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# Copyright (c) OpenMMLab. All rights reserved.
import re
from typing import Dict, Tuple
import yaml
from mmocr.registry import DATA_PARSERS
from .base import BaseParser
@DATA_PARSERS.register_module()
class TotaltextTextDetAnnParser(BaseParser):
"""TotalText Text Detection Parser.
The original annotation format of this dataset is stored in txt files,
which is formed as the following format:
x: [[x1 x2 x3 ... xn]], y: [[y1 y2 y3 ... yn]],
ornt: [u'c'], transcriptions: [u'transcription']
Args:
data_root (str): Path to the dataset root.
ignore (str): The text of the ignored instances. Default: '#'.
nproc (int): Number of processes to load the data. Default: 1.
"""
def __init__(self, ignore: str = '#', **kwargs) -> None:
self.ignore = ignore
super().__init__(**kwargs)
def parse_file(self, img_path: str, ann_path: str) -> Dict:
"""Convert single annotation."""
instances = list()
for poly, text in self.loader(ann_path):
instances.append(
dict(poly=poly, text=text, ignore=text == self.ignore))
return img_path, instances
def loader(self, file_path: str) -> str:
"""The annotation of the totaltext dataset may be stored in multiple
lines, this loader is designed for this special case.
Args:
file_path (str): Path to the txt file
Yield:
str: Complete annotation of the txt file
"""
def parsing_line(line: str) -> Tuple:
"""Parsing a line of the annotation.
Args:
line (str): A line of the annotation.
Returns:
Tuple: A tuple of (polygon, transcription).
"""
line = '{' + line.replace('[[', '[').replace(']]', ']') + '}'
ann_dict = re.sub('([0-9]) +([0-9])', r'\1,\2', line)
ann_dict = re.sub('([0-9]) +([ 0-9])', r'\1,\2', ann_dict)
ann_dict = re.sub('([0-9]) -([0-9])', r'\1,-\2', ann_dict)
ann_dict = ann_dict.replace("[u',']", "[u'#']")
ann_dict = yaml.safe_load(ann_dict)
# polygon
xs, ys = ann_dict['x'], ann_dict['y']
poly = []
for x, y in zip(xs, ys):
poly.append(x)
poly.append(y)
# text
text = ann_dict['transcriptions']
if len(text) == 0:
text = '#'
else:
word = text[0]
if len(text) > 1:
for ann_word in text[1:]:
word += ',' + ann_word
text = str(eval(word))
return poly, text
with open(file_path, 'r') as f:
for idx, line in enumerate(f):
line = line.strip()
if idx == 0:
tmp_line = line
continue
if not line.startswith('x:'):
tmp_line += ' ' + line
continue
complete_line = tmp_line
tmp_line = line
yield parsing_line(complete_line)
if tmp_line != '':
yield parsing_line(tmp_line)
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