Update magic_pdf/__init__.py, magic_pdf/config.ini, magic_pdf/tmp.py,...

Update magic_pdf/__init__.py, magic_pdf/config.ini, magic_pdf/tmp.py, magic_pdf/pdf_parse_by_ocr.py, magic_pdf/pdf_parse_by_txt.py, magic_pdf/user_api.py, magic_pdf/pdf_parse_union_core.py, magic_pdf/pdf_parse_union_core_v2.py, magic_pdf/config/__init__.py, magic_pdf/config/enums.py, magic_pdf/config/exceptions.py, magic_pdf/data/__init__.py, magic_pdf/data/schemas.py, magic_pdf/data/dataset.py, magic_pdf/data/utils.py, magic_pdf/data/read_api.py, magic_pdf/data/data_reader_writer/__init__.py, magic_pdf/data/data_reader_writer/base.py, magic_pdf/data/data_reader_writer/filebase.py, magic_pdf/data/data_reader_writer/s3.py, magic_pdf/data/data_reader_writer/multi_bucket_s3.py, magic_pdf/data/io/__init__.py, magic_pdf/data/io/base.py, magic_pdf/data/io/s3.py, magic_pdf/data/io/http.py, magic_pdf/dict2md/__init__.py, magic_pdf/dict2md/ocr_vllm_client.py, magic_pdf/dict2md/ocr_vllm_server.py, magic_pdf/dict2md/ocr_mkcontent.py, magic_pdf/dict2md/mkcontent.py, magic_pdf/dict2md/ocr_server.py, magic_pdf/dict2md/ocr_client.py, magic_pdf/filter/__init__.py, magic_pdf/filter/pdf_classify_by_type.py, magic_pdf/filter/pdf_meta_scan.py, magic_pdf/integrations/__init__.py, magic_pdf/integrations/rag/__init__.py, magic_pdf/integrations/rag/api.py, magic_pdf/integrations/rag/utils.py, magic_pdf/integrations/rag/type.py, magic_pdf/layout/__init__.py, magic_pdf/layout/layout_det_utils.py, magic_pdf/layout/layout_spiler_recog.py, magic_pdf/layout/mcol_sort.py, magic_pdf/layout/layout_sort.py, magic_pdf/layout/bbox_sort.py, magic_pdf/libs/__init__.py, magic_pdf/libs/boxbase.py, magic_pdf/libs/calc_span_stats.py, magic_pdf/libs/clean_memory.py, magic_pdf/libs/convert_utils.py, magic_pdf/libs/detect_language_from_model.py, magic_pdf/libs/coordinate_transform.py, magic_pdf/libs/drop_tag.py, magic_pdf/libs/nlp_utils.py, magic_pdf/libs/ocr_content_type.py, magic_pdf/libs/hash_utils.py, magic_pdf/libs/path_utils.py, magic_pdf/libs/pdf_check.py, magic_pdf/libs/language.py, magic_pdf/libs/markdown_utils.py, magic_pdf/libs/drop_reason.py, magic_pdf/libs/pdf_image_tools.py, magic_pdf/libs/config_reader.py, magic_pdf/libs/Constants.py, magic_pdf/libs/local_math.py, magic_pdf/libs/ModelBlockTypeEnum.py, magic_pdf/libs/draw_bbox.py, magic_pdf/libs/vis_utils.py, magic_pdf/libs/textbase.py, magic_pdf/libs/safe_filename.py, magic_pdf/libs/MakeContentConfig.py, magic_pdf/libs/version.py, magic_pdf/libs/json_compressor.py, magic_pdf/libs/commons.py, magic_pdf/model/__init__.py, magic_pdf/model/doc_analyze_by_custom_model.py, magic_pdf/model/magic_model.py, magic_pdf/model/model_list.py, magic_pdf/model/pp_structure_v2.py, magic_pdf/model/ppTableModel.py, magic_pdf/model/pdf_extract_kit.py, magic_pdf/model/pek_sub_modules/__init__.py, magic_pdf/model/pek_sub_modules/self_modify.py, magic_pdf/model/pek_sub_modules/post_process.py, magic_pdf/model/pek_sub_modules/layoutlmv3/__init__.py, magic_pdf/model/pek_sub_modules/layoutlmv3/backbone.py, magic_pdf/model/pek_sub_modules/layoutlmv3/beit.py, magic_pdf/model/pek_sub_modules/layoutlmv3/deit.py, magic_pdf/model/pek_sub_modules/layoutlmv3/model_init.py, magic_pdf/model/pek_sub_modules/layoutlmv3/visualizer.py, magic_pdf/model/pek_sub_modules/layoutlmv3/rcnn_vl.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/__init__.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/data/__init__.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/data/funsd.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/data/data_collator.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/data/cord.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/data/image_utils.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/data/xfund.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/models/__init__.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/models/layoutlmv3/__init__.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/models/layoutlmv3/tokenization_layoutlmv3.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/models/layoutlmv3/tokenization_layoutlmv3_fast.py, magic_pdf/model/pek_sub_modules/layoutlmv3/layoutlmft/models/layoutlmv3/configuration_layoutlmv3.py, magic_pdf/model/pek_sub_modules/structeqtable/__init__.py, magic_pdf/model/pek_sub_modules/structeqtable/StructTableModel.py, magic_pdf/para/__init__.py, magic_pdf/para/commons.py, magic_pdf/para/draw.py, magic_pdf/para/layout_match_processor.py, magic_pdf/para/raw_processor.py, magic_pdf/para/title_processor.py, magic_pdf/para/para_split.py, magic_pdf/para/denoise.py, magic_pdf/para/block_continuation_processor.py, magic_pdf/para/block_termination_processor.py, magic_pdf/para/para_pipeline.py, magic_pdf/para/para_split_v2.py, magic_pdf/para/para_split_v3.py, magic_pdf/para/stats.py, magic_pdf/para/exceptions.py, magic_pdf/parse/__init__.py, magic_pdf/parse/excel_parse.py, magic_pdf/parse/common_parse.py, magic_pdf/parse/ofd_parse.py, magic_pdf/parse/pdf_client.py, magic_pdf/pipe/__init__.py, magic_pdf/pipe/AbsPipe.py, magic_pdf/pipe/OCRPipe.py, magic_pdf/pipe/TXTPipe.py, magic_pdf/pipe/UNIPipe.py, magic_pdf/post_proc/__init__.py, magic_pdf/post_proc/pdf_post_filter.py, magic_pdf/post_proc/remove_spaces_html.py, magic_pdf/post_proc/remove_footnote.py, magic_pdf/post_proc/detect_para.py, magic_pdf/pre_proc/__init__.py, magic_pdf/pre_proc/post_layout_split.py, magic_pdf/pre_proc/citationmarker_remove.py, magic_pdf/pre_proc/detect_equation.py, magic_pdf/pre_proc/detect_footer_by_model.py, magic_pdf/pre_proc/cut_image.py, magic_pdf/pre_proc/construct_page_dict.py, magic_pdf/pre_proc/ocr_detect_layout.py, magic_pdf/pre_proc/pdf_pre_filter.py, magic_pdf/pre_proc/ocr_dict_merge.py, magic_pdf/pre_proc/ocr_span_list_modify.py, magic_pdf/pre_proc/remove_bbox_overlap.py, magic_pdf/pre_proc/remove_colored_strip_bbox.py, magic_pdf/pre_proc/remove_footer_header.py, magic_pdf/pre_proc/detect_header.py, magic_pdf/pre_proc/detect_page_number.py, magic_pdf/pre_proc/detect_tables.py, magic_pdf/pre_proc/detect_footer_header_by_statistics.py, magic_pdf/pre_proc/detect_footnote.py, magic_pdf/pre_proc/remove_rotate_bbox.py, magic_pdf/pre_proc/resolve_bbox_conflict.py, magic_pdf/pre_proc/solve_line_alien.py, magic_pdf/pre_proc/statistics.py, magic_pdf/pre_proc/detect_images.py, magic_pdf/pre_proc/equations_replace.py, magic_pdf/pre_proc/fix_image.py, magic_pdf/pre_proc/ocr_detect_all_bboxes.py, magic_pdf/pre_proc/fix_table.py, magic_pdf/pre_proc/main_text_font.py, magic_pdf/resources/fasttext-langdetect/lid.176.ftz, magic_pdf/resources/model_config/model_configs.yaml, magic_pdf/resources/model_config/layoutlmv3/layoutlmv3_base_inference.yaml, magic_pdf/resources/model_config/UniMERNet/demo.yaml, magic_pdf/rw/__init__.py, magic_pdf/rw/AbsReaderWriter.py, magic_pdf/rw/DiskReaderWriter.py, magic_pdf/rw/draw_ofd.py, magic_pdf/rw/ofdtemplate.py, magic_pdf/rw/pdf_parse.py, magic_pdf/rw/draw_pdf.py, magic_pdf/rw/S3ReaderWriter.py, magic_pdf/spark/__init__.py, magic_pdf/spark/spark_api.py, magic_pdf/tools/__init__.py, magic_pdf/tools/cli.py, magic_pdf/tools/cli_dev.py, magic_pdf/tools/common.py, magic_pdf/tools/file_deal.py, magic_pdf/tools/img_deal.py, magic_pdf/tools/find_seal_img.py, magic_pdf/tools/font_tools.py, magic_pdf/tools/file_parser.py, magic_pdf/tools/parameter_parser.py, magic_pdf/tools/ofd.py, magic_pdf/tools/pdf_server.py, magic_pdf/tools/ofd_parser.py, magic_pdf/utils/__init__.py, magic_pdf/utils/annotations.py files

