Delete ICDAR-2011.py

ICDAR-2011.py

@@ -1,119 +0,0 @@
-"""Dataset class for Individuality Of Handwriting dataset."""
-
-import itertools
-import pathlib
-import zipfile
-
-import tqdm
-from datasets.tasks import ImageClassification
-
-import datasets
-
-_BASE_URLS = {
-    "train": "http://iapr-tc11.org/dataset/ICDAR_SignatureVerification/SigComp2011/sigComp2011-trainingSet.zip",
-    "test": "http://iapr-tc11.org/dataset/ICDAR_SignatureVerification/SigComp2011/sigComp2011-test.zip"
-}
-
-_BASE_URLS_PWD = b"I hereby accept the SigComp 2011 disclaimer."
-
-_HOMEPAGE = "http://iapr-tc11.org/mediawiki/index.php/ICDAR_2011_Signature_Verification_Competition_(SigComp2011)"
-
-_DESCRIPTION = """
-The collection contains simultaneously acquired online and offline samples.
-The collection contains offline and online signature samples.
-The offline dataset comprises PNG images, scanned at 400 dpi, RGB color.
-The online dataset comprises ascii files with the format: X, Y, Z (per line).
-"""
-
-_NAMES = [
-    "genuine",
-    "forgeries",
-]
-
-
-class ICDAR2011(datasets.GeneratorBasedBuilder):
-    """ICDAR-2011 Images dataset."""
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "image": datasets.Image(),
-                    "label": datasets.ClassLabel(names=_NAMES),
-                    "forger": datasets.Value("int32"),
-                    "writer": datasets.Value("uint32"),
-                    "attempt": datasets.Value("uint32"),
-                }
-            ),
-            supervised_keys=("image", "label"),
-            homepage=_HOMEPAGE,
-            task_templates=[ImageClassification(image_column="image", label_column="label")],
-        )
-
-    def _split_generators(self, dl_manager):
-        train_archive_path = pathlib.Path(dl_manager.download(_BASE_URLS["train"]))
-        test_archive_path = pathlib.Path(dl_manager.download(_BASE_URLS["test"]))
-
-        with zipfile.ZipFile(train_archive_path, 'r') as zf:
-            train_dir = train_archive_path.parent / "extracted" / train_archive_path.name
-            print(train_dir)
-            for member in tqdm.tqdm(zf.infolist(), desc="Extracting training data"):
-                try:
-                    if not pathlib.Path(train_dir / member.filename).exists():
-                        zf.extract(member, train_dir, pwd=_BASE_URLS_PWD)
-                except zipfile.error:
-                    print("Error extracting", member.filename)
-            zf.close()
-        
-        with zipfile.ZipFile(test_archive_path, 'r') as zf:
-            test_dir = test_archive_path.parent / "extracted" / test_archive_path.name
-            for member in tqdm.tqdm(zf.infolist(), desc="Extracting test data"):
-                try:
-                    if not pathlib.Path(test_dir / member.filename).exists():
-                        zf.extract(member, test_dir, pwd=_BASE_URLS_PWD)
-                except zipfile.error:
-                    print("Error extracting", member.filename)
-            zf.close()
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "data_dir": train_dir,
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "data_dir": test_dir,
-                },
-            ),
-        ]
-
-    def _generate_examples(self, data_dir):
-        """Generate images and labels for splits."""
-        rglob_lowercase = pathlib.Path(data_dir).rglob("*.png")
-        rglob_uppercase = pathlib.Path(data_dir).rglob("*.PNG")
-        rglob = itertools.chain(rglob_lowercase, rglob_uppercase)
-
-        for index, filepath in enumerate(rglob):
-            filename = filepath.with_suffix("").name
-            prefix, attempt = filename.split("_")
-
-            if len(prefix) == 7:
-                forger = prefix[:4]
-                writer = prefix[4:]
-                label = "forgeries"
-            else:
-                writer = prefix
-                forger = -1
-                label = "genuine"
-
-            yield index, {
-                "image": str(filepath),
-                "label": label,
-                "forger": forger,
-                "writer": writer,
-                "attempt": attempt,
-            }