update data loading script

food_vision_199_classes.py

@@ -243,8 +243,7 @@ class Food199(datasets.GeneratorBasedBuilder):
             supervised_keys=("image", "label"),
             homepage=_HOMEPAGE,
             citation=_CITATION,
-            license=_LICENSE,
-            task_templates=[ImageClassification(image_column="image", label_column="label")],
+            license=_LICENSE
         )
 
     def _split_generators(self, dl_manager):
@@ -252,9 +251,10 @@ class Food199(datasets.GeneratorBasedBuilder):
         This function returns the logic to split the dataset into different splits as well as labels.
         """
         csv = dl_manager.download("annotations_with_links.csv")
-        df = pd.read_csv(csv)
+        df = pd.read_csv(csv, low_memory=False)
         print("Downloaded annotations.csv")
-        df_train_annotations = df[["image", "class_name"]][df["split"] == "train"].to_dict(orient="records")
+        df_train_annotations = df[["image", "label"]][df["split"] == "train"].to_dict(orient="records")
+        print(df_train_annotations[:5])
         # df_test_annotations = df[["filename", "label"]][df["split"] == "test"].to_dict(orient="records")
 
         return [
@@ -277,6 +277,7 @@ class Food199(datasets.GeneratorBasedBuilder):
         """
         for id_, row in enumerate(annotations):
             row["image"] = str(row.pop("image"))
-            row["label"] = row.pop("class_name")
+            row["label"] = row.pop("label")
+            print(id_, row)
             yield id_, row