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01571f23b7
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7 changed files with 32 additions and 14 deletions
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@ -9,7 +9,9 @@ from .extracted_text import ExtractedText
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@multimethod
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@multimethod
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def character_error_rate_n(reference: list[str], compared: list[str]) -> Tuple[float, int]:
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def character_error_rate_n(
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reference: list[str], compared: list[str]
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) -> Tuple[float, int]:
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"""
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"""
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Compute character error rate.
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Compute character error rate.
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@ -39,7 +41,9 @@ def character_error_rate_n(reference: str, compared: str) -> Tuple[float, int]:
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def character_error_rate_n(
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def character_error_rate_n(
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reference: ExtractedText, compared: ExtractedText
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reference: ExtractedText, compared: ExtractedText
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) -> Tuple[float, int]:
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) -> Tuple[float, int]:
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return character_error_rate_n(reference.grapheme_clusters, compared.grapheme_clusters)
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return character_error_rate_n(
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reference.grapheme_clusters, compared.grapheme_clusters
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)
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def character_error_rate(reference, compared) -> float:
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def character_error_rate(reference, compared) -> float:
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@ -26,7 +26,7 @@ def common_suffix(its):
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def removesuffix(text, suffix):
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def removesuffix(text, suffix):
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if suffix and text.endswith(suffix):
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if suffix and text.endswith(suffix):
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return text[:-len(suffix)]
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return text[: -len(suffix)]
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return text
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return text
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@ -46,7 +46,9 @@ def process(gt_dir, ocr_dir, report_prefix, *, metrics=True):
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ocr = removesuffix(gt, gt_suffix) + ocr_suffix
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ocr = removesuffix(gt, gt_suffix) + ocr_suffix
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gt_text = plain_extract(os.path.join(gt_dir, gt), include_filename_in_id=True)
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gt_text = plain_extract(os.path.join(gt_dir, gt), include_filename_in_id=True)
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ocr_text = plain_extract(os.path.join(ocr_dir, ocr), include_filename_in_id=True)
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ocr_text = plain_extract(
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os.path.join(ocr_dir, ocr), include_filename_in_id=True
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)
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gt_words = words_normalized(gt_text)
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gt_words = words_normalized(gt_text)
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ocr_words = words_normalized(ocr_text)
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ocr_words = words_normalized(ocr_text)
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@ -56,7 +58,9 @@ def process(gt_dir, ocr_dir, report_prefix, *, metrics=True):
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cer, n_characters = l_cer, l_n_characters
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cer, n_characters = l_cer, l_n_characters
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else:
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else:
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# Rolling update
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# Rolling update
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cer = (cer * n_characters + l_cer * l_n_characters) / (n_characters + l_n_characters)
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cer = (cer * n_characters + l_cer * l_n_characters) / (
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n_characters + l_n_characters
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)
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n_characters = n_characters + l_n_characters
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n_characters = n_characters + l_n_characters
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# Compute WER
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# Compute WER
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@ -17,6 +17,7 @@ def distance(seq1: list[str], seq2: list[str]):
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"""
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"""
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return Levenshtein.distance(seq1, seq2)
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return Levenshtein.distance(seq1, seq2)
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@multimethod
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@multimethod
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def distance(s1: str, s2: str):
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def distance(s1: str, s2: str):
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"""Compute the Levenshtein edit distance between two Unicode strings
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"""Compute the Levenshtein edit distance between two Unicode strings
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@ -175,7 +175,7 @@ class ExtractedText:
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return self._grapheme_clusters
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return self._grapheme_clusters
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else:
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else:
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clusters = []
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clusters = []
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for seg in self.segments:
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for seg in self.segments:
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# todo could there be cases where joiner is no grapheme cluster?
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# todo could there be cases where joiner is no grapheme cluster?
