Update funsd.py

funsd.py

@@ -7,10 +7,20 @@ from PIL import Image
 import datasets
 from transformers import AutoTokenizer
 
+_CITATION = """\
+@article{Jaume2019FUNSDAD,
+  title={FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents},
+  author={Guillaume Jaume and H. K. Ekenel and J. Thiran},
+  journal={2019 International Conference on Document Analysis and Recognition Workshops (ICDARW)},
+  year={2019},
+  volume={2},
+  pages={1-6}
+}
+"""
+_DESCRIPTION = """\
+https://guillaumejaume.github.io/FUNSD/
+"""
 
-_URL = "https://github.com/doc-analysis/XFUND/releases/download/v1.0/"
-
-_LANG = ["zh", "de", "es", "fr", "en", "it", "ja", "pt"]
 logger = logging.getLogger(__name__)
 
 
@@ -47,29 +57,29 @@ def load_image(image_path):
     image = image.transpose(2, 0, 1) # move channels to first dimension
     return image, (w, h)
 
-class XFUNDConfig(datasets.BuilderConfig):
-    """BuilderConfig for XFUND."""
+class FunsdConfig(datasets.BuilderConfig):
+    """BuilderConfig for FUNSD"""
 
-    def __init__(self, lang, additional_langs=None, **kwargs):
-        """
+    def __init__(self, **kwargs):
+        """BuilderConfig for FUNSD.
         Args:
-            lang: string, language for the input text
-            **kwargs: keyword arguments forwarded to super.
+          **kwargs: keyword arguments forwarded to super.
         """
-        super(XFUNDConfig, self).__init__(**kwargs)
-        self.lang = lang
-        self.additional_langs = additional_langs
+        super(FunsdConfig, self).__init__(**kwargs)
 
 
-class XFUND(datasets.GeneratorBasedBuilder):
-    """XFUND dataset."""
+class Funsd(datasets.GeneratorBasedBuilder):
+    """FUNSD dataset."""
 
-    BUILDER_CONFIGS = [XFUNDConfig(name=f"xfund.{lang}", lang=lang) for lang in _LANG]
+    BUILDER_CONFIGS = [
+        FunsdConfig(name="funsd", version=datasets.Version("1.0.0"), description="FUNSD dataset"),
+    ]
 
     tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-base")
 
     def _info(self):
         return datasets.DatasetInfo(
+            description=_DESCRIPTION,
             features=datasets.Features(
                 {
                     "id": datasets.Value("string"),
@@ -103,33 +113,14 @@ class XFUND(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        urls_to_download = {
-            "train": [f"{_URL}{self.config.lang}.train.json", f"{_URL}{self.config.lang}.train.zip"],
-            "val": [f"{_URL}{self.config.lang}.val.json", f"{_URL}{self.config.lang}.val.zip"],
-            # "test": [f"{_URL}{self.config.lang}.test.json", f"{_URL}{self.config.lang}.test.zip"],
-        }
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-        train_files_for_many_langs = [downloaded_files["train"]]
-        val_files_for_many_langs = [downloaded_files["val"]]
-        # test_files_for_many_langs = [downloaded_files["test"]]
-        if self.config.additional_langs:
-            additional_langs = self.config.additional_langs.split("+")
-            if "all" in additional_langs:
-                additional_langs = [lang for lang in _LANG if lang != self.config.lang]
-            for lang in additional_langs:
-                urls_to_download = {"train": [f"{_URL}{lang}.train.json", f"{_URL}{lang}.train.zip"]}
-                additional_downloaded_files = dl_manager.download_and_extract(urls_to_download)
-                train_files_for_many_langs.append(additional_downloaded_files["train"])
-
-        logger.info(f"Training on {self.config.lang} with additional langs({self.config.additional_langs})")
-        logger.info(f"Evaluating on {self.config.lang}")
-        logger.info(f"Testing on {self.config.lang}")
+        downloaded_file = dl_manager.download_and_extract("https://guillaumejaume.github.io/FUNSD/dataset.zip")
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_files_for_many_langs}),
             datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION, gen_kwargs={"filepaths": val_files_for_many_langs}
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": f"{downloaded_file}/dataset/training_data/"}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": f"{downloaded_file}/dataset/testing_data/"}
             ),
-            # datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepaths": test_files_for_many_langs}),
         ]
 
     def _generate_examples(self, filepaths):