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magic_pdf-
...
magic_pdf-
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b1ac8d03da | ||
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8486793393 | ||
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195998a07f | ||
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25a0fd0665 | ||
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084e9328d0 | ||
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f68c66290c |
1
.gitignore
vendored
1
.gitignore
vendored
@@ -31,5 +31,6 @@ tmp
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.vscode
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.vscode/
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/tests/
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ocr_demo
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/app/common/__init__.py
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@@ -4,7 +4,7 @@ import os
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from loguru import logger
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from pathlib import Path
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from magic_pdf.dict2md.ocr_mkcontent import ocr_mk_nlp_markdown, ocr_mk_mm_markdown
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from magic_pdf.dict2md.ocr_mkcontent import mk_mm_markdown2, mk_nlp_markdown, mk_mm_markdown
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from magic_pdf.libs.commons import join_path
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from magic_pdf.pdf_parse_by_ocr import parse_pdf_by_ocr
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@@ -34,8 +34,9 @@ if __name__ == '__main__':
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ocr_json_file_path = r"D:\project\20231108code-clean\ocr\new\双栏\s0043-1354(02)00581-x.json"
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# ocr_pdf_path = r"D:\project\20231108code-clean\ocr\new\双栏\j.1540-627x.2006.00176.x.pdf"
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# ocr_json_file_path = r"D:\project\20231108code-clean\ocr\new\双栏\j.1540-627x.2006.00176.x.json"
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# ocr_pdf_path = r"D:\project\20231108code-clean\ocr\new\demo_4\ocr_demo\ocr_1_org.pdf"
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# ocr_json_file_path = r"D:\project\20231108code-clean\ocr\new\demo_4\ocr_demo\ocr_1_fix.json"
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ocr_pdf_path = r"/home/cxu/workspace/Magic-PDF/ocr_demo/j.1540-627x.2006.00176.x.pdf"
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ocr_json_file_path = r"/home/cxu/workspace/Magic-PDF/ocr_demo/j.1540-627x.2006.00176.x.json"
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try:
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ocr_pdf_model_info = read_json_file(ocr_json_file_path)
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pth = Path(ocr_json_file_path)
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@@ -56,8 +57,8 @@ if __name__ == '__main__':
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if not os.path.exists(parent_dir):
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os.makedirs(parent_dir)
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# markdown_content = ocr_mk_nlp_markdown(pdf_info_dict)
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markdown_content = ocr_mk_mm_markdown(pdf_info_dict)
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# markdown_content = mk_nlp_markdown(pdf_info_dict)
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markdown_content = mk_mm_markdown2(pdf_info_dict)
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with open(text_content_save_path, "w", encoding="utf-8") as f:
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f.write(markdown_content)
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@@ -54,6 +54,31 @@ def ocr_mk_mm_markdown(pdf_info_dict: dict):
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markdown.append(line_text.strip() + ' ')
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return '\n'.join(markdown)
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def mk_mm_markdown2(pdf_info_dict:dict):
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markdown = []
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for _, page_info in pdf_info_dict.items():
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paras = page_info.get("para_blocks")
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if not paras:
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continue
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for para in paras:
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para_text = ''
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for line in para:
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for span in line['spans']:
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span_type = span.get('type')
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if span_type == ContentType.Text:
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para_text += span['content']
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elif span_type == ContentType.InlineEquation:
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para_text += f" ${span['content']}$ "
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elif span_type == ContentType.InterlineEquation:
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para_text += f"$$\n{span['content']}\n$$ "
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elif span_type == ContentType.Image:
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para_text += f" "
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markdown.append(para_text)
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return '\n\n'.join(markdown)
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def ocr_mk_mm_standard_format():
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'''
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content_list
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@@ -16,7 +16,8 @@ def get_delta_time(input_time):
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def join_path(*args):
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return '/'.join(s.rstrip('/') for s in args)
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return '/'.join(str(s).rstrip('/') for s in args)
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#配置全局的errlog_path,方便demo同步引用
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error_log_path = "s3://llm-pdf-text/err_logs/"
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206
magic_pdf/para/para_split.py
Normal file
206
magic_pdf/para/para_split.py
Normal file
@@ -0,0 +1,206 @@
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from sklearn.cluster import DBSCAN
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import numpy as np
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from loguru import logger
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from magic_pdf.libs.boxbase import _is_in
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LINE_STOP_FLAG = ['.', '!', '?', '。', '!', '?',":", ":", ")", ")", ";"]
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INLINE_EQUATION = 'inline_equation'
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INTER_EQUATION = "displayed_equation"
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TEXT = "text"
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def __add_line_period(blocks, layout_bboxes):
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"""
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为每行添加句号
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如果这个行
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1. 以行内公式结尾,但没有任何标点符号,此时加个句号,认为他就是段落结尾。
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"""
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for block in blocks:
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for line in block['lines']:
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last_span = line['spans'][-1]
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span_type = last_span['type']
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if span_type in [TEXT, INLINE_EQUATION]:
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span_content = last_span['content'].strip()
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if span_type==INLINE_EQUATION and span_content[-1] not in LINE_STOP_FLAG:
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if span_type in [INLINE_EQUATION, INTER_EQUATION]:
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last_span['content'] = span_content + '.'
