CustomBuilderConfig(
+    #         name="t2_SPACE_scan_types",
+    #         version=VERSION,
+    #         description="Use images of t2 SPACE scan types only",
+    #         scan_types=['t2_SPACE'],
+    #         resize_dims=DEFAULT_RESIZE,
+    #     ),
+    # ]
+
+    # DEFAULT_CONFIG_NAME = "all_scan_types"
+
+    def __init__(
+        self,
+        *args,
+        scan_types: List[str] = DEFAULT_SCAN_TYPES,
+        resize_dims: Tuple[int, int, int] = DEFAULT_RESIZE,
+        **kwargs,
+    ):
+        super().__init__(*args, **kwargs)
+        self.scan_types = scan_types
+        self.resize_dims = resize_dims
 
     def _info(self):
         """
@@ -133,7 +158,7 @@ class SPIDER(datasets.GeneratorBasedBuilder):
             "patient_id": datasets.Value("string"),
             "scan_type": datasets.Value("string"),
             # "raw_image": datasets.Image(),
-            "numeric_array": datasets.Array3D(dtype='int16'),
+            "numeric_array": datasets.Array3D(shape=self.resize_dims, dtype='int16'),
             "metadata": {
                 "num_vertebrae": datasets.Value(dtype="string"),
                 "num_discs": datasets.Value(dtype="string"),
@@ -214,14 +239,14 @@ class SPIDER(datasets.GeneratorBasedBuilder):
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         paths_dict = dl_manager.download_and_extract(_URLS)
-        scan_types = self.config.scan_types
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
                     "paths_dict": paths_dict,
                     "split": "train",
-                    "scan_types": scan_types,
+                    "scan_types": self.scan_types,
+                    "resize_dims": self.resize_dims,
                 },
             ),
             datasets.SplitGenerator(
@@ -229,7 +254,8 @@ class SPIDER(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "paths_dict": paths_dict,
                     "split": "validate",
-                    "scan_types": scan_types,
+                    "scan_types": self.scan_types,
+                    "resize_dims": self.resize_dims,
                 },
             ),
             datasets.SplitGenerator(
@@ -237,7 +263,8 @@ class SPIDER(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "paths_dict": paths_dict,
                     "split": "test",
-                    "scan_types": scan_types,
+                    "scan_types": self.scan_types,
+                    "resize_dims": self.resize_dims,
                 },
             ),
         ]
@@ -245,8 +272,9 @@ class SPIDER(datasets.GeneratorBasedBuilder):
     def _generate_examples(
         self,
         paths_dict: Dict[str, str],
-        split: str = 'train',
-        scan_types: List[str] = ['t1', 't2', 't2_SPACE'],
+        split: str,
+        scan_types: List[str],
+        resize_dims: Tuple[int, int, int],
         validate_share: float = 0.3,
         test_share: float = 0.2,
         raw_image: bool = True,
@@ -385,7 +413,7 @@ class SPIDER(datasets.GeneratorBasedBuilder):
                 if col not in ['Patient']
             }
 
-        # Import image and mask data
+        # Get list of image and mask data files
         image_files = [
             file for file in os.listdir(os.path.join(paths_dict['images'], 'images'))
             if file.endswith('.mha')
@@ -398,7 +426,7 @@ class SPIDER(datasets.GeneratorBasedBuilder):
         ]
         assert len(mask_files) > 0, "No mask files found--check directory path."
         
-        # Filter image and mask data based on scan types
+        # Filter image and mask data files based on scan types
         image_files = [
             file for file in image_files 
             if any(scan_type in file for scan_type in scan_types)