Update EMT.py

EMT.py

@@ -225,7 +225,8 @@ class EMT(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        """Download train/test images and annotations."""
+        """Download (if not cached) and prepare dataset splits."""
+        
         image_urls = {
             "train": _TRAIN_IMAGE_ARCHIVE_URL,
             "test": _TEST_IMAGE_ARCHIVE_URL,
@@ -235,38 +236,32 @@ class EMT(datasets.GeneratorBasedBuilder):
             "train": _TRAIN_ANNOTATION_ARCHIVE_URL,
             "test": _TEST_ANNOTATION_ARCHIVE_URL,
         }
-        
-        # Download image files
-        images = {
-            "train": dl_manager.iter_archive(image_urls["train"]),
-            "test": dl_manager.iter_archive(image_urls["test"]),
-        }
     
-        # Download annotation files and extract them
-        annotations = {
-            "train": dl_manager.download_and_extract(annotation_urls["train"]),
-            "test": dl_manager.download_and_extract(annotation_urls["test"]),
-        }
-
-        print("Extracted train annotations path:", annotations["train"])
-        print("Extracted test annotations path:", annotations["test"])
+        # Ensure paths are correctly resolved
+        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"], "annotations", "train")
+        test_annotation_path = os.path.join(extracted_paths["test"], "annotations", "test")
     
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "images": images["train"],
-                    "annotation_path": annotations["train"],
+                    "images": dl_manager.iter_archive(image_archives["train"]),
+                    "annotation_path": train_annotation_path,  # ✅ Corrected path
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
-                    "images": images["test"],
-                    "annotation_path": annotations["test"],
+                    "images": dl_manager.iter_archive(image_archives["test"]),
+                    "annotation_path": test_annotation_path,  # ✅ Corrected path
                 },
             ),
-            ]
+    ]
+
     def _generate_examples(self, images, annotation_path):
         """Generate dataset examples by matching images to their corresponding annotations."""