Ensure image is first feature

SATIN.py

@@ -7,11 +7,9 @@ _CONSTITUENT_DATASETS = ['SAT-4', 'SAT-6', 'NASC-TG2', 'WHU-RS19', 'RSSCN7', 'RS
                          'Airbus-Wind-Turbines-Patches', 'USTC_SmokeRS', 'Canadian_Cropland',
                          'Ships-In-Satellite-Imagery', 'Satellite-Images-of-Hurricane-Damage',
                          'Brazilian_Coffee_Scenes', 'Brazilian_Cerrado-Savanna_Scenes', 'Million-AID',
-                         'UC_Merced_LandUse_MultiLabel', 'MLRSNet', 
+                         'UC_Merced_LandUse_MultiLabel', 'MLRSNet',
                          'MultiScene', 'RSI-CB256']
-"""
-_CONSTITUENT_DATASETS = ['EuroSAT']
-"""
+
 
 class SATINConfig(datasets.BuilderConfig):
     """BuilderConfig for SATIN"""
@@ -24,38 +22,22 @@ class SATINConfig(datasets.BuilderConfig):
         self.description = None
         self.features = None
 
-        #stream_dataset_info = load_dataset(self.hf_dataset_name, streaming=True, split='train').info
-        #self.description = stream_dataset_info.description
-        #self.features = stream_dataset_info.features
-
 
 class SATIN(datasets.GeneratorBasedBuilder):
     """SATIN Images dataset"""
 
     BUILDER_CONFIGS = [SATINConfig(name=dataset_name) for dataset_name in _CONSTITUENT_DATASETS]
 
-    """
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self.config.hf_dataset = load_dataset(self.config.hf_dataset_name)
-        self.config.description = self.config.hf_dataset['train'].description
-        self.config.features = self.config.hf_dataset['train'].features
-        print(self.config.features)
-    """
-
     def _info(self):
         if self.config.description is None or self.config.features is None:
             stream_dataset_info = load_dataset(self.config.hf_dataset_name, streaming=True, split='train').info
             self.config.description = stream_dataset_info.description
             self.config.features = stream_dataset_info.features
-        #print(f'info {self.config.features}')
         return datasets.DatasetInfo(
             description=self.config.description,
             features=self.config.features,
-            #supervised_keys=("image", "label"),
         )
 
-
     def _split_generators(self, dl_manager):
         dataset = load_dataset(self.config.hf_dataset_name)
         return [
@@ -71,7 +53,11 @@ class SATIN(datasets.GeneratorBasedBuilder):
         huggingface_dataset = data_path['train']
         features = huggingface_dataset.features
         for idx, row in enumerate(huggingface_dataset):
-            yield idx, {feature: row[feature] for feature in features}
+            features_dict = {feature: row[feature] for feature in features}
+            # Reorder features to make image the first feature
+            image = features_dict.pop('image')
+            features_dict = {'image': image, **features_dict}
+            yield idx, features_dict