Update prostate158.py

prostate158.py

@@ -17,16 +17,16 @@ class Prostate158Dataset(datasets.GeneratorBasedBuilder):
             version=VERSION,
             description="Return all the dataset in a 2d image format",
         ),
-        datasets.BuilderConfig(
-            name="2d_array",
-            version=VERSION,
-            description="Return all the dataset in a 2d array format",
-        ),
-        datasets.BuilderConfig(
-            name="3d_array",
-            version=VERSION,
-            description="Return all the dataset in a 2d array format",
-        ),
+        # datasets.BuilderConfig(
+        #     name="2d_array",
+        #     version=VERSION,
+        #     description="Return all the dataset in a 2d array format",
+        # ),
+        # datasets.BuilderConfig(
+        #     name="3d_array",
+        #     version=VERSION,
+        #     description="Return all the dataset in a 2d array format",
+        # ),
         datasets.BuilderConfig(
             name="3d_path",
             version=VERSION,
@@ -48,16 +48,16 @@ class Prostate158Dataset(datasets.GeneratorBasedBuilder):
                     "adc_tumor_reader1": datasets.Image(),
                 }
             )
-        elif self.config.name == "2d_array":
-            features = datasets.Features(
-                {
-                    "t2": datasets.Array2D(shape=(200,200), dtype="int"),
-                    "adc": datasets.Array2D(shape=(200,200), dtype="int"),
-                    "dwi": datasets.Array2D(shape=(200,200), dtype="int"),
-                    "t2_anatomy_reader1": datasets.Array2D(shape=(200,200), dtype="int"),
-                    "adc_tumor_reader1": datasets.Array2D(shape=(200,200), dtype="int"),
-                }
-            )
+        # elif self.config.name == "2d_array":
+        #     features = datasets.Features(
+        #         {
+        #             "t2": datasets.Array2D(shape=(200,200), dtype="int"),
+        #             "adc": datasets.Array2D(shape=(200,200), dtype="int"),
+        #             "dwi": datasets.Array2D(shape=(200,200), dtype="int"),
+        #             "t2_anatomy_reader1": datasets.Array2D(shape=(200,200), dtype="int"),
+        #             "adc_tumor_reader1": datasets.Array2D(shape=(200,200), dtype="int"),
+        #         }
+        #     )
             
         elif self.config.name == "3d_path":
             features = datasets.Features(
@@ -70,16 +70,16 @@ class Prostate158Dataset(datasets.GeneratorBasedBuilder):
                 }
             )
 
-        elif self.config.name == "3d_array":
-            features = datasets.Features(
-                {
-                    "t2": datasets.Array3D(shape=(200,200,20), dtype="int"),
-                    "adc": datasets.Array3D(shape=(200,200,20), dtype="int"),
-                    "dwi": datasets.Array3D(shape=(200,200,20), dtype="int"),
-                    "t2_anatomy_reader1": datasets.Array3D(shape=(200,200,20), dtype="int"),
-                    "adc_tumor_reader1": datasets.Array3D(shape=(200,200,20), dtype="int"),
-                }
-            )
+        # elif self.config.name == "3d_array":
+        #     features = datasets.Features(
+        #         {
+        #             "t2": datasets.Array3D(shape=(200,200,20), dtype="int"),
+        #             "adc": datasets.Array3D(shape=(200,200,20), dtype="int"),
+        #             "dwi": datasets.Array3D(shape=(200,200,20), dtype="int"),
+        #             "t2_anatomy_reader1": datasets.Array3D(shape=(200,200,20), dtype="int"),
+        #             "adc_tumor_reader1": datasets.Array3D(shape=(200,200,20), dtype="int"),
+        #         }
+        #     )
     
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
@@ -130,22 +130,22 @@ class Prostate158Dataset(datasets.GeneratorBasedBuilder):
                     yield_index += 1
                     yield yield_index, {image_name: Image.fromarray(image[:, :, i]) for image_name, image in images_data.items()}
 
-        elif self.config.name == "2d_array":
-            import nibabel as nib
+        # elif self.config.name == "2d_array":
+        #     import nibabel as nib
             
-            yield_index = -1
-            for row in df.to_dict(orient="records"):
-                images_data = {image_name: nib.load(downloaded_files / row[image_name]).get_fdata() for image_name in images_list}
-                for i in range(images_data["t2"].shape[2]):
-                    yield_index += 1
-                    yield yield_index, {image_name: image[:, :, i] for image_name, image in images_data.items()}
+        #     yield_index = -1
+        #     for row in df.to_dict(orient="records"):
+        #         images_data = {image_name: nib.load(downloaded_files / row[image_name]).get_fdata() for image_name in images_list}
+        #         for i in range(images_data["t2"].shape[2]):
+        #             yield_index += 1
+        #             yield yield_index, {image_name: image[:, :, i] for image_name, image in images_data.items()}
 
         elif self.config.name == "3d_path":
             for idx, row in enumerate(df.to_dict(orient="records")):
                 yield idx, {image_name+"_path": downloaded_files / row[image_name] for image_name in images_list}
 
-        elif self.config.name == "3d_array":
-            import nibabel as nib
+        # elif self.config.name == "3d_array":
+        #     import nibabel as nib
             
-            for idx, row in enumerate(df.to_dict(orient="records")):
-                yield idx, {image_name: nib.load(downloaded_files / row[image_name]).get_fdata() for image_name in images_list}
+        #     for idx, row in enumerate(df.to_dict(orient="records")):
+        #         yield idx, {image_name: nib.load(downloaded_files / row[image_name]).get_fdata() for image_name in images_list}