diff options
Diffstat (limited to 'text_recognizer/data/iam_paragraphs.py')
| -rw-r--r-- | text_recognizer/data/iam_paragraphs.py | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/text_recognizer/data/iam_paragraphs.py b/text_recognizer/data/iam_paragraphs.py index 402a8d4..f588587 100644 --- a/text_recognizer/data/iam_paragraphs.py +++ b/text_recognizer/data/iam_paragraphs.py @@ -93,14 +93,14 @@ class IAMParagraphs(BaseDataModule): def _load_dataset(split: str, augment: bool) -> BaseDataset: crops, labels = _load_processed_crops_and_labels(split) - data = [_resize_image(crop, IMAGE_SCALE_FACTOR) for crop in crops] + data = [resize_image(crop, IMAGE_SCALE_FACTOR) for crop in crops] targets = convert_strings_to_labels( strings=labels, mapping=self.inverse_mapping, length=self.output_dims[0] ) return BaseDataset( data, targets, - transform=_get_transform(image_shape=self.dims[1:], augment=augment), + transform=get_transform(image_shape=self.dims[1:], augment=augment), ) logger.info(f"Loading IAM paragraph regions and lines for {stage}...") @@ -142,7 +142,7 @@ class IAMParagraphs(BaseDataModule): return basic + data -def _get_dataset_properties() -> Dict: +def get_dataset_properties() -> Dict: """Return properties describing the overall dataset.""" with (PROCESSED_DATA_DIRNAME / "_properties.json").open("r") as f: properties = json.load(f) @@ -173,7 +173,7 @@ def _validate_data_dims( input_dims: Optional[Tuple[int, ...]], output_dims: Optional[Tuple[int, ...]] ) -> None: """Validates input and output dimensions against the properties of the dataset.""" - properties = _get_dataset_properties() + properties = get_dataset_properties() max_image_shape = properties["crop_shape"]["max"] / IMAGE_SCALE_FACTOR if ( @@ -192,7 +192,7 @@ def _validate_data_dims( ) -def _resize_image(image: Image.Image, scale_factor: int) -> Image.Image: +def resize_image(image: Image.Image, scale_factor: int) -> Image.Image: """Resize image by scale factor.""" if scale_factor == 1: return image @@ -219,7 +219,7 @@ def _get_paragraph_crops_and_labels( image = ImageOps.invert(image) line_regions = iam.line_regions_by_id[id_] - parameter_box = [ + paragraph_box = [ min([region["x1"] for region in line_regions]), min([region["y1"] for region in line_regions]), max([region["x2"] for region in line_regions]), @@ -227,7 +227,7 @@ def _get_paragraph_crops_and_labels( ] lines = iam.line_strings_by_id[id_] - crops[id_] = image.crop(parameter_box) + crops[id_] = image.crop(paragraph_box) labels[id_] = NEW_LINE_TOKEN.join(lines) if len(crops) != len(labels): @@ -269,7 +269,7 @@ def _load_processed_crops_and_labels( return ordered_crops, ordered_labels -def _get_transform(image_shape: Tuple[int, int], augment: bool) -> transforms.Compose: +def get_transform(image_shape: Tuple[int, int], augment: bool) -> transforms.Compose: """Get transformations for images.""" if augment: transforms_list = [ |