magic_pdf/dict2md/mkcontent.py

+import math
+from loguru import logger
+
+from magic_pdf.libs.boxbase import find_bottom_nearest_text_bbox, find_top_nearest_text_bbox
+from magic_pdf.libs.commons import join_path
+from magic_pdf.libs.ocr_content_type import ContentType
+
+TYPE_INLINE_EQUATION = ContentType.InlineEquation
+TYPE_INTERLINE_EQUATION = ContentType.InterlineEquation
+UNI_FORMAT_TEXT_TYPE = ['text', 'h1', 'h2', 'h3', 'h4', 'h5', 'h6']
+
+
+@DeprecationWarning
+def mk_nlp_markdown_1(para_dict: dict):
+    """
+    对排序后的bboxes拼接内容
+    """
+    content_lst = []
+    for _, page_info in para_dict.items():
+        para_blocks = page_info.get("para_blocks")
+        if not para_blocks:
+            continue
+
+        for block in para_blocks:
+            item = block["paras"]
+            for _, p in item.items():
+                para_text = p["para_text"]
+                is_title = p["is_para_title"]
+                title_level = p['para_title_level']
+                md_title_prefix = "#"*title_level
+                if is_title:
+                    content_lst.append(f"{md_title_prefix} {para_text}")
+                else:
+                    content_lst.append(para_text)
+
+    content_text = "\n\n".join(content_lst)
+
+    return content_text
+
+
+
+# 找到目标字符串在段落中的索引
+def __find_index(paragraph, target):
+    index = paragraph.find(target)
+    if index != -1:
+        return index
+    else:
+        return None
+
+
+def __insert_string(paragraph, target, postion):
+    new_paragraph = paragraph[:postion] + target + paragraph[postion:] 
+    return new_paragraph
+
+
+def __insert_after(content, image_content, target):
+    """
+    在content中找到target，将image_content插入到target后面
+    """
+    index = content.find(target)
+    if index != -1:
+        content = content[:index+len(target)] + "\n\n" + image_content + "\n\n" + content[index+len(target):]
+    else:
+        logger.error(f"Can't find the location of image {image_content} in the markdown file, search target is {target}")
+    return content
+
+def __insert_before(content, image_content, target):
+    """
+    在content中找到target，将image_content插入到target前面
+    """
+    index = content.find(target)
+    if index != -1:
+        content = content[:index] + "\n\n" + image_content + "\n\n" + content[index:]
+    else:
+        logger.error(f"Can't find the location of image {image_content} in the markdown file, search target is {target}")
+    return content
+
+
+@DeprecationWarning
+def mk_mm_markdown_1(para_dict: dict):
+    """拼装多模态markdown"""
+    content_lst = []
+    for _, page_info in para_dict.items():
+        page_lst = [] # 一个page内的段落列表
+        para_blocks = page_info.get("para_blocks")
+        pymu_raw_blocks = page_info.get("preproc_blocks")
+        
+        all_page_images = []
+        all_page_images.extend(page_info.get("images",[]))
+        all_page_images.extend(page_info.get("image_backup", []) )
+        all_page_images.extend(page_info.get("tables",[]))
+        all_page_images.extend(page_info.get("table_backup",[]) )
+        
+        if not para_blocks or not pymu_raw_blocks: # 只有图片的拼接的场景
+            for img in all_page_images:
+                page_lst.append(f"![]({img['image_path']})") # TODO 图片顺序
+            page_md = "\n\n".join(page_lst)
+            
+        else:
+            for block in para_blocks:
+                item = block["paras"]
+                for _, p in item.items():
+                    para_text = p["para_text"]
+                    is_title = p["is_para_title"]
+                    title_level = p['para_title_level']
+                    md_title_prefix = "#"*title_level
+                    if is_title:
+                        page_lst.append(f"{md_title_prefix} {para_text}")
+                    else:
+                        page_lst.append(para_text)
+                        
+            """拼装成一个页面的文本"""
+            page_md = "\n\n".join(page_lst)
+            """插入图片"""
+            for img in all_page_images:
+                imgbox = img['bbox']
+                img_content = f"![]({img['image_path']})"
+                # 先看在哪个block内
+                for block in pymu_raw_blocks:
+                    bbox = block['bbox']
+                    if bbox[0]-1 <= imgbox[0] < bbox[2]+1 and bbox[1]-1 <= imgbox[1] < bbox[3]+1:# 确定在block内
+                        for l in block['lines']:
+                            line_box = l['bbox']
+                            if line_box[0]-1 <= imgbox[0] < line_box[2]+1 and line_box[1]-1 <= imgbox[1] < line_box[3]+1: # 在line内的，插入line前面
+                                line_txt = "".join([s['text'] for s in l['spans']])
+                                page_md = __insert_before(page_md, img_content, line_txt)
+                                break
+                            break
+                        else:# 在行与行之间
+                            # 找到图片x0,y0与line的x0,y0最近的line
+                            min_distance = 100000
+                            min_line = None
+                            for l in block['lines']:
+                                line_box = l['bbox']
+                                distance = math.sqrt((line_box[0] - imgbox[0])**2 + (line_box[1] - imgbox[1])**2)
+                                if distance < min_distance:
+                                    min_distance = distance
+                                    min_line = l
+                            if min_line:
+                                line_txt = "".join([s['text'] for s in min_line['spans']])
+                                img_h = imgbox[3] - imgbox[1]
+                                if min_distance<img_h: # 文字在图片前面
+                                    page_md = __insert_after(page_md, img_content, line_txt)
+                                else:
+                                    page_md = __insert_before(page_md, img_content, line_txt)
+                            else:
+                                logger.error(f"Can't find the location of image {img['image_path']} in the markdown file #1")
+                else:# 应当在两个block之间
+                    # 找到上方最近的block，如果上方没有就找大下方最近的block
+                    top_txt_block = find_top_nearest_text_bbox(pymu_raw_blocks, imgbox)
+                    if top_txt_block:
+                        line_txt = "".join([s['text'] for s in top_txt_block['lines'][-1]['spans']])
+                        page_md = __insert_after(page_md, img_content, line_txt)
+                    else:
+                        bottom_txt_block = find_bottom_nearest_text_bbox(pymu_raw_blocks, imgbox)
+                        if bottom_txt_block:
+                            line_txt = "".join([s['text'] for s in bottom_txt_block['lines'][0]['spans']])
+                            page_md = __insert_before(page_md, img_content, line_txt)
+                        else:
+                            logger.error(f"Can't find the location of image {img['image_path']} in the markdown file #2")
+                    
+        content_lst.append(page_md)
+                    
+    """拼装成全部页面的文本"""
+    content_text = "\n\n".join(content_lst)
+
+    return content_text
+
+
+def __insert_after_para(text, type, element, content_list):
+    """
+    在content_list中找到text，将image_path作为一个新的node插入到text后面
+    """
+    for i, c in enumerate(content_list):
+        content_type = c.get("type")
+        if content_type in UNI_FORMAT_TEXT_TYPE and text in c.get("text", ''):
+            if type == "image":
+                content_node = {
+                    "type": "image",
+                    "img_path": element.get("image_path"),
+                    "img_alt": "",
+                    "img_title": "",
+                    "img_caption": "",
+                }
+            elif type == "table":
+                content_node = {
+                    "type": "table",
+                    "img_path": element.get("image_path"),
+                    "table_latex": element.get("text"),
+                    "table_title": "",
+                    "table_caption": "",
+                    "table_quality": element.get("quality"),
+                }
+            content_list.insert(i+1, content_node)
+            break
+    else:
+        logger.error(f"Can't find the location of image {element.get('image_path')} in the markdown file, search target is {text}")
+    
+
+
+def __insert_before_para(text, type, element, content_list):
+    """
+    在content_list中找到text，将image_path作为一个新的node插入到text前面
+    """
+    for i, c in enumerate(content_list):
+        content_type = c.get("type")
+        if content_type in  UNI_FORMAT_TEXT_TYPE and text in c.get("text", ''):
+            if type == "image":
+                content_node = {
+                    "type": "image",
+                    "img_path": element.get("image_path"),
+                    "img_alt": "",
+                    "img_title": "",
+                    "img_caption": "",
+                }
+            elif type == "table":
+                content_node = {
+                    "type": "table",
+                    "img_path": element.get("image_path"),
+                    "table_latex": element.get("text"),
+                    "table_title": "",
+                    "table_caption": "",
+                    "table_quality": element.get("quality"),
+                }
+            content_list.insert(i, content_node)
+            break
+    else:
+        logger.error(f"Can't find the location of image {element.get('image_path')} in the markdown file, search target is {text}")
+         
+
+def mk_universal_format(pdf_info_list: list, img_buket_path):
+    """
+    构造统一格式 https://aicarrier.feishu.cn/wiki/FqmMwcH69iIdCWkkyjvcDwNUnTY
+    """
+    content_lst = []
+    for page_info in pdf_info_list:
+        page_lst = [] # 一个page内的段落列表
+        para_blocks = page_info.get("para_blocks")
+        pymu_raw_blocks = page_info.get("preproc_blocks")
+        
+        all_page_images = []
+        all_page_images.extend(page_info.get("images",[]))
+        all_page_images.extend(page_info.get("image_backup", []) )
+        # all_page_images.extend(page_info.get("tables",[]))
+        # all_page_images.extend(page_info.get("table_backup",[]) )
+        all_page_tables = []
+        all_page_tables.extend(page_info.get("tables", []))
+
+        if not para_blocks or not pymu_raw_blocks: # 只有图片的拼接的场景
+            for img in all_page_images:
+                content_node = {
+                    "type": "image",
+                    "img_path": join_path(img_buket_path, img['image_path']),
+                    "img_alt":"",
+                    "img_title":"",
+                    "img_caption":""
+                }
+                page_lst.append(content_node) # TODO 图片顺序
+            for table in all_page_tables:
+                content_node = {
+                    "type": "table",
+                    "img_path": join_path(img_buket_path, table['image_path']),
+                    "table_latex": table.get("text"),
+                    "table_title": "",
+                    "table_caption": "",
+                    "table_quality": table.get("quality"),
+                }
+                page_lst.append(content_node) # TODO 图片顺序
+        else:
+            for block in para_blocks:
+                item = block["paras"]
+                for _, p in item.items():
+                    font_type = p['para_font_type']# 对于文本来说，要么是普通文本，要么是个行间公式
+                    if font_type == TYPE_INTERLINE_EQUATION:
+                        content_node = {
+                            "type": "equation",
+                            "latex": p["para_text"]
+                        }
+                        page_lst.append(content_node)
+                    else:
+                        para_text = p["para_text"]
+                        is_title = p["is_para_title"]
+                        title_level = p['para_title_level']
+                        
+                        if is_title:
+                            content_node = {
+                                "type": f"h{title_level}",
+                                "text": para_text
+                            }
+                            page_lst.append(content_node)
+                        else:
+                            content_node = {
+                                "type": "text",
+                                "text": para_text
+                            }
+                            page_lst.append(content_node)
+                            
+        content_lst.extend(page_lst)
+        
+        """插入图片"""
+        for img in all_page_images:
+            insert_img_or_table("image", img, pymu_raw_blocks, content_lst)
+
+        """插入表格"""
+        for table in all_page_tables:
+            insert_img_or_table("table", table, pymu_raw_blocks, content_lst)
+    # end for
+    return content_lst
+
+
+def insert_img_or_table(type, element, pymu_raw_blocks, content_lst):
+    element_bbox = element['bbox']
+    # 先看在哪个block内
+    for block in pymu_raw_blocks:
+        bbox = block['bbox']
+        if bbox[0] - 1 <= element_bbox[0] < bbox[2] + 1 and bbox[1] - 1 <= element_bbox[1] < bbox[
+            3] + 1:  # 确定在这个大的block内，然后进入逐行比较距离
+            for l in block['lines']:
+                line_box = l['bbox']
+                if line_box[0] - 1 <= element_bbox[0] < line_box[2] + 1 and line_box[1] - 1 <= element_bbox[1] < line_box[
+                    3] + 1:  # 在line内的，插入line前面
+                    line_txt = "".join([s['text'] for s in l['spans']])
+                    __insert_before_para(line_txt, type, element, content_lst)
+                    break
+                break
+            else:  # 在行与行之间
+                # 找到图片x0,y0与line的x0,y0最近的line
+                min_distance = 100000
+                min_line = None
+                for l in block['lines']:
+                    line_box = l['bbox']
+                    distance = math.sqrt((line_box[0] - element_bbox[0]) ** 2 + (line_box[1] - element_bbox[1]) ** 2)
+                    if distance < min_distance:
+                        min_distance = distance
+                        min_line = l
+                if min_line:
+                    line_txt = "".join([s['text'] for s in min_line['spans']])
+                    img_h = element_bbox[3] - element_bbox[1]
+                    if min_distance < img_h:  # 文字在图片前面
+                        __insert_after_para(line_txt, type, element, content_lst)
+                    else:
+                        __insert_before_para(line_txt, type, element, content_lst)
+                    break
+                else:
+                    logger.error(f"Can't find the location of image {element.get('image_path')} in the markdown file #1")
+    else:  # 应当在两个block之间
+        # 找到上方最近的block，如果上方没有就找大下方最近的block
+        top_txt_block = find_top_nearest_text_bbox(pymu_raw_blocks, element_bbox)
+        if top_txt_block:
+            line_txt = "".join([s['text'] for s in top_txt_block['lines'][-1]['spans']])
+            __insert_after_para(line_txt, type, element, content_lst)
+        else:
+            bottom_txt_block = find_bottom_nearest_text_bbox(pymu_raw_blocks, element_bbox)
+            if bottom_txt_block:
+                line_txt = "".join([s['text'] for s in bottom_txt_block['lines'][0]['spans']])
+                __insert_before_para(line_txt, type, element, content_lst)
+            else:  # TODO ，图片可能独占一列，这种情况上下是没有图片的
+                logger.error(f"Can't find the location of image {element.get('image_path')} in the markdown file #2")
+
+
+def mk_mm_markdown(content_list):
+    """
+    基于同一格式的内容列表，构造markdown，含图片
+    """
+    content_md = []
+    for c in content_list:
+        content_type = c.get("type")
+        if content_type == "text":
+            content_md.append(c.get("text"))
+        elif content_type == "equation":
+            content = c.get("latex")
+            if content.startswith("$$") and content.endswith("$$"):
+                content_md.append(content)
+            else:
+                content_md.append(f"\n$$\n{c.get('latex')}\n$$\n")
+        elif content_type in UNI_FORMAT_TEXT_TYPE:
+            content_md.append(f"{'#'*int(content_type[1])} {c.get('text')}")
+        elif content_type == "image":
+            content_md.append(f"![]({c.get('img_path')})")
+    return "\n\n".join(content_md)
+
+def mk_nlp_markdown(content_list):
+    """
+    基于同一格式的内容列表，构造markdown，不含图片
+    """
+    content_md = []
+    for c in content_list:
+        content_type = c.get("type")
+        if content_type == "text":
+            content_md.append(c.get("text"))
+        elif content_type == "equation":
+            content_md.append(f"$$\n{c.get('latex')}\n$$")
+        elif content_type == "table":
+            content_md.append(f"$$$\n{c.get('table_latex')}\n$$$")
+        elif content_type in UNI_FORMAT_TEXT_TYPE:
+            content_md.append(f"{'#'*int(content_type[1])} {c.get('text')}")
+    return "\n\n".join(content_md)
\ No newline at end of file