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clusters.extend(seg.grapheme_clusters + [self.joiner])
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clusters.extend(seg.grapheme_clusters + [self.joiner])
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return clusters[:-1]
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return clusters[:-1]
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@ -242,7 +242,9 @@ class ExtractedText:
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def from_str(cls, text, normalization=Normalization.NFC_SBB):
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def from_str(cls, text, normalization=Normalization.NFC_SBB):
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normalized_text = normalize(text, normalization)
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normalized_text = normalize(text, normalization)
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clusters = list(grapheme_clusters(normalized_text))
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clusters = list(grapheme_clusters(normalized_text))
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return cls(None, None, None, normalized_text, clusters, normalization=normalization)
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return cls(
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None, None, None, normalized_text, clusters, normalization=normalization
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)
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def invert_dict(d):
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def invert_dict(d):
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@ -98,14 +98,18 @@ def extract_texts_from_reading_order_group(group, tree, nsmap, textequiv_level):
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ro_children = filter(lambda child: "index" in child.attrib.keys(), ro_children)
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ro_children = filter(lambda child: "index" in child.attrib.keys(), ro_children)
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ro_children = sorted(ro_children, key=lambda child: int(child.attrib["index"]))
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ro_children = sorted(ro_children, key=lambda child: int(child.attrib["index"]))
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elif ET.QName(group.tag).localname in ["UnorderedGroup","UnorderedGroupIndexed"]:
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elif ET.QName(group.tag).localname in ["UnorderedGroup", "UnorderedGroupIndexed"]:
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ro_children = list(group)
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ro_children = list(group)
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else:
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else:
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raise NotImplementedError
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raise NotImplementedError
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for ro_child in ro_children:
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for ro_child in ro_children:
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if ET.QName(ro_child.tag).localname in ["OrderedGroup", "OrderedGroupIndexed", "UnorderedGroup", "UnorderedGroupIndexed"]:
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if ET.QName(ro_child.tag).localname in [
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"OrderedGroup",
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"OrderedGroupIndexed",
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"UnorderedGroup",
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"UnorderedGroupIndexed",
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]:
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regions.extend(
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regions.extend(
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extract_texts_from_reading_order_group(
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extract_texts_from_reading_order_group(
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ro_child, tree, nsmap, textequiv_level
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ro_child, tree, nsmap, textequiv_level
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@ -139,7 +143,11 @@ def plain_extract(filename, include_filename_in_id=False):
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clusters = list(grapheme_clusters(normalized_text))
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clusters = list(grapheme_clusters(normalized_text))
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return ExtractedText(
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return ExtractedText(
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id_template.format(filename=os.path.basename(filename), no=no),
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id_template.format(filename=os.path.basename(filename), no=no),
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None, None, normalized_text, clusters)
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None,
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None,
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normalized_text,
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clusters,
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)
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with open(filename, "r") as f:
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with open(filename, "r") as f:
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return ExtractedText(
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return ExtractedText(
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@ -147,7 +155,7 @@ def plain_extract(filename, include_filename_in_id=False):
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[make_segment(no, line) for no, line in enumerate(f.readlines())],
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[make_segment(no, line) for no, line in enumerate(f.readlines())],
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"\n",
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"\n",
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None,
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None,
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None
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None,
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)
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)
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# XXX hardcoded SBB normalization
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# XXX hardcoded SBB normalization
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@ -33,7 +33,7 @@ class OcrdDinglehopperEvaluate(Processor):
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textequiv_level = self.parameter["textequiv_level"]
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textequiv_level = self.parameter["textequiv_level"]
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gt_grp, ocr_grp = self.input_file_grp.split(",")
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gt_grp, ocr_grp = self.input_file_grp.split(",")
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input_file_tuples = self.zip_input_files(on_error='abort')
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input_file_tuples = self.zip_input_files(on_error="abort")
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for n, (gt_file, ocr_file) in enumerate(input_file_tuples):
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for n, (gt_file, ocr_file) in enumerate(input_file_tuples):
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if not gt_file or not ocr_file:
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if not gt_file or not ocr_file:
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# file/page was not found in this group
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# file/page was not found in this group
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@ -40,7 +40,6 @@ def words(s: str):
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if not word_break_patched:
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if not word_break_patched:
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patch_word_break()
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patch_word_break()
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# Check if c is an unwanted character, i.e. whitespace, punctuation, or similar
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# Check if c is an unwanted character, i.e. whitespace, punctuation, or similar
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def unwanted(c):
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def unwanted(c):
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