Create star.py

star.py

@@ -0,0 +1,36 @@
+import datasets
+import numpy as np
+import os
+
+class STARDataset(datasets.GeneratorBasedBuilder):
+    """STAR Dataset with NPY file loading"""
+    
+    VERSION = datasets.Version("1.0.0")
+    
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features({
+                "id": datasets.Value("int32"),
+                "hr_path": datasets.Value("string"),
+                "lr_path": datasets.Value("string"),
+                "split": datasets.Value("string"),
+            })
+        )
+    
+    def _split_generators(self, dl_manager):
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": "sampled_data/x2/train_metadata.jsonl"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": "sampled_data/x2/validation_metadata.jsonl"},
+            ),
+        ]
+    
+    def _generate_examples(self, filepath):
+        import json
+        with open(filepath, 'r') as f:
+            for idx, line in enumerate(f):
+                yield idx, json.loads(line)