diff options
Diffstat (limited to 'text_recognizer/data')
| -rw-r--r-- | text_recognizer/data/iam_extended_paragraphs.py | 12 | ||||
| -rw-r--r-- | text_recognizer/data/iam_paragraphs.py | 13 | ||||
| -rw-r--r-- | text_recognizer/data/iam_synthetic_paragraphs.py | 2 | ||||
| -rw-r--r-- | text_recognizer/data/mappings.py | 12 | ||||
| -rw-r--r-- | text_recognizer/data/transforms.py | 4 |
5 files changed, 19 insertions, 24 deletions
diff --git a/text_recognizer/data/iam_extended_paragraphs.py b/text_recognizer/data/iam_extended_paragraphs.py index 2380660..0a30a42 100644 --- a/text_recognizer/data/iam_extended_paragraphs.py +++ b/text_recognizer/data/iam_extended_paragraphs.py @@ -19,18 +19,10 @@ class IAMExtendedParagraphs(BaseDataModule): super().__init__(batch_size, num_workers) self.iam_paragraphs = IAMParagraphs( - batch_size, - num_workers, - train_fraction, - augment, - word_pieces, + batch_size, num_workers, train_fraction, augment, word_pieces, ) self.iam_synthetic_paragraphs = IAMSyntheticParagraphs( - batch_size, - num_workers, - train_fraction, - augment, - word_pieces, + batch_size, num_workers, train_fraction, augment, word_pieces, ) self.dims = self.iam_paragraphs.dims diff --git a/text_recognizer/data/iam_paragraphs.py b/text_recognizer/data/iam_paragraphs.py index 62c44f9..24409bc 100644 --- a/text_recognizer/data/iam_paragraphs.py +++ b/text_recognizer/data/iam_paragraphs.py @@ -101,7 +101,7 @@ class IAMParagraphs(BaseDataModule): data, targets, transform=get_transform(image_shape=self.dims[1:], augment=augment), - target_transform=get_target_transform(self.word_pieces) + target_transform=get_target_transform(self.word_pieces), ) logger.info(f"Loading IAM paragraph regions and lines for {stage}...") @@ -162,10 +162,7 @@ def get_dataset_properties() -> Dict: "min": min(_get_property_values("num_lines")), "max": max(_get_property_values("num_lines")), }, - "crop_shape": { - "min": crop_shapes.min(axis=0), - "max": crop_shapes.max(axis=0), - }, + "crop_shape": {"min": crop_shapes.min(axis=0), "max": crop_shapes.max(axis=0),}, "aspect_ratio": { "min": aspect_ratio.min(axis=0), "max": aspect_ratio.max(axis=0), @@ -286,9 +283,7 @@ def get_transform(image_shape: Tuple[int, int], augment: bool) -> transforms.Com ), transforms.ColorJitter(brightness=(0.8, 1.6)), transforms.RandomAffine( - degrees=1, - shear=(-10, 10), - interpolation=InterpolationMode.BILINEAR, + degrees=1, shear=(-10, 10), interpolation=InterpolationMode.BILINEAR, ), ] else: @@ -296,10 +291,12 @@ def get_transform(image_shape: Tuple[int, int], augment: bool) -> transforms.Com transforms_list.append(transforms.ToTensor()) return transforms.Compose(transforms_list) + def get_target_transform(word_pieces: bool) -> Optional[transforms.Compose]: """Transform emnist characters to word pieces.""" return transforms.Compose([WordPiece()]) if word_pieces else None + def _labels_filename(split: str) -> Path: """Return filename of processed labels.""" return PROCESSED_DATA_DIRNAME / split / "_labels.json" diff --git a/text_recognizer/data/iam_synthetic_paragraphs.py b/text_recognizer/data/iam_synthetic_paragraphs.py index 4ccc5c2..78e6c05 100644 --- a/text_recognizer/data/iam_synthetic_paragraphs.py +++ b/text_recognizer/data/iam_synthetic_paragraphs.py @@ -97,7 +97,7 @@ class IAMSyntheticParagraphs(IAMParagraphs): transform=get_transform( image_shape=self.dims[1:], augment=self.augment ), - target_transform=get_target_transform(self.word_pieces) + target_transform=get_target_transform(self.word_pieces), ) def __repr__(self) -> str: diff --git a/text_recognizer/data/mappings.py b/text_recognizer/data/mappings.py index f4016ba..190febe 100644 --- a/text_recognizer/data/mappings.py +++ b/text_recognizer/data/mappings.py @@ -58,13 +58,13 @@ class WordPieceMapping(EmnistMapping): def __init__( self, num_features: int = 1000, - tokens: str = "iamdb_1kwp_tokens_1000.txt" , + tokens: str = "iamdb_1kwp_tokens_1000.txt", lexicon: str = "iamdb_1kwp_lex_1000.txt", data_dir: Optional[Union[str, Path]] = None, use_words: bool = False, prepend_wordsep: bool = False, special_tokens: Sequence[str] = ("<s>", "<e>", "<p>"), - extra_symbols: Optional[Sequence[str]] = ("\n", ), + extra_symbols: Optional[Sequence[str]] = ("\n",), ) -> None: super().__init__(extra_symbols) self.wordpiece_processor = self._configure_wordpiece_processor( @@ -90,7 +90,13 @@ class WordPieceMapping(EmnistMapping): extra_symbols: Optional[Sequence[str]], ) -> Preprocessor: data_dir = ( - (Path(__file__).resolve().parents[2] / "data" / "downloaded" / "iam" / "iamdb") + ( + Path(__file__).resolve().parents[2] + / "data" + / "downloaded" + / "iam" + / "iamdb" + ) if data_dir is None else Path(data_dir) ) diff --git a/text_recognizer/data/transforms.py b/text_recognizer/data/transforms.py index 8d1bedd..d0f1f35 100644 --- a/text_recognizer/data/transforms.py +++ b/text_recognizer/data/transforms.py @@ -13,7 +13,7 @@ class WordPiece: def __init__( self, num_features: int = 1000, - tokens: str = "iamdb_1kwp_tokens_1000.txt" , + tokens: str = "iamdb_1kwp_tokens_1000.txt", lexicon: str = "iamdb_1kwp_lex_1000.txt", data_dir: Optional[Union[str, Path]] = None, use_words: bool = False, @@ -35,4 +35,4 @@ class WordPiece: self.max_len = max_len def __call__(self, x: Tensor) -> Tensor: - return self.mapping.emnist_to_wordpiece_indices(x)[:self.max_len] + return self.mapping.emnist_to_wordpiece_indices(x)[: self.max_len] |