Update hugging_face.py

hugging_face.py

@@ -36,9 +36,6 @@ _LICENSE = ""
 # TODO: Add link to the official dataset URLs here
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URLS = {
-    "dataset": "https://prod-dcd-datasets-cache-zipfiles.s3.eu-west-1.amazonaws.com/5ty2wb6gvg-1.zip"
-}
 
 
 # TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
@@ -61,7 +58,7 @@ class RDD2020_Dataset(datasets.GeneratorBasedBuilder):
                     "depth": datasets.Value("int32"),
                 }),
                 "image_path": datasets.Value("string"),
-                "pics_array": datasets.Array3D(shape=(None, None, 3), dtype="uint8"),
+                #"pics_array": datasets.Array3D(shape=(None, None, 3), dtype="uint8"),
                 "crack_type": datasets.Sequence(datasets.Value("string")),
                 "crack_coordinates": datasets.Sequence(datasets.Features({
                     "x_min": datasets.Value("int32"),
@@ -75,79 +72,87 @@ class RDD2020_Dataset(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        """This method downloads/extracts the data and defines the splits."""
-        data_dir = dl_manager.download_and_extract(_URLS["dataset"])
+        # The URL provided must be the direct link to the zip file
+        urls_to_download = {
+            "dataset": "https://huggingface.co/datasets/ShixuanAn/RDD2020/resolve/main/RDD2020.zip"
+        }
+
+        # Download and extract the dataset using the dl_manager
+        downloaded_files = dl_manager.download_and_extract(urls_to_download["dataset"])
+
+        # Assuming the ZIP file extracts to a folder named 'RDD2020'
+        extracted_path = os.path.join(downloaded_files, "RDD2020")
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "images_dir": os.path.join(data_dir, "train"),
-                    "annotations_dir": os.path.join(data_dir, "train", "annotations"),
+                    "images_dir": os.path.join(extracted_path, "train", "images"),
+                    "annotations_dir": os.path.join(extracted_path, "train", "annotations", "xmls"),
                     "split": "train",
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
-                    "images_dir": os.path.join(data_dir, "test1"),
-                    "annotations_dir": os.path.join(data_dir, "test1", "annotations"),
+                    "images_dir": os.path.join(extracted_path, "test1", "images"),
+                    "annotations_dir": None,  # No annotations for test1
                     "split": "test1",
                 },
             ),
             datasets.SplitGenerator(
-                name=datasets.Split.TEST,
+                name=datasets.Split.VALIDATION,
                 gen_kwargs={
-                    "images_dir": os.path.join(data_dir, "test2"),
-                    "annotations_dir": os.path.join(data_dir, "test2", "annotations"),
+                    "images_dir": os.path.join(extracted_path, "test2", "images"),
+                    "annotations_dir": None,  # No annotations for test2
                     "split": "test2",
                 },
             ),
         ]
 
-    def _generate_examples(self, images_dir, annotations_dir, split):
-        """Yields examples as (key, example) tuples."""
-        for image_file in os.listdir(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(annotations_dir, annotation_file)
-
-            if not os.path.exists(annotation_path):
-                continue
-
-            tree = ET.parse(annotation_path)
-            root = tree.getroot()
-
-            country = split.capitalize()
-            image_path = os.path.join(images_dir, image_file)
-            crack_type = []
-            crack_coordinates = []
-
-            for obj in root.findall('object'):
-                crack_type.append(obj.find('name').text)
-                bndbox = obj.find('bndbox')
-                coordinates = {
-                    "x_min": int(bndbox.find('xmin').text),
-                    "x_max": int(bndbox.find('xmax').text),
-                    "y_min": int(bndbox.find('ymin').text),
-                    "y_max": int(bndbox.find('ymax').text),
+    def _generate_examples(self, base_path, split):
+        # Iterate over each country directory
+        for country_dir in ['Czech', 'India', 'Japan']:
+            images_dir = f"{extracted_path}/{country_dir}/images"
+            annotations_dir = f"{extracted_path}/{country_dir}/annotations/xmls" if split == "train" else None
+
+            # Iterate over each image in the country's image directory
+            for image_file in os.listdir(images_dir):
+                if not image_file.endswith('.jpg'):
+                    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
+                    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')
+                        coordinates = {
+                            "x_min": int(bndbox.find('xmin').text),
+                            "x_max": int(bndbox.find('xmax').text),
+                            "y_min": int(bndbox.find('ymin').text),
+                            "y_max": int(bndbox.find('ymax').text),
+                        }
+                        crack_coordinates.append(coordinates)
+                else:
+                    crack_type = []
+                    crack_coordinates = []
+
+                image_resolution = {"width": 600, "height": 600, "depth": 3}
+                yield image_id, {
+                    "image_id": image_id,
+                    "country": country_dir,
+                    "type": split,
+                    "image_resolution": image_resolution,
+                    "image_path": image_path,
+                    "crack_type": crack_type,
+                    "crack_coordinates": crack_coordinates,
                 }
-                crack_coordinates.append(coordinates)
-
-            # 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 != "India" else {"width": 720,
-                                                                                                     "height": 720,
-                                                                                                    "depth": 3}
-            yield image_id, {
-                "image_id": image_id,
-                "country": country,
-                "type": split,
-                "image_resolution": image_resolution,
-                "image_path": image_path,
-                "crack_type": crack_type,
-                "crack_coordinates": crack_coordinates,
-            }
-
-