Update EMT.py

EMT.py

@@ -281,9 +281,50 @@ class EMT(datasets.GeneratorBasedBuilder):
             citation=_CITATION,
         )
 
-    def _split_generators(self, dl_manager):
-        """Download (if not cached) and prepare dataset splits."""
+    # def _split_generators(self, dl_manager):
+    #     """Download (if not cached) and prepare dataset splits."""
+        
+    #     image_urls = {
+    #         "train": _TRAIN_IMAGE_ARCHIVE_URL,
+    #         "test": _TEST_IMAGE_ARCHIVE_URL,
+    #     }
+        
+    #     annotation_urls = {
+    #         "train": _TRAIN_ANNOTATION_ARCHIVE_URL,
+    #         "test": _TEST_ANNOTATION_ARCHIVE_URL,
+    #     }
+        
+    #     # Ensure paths are correctly resolved for the requested split
+    #     extracted_paths = dl_manager.download_and_extract(annotation_urls)
+    #     image_archives = dl_manager.download_and_extract(image_urls)
+        
+    #     # Ensure annotation paths point to the correct subdirectory
+    #     train_annotation_path = os.path.join(extracted_paths["train"], "EMT", "annotations", "train")
+    #     test_annotation_path = os.path.join(extracted_paths["test"], "EMT", "annotations", "test")
+        
         
+    #     return [
+    #         datasets.SplitGenerator(
+    #             name=datasets.Split.TRAIN,
+    #             gen_kwargs={
+    #                 "images": dl_manager.iter_archive(image_archives["train"]),
+    #                 "annotation_path": train_annotation_path,
+    #             },
+    #         ),
+    #         datasets.SplitGenerator(
+    #             name=datasets.Split.TEST,
+    #             gen_kwargs={
+    #                 "images": dl_manager.iter_archive(image_archives["test"]),
+    #                 "annotation_path": test_annotation_path,
+    #             },
+    #         ),
+    #     ]
+    def _split_generators(self, dl_manager):
+        """Download (if not cached) and prepare only the requested dataset split."""
+    
+        # Get the requested split
+        requested_split = self.config.name
+    
         image_urls = {
             "train": _TRAIN_IMAGE_ARCHIVE_URL,
             "test": _TEST_IMAGE_ARCHIVE_URL,
@@ -293,32 +334,29 @@ class EMT(datasets.GeneratorBasedBuilder):
             "train": _TRAIN_ANNOTATION_ARCHIVE_URL,
             "test": _TEST_ANNOTATION_ARCHIVE_URL,
         }
-        
-        # Ensure paths are correctly resolved for the requested split
-        extracted_paths = dl_manager.download_and_extract(annotation_urls)
-        image_archives = dl_manager.download_and_extract(image_urls)
-        
-        # Ensure annotation paths point to the correct subdirectory
-        train_annotation_path = os.path.join(extracted_paths["train"], "EMT", "annotations", "train")
-        test_annotation_path = os.path.join(extracted_paths["test"], "EMT", "annotations", "test")
-        
-        
+    
+        # Validate split name
+        if requested_split not in image_urls:
+            raise ValueError(f"Invalid split '{requested_split}'. Available splits: 'train', 'test'.")
+    
+        # Extract only the requested split
+        extracted_images = dl_manager.download_and_extract({requested_split: image_urls[requested_split]})
+        extracted_annotations = dl_manager.download_and_extract({requested_split: annotation_urls[requested_split]})
+    
+        # Define paths based on the requested split
+        annotation_path = os.path.join(extracted_annotations[requested_split], "annotations", requested_split)
+        image_path = extracted_images[requested_split]
+    
         return [
             datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
+                name=datasets.Split.TRAIN if requested_split == "train" else datasets.Split.TEST,
                 gen_kwargs={
-                    "images": dl_manager.iter_archive(image_archives["train"]),
-                    "annotation_path": train_annotation_path,
+                    "image_dir": image_path,
+                    "annotation_path": annotation_path,
                 },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "images": dl_manager.iter_archive(image_archives["test"]),
-                    "annotation_path": test_annotation_path,
-                },
-            ),
+            )
         ]
+    
 
     def _generate_examples(self, images, annotation_path):
         """Generate dataset examples by matching images to their corresponding annotations."""