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def __valign_lines(blocks, layout_bboxes):
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"""
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对齐行的左侧和右侧。
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扫描行的左侧和右侧,如果x0, x1差距不超过3就强行对齐到所处layout的左右两侧(和layout有一段距离)。
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3是个经验值,TODO,计算得来
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"""
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min_distance = 3
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min_sample = 2
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for layout_box in layout_bboxes:
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blocks_in_layoutbox = [b for b in blocks if _is_in(b['bbox'], layout_box['layout_bbox'])]
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if len(blocks_in_layoutbox)==0:
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continue
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x0_lst = np.array([[line['bbox'][0], 0] for block in blocks_in_layoutbox for line in block['lines']])
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x1_lst = np.array([[line['bbox'][2], 0] for block in blocks_in_layoutbox for line in block['lines']])
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x0_clusters = DBSCAN(eps=min_distance, min_samples=min_sample).fit(x0_lst)
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x1_clusters = DBSCAN(eps=min_distance, min_samples=min_sample).fit(x1_lst)
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x0_uniq_label = np.unique(x0_clusters.labels_)
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x1_uniq_label = np.unique(x1_clusters.labels_)
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x0_2_new_val = {} # 存储旧值对应的新值映射
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x1_2_new_val = {}
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for label in x0_uniq_label:
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if label==-1:
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continue
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x0_index_of_label = np.where(x0_clusters.labels_==label)
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x0_raw_val = x0_lst[x0_index_of_label][:,0]
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x0_new_val = np.min(x0_lst[x0_index_of_label][:,0])
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x0_2_new_val.update({idx: x0_new_val for idx in x0_raw_val})
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for label in x1_uniq_label:
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if label==-1:
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continue
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x1_index_of_label = np.where(x1_clusters.labels_==label)
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x1_raw_val = x1_lst[x1_index_of_label][:,0]
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x1_new_val = np.max(x1_lst[x1_index_of_label][:,0])
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x1_2_new_val.update({idx: x1_new_val for idx in x1_raw_val})
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for block in blocks_in_layoutbox:
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for line in block['lines']:
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x0, x1 = line['bbox'][0], line['bbox'][2]
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if x0 in x0_2_new_val:
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line['bbox'][0] = int(x0_2_new_val[x0])
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if x1 in x1_2_new_val:
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line['bbox'][2] = int(x1_2_new_val[x1])
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# 其余对不齐的保持不动
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# 由于修改了block里的line长度,现在需要重新计算block的bbox
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for block in blocks_in_layoutbox:
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block['bbox'] = [min([line['bbox'][0] for line in block['lines']]),
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min([line['bbox'][1] for line in block['lines']]),
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max([line['bbox'][2] for line in block['lines']]),
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max([line['bbox'][3] for line in block['lines']])]
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def __common_pre_proc(blocks, layout_bboxes):
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"""
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不分语言的,对文本进行预处理
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"""
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__add_line_period(blocks, layout_bboxes)
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__valign_lines(blocks, layout_bboxes)
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def __pre_proc_zh_blocks(blocks, layout_bboxes):
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"""
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对中文文本进行分段预处理
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"""
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pass
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def __pre_proc_en_blocks(blocks, layout_bboxes):
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"""
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对英文文本进行分段预处理
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"""
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pass
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def __group_line_by_layout(blocks, layout_bboxes, lang="en"):
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"""
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每个layout内的行进行聚合
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"""
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# 因为只是一个block一行目前, 一个block就是一个段落
