Update rsna-atd.py

rsna-atd.py

@@ -1,5 +1,6 @@
 import datasets
 import pandas as pd
+import hickle as hkl
 
 _CITATION = """\
 @InProceedings{huggingface:dataset,
@@ -30,8 +31,6 @@ class RSNAATD(datasets.GeneratorBasedBuilder):
             description=_DESCRIPTION,
             features=datasets.Features(
                 {
-                    "image_path": datasets.Value("string"),
-                    "mask_path": datasets.Value("string")
                     # "patient_id": datasets.Value("int64"),
                     # "series_id": datasets.Value("int64"),
                     # "aortic_hu": datasets.Value("float64"),
@@ -50,8 +49,8 @@ class RSNAATD(datasets.GeneratorBasedBuilder):
                     # "spleen_low": datasets.Value("int64"),
                     # "spleen_high": datasets.Value("int64"),
                     # "any_injury": datasets.Value("int64"),
-                    # "image": datasets.Array3D(shape=(None, 512, 512)),
-                    # "mask": datasets.Array3D(shape=(None, 512, 512)),
+                    "image": datasets.Array3D(shape=(None, 512, 512)),
+                    "mask": datasets.Array3D(shape=(None, 512, 512)),
                 }
             ),
             supervised_keys=None,
@@ -80,16 +79,20 @@ class RSNAATD(datasets.GeneratorBasedBuilder):
 
     def _generate_examples(self, images, masks, metadata):
         df = pd.read_csv(metadata)
+        for idx, data in df.to_numpy():
+            image, mask = hkl.load(f"images/{data[0]}"), hkl.load(f"masks/{data[0]}")
 
-        for idx, ((image_path), (mask_path)) in enumerate(zip(images, masks)):
-            # row = df.loc[df["path"] == image_path.lower().replace("images/", "")]
+            yield idx, {"image": image, "mask": mask}
 
-            yield idx, {
-                "image_path": image_path,
-                "mask_path": mask_path
-                # "patient_id": row["patient_id"].values[0],
-                # "series_id": row["series_id"].values[0],
-                # "frame_id": row["frame_id"].values[0],
-                # "image": {"path": image_path, "bytes": image.read()},
-                # "mask": {"path": mask_path, "bytes": mask.read()},
-            }
+        # for idx, ((image_path), (mask_path)) in enumerate(zip(images, masks)):
+        #     # row = df.loc[df["path"] == image_path.lower().replace("images/", "")]
+
+        #     yield idx, {
+        #         "image_path": image_path,
+        #         "mask_path": mask_path
+        #         # "patient_id": row["patient_id"].values[0],
+        #         # "series_id": row["series_id"].values[0],
+        #         # "frame_id": row["frame_id"].values[0],
+        #         # "image": {"path": image_path, "bytes": image.read()},
+        #         # "mask": {"path": mask_path, "bytes": mask.read()},
+        #     }