magic_pdf/dict2md/ocr_client.py

+import configparser
+import os
+import json
+import requests
+from loguru import logger
+import argparse
+import time
+from PIL import Image
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        '--config_path',
+        default='/home/practice/magic_pdf-main/magic_pdf/config.ini',
+    )
+    parser.add_argument(
+        '--image_path',
+        default='/home/wanglch/projects/Qwen2-VL/20240920-163701.png',
+    )
+    parser.add_argument(
+        '--text',
+        default="描述你在图片中看到的内容",
+    )
+    args = parser.parse_args()
+    return args
+
+
+def parse_text(text):
+    lines = text.split("\n")
+    lines = [line for line in lines if line.strip() != ""]  # 去除空行
+    count = 0
+    parsed_lines = []
+
+    for i, line in enumerate(lines):
+        if "```" in line:
+            count += 1
+            items = line.split("`")
+            if count % 2 == 1:
+                # 开始代码块
+                parsed_lines.append(f'<pre><code class="language-{items[-1]}">')
+            else:
+                # 结束代码块
+                parsed_lines.append(f"</code></pre>")
+        else:
+            if i > 0 and count % 2 == 1:
+                # 转义代码块内的特殊字符
+                line = line.replace("`", r"\`")
+                line = line.replace("<", "&lt;")
+                line = line.replace(">", "&gt;")
+                line = line.replace(" ", "&nbsp;")
+                line = line.replace("*", "&ast;")
+                line = line.replace("_", "&lowbar;")
+                line = line.replace("-", "&#45;")
+                line = line.replace(".", "&#46;")
+                line = line.replace("!", "&#33;")
+                line = line.replace("(", "&#40;")
+                line = line.replace(")", "&#41;")
+                line = line.replace("$", "&#36;")
+            # 使用空格连接行
+            if parsed_lines:
+                parsed_lines[-1] += " " + line
+            else:
+                parsed_lines.append(line)
+
+    text = "".join(parsed_lines)
+    return text
+
+
+def unparse_text(parsed_text):
+    in_code_block = False
+    lines = parsed_text.split("\n")
+    unparsed_lines = []
+
+    for line in lines:
+        if "<pre><code" in line:
+            in_code_block = True
+            # 移除开始标签
+            line = line.split(">", 1)[1]
+        elif "</code></pre>" in line:
+            in_code_block = False
+            # 移除结束标签
+            line = line.rsplit("<", 1)[0]
+
+        # 反转 HTML 实体
+        line = line.replace("&lt;", "<")
+        line = line.replace("&gt;", ">")
+        line = line.replace("&nbsp;", " ")
+        line = line.replace("&ast;", "*")
+        line = line.replace("&lowbar;", "_")
+        line = line.replace("&#45;", "-")
+        line = line.replace("&#46;", ".")
+        line = line.replace("&#33;", "!")
+        line = line.replace("&#40;", "(")
+        line = line.replace("&#41;", ")")
+        line = line.replace("&#36;", "$")
+
+        # 如果在代码块内，还原反斜杠转义
+        if in_code_block:
+            line = line.replace(r"\`", "`")
+
+        unparsed_lines.append(line)
+
+    # 合并所有行
+    unparsed_text = "\n".join(unparsed_lines)
+    return unparsed_text
+
+
+def compress_image(image_path, max_size=(1024, 1024)):
+    img = Image.open(image_path)
+    width, height = img.size
+    aspect_ratio = width / height
+
+    if width > max_size[0] or height > max_size[1]:
+        if width > height:
+            new_width = max_size[0]
+            new_height = int(new_width / aspect_ratio)
+        else:
+            new_height = max_size[1]
+            new_width = int(new_height * aspect_ratio)
+
+        img = img.resize((new_width, new_height), Image.LANCZOS)
+        img.save(image_path, optimize=True, quality=80)
+
+
+class PredictClient:
+    def __init__(self, api_url):
+        self.api_url = api_url
+
+    def check_health(self):
+        health_check_url = f'{self.api_url}/health'
+        try:
+            response = requests.get(health_check_url)
+            if response.status_code == 200:
+                logger.info("Server is healthy and ready to process requests.")
+                return True
+            else:
+                logger.error(f'Server health check failed with status code:{response.status_code}')
+                return False
+        except requests.exceptions.RequestException as e:
+            logger.error(f'Health check request failed:{e}')
+            return False
+
+
+    def predict(self, image_path: str, text: str):
+        payload = {
+            "image_path": image_path,
+            "text": text
+        }
+        headers = {'Content-Type': 'application/json'}
+        response = requests.post(f"{self.api_url}/predict", json=payload, headers=headers)
+
+        if response.status_code == 200:
+            result = response.json()
+            return result.get('Generated Text', '')
+        else:
+            raise Exception(f"Predict API request failed with status code {response.status_code}")
+
+
+def main():
+    args = parse_args()
+
+    config = configparser.ConfigParser()
+    config.read(args.config_path)
+    ocr_server = config.get('server', 'ocr_server')
+    client = PredictClient(ocr_server)
+    try:
+        start_time = time.time()  # 记录开始时间
+        # 压缩图片
+        #compress_image(args.image_path)
+
+        generated_text = client.predict(args.image_path, parse_text(args.text))
+        end_time = time.time()  # 记录结束时间
+        elapsed_time = end_time - start_time  # 计算运行时间
+
+        if generated_text:
+            clean_text = unparse_text(generated_text)  # 解析生成的文本
+            logger.info(f"Image Path: {args.image_path}")
+            logger.info(f"Generated Text: {clean_text}")
+            logger.info(f"耗时为: {elapsed_time}秒")  # 打印运行时间
+        else:
+            logger.warning("Received empty generated text.")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Error while making request to predict service: {e}")
+    except Exception as e:
+        logger.error(f"Unexpected error occurred: {e}")
+
+
+if __name__ == "__main__":
+    main()

