TAR functionality

unit-test_PDFfolder.py

@@ -8,34 +8,20 @@ logger = datasets.logging.get_logger(__name__)
 
 _DESCRIPTION = "A generic pdf folder"
 
-_CLASSES = ["categoryA", "categoryB"] #define in advance
+_CLASSES = ["categoryA", "categoryB"]  # define in advance
 
 _URL = "https://huggingface.co/datasets/jordyvl/unit-test_PDFfolder/resolve/main/data/data.tar.gz"
 
-#folder
+# folder
 #   train
 #       categoryA
 #           file1
 #   test
-#...
+# ...
 
-#RVL-CDIP_multi
 
 class PdfFolder(datasets.GeneratorBasedBuilder):
     def _info(self):
-
-        """
-        folder = None
-        elif isinstance(self.config.data_files, str):
-            folder = self.config.data_files
-        elif isinstance(self.config.data_files, dict):
-            folder = self.config.data_files.get("train", None)
-
-        if folder is None:
-            raise RuntimeError()
-        """
-        #classes = sorted([x.name.lower() for x in Path(_URL).glob("*/**")])
-
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=datasets.Features(
@@ -58,66 +44,37 @@ class PdfFolder(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
                     "archive_iterator": dl_manager.iter_archive(archive_path),
-                    "supposed_labelset": "train"
+                    "supposed_labelset": "train",
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
                     "archive_iterator": dl_manager.iter_archive(archive_path),
-                    "supposed_labelset": "test"
+                    "supposed_labelset": "test",
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
                     "archive_iterator": dl_manager.iter_archive(archive_path),
-                    "supposed_labelset": "val"
+                    "supposed_labelset": "val",
                 },
             ),
         ]
 
-
-        # if isinstance(self.config.data_files, str):
-        #     return [
-        #         datasets.SplitGenerator(
-        #             name=datasets.Split.TRAIN, gen_kwargs={"archive_path": self.config.data_files}
-        #         )
-        #     ]
-
-        # splits = []
-        # for split_name, folder in self.config.data_files.items():
-        #     splits.append(
-        #         datasets.SplitGenerator(name=split_name, gen_kwargs={"archive_path": folder})
-        #     )
-
-        # return splits
-
     def _generate_examples(self, archive_iterator, supposed_labelset):
 
-        #could also get the label from somewhere else 
-
-        #data/train/categoryB/581261-brown-invoice-10-29-11-04-12-2-13530037073412-pdf.pdf
-        #folder/labelset/label/filename
-
-        #full_path = os.path.join(archive_iterator.args[0], file_path)
-
-        #archive_path = archive_iterator.args[0]
-
         extensions = {"pdf", "PDF"}
         for file_path, file_obj in archive_iterator:
 
-            if file_path.split(".")[-1] not in extensions: #metadata.jsonlines
+            if file_path.split(".")[-1] not in extensions:  # metadata.jsonlines
                 continue
 
             folder, labelset, label, filename = file_path.split("/")
             if labelset != supposed_labelset:
                 continue
-            
-            images = pdf2image.convert_from_bytes(file_obj.read()) #can only read it once
-            #simple = {"path": file_path, "bytes": file_obj.read(), "labels": label}
 
-            yield file_path, {"file": images, "labels": label}
+            images = pdf2image.convert_from_bytes(file_obj.read())
 
-        #labels = self.info.features["labels"]
-        #labels.encode_example(path.parent.name.lower())
+            yield file_path, {"file": images, "labels": label}