def text(self, content, extracted=False):
"""针对文本类型的输入的编码"""
if isinstance(content, bytes):
content = content.decode("utf8")
# 如果标签来源为文件名形如 aaa_md5.png
if self.model_conf.label_from == LabelFrom.FileName:
# 如果标签尚未提取解析
if not extracted:
found = re.search(self.model_conf.extract_regex, content)
if not found:
exception(
text=
"The regex is not extracted to the corresponding label",
code=-777)
found = found.group()
else:
found = content
# 如果匹配内置的大小写规范，触发自动转换
if isinstance(self.category_param,
str) and '_LOWER' in self.category_param:
found = found.lower()
if isinstance(self.category_param,
str) and '_UPPER' in self.category_param:
found = found.upper()
# 标签是否包含分隔符
if self.model_conf.label_split:
labels = found.split(self.model_conf.label_split)
elif self.model_conf.max_label_num == 1:
labels = [found]
else:
labels = [_ for _ in found]
labels = self.filter_full_angle(labels)
try:
if not labels:
return [0]
# 根据类别集合找到对应映射编码为dense数组
if self.model_conf.loss_func == LossFunction.CTC:
label = self.split_continuous_char([
encode_maps(self.model_conf.category)[i]
for i in labels
])
else:
label = self.auto_padding_char([
encode_maps(self.model_conf.category)[i]
for i in labels
])
return label
except KeyError as e:
exception(
'The sample label {} contains invalid charset: {}.'.format(
content, e.args[0]),
ConfigException.SAMPLE_LABEL_ERROR)
def text(self, content):
"""针对文本类型的输入的编码"""
if isinstance(content, bytes):
content = content.decode("utf8")
found = content
# 如果匹配内置的大小写规范，触发自动转换
if isinstance(self.category_param, str) and '_LOWER' in self.category_param:
found = found.lower()
if isinstance(self.category_param, str) and '_UPPER' in self.category_param:
found = found.upper()
if self.model_conf.category_param == 'ARITHMETIC':
found = found.replace("x", "×").replace('？', "?")
# 标签是否包含分隔符
if self.model_conf.label_split:
labels = found.split(self.model_conf.label_split)
elif '&' in found:
labels = found.split('&')
elif self.model_conf.max_label_num == 1:
labels = [found]
else:
labels = [_ for _ in found]
labels = self.filter_full_angle(labels)
try:
if not labels:
return [0]
# 根据类别集合找到对应映射编码为dense数组
if self.model_conf.loss_func == LossFunction.CTC:
label = self.split_continuous_char(
[encode_maps(self.model_conf.category)[i] for i in labels]
)
else:
label = self.auto_padding_char(
[encode_maps(self.model_conf.category)[i] for i in labels]
)
return label
except KeyError as e:
return dict(e=e, label=content, char=e.args[0])