magic_pdf/dict2md/ocr_mkcontent.py

+import re
+
+from loguru import logger
+
+from magic_pdf.libs.commons import join_path
+from magic_pdf.libs.language import detect_lang
+from magic_pdf.libs.MakeContentConfig import DropMode, MakeMode
+from magic_pdf.libs.markdown_utils import ocr_escape_special_markdown_char
+from magic_pdf.libs.ocr_content_type import BlockType, ContentType
+from magic_pdf.para.para_split_v3 import ListLineTag
+
+
+def __is_hyphen_at_line_end(line):
+    """
+    Check if a line ends with one or more letters followed by a hyphen.
+    
+    Args:
+    line (str): The line of text to check.
+    
+    Returns:
+    bool: True if the line ends with one or more letters followed by a hyphen, False otherwise.
+    """
+    # Use regex to check if the line ends with one or more letters followed by a hyphen
+    return bool(re.search(r'[A-Za-z]+-\s*$', line))
+
+
+def ocr_mk_mm_markdown_with_para_and_pagination(pdf_info_dict: list,
+                                                img_buket_path):
+    markdown_with_para_and_pagination = []
+    page_no = 0
+    for page_info in pdf_info_dict:
+        paras_of_layout = page_info.get('para_blocks')
+        if not paras_of_layout:
+            continue
+        page_markdown = ocr_mk_markdown_with_para_core_v2(
+            paras_of_layout, 'mm', img_buket_path)
+        markdown_with_para_and_pagination.append({
+            'page_no':
+                page_no,
+            'md_content':
+                '\n\n'.join(page_markdown)
+        })
+        page_no += 1
+    return markdown_with_para_and_pagination
+
+
+def ocr_mk_markdown_with_para_core_v2(paras_of_layout,
+                                      mode,
+                                      img_buket_path='',
+                                      ):
+    page_markdown = []
+    for para_block in paras_of_layout:
+        para_text = ''
+        para_type = para_block['type']
+        if para_type in [BlockType.Text, BlockType.List, BlockType.Index]:
+            para_text = merge_para_with_text(para_block)
+        elif para_type == BlockType.Title:
+            para_text = f'# {merge_para_with_text(para_block)}'
+        elif para_type == BlockType.InterlineEquation:
+            para_text = merge_para_with_text(para_block)
+        elif para_type == BlockType.Image:
+            if mode == 'nlp':
+                continue
+            elif mode == 'mm':
+                for block in para_block['blocks']:  # 1st.拼image_body
+                    if block['type'] == BlockType.ImageBody:
+                        for line in block['lines']:
+                            for span in line['spans']:
+                                if span['type'] == ContentType.Image:
+                                    if span.get('image_path', ''):
+                                        para_text += f"\n"
+                for block in para_block['blocks']:  # 2nd.拼image_caption
+                    if block['type'] == BlockType.ImageCaption:
+                        para_text += merge_para_with_text(block) + '  \n'
+                for block in para_block['blocks']:  # 3rd.拼image_footnote
+                    if block['type'] == BlockType.ImageFootnote:
+                        para_text += merge_para_with_text(block) + '  \n'
+        elif para_type == BlockType.Table:
+            if mode == 'nlp':
+                continue
+            elif mode == 'mm':
+                for block in para_block['blocks']:  # 1st.拼table_caption
+                    if block['type'] == BlockType.TableCaption:
+                        para_text += merge_para_with_text(block) + '  \n'
+                for block in para_block['blocks']:  # 2nd.拼table_body
+                    if block['type'] == BlockType.TableBody:
+                        for line in block['lines']:
+                            for span in line['spans']:
+                                if span['type'] == ContentType.Table:
+                                    # if processed by table model
+                                    if span.get('latex', ''):
+                                        para_text += f"\n\n$\n {span['latex']}\n$\n\n"
+                                    elif span.get('html', ''):
+                                        para_text += f"\n\n{span['html']}\n\n"
+                                    elif span.get('image_path', ''):
+                                        para_text += span['image_path']
+                for block in para_block['blocks']:  # 3rd.拼table_footnote
+                    if block['type'] == BlockType.TableFootnote:
+                        para_text += merge_para_with_text(block) + '  \n'
+
+        if para_text.strip() == '':
+            continue
+        else:
+            page_markdown.append(para_text.strip() + '  ')
+
+    return page_markdown
+
+
+def detect_language(text):
+    en_pattern = r'[a-zA-Z]+'
+    en_matches = re.findall(en_pattern, text)
+    en_length = sum(len(match) for match in en_matches)
+    if len(text) > 0:
+        if en_length / len(text) >= 0.5:
+            return 'en'
+        else:
+            return 'unknown'
+    else:
+        return 'empty'
+
+
+def merge_para_with_text(para_block):
+    para_text = ''
+    for i, line in enumerate(para_block['lines']):
+
+        if i >= 1 and line.get(ListLineTag.IS_LIST_START_LINE, False):
+            para_text += '  \n'
+
+        line_text = ''
+        line_lang = ''
+        for span in line['spans']:
+            span_type = span['type']
+            if span_type == ContentType.Text:
+                line_text += span['content'].strip()
+        if line_text != '':
+            line_lang = detect_lang(line_text)
+        for span in line['spans']:
+
+            span_type = span['type']
+            content = ''
+            if span_type == ContentType.Text:
+                content = ocr_escape_special_markdown_char(span['content'])
+            elif span_type == ContentType.InlineEquation:
+                content = f" ${span['content']}$ "
+            elif span_type == ContentType.InterlineEquation:
+                content = f"\n$$\n{span['content']}\n$$\n"
+
+            if content != '':
+                langs = ['zh', 'ja', 'ko']
+                if line_lang in langs:  # 遇到一些一个字一个span的文档，这种单字语言判断不准，需要用整行文本判断
+                    para_text += content  # 中文/日语/韩文语境下，content间不需要空格分隔
+                elif line_lang == 'en':
+                    # 如果是前一行带有-连字符，那么末尾不应该加空格
+                    if __is_hyphen_at_line_end(content):
+                        para_text += content[:-1]
+                    else:
+                        para_text += content + ' '
+                else:
+                    para_text += content + ' '  # 西方文本语境下 content间需要空格分隔
+    return para_text
+
+
+def para_to_standard_format_v2(para_block, img_buket_path, page_idx, drop_reason=None):
+    para_type = para_block['type']
+    para_content = {}
+    if para_type in [BlockType.Text, BlockType.List, BlockType.Index]:
+        para_content = {
+            'type': 'text',
+            'text': merge_para_with_text(para_block),
+        }
+    elif para_type == BlockType.Title:
+        para_content = {
+            'type': 'text',
+            'text': merge_para_with_text(para_block),
+            'text_level': 1,
+        }
+    elif para_type == BlockType.InterlineEquation:
+        para_content = {
+            'type': 'equation',
+            'text': merge_para_with_text(para_block),
+            'text_format': 'latex',
+        }
+    elif para_type == BlockType.Image:
+        para_content = {'type': 'image', 'img_path': '', 'img_caption': [], 'img_footnote': []}
+        for block in para_block['blocks']:
+            if block['type'] == BlockType.ImageBody:
+                for line in block['lines']:
+                    for span in line['spans']:
+                        if span['type'] == ContentType.Image:
+                            if span.get('image_path', ''):
+                                para_content['img_path'] = join_path(img_buket_path, span['image_path'])
+            if block['type'] == BlockType.ImageCaption:
+                para_content['img_caption'].append(merge_para_with_text(block))
+            if block['type'] == BlockType.ImageFootnote:
+                para_content['img_footnote'].append(merge_para_with_text(block))
+    elif para_type == BlockType.Table:
+        para_content = {'type': 'table', 'img_path': '', 'table_caption': [], 'table_footnote': []}
+        for block in para_block['blocks']:
+            if block['type'] == BlockType.TableBody:
+                for line in block['lines']:
+                    for span in line['spans']:
+                        if span['type'] == ContentType.Table:
+
+                            if span.get('latex', ''):
+                                para_content['table_body'] = f"\n\n$\n {span['latex']}\n$\n\n"
+                            elif span.get('html', ''):
+                                para_content['table_body'] = f"\n\n{span['html']}\n\n"
+
+                            if span.get('image_path', ''):
+                                para_content['img_path'] = join_path(img_buket_path, span['image_path'])
+
+            if block['type'] == BlockType.TableCaption:
+                para_content['table_caption'].append(merge_para_with_text(block))
+            if block['type'] == BlockType.TableFootnote:
+                para_content['table_footnote'].append(merge_para_with_text(block))
+
+    para_content['page_idx'] = page_idx
+
+    if drop_reason is not None:
+        para_content['drop_reason'] = drop_reason
+
+    return para_content
+
+
+def union_make(pdf_info_dict: list,
+               make_mode: str,
+               drop_mode: str,
+               img_buket_path: str = '',
+               ):
+    output_content = []
+    for page_info in pdf_info_dict:
+        drop_reason_flag = False
+        drop_reason = None
+        if page_info.get('need_drop', False):
+            drop_reason = page_info.get('drop_reason')
+            if drop_mode == DropMode.NONE:
+                pass
+            elif drop_mode == DropMode.NONE_WITH_REASON:
+                drop_reason_flag = True
+            elif drop_mode == DropMode.WHOLE_PDF:
+                raise Exception((f'drop_mode is {DropMode.WHOLE_PDF} ,'
+                                 f'drop_reason is {drop_reason}'))
+            elif drop_mode == DropMode.SINGLE_PAGE:
+                logger.warning((f'drop_mode is {DropMode.SINGLE_PAGE} ,'
+                                f'drop_reason is {drop_reason}'))
+                continue
+            else:
+                raise Exception('drop_mode can not be null')
+
+        paras_of_layout = page_info.get('para_blocks')
+        page_idx = page_info.get('page_idx')
+        if not paras_of_layout:
+            continue
+        if make_mode == MakeMode.MM_MD:
+            page_markdown = ocr_mk_markdown_with_para_core_v2(
+                paras_of_layout, 'mm', img_buket_path)
+            output_content.extend(page_markdown)
+        elif make_mode == MakeMode.NLP_MD:
+            page_markdown = ocr_mk_markdown_with_para_core_v2(
+                paras_of_layout, 'nlp')
+            output_content.extend(page_markdown)
+        elif make_mode == MakeMode.STANDARD_FORMAT:
+            for para_block in paras_of_layout:
+                if drop_reason_flag:
+                    para_content = para_to_standard_format_v2(
+                        para_block, img_buket_path, page_idx)
+                else:
+                    para_content = para_to_standard_format_v2(
+                        para_block, img_buket_path, page_idx)
+                output_content.append(para_content)
+    if make_mode in [MakeMode.MM_MD, MakeMode.NLP_MD]:
+        return '\n\n'.join(output_content)
+    elif make_mode == MakeMode.STANDARD_FORMAT:
+        return output_content

