update annotations and loading script

README.md

@@ -210,9 +210,6 @@ dataset_info:
   - name: train
     num_bytes: 1331816
     num_examples: 19747
-  - name: test
-    num_bytes: 328749
-    num_examples: 4941
-  download_size: 2778026
-  dataset_size: 1660565
+  download_size: 2863352
+  dataset_size: 1331816
 ---

annotations.csv

@@ -1,4 +1,4 @@
-filename,image_name,class_names,label,split
+filename,image_name,class_name,label,split
 test/pain_au_chocolat/4fd7cb42-bd7f-48f1-bfdc-607c2f54b788.jpg,4fd7cb42-bd7f-48f1-bfdc-607c2f54b788.jpg,pain_au_chocolat,121,test
 test/pain_au_chocolat/2062f52a-781c-4e4f-b8a7-0a108934f453.jpg,2062f52a-781c-4e4f-b8a7-0a108934f453.jpg,pain_au_chocolat,121,test
 test/pain_au_chocolat/8003e0f6-37e8-460d-9c14-e7c6fe44a37f.jpg,8003e0f6-37e8-460d-9c14-e7c6fe44a37f.jpg,pain_au_chocolat,121,test

food_vision_199_classes.py

@@ -254,7 +254,7 @@ class Food199(datasets.GeneratorBasedBuilder):
         csv = dl_manager.download("annotations.csv")
         df = pd.read_csv(csv)
         print("Downloaded annotations.csv")
-        df_train_annotations = df[["filename", "label"]][df["split"] == "train"].to_dict(orient="records")
+        df_train_annotations = df[["filename", "class_name"]][df["split"] == "train"].to_dict(orient="records")
         # df_test_annotations = df[["filename", "label"]][df["split"] == "test"].to_dict(orient="records")
 
         return [