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| # Copyright (c) OpenMMLab. All rights reserved. | |
| import os.path as osp | |
| import xml.etree.ElementTree as ET | |
| from typing import List, Tuple | |
| from mmocr.registry import DATA_PARSERS | |
| from .base import BaseParser | |
| class SVTTextDetAnnParser(BaseParser): | |
| """SVT Text Detection Parser. | |
| Args: | |
| data_root (str): The root of the dataset. Defaults to None. | |
| nproc (int): The number of processes to parse the annotation. Defaults | |
| to 1. | |
| """ | |
| def parse_files(self, img_dir: str, ann_path: str) -> List: | |
| """Parse annotations.""" | |
| assert isinstance(ann_path, str) | |
| samples = list() | |
| for img_name, instance in self.loader(ann_path): | |
| samples.append((osp.join(img_dir, | |
| osp.basename(img_name)), instance)) | |
| return samples | |
| def loader(self, file_path: str) -> Tuple[str, List]: | |
| """Load annotation from SVT xml format file. See annotation example in | |
| dataset_zoo/svt/sample_anno.md. | |
| Args: | |
| file_path (str): The path of the annotation file. | |
| Returns: | |
| Tuple[str, List]: The image name and the annotation list. | |
| Yields: | |
| Iterator[Tuple[str, List]]: The image name and the annotation list. | |
| """ | |
| tree = ET.parse(file_path) | |
| root = tree.getroot() | |
| for image in root.findall('image'): | |
| image_name = image.find('imageName').text | |
| instances = list() | |
| for rectangle in image.find('taggedRectangles'): | |
| x = int(rectangle.get('x')) | |
| y = int(rectangle.get('y')) | |
| w = int(rectangle.get('width')) | |
| h = int(rectangle.get('height')) | |
| # The text annotation of this dataset is not case sensitive. | |
| # All of the texts were labeled as upper case. We convert them | |
| # to lower case for convenience. | |
| text = rectangle.find('tag').text.lower() | |
| instances.append( | |
| dict( | |
| poly=[x, y, x + w, y, x + w, y + h, x, y + h], | |
| text=text, | |
| ignore=False)) | |
| yield image_name, instances | |