magic_pdf/dict2md/ocr_server.py

+# Copyright (c) Alibaba Cloud.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree
+import configparser
+import copy
+import re
+import gc
+import time
+
+import torch
+from argparse import ArgumentParser
+from threading import Thread
+from qwen_vl_utils import process_vision_info
+from transformers import AutoProcessor, Qwen2VLForConditionalGeneration, TextIteratorStreamer
+
+from fastapi import FastAPI
+from pydantic import BaseModel
+from typing import Optional
+from loguru import logger
+
+app = FastAPI()
+
+DEFAULT_CKPT_PATH = '/home/practice/model/Qwen2-VL-7B-Instruct'
+REVISION = 'v1.0.4'
+BOX_TAG_PATTERN = r"<box>([\s\S]*?)</box>"
+PUNCTUATION = "！？。＂＃＄％＆＇（）＊＋，－／：；＜＝＞＠［＼］＾＿｀｛｜｝～｟｠｢｣､、〃》「」『』【】〔〕〖〗〘〙〚〛〜〝〞〟〰〾〿–—‘’‛“”„‟…‧﹏."
+
+logger.add("parse.log", rotation="10 MB", level="INFO",
+           format="{time} {level} {message}", encoding='utf-8', enqueue=True)
+
+def _get_args():
+    parser = ArgumentParser()
+
+    parser.add_argument('-c', '--checkpoint_path', type=str, default=DEFAULT_CKPT_PATH,
+                        help='Checkpoint name or path, default to %(default)r')
+    parser.add_argument('--cpu_only', action='store_true', help='Run demo with CPU only')
+    parser.add_argument('--flash_attn2', action='store_true', default=False,
+                        help='Enable flash_attention_2 when loading the model.')
+    parser.add_argument('--share', action='store_true', default=False,
+                        help='Create a publicly shareable link for the interface.')
+    parser.add_argument('--inbrowser', action='store_true', default=False,
+                        help='Automatically launch the interface in a new tab on the default browser.')
+    parser.add_argument('--dcu_id', type=str, default='0', help='Specify the GPU ID to load the model onto.')
+    parser.add_argument(
+        '--config_path',
+        default='/home/practice/magic_pdf-main/magic_pdf/config.ini',
+        )
+    args = parser.parse_args()
+    return args
+
+
+def _load_model_processor(args):
+    if args.cpu_only:
+        device_map = 'cpu'
+    else:
+        if args.dcu_id is not None:
+            device_map = {'': f'cuda:{args.dcu_id}'}
+            print('使用DCU推理:', f'cuda:{args.dcu_id}')
+        else:
+            device_map = 'auto'
+
+    if args.flash_attn2:
+        model = Qwen2VLForConditionalGeneration.from_pretrained(
+            args.checkpoint_path,
+            torch_dtype=torch.float16,
+            attn_implementation='flash_attention_2',
+            device_map=device_map
+        )
+    else:
+        model = Qwen2VLForConditionalGeneration.from_pretrained(
+            args.checkpoint_path,
+            torch_dtype=torch.float16,
+            device_map=device_map
+        )
+
+    processor = AutoProcessor.from_pretrained(args.checkpoint_path)
+    return model, processor
+
+
+def _parse_text(text):
+    lines = text.split("\n")
+    lines = [line for line in lines if line.strip() != ""]  # 去除空行
+    count = 0
+    parsed_lines = []
+
+    for i, line in enumerate(lines):
+        if "```" in line:
+            count += 1
+            items = line.split("`")
+            if count % 2 == 1:
+                # 开始代码块
+                parsed_lines.append(f'<pre><code class="language-{items[-1]}">')
+            else:
+                # 结束代码块
+                parsed_lines.append(f"</code></pre>")
+        else:
+            if i > 0 and count % 2 == 1:
+                # 转义代码块内的特殊字符
+                line = line.replace("`", r"\`")
+                line = line.replace("<", "&lt;")
+                line = line.replace(">", "&gt;")
+                line = line.replace(" ", "&nbsp;")
+                line = line.replace("*", "&ast;")
+                line = line.replace("_", "&lowbar;")
+                line = line.replace("-", "&#45;")
+                line = line.replace(".", "&#46;")
+                line = line.replace("!", "&#33;")
+                line = line.replace("(", "&#40;")
+                line = line.replace(")", "&#41;")
+                line = line.replace("$", "&#36;")
+            # 使用空格连接行
+            if parsed_lines:
+                parsed_lines[-1] += " " + line
+            else:
+                parsed_lines.append(line)
+
+    text = "".join(parsed_lines)
+    return text
+
+
+def _remove_image_special(text):
+    text = text.replace('<ref>', '').replace('</ref>', '')
+    return re.sub(r'<box>.*?(</box>|$)', '', text)
+
+
+def _is_video_file(filename):
+    video_extensions = ['.mp4', '.avi', '.mkv', '.mov', '.wmv', '.flv', '.webm', '.mpeg']
+    return any(filename.lower().endswith(ext) for ext in video_extensions)
+
+
+def _transform_messages(original_messages):
+    transformed_messages = []
+    for message in original_messages:
+        new_content = []
+        for item in message['content']:
+            if 'image' in item:
+                new_item = {'type': 'image', 'image': item['image']}
+            elif 'text' in item:
+                new_item = {'type': 'text', 'text': item['text']}
+            elif 'video' in item:
+                new_item = {'type': 'video', 'video': item['video']}
+            else:
+                continue
+            new_content.append(new_item)
+
+        new_message = {'role': message['role'], 'content': new_content}
+        transformed_messages.append(new_message)
+
+    return transformed_messages
+
+
+def _gc():
+    gc.collect()
+    if torch.cuda.is_available():
+        torch.cuda.empty_cache()
+
+
+def call_local_model(model, processor, messages):
+    messages = _transform_messages(messages)
+
+    text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    image_inputs, video_inputs = process_vision_info(messages)
+    inputs = processor(text=[text], images=image_inputs, videos=video_inputs, padding=True, return_tensors='pt')
+    inputs = inputs.to(model.device)
+
+    tokenizer = processor.tokenizer
+    streamer = TextIteratorStreamer(tokenizer, timeout=20.0, skip_prompt=True, skip_special_tokens=True)
+
+    gen_kwargs = {'max_new_tokens': 512, 'streamer': streamer, **inputs}
+
+    thread = Thread(target=model.generate, kwargs=gen_kwargs)
+    thread.start()
+
+    generated_text = ''
+    for new_text in streamer:
+        generated_text += new_text
+        yield _parse_text(generated_text)
+
+
+def create_predict_fn(model, processor):
+    def predict(_chatbot, task_history):
+        chat_query = _chatbot[-1][0]
+        query = task_history[-1][0]
+        if len(chat_query) == 0:
+            _chatbot.pop()
+            task_history.pop()
+            return _chatbot
+        print('User: ' + _parse_text(query))
+        history_cp = copy.deepcopy(task_history)
+        full_response = ''
+        messages = []
+        content = []
+        for q, a in history_cp:
+            if isinstance(q, (tuple, list)):
+                if _is_video_file(q[0]):
+                    content.append({'video': f'file://{q[0]}'})
+                else:
+                    content.append({'image': f'file://{q[0]}'})
+            else:
+                content.append({'text': q})
+                messages.append({'role': 'user', 'content': content})
+                messages.append({'role': 'assistant', 'content': [{'text': a}]})
+                content = []
+        messages.pop()
+
+        for response in call_local_model(model, processor, messages):
+            _chatbot[-1] = (_parse_text(chat_query), _remove_image_special(_parse_text(response)))
+
+            yield _chatbot
+            full_response = _parse_text(response)
+
+        task_history[-1] = (query, full_response)
+        print('Qwen-VL-Chat: ' + _parse_text(full_response))
+        yield _chatbot
+
+    return predict
+
+
+# 启用加载模型
+args = _get_args()
+model, processor = _load_model_processor(args)
+
+
+class Item(BaseModel):
+    image_path: str
+    text: str
+
+@app.get("/health")
+async def health_check():
+    return {"status": "healthy"}
+
+
+@app.post("/predict")
+async def predict(item: Item):
+    messages = [
+        {
+            'role': 'user',
+            'content': [
+                {'image': item.image_path},
+                {'text': item.text}
+            ]
+        }
+    ]
+    start = time.time()
+    generated_text = ''
+    for response in call_local_model(model, processor, messages):
+        generated_text = _parse_text(response)
+
+    _gc()
+    end = time.time()
+    logger.info(f'【{item.image_path}】解析的结果是：{generated_text},耗时为：{end-start}')
+    return {"Generated Text": generated_text}
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    args = _get_args()
+    config = configparser.ConfigParser()
+    config.read(args.config_path)
+    # host = config.get('server', 'ocr_host')
+    host, port = config.get('server', 'ocr_server').split('://')[1].split(':')[0], int(
+        config.get('server', 'ocr_server').split('://')[1].split(':')[1])
+    # port = int(config.get('server', 'ocr_port'))
+    uvicorn.run(app, host=host, port=port)
+
+
+

