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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
@DATA_PARSERS.register_module()
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
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