Update rsna-2023-abdominal-trauma-detection.py

rsna-2023-abdominal-trauma-detection.py

@@ -224,7 +224,9 @@ class RSNA2023AbdominalTraumaDetectionSegmentation(datasets.GeneratorBasedBuilde
         seg_files,
     ):
         series_meta_df = pd.read_csv(series_meta_file)
-        dicom_tags_df = datasets.load_dataset("parquet", data_files=dicom_tags_file)["train"].to_pandas()[
+        dicom_tags_df = datasets.load_dataset("parquet", data_files=dicom_tags_file)[
+            "train"
+        ].to_pandas()[
             [
                 "SeriesInstanceUID",
                 "PixelRepresentation",
@@ -248,7 +250,9 @@ class RSNA2023AbdominalTraumaDetectionSegmentation(datasets.GeneratorBasedBuilde
         series_meta_df = pd.merge(
             left=series_meta_df, right=dicom_tags_df, how="inner", on="series_id"
         )
-        labels_df = pd.read_csv(labels_file) if self.config.name != "segmentation" else None
+        labels_df = (
+            pd.read_csv(labels_file) if self.config.name != "segmentation" else None
+        )
 
         if self.config.name == "segmentation":
             for key, (series_id, img_path, seg_path) in enumerate(
@@ -288,25 +292,31 @@ class RSNA2023AbdominalTraumaDetectionSegmentation(datasets.GeneratorBasedBuilde
                     .iloc[0]
                     .to_dict()
                 )
+
                 yield key, {
                     "img_path": img_path,
                     "seg_path": seg_path,
-                    "bowel": datasets.ClassLabel(
-                        num_classes=2, names=["healthy", "injury"]
-                    ),
-                    "extravasation": datasets.ClassLabel(
-                        num_classes=2, names=["healthy", "injury"]
-                    ),
-                    "kidney": datasets.ClassLabel(
-                        num_classes=3, names=["healthy", "low", "high"]
-                    ),
-                    "liver": datasets.ClassLabel(
-                        num_classes=3, names=["healthy", "low", "high"]
-                    ),
-                    "spleen": datasets.ClassLabel(
-                        num_classes=3, names=["healthy", "low", "high"]
-                    ),
-                    "any_injury": datasets.Value("bool"),
+                    "bowel": [label_data["bowel_healthy"], label_data["bowel_injury"]],
+                    "extravasation": [
+                        label_data["extravasation_healthy"],
+                        label_data["extravasation_injury"],
+                    ],
+                    "kidney": [
+                        label_data["kidney_healthy"],
+                        label_data["kidney_low"],
+                        label_data["kidney_high"],
+                    ],
+                    "liver": [
+                        label_data["liver_healthy"],
+                        label_data["liver_low"],
+                        label_data["liver_high"],
+                    ],
+                    "spleen": [
+                        label_data["spleen_healthy"],
+                        label_data["spleen_low"],
+                        label_data["spleen_high"],
+                    ],
+                    "any_injury": label_data["any_injury"],
                     "metadata": {
                         "series_id": series_id,
                         "patient_id": series_meta["patient_id"],