50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
# 排版解析-单栏-自然段
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from .parser_single_line import SingleLine
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from .parser_tools.line_preprocessing import linePreprocessing # 行预处理
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from .parser_tools.paragraph_parse import ParagraphParse # 段内分析器
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class SinglePara(SingleLine):
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def __init__(self):
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self.tbpuName = "排版解析-单栏-自然段"
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# 段内分析器对象
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get_info = lambda tb: (tb["normalized_bbox"], tb["text"])
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def set_end(tb, end): # 获取预测的块尾分隔符
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tb["line"][-1]["end"] = end
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self.pp = ParagraphParse(get_info, set_end)
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def run(self, textBlocks):
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textBlocks = linePreprocessing(textBlocks) # 预处理
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lines = self.get_lines(textBlocks) # 获取每一行
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# 将行封装为tb
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temp_tbs = []
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for line in lines:
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b0, b1, b2, b3 = line[0]["normalized_bbox"]
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# 搜索bbox
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for i in range(1, len(line)):
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bb = line[i]["normalized_bbox"]
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b1 = min(b1, bb[1])
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b2 = max(b1, bb[2])
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b3 = max(b1, bb[3])
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# 构建tb
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temp_tbs.append(
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{
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"normalized_bbox": (b0, b1, b2, b3),
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"text": line[0]["text"][0] + line[-1]["text"][-1],
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"line": line,
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}
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)
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# 预测结尾分隔符
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self.pp.run(temp_tbs)
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# 解包
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textBlocks = []
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for t in temp_tbs:
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for tb in t["line"]:
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del tb["normalized_bbox"]
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textBlocks.append(tb)
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return textBlocks
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