magic_pdf/dict2md/ocr_vllm_client.py

+import os
+import json
+import requests
+from loguru import logger
+import argparse
+import time
+from PIL import Image
+import configparser
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        '--config_path',
+        default='/home/practice/magic_pdf-main/magic_pdf/config.ini',
+    )
+    parser.add_argument(
+        '--image_path',
+        default='/path/to/your/image.png',
+        help='Path to the image file'
+    )
+    parser.add_argument(
+        '--text',
+        default="描述你在图片中看到的内容",
+        help='Text input for the model'
+    )
+    args = parser.parse_args()
+    return args
+
+
+def parse_text(text):
+    lines = text.split("\n")
+    lines = [line for line in lines if line.strip() != ""]  # 去除空行
+    count = 0
+    parsed_lines = []
+
+    for i, line in enumerate(lines):
+        if "```" in line:
+            count += 1
+            items = line.split("`")
+            if count % 2 == 1:
+                # 开始代码块
+                parsed_lines.append(f'<pre><code class="language-{items[-1]}">')
+            else:
+                # 结束代码块
+                parsed_lines.append(f"</code></pre>")
+        else:
+            if i > 0 and count % 2 == 1:
+                # 转义代码块内的特殊字符
+                line = line.replace("`", r"\`")
+                line = line.replace("<", "&lt;")
+                line = line.replace(">", "&gt;")
+                line = line.replace(" ", "&nbsp;")
+                line = line.replace("*", "&ast;")
+                line = line.replace("_", "&lowbar;")
+                line = line.replace("-", "&#45;")
+                line = line.replace(".", "&#46;")
+                line = line.replace("!", "&#33;")
+                line = line.replace("(", "&#40;")
+                line = line.replace(")", "&#41;")
+                line = line.replace("$", "&#36;")
+            # 使用空格连接行
+            if parsed_lines:
+                parsed_lines[-1] += " " + line
+            else:
+                parsed_lines.append(line)
+
+    text = "".join(parsed_lines)
+    return text
+
+
+def unparse_text(parsed_text):
+    in_code_block = False
+    lines = parsed_text.split("\n")
+    unparsed_lines = []
+
+    for line in lines:
+        if "<pre><code" in line:
+            in_code_block = True
+            # 移除开始标签
+            line = line.split(">", 1)[1]
+        elif "</code></pre>" in line:
+            in_code_block = False
+            # 移除结束标签
+            line = line.rsplit("<", 1)[0]
+
+        # 反转 HTML 实体
+        line = line.replace("&lt;", "<")
+        line = line.replace("&gt;", ">")
+        line = line.replace("&nbsp;", " ")
+        line = line.replace("&ast;", "*")
+        line = line.replace("&lowbar;", "_")
+        line = line.replace("&#45;", "-")
+        line = line.replace("&#46;", ".")
+        line = line.replace("&#33;", "!")
+        line = line.replace("&#40;", "(")
+        line = line.replace("&#41;", ")")
+        line = line.replace("&#36;", "$")
+
+        # 如果在代码块内，还原反斜杠转义
+        if in_code_block:
+            line = line.replace(r"\`", "`")
+
+        unparsed_lines.append(line)
+
+    # 合并所有行
+    unparsed_text = "\n".join(unparsed_lines)
+    return unparsed_text
+
+
+def compress_image(image_path, max_size=(512, 512)):
+    img = Image.open(image_path)
+    width, height = img.size
+    aspect_ratio = width / height
+
+    if width > max_size[0] or height > max_size[1]:
+        if width > height:
+            new_width = max_size[0]
+            new_height = int(new_width / aspect_ratio)
+        else:
+            new_height = max_size[1]
+            new_width = int(new_height * aspect_ratio)
+
+        img = img.resize((new_width, new_height), Image.LANCZOS)
+        img.save(image_path, optimize=True, quality=80)
+
+
+class PredictClient:
+    def __init__(self, api_url):
+        self.api_url = api_url
+
+    def check_health(self):
+        health_check_url = f'{self.api_url}/health'
+        try:
+            response = requests.get(health_check_url)
+            if response.status_code == 200:
+                logger.info("Server is healthy and ready to process requests.")
+                return True
+            else:
+                logger.error(f'Server health check failed with status code:{response.status_code}')
+                return False
+        except requests.exceptions.RequestException as e:
+            logger.error(f'Health check request failed:{e}')
+            return False
+
+    def predict(self, image_path: str, text: str):
+        payload = {
+            "image_path": image_path,
+            "text": text
+        }
+        headers = {'Content-Type': 'application/json'}
+        response = requests.post(f"{self.api_url}/predict", json=payload, headers=headers)
+
+        if response.status_code == 200:
+            result = response.json()
+            return result.get('Generated Text', '')
+        else:
+            raise Exception(f"Predict API request failed with status code {response.status_code}")
+
+
+def main():
+    args = parse_args()
+    config = configparser.ConfigParser()
+    config.read(args.config_path)
+    ocr_server = config.get('server', 'ocr_server')
+    client = PredictClient(ocr_server)
+
+    try:
+        start_time = time.time()  # 记录开始时间
+        # 压缩图片
+        compress_image(args.image_path)
+
+        generated_text = client.predict(args.image_path, parse_text(args.text))
+        end_time = time.time()  # 记录结束时间
+        elapsed_time = end_time - start_time  # 计算运行时间
+
+        if generated_text:
+            clean_text = unparse_text(generated_text)  # 解析生成的文本
+            logger.info(f"Image Path: {args.image_path}")
+            logger.info(f"Generated Text: {clean_text}")
+            logger.info(f"耗时为: {elapsed_time}秒")  # 打印运行时间
+        else:
+            logger.warning("Received empty generated text.")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Error while making request to predict service: {e}")
+    except Exception as e:
+        logger.error(f"Unexpected error occurred: {e}")
+
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file

