diff options
Diffstat (limited to 'text_recognizer/data/iam_synthetic_paragraphs.py')
| -rw-r--r-- | text_recognizer/data/iam_synthetic_paragraphs.py | 19 |
1 files changed, 10 insertions, 9 deletions
diff --git a/text_recognizer/data/iam_synthetic_paragraphs.py b/text_recognizer/data/iam_synthetic_paragraphs.py index f00a494..c938f8b 100644 --- a/text_recognizer/data/iam_synthetic_paragraphs.py +++ b/text_recognizer/data/iam_synthetic_paragraphs.py @@ -3,7 +3,7 @@ import random from typing import Any, List, Sequence, Tuple import attr -from loguru import logger +from loguru import logger as log import numpy as np from PIL import Image @@ -21,6 +21,7 @@ from text_recognizer.data.iam_paragraphs import ( IMAGE_SCALE_FACTOR, resize_image, ) +from text_recognizer.data.mappings import EmnistMapping from text_recognizer.data.iam import IAM from text_recognizer.data.iam_lines import ( line_crops_and_labels, @@ -43,10 +44,10 @@ class IAMSyntheticParagraphs(IAMParagraphs): if PROCESSED_DATA_DIRNAME.exists(): return - logger.info("Preparing IAM lines for synthetic paragraphs dataset.") - logger.info("Cropping IAM line regions and loading labels.") + log.info("Preparing IAM lines for synthetic paragraphs dataset.") + log.info("Cropping IAM line regions and loading labels.") - iam = IAM() + iam = IAM(mapping=EmnistMapping()) iam.prepare_data() crops_train, labels_train = line_crops_and_labels(iam, "train") @@ -55,7 +56,7 @@ class IAMSyntheticParagraphs(IAMParagraphs): crops_train = [resize_image(crop, IMAGE_SCALE_FACTOR) for crop in crops_train] crops_test = [resize_image(crop, IMAGE_SCALE_FACTOR) for crop in crops_test] - logger.info(f"Saving images and labels at {PROCESSED_DATA_DIRNAME}") + log.info(f"Saving images and labels at {PROCESSED_DATA_DIRNAME}") save_images_and_labels( crops_train, labels_train, "train", PROCESSED_DATA_DIRNAME ) @@ -64,7 +65,7 @@ class IAMSyntheticParagraphs(IAMParagraphs): def setup(self, stage: str = None) -> None: """Loading synthetic dataset.""" - logger.info(f"IAM Synthetic dataset steup for stage {stage}...") + log.info(f"IAM Synthetic dataset steup for stage {stage}...") if stage == "fit" or stage is None: line_crops, line_labels = load_line_crops_and_labels( @@ -76,7 +77,7 @@ class IAMSyntheticParagraphs(IAMParagraphs): targets = convert_strings_to_labels( strings=paragraphs_labels, - mapping=self.inverse_mapping, + mapping=self.mapping.inverse_mapping, length=self.output_dims[0], ) self.data_train = BaseDataset( @@ -144,7 +145,7 @@ def generate_synthetic_paragraphs( [line_labels[i] for i in paragraph_indices] ) if len(paragraph_label) > paragraphs_properties["label_length"]["max"]: - logger.info( + log.info( "Label longer than longest label in original IAM paragraph dataset - hence dropping." ) continue @@ -158,7 +159,7 @@ def generate_synthetic_paragraphs( paragraph_crop.height > max_paragraph_shape[0] or paragraph_crop.width > max_paragraph_shape[1] ): - logger.info( + log.info( "Crop larger than largest crop in original IAM paragraphs dataset - hence dropping" ) continue |