Update fairface_val.py

fairface_val.py

@@ -20,15 +20,13 @@ import json
 from huggingface_hub import hf_hub_url
 
 _INPUT_CSV = "fairface_labeled_val.csv"
-_INPUT_IMAGES_025 = "fairface_val_images"
 _INPUT_IMAGES_125 = 'fairface_val_images_125'
 _REPO_ID = "nlphuji/fairface_val"
 
 class Dataset(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.1.0")
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="padding_025", version=VERSION, description="Padding=0.25"),
-        datasets.BuilderConfig(name="padding_125", version=VERSION, description="Padding=0.25"),
+        datasets.BuilderConfig(name="TEST", version=VERSION, description="test"),
     ]
 
     def _info(self):
@@ -51,19 +49,12 @@ class Dataset(datasets.GeneratorBasedBuilder):
         """Returns SplitGenerators."""
 
         repo_id = _REPO_ID
-        data_dir_025 = dl_manager.download_and_extract({
-            "examples_csv": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=_INPUT_CSV),
-            "images_dir": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=f"{_INPUT_IMAGES_025}.zip")
-        })
         data_dir_125 = dl_manager.download_and_extract({
             "examples_csv": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=_INPUT_CSV),
             "images_dir": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=f"{_INPUT_IMAGES_125}.zip")
         })
 
-        splits = [datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=data_dir_025),
-                 datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs=data_dir_125)]
-
-        return splits
+        return [datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs=data_dir_125)]
 
 
     def _generate_examples(self, examples_csv, images_dir):
@@ -72,6 +63,6 @@ class Dataset(datasets.GeneratorBasedBuilder):
 
         for r_idx, r in df.iterrows():
             r_dict = r.to_dict()
-            image_path = os.path.join(images_dir, images_dir.replace(".zip",""), r_dict['image_name'])
+            image_path = os.path.join(images_dir, _INPUT_IMAGES_125, r_dict['image_name'])
             r_dict['image'] = image_path
             yield r_idx, r_dict