magic_pdf/dict2md/ocr_vllm_server.py

+# Copyright (c) Alibaba Cloud.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree
+
+import copy
+import re
+import gc
+import torch
+from argparse import ArgumentParser
+from threading import Thread
+from qwen_vl_utils import process_vision_info
+from transformers import AutoProcessor
+from vllm import LLM, SamplingParams
+import os
+import configparser
+
+from fastapi import FastAPI
+from pydantic import BaseModel
+from typing import Optional
+
+app = FastAPI()
+
+DEFAULT_CKPT_PATH = '/home/practice/model/Qwen2-VL-7B-Instruct'
+REVISION = 'v1.0.4'
+BOX_TAG_PATTERN = r"<box>([\s\S]*?)</box>"
+PUNCTUATION = "！？。＂＃＄％＆＇（）＊＋，－／：；＜＝＞＠［＼］＾＿｀｛｜｝～｟｠｢｣､、〃》「」『』【】〔〕〖〗〘〙〚〛〜〝〞〟〰〾〿–—‘’‛“”„‟…‧﹏."
+
+
+def get_args():
+    parser = ArgumentParser()
+
+    parser.add_argument('-c', '--checkpoint_path', type=str, default=DEFAULT_CKPT_PATH,
+                        help='Checkpoint name or path, default to %(default)r')
+    parser.add_argument('--cpu_only', default=False, action='store_true', help='Run demo with CPU only')
+    parser.add_argument('--flash_attn2', action='store_true', default=False,
+                        help='Enable flash_attention_2 when loading the model.')
+    parser.add_argument('--share', action='store_true', default=False,
+                        help='Create a publicly shareable link for the interface.')
+    parser.add_argument('--inbrowser', action='store_true', default=False,
+                        help='Automatically launch the interface in a new tab on the default browser.')
+    parser.add_argument('--gpu_nums', type=int, default=1, help='Number of GPUs to use for tensor parallelism.')
+    parser.add_argument('--dcu_id', type=str, default='0', help='Specify the GPU ID to load the model onto.')
+    parser.add_argument(
+        '--config_path',
+        default='/home/practice/magic_pdf-main/magic_pdf/config.ini',
+    )
+    args = parser.parse_args()
+    return args
+
+
+def load_model_processor(args):
+    if args.cpu_only:
+        device = 'cpu'
+    else:
+        os.environ['CUDA_VISIBLE_DEVICES'] = args.dcu_id
+        print(f"Visible CUDA devices: {os.environ.get('CUDA_VISIBLE_DEVICES')}")
+
+    llm = LLM(
+        model=args.checkpoint_path,
+        limit_mm_per_prompt={"image": 10, "video": 10},
+        trust_remote_code=True,
+        tensor_parallel_size=args.gpu_nums,  # 用args.gpu_nums根据实际情况调整
+        gpu_memory_utilization=0.99,
+        dtype='float16',  # 或者 'bfloat16'
+    )
+
+    processor = AutoProcessor.from_pretrained(args.checkpoint_path)
+    return llm, processor
+
+
+def parse_text(text):
+    lines = text.split("\n")
+    lines = [line for line in lines if line.strip() != ""]  # 去除空行
+    count = 0
+    parsed_lines = []
+
+    for i, line in enumerate(lines):
+        if "```" in line:
+            count += 1
+            items = line.split("`")
+            if count % 2 == 1:
+                # 开始代码块
+                parsed_lines.append(f'<pre><code class="language-{items[-1]}">')
+            else:
+                # 结束代码块
+                parsed_lines.append(f"</code></pre>")
+        else:
+            if i > 0 and count % 2 == 1:
+                # 转义代码块内的特殊字符
+                line = line.replace("`", r"\`")
+                line = line.replace("<", "&lt;")
+                line = line.replace(">", "&gt;")
+                line = line.replace(" ", "&nbsp;")
+                line = line.replace("*", "&ast;")
+                line = line.replace("_", "&lowbar;")
+                line = line.replace("-", "&#45;")
+                line = line.replace(".", "&#46;")
+                line = line.replace("!", "&#33;")
+                line = line.replace("(", "&#40;")
+                line = line.replace(")", "&#41;")
+                line = line.replace("$", "&#36;")
+            # 使用空格连接行
+            if parsed_lines:
+                parsed_lines[-1] += " " + line
+            else:
+                parsed_lines.append(line)
+
+    text = "".join(parsed_lines)
+    return text
+
+
+def unparse_text(parsed_text):
+    in_code_block = False
+    lines = parsed_text.split("\n")
+    unparsed_lines = []
+
+    for line in lines:
+        if "<pre><code" in line:
+            in_code_block = True
+            # 移除开始标签
+            line = line.split(">", 1)[1]
+        elif "</code></pre>" in line:
+            in_code_block = False
+            # 移除结束标签
+            line = line.rsplit("<", 1)[0]
+
+        # 反转 HTML 实体
+        line = line.replace("&lt;", "<")
+        line = line.replace("&gt;", ">")
+        line = line.replace("&nbsp;", " ")
+        line = line.replace("&ast;", "*")
+        line = line.replace("&lowbar;", "_")
+        line = line.replace("&#45;", "-")
+        line = line.replace("&#46;", ".")
+        line = line.replace("&#33;", "!")
+        line = line.replace("&#40;", "(")
+        line = line.replace("&#41;", ")")
+        line = line.replace("&#36;", "$")
+
+        # 如果在代码块内，还原反斜杠转义
+        if in_code_block:
+            line = line.replace(r"\`", "`")
+
+        unparsed_lines.append(line)
+
+    # 合并所有行
+    unparsed_text = "\n".join(unparsed_lines)
+    return unparsed_text
+
+
+def remove_image_special(text):
+    text = text.replace('<ref>', '').replace('</ref>', '')
+    return re.sub(r'<box>.*?(</box>|$)', '', text)
+
+
+def is_video_file(filename):
+    video_extensions = ['.mp4', '.avi', '.mkv', '.mov', '.wmv', '.flv', '.webm', '.mpeg']
+    return any(filename.lower().endswith(ext) for ext in video_extensions)
+
+
+def transform_messages(original_messages):
+    transformed_messages = []
+    for message in original_messages:
+        new_content = []
+        for item in message['content']:
+            if 'image' in item:
+                new_item = {'type': 'image', 'image': item['image']}
+            elif 'text' in item:
+                new_item = {'type': 'text', 'text': item['text']}
+            elif 'video' in item:
+                new_item = {'type': 'video', 'video': item['video']}
+            else:
+                continue
+            new_content.append(new_item)
+
+        new_message = {'role': message['role'], 'content': new_content}
+        transformed_messages.append(new_message)
+
+    return transformed_messages
+
+
+def _gc():
+    gc.collect()
+    if torch.cuda.is_available():
+        torch.cuda.empty_cache()
+
+
+def call_local_model(llm, processor, messages):
+    messages = transform_messages(messages)
+
+    text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    image_inputs, video_inputs = process_vision_info(messages)
+    mm_data = {}
+    if image_inputs is not None:
+        mm_data["image"] = image_inputs
+    if video_inputs is not None:
+        mm_data["video"] = video_inputs
+
+    llm_inputs = {
+        "prompt": text,
+        "multi_modal_data": mm_data,
+    }
+
+    sampling_params = SamplingParams(
+        temperature=0.1,
+        top_p=0.001,
+        repetition_penalty=1.05,
+        max_tokens=256,
+        stop_token_ids=[],
+    )
+
+    outputs = llm.generate([llm_inputs], sampling_params=sampling_params)
+    generated_text = outputs[0].outputs[0].text
+
+    yield parse_text(generated_text)
+
+
+def create_predict_fn(llm, processor):
+    def predict(_chatbot, task_history):
+        chat_query = _chatbot[-1][0]
+        query = task_history[-1][0]
+        if len(chat_query) == 0:
+            _chatbot.pop()
+            task_history.pop()
+            return _chatbot
+        print('User: ' + parse_text(query))
+        history_cp = copy.deepcopy(task_history)
+        full_response = ''
+        messages = []
+        content = []
+        for q, a in history_cp:
+            if isinstance(q, (tuple, list)):
+                if is_video_file(q[0]):
+                    content.append({'video': f'file://{q[0]}'})
+                else:
+                    content.append({'image': f'file://{q[0]}'})
+            else:
+                content.append({'text': q})
+                messages.append({'role': 'user', 'content': content})
+                messages.append({'role': 'assistant', 'content': [{'text': a}]})
+                content = []
+        messages.pop()
+
+        for response in call_local_model(llm, processor, messages):
+            _chatbot[-1] = (parse_text(chat_query), remove_image_special(parse_text(response)))
+
+            yield _chatbot
+            full_response = parse_text(response)
+
+        task_history[-1] = (query, full_response)
+        print('Qwen-VL-Chat: ' + unparse_text(full_response))
+        yield _chatbot
+
+    return predict
+
+
+# 启用加载模型
+args = get_args()
+llm, processor = load_model_processor(args)
+
+
+class Item(BaseModel):
+    image_path: str
+    text: str
+
+
+@app.get("/health")
+async def health_check():
+    return {"status": "healthy"}
+
+
+@app.post("/predict")
+async def predict(item: Item):
+    messages = [
+        {
+            'role': 'user',
+            'content': [
+                {'image': item.image_path},
+                {'text': item.text}
+            ]
+        }
+    ]
+
+    generated_text = ''
+    for response in call_local_model(llm, processor, messages):
+        generated_text = unparse_text(response)
+
+    _gc()
+
+    return {"Generated Text": generated_text}
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    args = get_args()
+    config = configparser.ConfigParser()
+    config.read(args.config_path)
+    # host = config.get('server', 'ocr_host')
+    host, port = config.get('server', 'ocr_server').split('://')[1].split(':')[0], int(
+        config.get('server', 'ocr_server').split('://')[1].split(':')[1])
+    # port = int(config.get('server', 'ocr_port'))
+    uvicorn.run(app, host=host, port=port)
\ No newline at end of file

