Delete loading script

gtsrb.py

@@ -1,83 +0,0 @@
-import datasets
-from datasets.data_files import DataFilesDict
-from datasets.packaged_modules.imagefolder.imagefolder import ImageFolder, ImageFolderConfig
-
-logger = datasets.logging.get_logger(__name__)
-
-
-class GTSRB(ImageFolder):
-    R"""
-    GTSRB dataset for image classification.
-    """
-
-    BUILDER_CONFIG_CLASS = ImageFolderConfig
-    BUILDER_CONFIGS = [
-        ImageFolderConfig(name='default', features=("images", "labels"), data_files=DataFilesDict({split: f"data/{split}.zip" for split in ["train", "test"] + ["contrast", "gaussian_noise", "impulse_noise", "jpeg_compression", "motion_blur", "pixelate", "spatter"]}),)
-    ]
-
-
-    classnames = [
-        "red and white circle 20 kph speed limit",
-        "red and white circle 30 kph speed limit",
-        "red and white circle 50 kph speed limit",
-        "red and white circle 60 kph speed limit",
-        "red and white circle 70 kph speed limit",
-        "red and white circle 80 kph speed limit",
-        "end / de-restriction of 80 kph speed limit",
-        "red and white circle 100 kph speed limit",
-        "red and white circle 120 kph speed limit",
-        "red and white circle red car and black car no passing",
-        "red and white circle red truck and black car no passing",
-        "red and white triangle road intersection warning",
-        "white and yellow diamond priority road",
-        "red and white upside down triangle yield right-of-way",
-        "stop",
-        "empty red and white circle",
-        "red and white circle no truck entry",
-        "red circle with white horizonal stripe no entry",
-        "red and white triangle with exclamation mark warning",
-        "red and white triangle with black left curve approaching warning",
-        "red and white triangle with black right curve approaching warning",
-        "red and white triangle with black double curve approaching warning",
-        "red and white triangle rough / bumpy road warning",
-        "red and white triangle car skidding / slipping warning",
-        "red and white triangle with merging / narrow lanes warning",
-        "red and white triangle with person digging / construction / road work warning",
-        "red and white triangle with traffic light approaching warning",
-        "red and white triangle with person walking warning",
-        "red and white triangle with child and person walking warning",
-        "red and white triangle with bicyle warning",
-        "red and white triangle with snowflake / ice warning",
-        "red and white triangle with deer warning",
-        "white circle with gray strike bar no speed limit",
-        "blue circle with white right turn arrow mandatory",
-        "blue circle with white left turn arrow mandatory",
-        "blue circle with white forward arrow mandatory",
-        "blue circle with white forward or right turn arrow mandatory",
-        "blue circle with white forward or left turn arrow mandatory",
-        "blue circle with white keep right arrow mandatory",
-        "blue circle with white keep left arrow mandatory",
-        "blue circle with white arrows indicating a traffic circle",
-        "white circle with gray strike bar indicating no passing for cars has ended",
-        "white circle with gray strike bar indicating no passing for trucks has ended",
-    ]
-
-    clip_templates = [
-        lambda c: f'a zoomed in photo of a "{c}" traffic sign.',
-        lambda c: f'a centered photo of a "{c}" traffic sign.',
-        lambda c: f'a close up photo of a "{c}" traffic sign.',
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description="GTSRB dataset for image classification.",
-            features=datasets.Features(
-                {
-                    "image": datasets.Image(),
-                    "label": datasets.ClassLabel(names=self.classnames),
-                }
-            ),
-            supervised_keys=("image", "label"),
-            task_templates=[datasets.ImageClassification(image_column="image", label_column="label")],
-        )
-