Update RDD_2020.py

RDD_2020.py

@@ -73,59 +73,70 @@ class RDD2020_Dataset(datasets.GeneratorBasedBuilder):
             homepage='https://data.mendeley.com/datasets/5ty2wb6gvg/1',
             citation=_CITATION,
         )
-
+        
     def _split_generators(self, dl_manager):
-        # Assuming the URLs are the GitHub raw URLs to the country directories within each split
-        train_dir = "https://github.com/ShixuanAn/RDD_2020/tree/main/train"
-        test1_dir = "https://github.com/ShixuanAn/RDD_2020/tree/main/test/test/test1"
-        test2_dir = "https://github.com/ShixuanAn/RDD_2020/tree/main/test/test/test2"
+        # The direct links to the zipped files on Hugging Face
+        urls_to_download = {
+            "train": "https://huggingface.co/datasets/ShixuanAn/RDD2020/blob/main/train.zip",
+            "test1": "https://huggingface.co/datasets/ShixuanAn/RDD2020/blob/main/test1.zip",
+            "test2": "https://huggingface.co/datasets/ShixuanAn/RDD2020/blob/main/test2.zip",
+        }
+
+        # Download and extract the dataset using the dl_manager
+        downloaded_files = {
+            key: dl_manager.download_and_extract(url) for key, url in urls_to_download.items()
+        }
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "base_path": train_dir,
+                    "images_dir": os.path.join(downloaded_files["train"], "images"),
+                    "annotations_dir": os.path.join(downloaded_files["train"], "annotations", "xmls"),
                     "split": "train",
                 },
             ),
             datasets.SplitGenerator(
-                name="test1",
+                name=datasets.Split.TEST,
                 gen_kwargs={
-                    "base_path": test1_dir,
+                    "images_dir": os.path.join(downloaded_files["test1"], "images"),
+                    "annotations_dir": None,  # No annotations for test1
                     "split": "test1",
                 },
             ),
             datasets.SplitGenerator(
-                name="test2",
+                name=datasets.Split.VALIDATION,
                 gen_kwargs={
-                    "base_path": test2_dir,
+                    "images_dir": os.path.join(downloaded_files["test2"], "images"),
+                    "annotations_dir": None,  # No annotations for test2
                     "split": "test2",
                 },
             ),
         ]
 
-    def _generate_examples(self, base_path, split):
-        # Iterate over each country directory
-        for country_dir in ['Czech', 'India', 'Japan']:
-            images_dir = f"{base_path}/{country_dir}/images"
-            annotations_dir = f"{base_path}/{country_dir}/annotations/xmls" if split == "train" else None
+    def _generate_examples(self, images_dir, annotations_dir, split):
+        # Loop over each country directory in the images_dir
+        for country_dir in os.listdir(images_dir):
+            country_images_dir = os.path.join(images_dir, country_dir)
+            country_annotations_dir = os.path.join(annotations_dir, country_dir, "xmls") if annotations_dir else None
 
-            # Iterate over each image in the country's image directory
-            for image_file in os.listdir(images_dir):
+            # Now loop over each image in the country's image directory
+            for image_file in os.listdir(country_images_dir):
                 if not image_file.endswith('.jpg'):
                     continue
+                image_id = image_file.split('.')[0]
+                annotation_file = image_id + '.xml'
+                annotation_path = os.path.join(country_annotations_dir, annotation_file) if country_annotations_dir else None
+
+                if annotation_path and not os.path.exists(annotation_path):
+                    continue
 
-                image_id = f"{country_dir}_{image_file.split('.')[0]}"
-                image_path = os.path.join(images_dir, image_file)
-                if annotations_dir:
-                    annotation_file = image_id + '.xml'
-                    annotation_path = os.path.join(annotations_dir, annotation_file)
-                    if not os.path.exists(annotation_path):
-                        continue
+                # Parse the XML file for annotations if it exists
+                crack_type = []
+                crack_coordinates = []
+                if annotation_path:
                     tree = ET.parse(annotation_path)
                     root = tree.getroot()
-                    crack_type = []
-                    crack_coordinates = []
                     for obj in root.findall('object'):
                         crack_type.append(obj.find('name').text)
                         bndbox = obj.find('bndbox')
@@ -136,17 +147,17 @@ class RDD2020_Dataset(datasets.GeneratorBasedBuilder):
                             "y_max": int(bndbox.find('ymax').text),
                         }
                         crack_coordinates.append(coordinates)
-                else:
-                    crack_type = []
-                    crack_coordinates = []
 
-                image_resolution = {"width": 600, "height": 600, "depth": 3}
+                # Assuming images are of uniform size, you might want to adjust this or extract from image directly
+                image_resolution = {"width": 600, "height": 600, "depth": 3} if country_dir != "India" else {"width": 720, "height": 720, "depth": 3}
+
+                # Yield the example as a key, value pair
                 yield image_id, {
                     "image_id": image_id,
                     "country": country_dir,
                     "type": split,
                     "image_resolution": image_resolution,
-                    "image_path": image_path,
+                    "image_path": os.path.join(country_images_dir, image_file),
                     "crack_type": crack_type,
                     "crack_coordinates": crack_coordinates,
                 }