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lines_group = []
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for lyout in layout_bboxes:
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lines = [line for block in blocks if _is_in(block['bbox'], lyout['layout_bbox']) for line in block['lines']]
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lines_group.append(lines)
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return lines_group
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def __split_para_in_layoutbox(lines_group, layout_bboxes, lang="en", char_avg_len=10):
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"""
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lines_group 进行行分段——layout内部进行分段。
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1. 先计算每个group的左右边界。
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2. 然后根据行末尾特征进行分段。
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末尾特征:以句号等结束符结尾。并且距离右侧边界有一定距离。
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"""
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def get_span_text(span):
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c = span.get('content', '')
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if len(c)==0:
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c = span.get('image-path', '')
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return c
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paras = []
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right_tail_distance = 1.5 * char_avg_len
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for lines in lines_group:
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if len(lines)==0:
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continue
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layout_right = max([line['bbox'][2] for line in lines])
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para = [] # 元素是line
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for line in lines:
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line_text = ''.join([get_span_text(span) for span in line['spans']])
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#logger.info(line_text)
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last_span_type = line['spans'][-1]['type']
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if last_span_type in [TEXT, INLINE_EQUATION]:
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last_char = line['spans'][-1]['content'][-1]
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if last_char in LINE_STOP_FLAG or line['bbox'][2] < layout_right - right_tail_distance:
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para.append(line)
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paras.append(para)
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# para_text = ''.join([span['content'] for line in para for span in line['spans']])
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# logger.info(para_text)
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para = []
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else:
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para.append(line)
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else: # 其他,图片、表格、行间公式,各自占一段
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para.append(line)
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paras.append(para)
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# para_text = ''.join([get_span_text(span) for line in para for span in line['spans']])
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# logger.info(para_text)
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para = []
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if len(para)>0:
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paras.append(para)
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# para_text = ''.join([get_span_text(span) for line in para for span in line['spans']])
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# logger.info(para_text)
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para = []
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return paras
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def __do_split(blocks, layout_bboxes, lang="en"):
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"""
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根据line和layout情况进行分段
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先实现一个根据行末尾特征分段的简单方法。
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"""
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"""
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算法思路:
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1. 扫描layout里每一行,找出来行尾距离layout有边界有一定距离的行。
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2. 从上述行中找到末尾是句号等可作为断行标志的行。
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3. 参照上述行尾特征进行分段。
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4. 图、表,目前独占一行,不考虑分段。
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"""
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lines_group = __group_line_by_layout(blocks, layout_bboxes, lang) # block内分段
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layout_paras = __split_para_in_layoutbox(lines_group, layout_bboxes, lang) # block间连接分段
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return layout_paras
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def para_split(blocks, layout_bboxes, lang="en"):
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"""
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根据line和layout情况进行分段
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"""
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__common_pre_proc(blocks, layout_bboxes)
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if lang=='en':
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__do_split(blocks, layout_bboxes, lang)
