Update EMT.py

EMT.py

@@ -1,12 +1,9 @@
-"""EMT dataset."""
-
 import os
 import datasets
+import tarfile
 
 _HOMEPAGE = "https://github.com/AV-Lab/emt-dataset"
-
 _LICENSE = "CC-BY-SA 4.0"
-
 _CITATION = """  
 @article{EMTdataset2025,  
       title={EMT: A Visual Multi-Task Benchmark Dataset for Autonomous Driving in the Arab Gulf Region},  
@@ -31,6 +28,10 @@ _ANNOTATION_REPO = "https://huggingface.co/datasets/KuAvLab/EMT/resolve/main/ann
 _TRAIN_IMAGE_ARCHIVE_URL = "https://huggingface.co/datasets/KuAvLab/EMT/resolve/main/train_images.tar.gz"
 _TEST_IMAGE_ARCHIVE_URL = "https://huggingface.co/datasets/KuAvLab/EMT/resolve/main/test_images.tar.gz"
 
+# Tar file URLs for annotations
+_TRAIN_ANNOTATION_ARCHIVE_URL = "https://huggingface.co/datasets/KuAvLab/EMT/resolve/main/train_annotation.tar.gz"
+_TEST_ANNOTATION_ARCHIVE_URL = "https://huggingface.co/datasets/KuAvLab/EMT/resolve/main/test_annotation.tar.gz"
+
 
 class EMT(datasets.GeneratorBasedBuilder):
     """EMT dataset."""
@@ -72,10 +73,10 @@ class EMT(datasets.GeneratorBasedBuilder):
             "test": _TEST_IMAGE_ARCHIVE_URL,
         }
     
-        # Download the individual annotation files for train and test
+        # Download the tar file for annotations
         annotation_urls = {
-            "train": _ANNOTATION_REPO + "/train/",
-            "test": _ANNOTATION_REPO + "/test/",
+            "train": _TRAIN_ANNOTATION_ARCHIVE_URL,
+            "test": _TEST_ANNOTATION_ARCHIVE_URL,
         }
     
         # Download image files
@@ -84,7 +85,7 @@ class EMT(datasets.GeneratorBasedBuilder):
             "test": dl_manager.iter_archive(image_urls["test"]),
         }
     
-        # Download annotation files
+        # 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"]),
@@ -112,35 +113,38 @@ class EMT(datasets.GeneratorBasedBuilder):
         
         annotations = {}
         
-        # Load all annotations into memory
+        # Extract the tar.gz file and read the annotations
         for ann_file in os.listdir(annotation_path):
             video_name = os.path.splitext(ann_file)[0]  # Get video folder name
             ann_path = os.path.join(annotation_path, ann_file)
             
-            with open(ann_path, "r", encoding="utf-8") as f:
-                for line in f:
-                    parts = line.strip().split()
-                    if len(parts) < 8:
-                        continue
-    
-                    frame_id, track_id, class_name = parts[:3]
-                    bbox = list(map(float, parts[4:8]))
-                    class_id = _GT_OBJECT_CLASSES.get(class_name, -1)
-                    img_name = f"{frame_id}.jpg"
+            # Read annotation file
+            with tarfile.open(ann_path, "r:gz") as tar:
+                for member in tar.getmembers():
+                    with tar.extractfile(member) as file:
+                        for line in file:
+                            parts = line.strip().split()
+                            if len(parts) < 8:
+                                continue
+
+                            frame_id, track_id, class_name = parts[:3]
+                            bbox = list(map(float, parts[4:8]))
+                            class_id = _GT_OBJECT_CLASSES.get(class_name, -1)
+                            img_name = f"{frame_id}.jpg"
     
-                    # Store annotation in a dictionary
-                    key = f"{video_name}/{img_name}"
-                    if key not in annotations:
-                        annotations[key] = []
+                            # Store annotation in a dictionary
+                            key = f"{video_name}/{img_name}"
+                            if key not in annotations:
+                                annotations[key] = []
     
-                    annotations[key].append(
-                        {
-                            "bbox": bbox,
-                            "class_id": class_id,
-                            "track_id": int(track_id),
-                            "class_name": class_name,
-                        }
-                    )
+                            annotations[key].append(
+                                {
+                                    "bbox": bbox,
+                                    "class_id": class_id,
+                                    "track_id": int(track_id),
+                                    "class_name": class_name,
+                                }
+                            )
         
         # Yield dataset entries
         idx = 0