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elif lang=='zh':
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__do_split(blocks, layout_bboxes, lang)
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splited_blocks = __do_split(blocks, layout_bboxes, lang)
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|
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return splited_blocks
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@@ -257,7 +257,6 @@ def parse_pdf_by_model(
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footnote_bboxes_by_model = parse_footnotes_by_model(page_id, page, model_output_json, md_bookname_save_path, debug_mode=debug_mode)
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# 通过规则识别到的footnote
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footnote_bboxes_by_rule = parse_footnotes_by_rule(remain_text_blocks, page_height, page_id, main_text_font)
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|
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"""进入pdf过滤器,去掉一些不合理的pdf"""
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is_good_pdf, err = pdf_filter(page, remain_text_blocks, table_bboxes, image_bboxes)
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if not is_good_pdf:
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@@ -16,6 +16,7 @@ from magic_pdf.libs.commons import (
|
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from magic_pdf.libs.coordinate_transform import get_scale_ratio
|
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from magic_pdf.libs.ocr_content_type import ContentType
|
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from magic_pdf.libs.safe_filename import sanitize_filename
|
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from magic_pdf.para.para_split import para_split
|
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from magic_pdf.pre_proc.detect_footer_by_model import parse_footers
|
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from magic_pdf.pre_proc.detect_footnote import parse_footnotes_by_model
|
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from magic_pdf.pre_proc.detect_header import parse_headers
|
||||
@@ -31,12 +32,13 @@ from magic_pdf.pre_proc.ocr_span_list_modify import remove_spans_by_bboxes, remo
|
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from magic_pdf.pre_proc.remove_bbox_overlap import remove_overlap_between_bbox
|
||||
|
||||
|
||||
def construct_page_component(blocks, layout_bboxes, page_id, page_w, page_h, layout_tree,
|
||||
def construct_page_component(blocks, para_blocks, layout_bboxes, page_id, page_w, page_h, layout_tree,
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images, tables, interline_equations, inline_equations,
|
||||
dropped_text_block, dropped_image_block, dropped_table_block,
|
||||
need_remove_spans_bboxes_dict):
|
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return_dict = {
|
||||
'preproc_blocks': blocks,
|
||||
"para_blocks": para_blocks, # 分好段落的blocks
|
||||
'layout_bboxes': layout_bboxes,
|
||||
'page_idx': page_id,
|
||||
'page_size': [page_w, page_h],
|
||||
@@ -234,13 +236,13 @@ def parse_pdf_by_ocr(
|
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blocks = merge_lines_to_block(lines)
|
||||
|
||||
# 根据block合并段落
|
||||
|
||||
|
||||
para_blocks = para_split(blocks, layout_bboxes)
|
||||
|
||||
# 获取QA需要外置的list
|
||||
images, tables, interline_equations, inline_equations = get_qa_need_list(blocks)
|
||||
|
||||
# 构造pdf_info_dict
|
||||
page_info = construct_page_component(blocks, layout_bboxes, page_id, page_w, page_h, layout_tree,
|
||||
page_info = construct_page_component(blocks, para_blocks, layout_bboxes, page_id, page_w, page_h, layout_tree,
|
||||
images, tables, interline_equations, inline_equations,
|
||||
dropped_text_block, dropped_image_block, dropped_table_block,
|
||||
need_remove_spans_bboxes_dict)
|
||||
|
||||
@@ -57,7 +57,7 @@ def meta_scan(jso: dict, doc_layout_check=True) -> dict:
|
||||
try:
|
||||
data_source = get_data_source(jso)
|
||||
file_id = jso.get('file_id')
|
||||
book_name = data_source + "/" + file_id
|
||||
book_name = f"{data_source}/{file_id}"
|
||||
|
||||
# 首页存在超量drawing问题
|
||||
# special_pdf_list = ['zlib/zlib_21822650']
|
||||
@@ -103,7 +103,7 @@ def classify_by_type(jso: dict, debug_mode=False) -> dict:
|
||||
pdf_meta = jso.get('pdf_meta')
|
||||
data_source = get_data_source(jso)
|
||||
file_id = jso.get('file_id')
|
||||
book_name = data_source + "/" + file_id
|
||||
book_name = f"{data_source}/{file_id}"
|
||||
total_page = pdf_meta["total_page"]
|
||||
page_width = pdf_meta["page_width_pts"]
|
||||
page_height = pdf_meta["page_height_pts"]
|
||||
@@ -169,7 +169,7 @@ def save_tables_to_s3(jso: dict, debug_mode=False) -> dict:
|
||||
try:
|
||||
data_source = get_data_source(jso)
|
||||
file_id = jso.get('file_id')
|
||||
book_name = data_source + "/" + file_id
|
||||
book_name = f"{data_source}/{file_id}"
|
||||
title = jso.get('title')
|
||||
url_encode_title = quote(title, safe='')
|
||||
if data_source != 'scihub':
|
||||
@@ -262,7 +262,7 @@ def parse_pdf(jso: dict, start_page_id=0, debug_mode=False) -> dict:
|
||||
model_output_json_list = jso.get('doc_layout_result')
|
||||
data_source = get_data_source(jso)
|
||||
file_id = jso.get('file_id')
|
||||
book_name = data_source + "/" + file_id
|
||||
book_name = f"{data_source}/{file_id}"
|
||||
|
||||
# 1.23.22已修复
|
||||
# if debug_mode:
|
||||
@@ -326,7 +326,7 @@ def ocr_parse_pdf(jso: dict, start_page_id=0, debug_mode=False) -> dict:
|
||||
model_output_json_list = jso.get('doc_layout_result')
|
||||
data_source = get_data_source(jso)
|
||||
file_id = jso.get('file_id')
|
||||
book_name = data_source + "/" + file_id
|
||||
book_name = f"{data_source}/{file_id}"
|
||||
try:
|
||||
save_path = "s3://mllm-raw-media/pdf2md_img/"
|
||||
image_s3_config = get_s3_config(save_path)
|
||||
|
||||
Reference in New Issue
Block a user