magic_pdf/filter/pdf_classify_by_type.py

+"""
+根据利用meta_scan得到的结果，对pdf是否为文字版进行分类。
+定义标准：
+一、什么pdf会是文字pdf，只要满足以下任意一条
+  1. 随机抽取N页，如果有任何一页文字数目大于100
+  2. 只要存在一个页面，图片的数量为0
+二、什么是扫描版pdf，只要满足以下任意一条
+  1. ~~80%页面上的最大图大小一样并且面积超过页面面积0.6~~
+  2. 大部分页面上文字的长度都是相等的。
+
+"""
+import json
+import sys
+from collections import Counter
+
+import click
+import numpy as np
+from loguru import logger
+
+from magic_pdf.libs.commons import mymax, get_top_percent_list
+from magic_pdf.filter.pdf_meta_scan import scan_max_page, junk_limit_min
+
+TEXT_LEN_THRESHOLD = 100
+AVG_TEXT_LEN_THRESHOLD = 100
+TEXT_LEN_SAMPLE_RATIO = 0.1  # 抽取0.1的页面进行文字长度统计
+
+
+# 一个拼接图片的方案，将某些特殊扫描版本的拆图拼成一张整图
+def merge_images(image_list, page_width, page_height, max_offset=5, max_gap=2):
+    # 先通过set去除所有bbox重叠的图片数据
+    image_list_result = []
+    for page_images in image_list:
+        page_result = []
+        dedup = set()
+        for img in page_images:
+            x0, y0, x1, y1, img_bojid = img
+            if (x0, y0, x1, y1) in dedup:  # 这里面会出现一些重复的bbox，无需重复出现，需要去掉
+                continue
+            else:
+                dedup.add((x0, y0, x1, y1))
+                page_result.append([x0, y0, x1, y1, img_bojid])
+        image_list_result.append(page_result)
+
+    # 接下来，将同一页可拼接的图片进行合并
+    merged_images = []
+    for page_images in image_list_result:
+        if not page_images:
+            continue
+
+        # 先将同一页的图片从上到下，从左到右进行排序
+        page_images.sort(key=lambda img: (img[1], img[0]))
+
+        merged = [page_images[0]]
+
+        for img in page_images[1:]:
+            x0, y0, x1, y1, imgid = img
+
+            last_img = merged[-1]
+            last_x0, last_y0, last_x1, last_y1, last_imgid = last_img
+
+            # 单张图片宽或者高覆盖页面宽高的9成以上是拼图的一个前置条件
+            full_width = abs(x1 - x0) >= page_width * 0.9
+            full_height = abs(y1 - y0) >= page_height * 0.9
+
+            # 如果宽达标，检测是否能竖着拼
+            if full_width:
+                # 竖着拼需要满足两个前提，左右边界各偏移不能超过 max_offset，第一张图的下边界和第二张图的上边界偏移不能超过 max_gap
+                close1 = (last_x0 - max_offset) <= x0 <= (last_x0 + max_offset) and (last_x1 - max_offset) <= x1 <= (
+                            last_x1 + max_offset) and (last_y1 - max_gap) <= y0 <= (last_y1 + max_gap)
+
+            # 如果高达标，检测是否可以横着拼
+            if full_height:
+                # 横着拼需要满足两个前提，上下边界各偏移不能超过 max_offset，第一张图的右边界和第二张图的左边界偏移不能超过 max_gap
+                close2 = (last_y0 - max_offset) <= y0 <= (last_y0 + max_offset) and (last_y1 - max_offset) <= y1 <= (
+                            last_y1 + max_offset) and (last_x1 - max_gap) <= x0 <= (last_x1 + max_gap)
+
+            # Check if the image can be merged with the last image
+            if (full_width and close1) or (full_height and close2):
+                # Merge the image with the last image
+                merged[-1] = [min(x0, last_x0), min(y0, last_y0),
+                              max(x1, last_x1), max(y1, last_y1), imgid]
+            else:
+                # Add the image as a new image
+                merged.append(img)
+
+        merged_images.append(merged)
+
+    return merged_images
+
+
+def classify_by_area(total_page: int, page_width, page_height, img_sz_list, text_len_list: list):
+    """
+    80%页面上的最大图大小一样并且面积超过页面面积0.6则返回False，否则返回True
+    :param pdf_path:
+    :param total_page:
+    :param page_width:
+    :param page_height:
+    :param img_sz_list:
+    :return:
+    """
+    # # 只要有一页没有图片，那么就是文字pdf。但是同时还需要满足一个条件就是这个页面上同时不能有文字。发现过一些扫描版pdf，上面有一些空白页面，既没有图片也没有文字。
+    # if any([len(img_sz) == 0 for img_sz in img_sz_list]):  # 含有不含图片的页面
+    #     # 现在找到这些页面的index
+    #     empty_page_index = [i for i, img_sz in enumerate(img_sz_list) if len(img_sz) == 0]
+    #     # 然后检查这些页面上是否有文字
+    #     text_len_at_page_idx = [text_len for i, text_len in enumerate(text_len_list) if i in empty_page_index and text_len > 0]
+    #     if len(text_len_at_page_idx) > TEXT_LEN_THRESHOLD:  # 没有图片，但是有文字，说明可能是个文字版，如果没有文字则无法判断，留给下一步,现在要求这页文字量超过一定阈值
+    #         return True
+
+    # 通过objid去掉重复出现10次以上的图片，这些图片是隐藏的透明图层，其特点是id都一样
+    # 先对每个id出现的次数做个统计
+    objid_cnt = Counter([objid for page_img_sz in img_sz_list for _, _, _, _, objid in page_img_sz])
+    # 再去掉出现次数大于10的
+    if total_page >= scan_max_page:  # 新的meta_scan只扫描前 scan_max_page 页，页数大于 scan_max_page 当total_page为 scan_max_page
+        total_page = scan_max_page
+
+    repeat_threshold = 2  # 把bad_image的阈值设为2
+    # repeat_threshold = min(2, total_page)  # 当total_page为1时，repeat_threshold为1，会产生误判导致所有img变成bad_img
+    bad_image_objid = set([objid for objid, cnt in objid_cnt.items() if cnt >= repeat_threshold])
+    # bad_image_page_idx = [i for i, page_img_sz in enumerate(img_sz_list) if any([objid in bad_image_objid for _, _, _, _, objid in page_img_sz])]
+    # text_len_at_bad_image_page_idx = [text_len for i, text_len in enumerate(text_len_list) if i in bad_image_page_idx and text_len > 0]
+
+    # 特殊情况，一个文字版pdf，每页覆盖一个超大的透明图片,超大的定义是图片占整页面积的90%以上
+    # fake_image_ids = [objid for objid in bad_image_objid if
+    #                   any([abs((x1 - x0) * (y1 - y0) / page_width * page_height) > 0.9 for images in img_sz_list for
+    #                        x0, y0, x1, y1, _ in images])]  # 原来的代码，any里面恒为true了，原因？？？
+    # fake_image_ids = [objid for objid in bad_image_objid for images in img_sz_list for x0, y0, x1, y1, img_id in images
+    #                   if img_id == objid and abs((x1 - x0) * (y1 - y0)) / (page_width * page_height) > 0.9]
+
+    # if len(fake_image_ids) > 0 and any([l > TEXT_LEN_THRESHOLD for l in text_len_at_bad_image_page_idx]):  # 这些透明图片所在的页面上有文字大于阈值
+    #     return True
+
+    img_sz_list = [[img_sz for img_sz in page_img_sz if img_sz[-1] not in bad_image_objid] for page_img_sz in
+                   img_sz_list]  # 过滤掉重复出现的图片
+
+    # 有的扫描版会把一页图片拆成很多张，需要先把图拼起来再计算
+    img_sz_list = merge_images(img_sz_list, page_width, page_height)
+
+    # 计算每个页面上最大的图的面积，然后计算这个面积占页面面积的比例
+    max_image_area_per_page = [mymax([(x1 - x0) * (y1 - y0) for x0, y0, x1, y1, _ in page_img_sz]) for page_img_sz in
+                               img_sz_list]
+    page_area = page_width * page_height
+    max_image_area_per_page = [area / page_area for area in max_image_area_per_page]
+    max_image_area_per_page = [area for area in max_image_area_per_page if area > 0.5]
+
+    if len(max_image_area_per_page) >= 0.5 * total_page:  # 阈值从0.8改到0.5，适配3页里面有两页和两页里面有一页的情况
+        # 这里条件成立的前提是把反复出现的图片去掉了。这些图片是隐藏的透明图层，其特点是id都一样
+        return False
+    else:
+        return True
+
+
+def classify_by_text_len(text_len_list: list, total_page: int):
+    """
+    随机抽取10%的页面，如果少于5个页面，那么就取全部页面。
+    查看页面上的文字长度，如果有任何一个页面的文字长度大于TEXT_LEN_THRESHOLD，那么就是文字pdf
+    :param total_page:
+    :param text_len_list:
+    :return:
+    """
+    select_page_cnt = int(total_page * TEXT_LEN_SAMPLE_RATIO)  # 选取10%的页面
+    if select_page_cnt < 5:
+        select_page_cnt = total_page
+
+    # # 排除头尾各10页
+    # if total_page > 20:  # 如果总页数大于20
+    #     page_range = list(range(10, total_page - 10))  # 从第11页到倒数第11页
+    # else:
+    #     page_range = list(range(total_page))  # 否则选择所有页面
+    # page_num = np.random.choice(page_range, min(select_page_cnt, len(page_range)), replace=False)
+    # 排除前后10页对只有21，22页的pdf很尴尬，如果选出来的中间那一两页恰好没字容易误判，有了avg_words规则，这个规则可以忽略
+    page_num = np.random.choice(total_page, select_page_cnt, replace=False)
+    text_len_lst = [text_len_list[i] for i in page_num]
+    is_text_pdf = any([text_len > TEXT_LEN_THRESHOLD for text_len in text_len_lst])
+    return is_text_pdf
+
+
+def classify_by_avg_words(text_len_list: list):
+    """
+    补充规则，如果平均每页字数少于 AVG_TEXT_LEN_THRESHOLD，就不是文字pdf
+    主要是各种图集
+    :param text_len_list:
+    :return:
+    """
+    sum_words = sum(text_len_list)
+    count_of_numbers = len(text_len_list)
+    if count_of_numbers == 0:
+        is_text_pdf = False
+    else:
+        avg_words = round(sum_words / count_of_numbers)
+        if avg_words > AVG_TEXT_LEN_THRESHOLD:
+            is_text_pdf = True
+        else:
+            is_text_pdf = False
+
+    return is_text_pdf
+
+
+def classify_by_img_num(img_sz_list: list, img_num_list: list):
+    """
+    补充规则，有一种扫描版本的PDF，每一页都会放所有的扫描页进去，在 metascan 时会被去重，
+    这种pdf的 metasca 扫描结果的特点是 img_sz_list 内全是空元素，img_num_list中每一页的数量都很大且相同
+    :param img_sz_list:
+    :param img_num_list:
+    :return:
+    """
+    # 计算img_sz_list中非空元素的个数
+    count_img_sz_list_not_none = sum(1 for item in img_sz_list if item)
+    # 获取前80%的元素
+    top_eighty_percent = get_top_percent_list(img_num_list, 0.8)
+    # img_sz_list中非空元素的个数小于1，前80%的元素都相等，且最大值大于等于junk_limit_min
+    if count_img_sz_list_not_none <= 1 and len(set(top_eighty_percent)) == 1 and max(img_num_list) >= junk_limit_min:
+
+        #拿max和min的值,用来判断list内的值是否全都相等
+        # min_imgs = min(img_num_list)
+        # max_imgs = max(img_num_list)
+        #
+        # if count_img_sz_list_not_none == 0 and max_imgs == min_imgs and max_imgs >= junk_limit_min:
+        return False  # 如果满足这个条件，一定不是文字版pdf
+    else:
+        return True  # 不满足这三个条件，可能是文字版pdf，通过其他规则判断
+
+
+def classify_by_text_layout(text_layout_per_page: list):
+    """
+    判断文本布局是否以竖排为主。
+
+    Args:
+        text_layout_per_page (list): 文本布局列表，列表中的每个元素表示一页的文本布局，
+                                     值为'vertical'表示竖排，值为'horizontal'表示横排。
+
+    Returns:
+        bool: 若文本布局以竖排为主，则返回False；否则返回True。
+    """
+    # 统计text_layout_per_page中竖排的个数
+    count_vertical = sum(1 for item in text_layout_per_page if item == 'vertical')
+    # 统计text_layout_per_page中横排的个数
+    count_horizontal = sum(1 for item in text_layout_per_page if item == 'horizontal')
+    # 计算text_layout_per_page中竖排的占比
+    known_layout_cnt = count_vertical + count_horizontal
+    if known_layout_cnt != 0:
+        ratio = count_vertical / known_layout_cnt
+        if ratio >= 0.5:  # 阈值设为0.5，适配3页里面有2页和两页里有一页的情况
+            return False  # 文本布局以竖排为主，认为不是文字版pdf
+        else:
+            return True  # 文本布局以横排为主，认为是文字版pdf
+    else:
+        return False  # 文本布局未知，默认认为不是文字版pdf
+
+
+def classify_by_img_narrow_strips(page_width, page_height, img_sz_list):
+    """
+    判断一页是否由细长条组成，有两个条件：
+    1. 图片的宽或高达到页面宽或高的90%，且长边需要是窄边长度的数倍以上
+    2. 整个页面所有的图片有80%以上满足条件1
+
+    Args:
+        page_width (float): 页面宽度
+        page_height (float): 页面高度
+        img_sz_list (list): 图片尺寸列表，每个元素为一个元组，表示图片的矩形区域和尺寸，形如(x0, y0, x1, y1, size)，其中(x0, y0)为矩形区域的左上角坐标，(x1, y1)为矩形区域的右下角坐标，size为图片的尺寸
+
+    Returns:
+        bool: 如果满足条件的页面的比例小于0.5，返回True，否则返回False
+    """
+
+    def is_narrow_strip(img):
+        x0, y0, x1, y1, _ = img
+        width, height = x1 - x0, y1 - y0
+        return any([
+            # 图片宽度大于等于页面宽度的90%，且宽度大于等于高度4倍
+            width >= page_width * 0.9 and width >= height * 4,
+            # 图片高度大于等于页面高度的90%，且高度大于等于宽度4倍
+            height >= page_height * 0.9 and height >= width * 4,
+        ])
+
+    # 初始化满足条件的页面数量
+    narrow_strip_pages_count = 0
+
+    # 遍历所有页面
+    for page_img_list in img_sz_list:
+        # 忽略空页面
+        if not page_img_list:
+            continue
+
+        # 计算页面中的图片总数
+        total_images = len(page_img_list)
+
+        # 计算页面中细长条图片的数量
+        narrow_strip_images_count = 0
+        for img in page_img_list:
+            if is_narrow_strip(img):
+                narrow_strip_images_count += 1
+        # 如果细长条图片的数量少于5，跳过
+        if narrow_strip_images_count < 5:
+            continue
+        else:
+            # 如果细长条图片的比例大于或等于0.8，增加满足条件的页面数量
+            if narrow_strip_images_count / total_images >= 0.8:
+                narrow_strip_pages_count += 1
+
+    # 计算满足条件的页面的比例
+    narrow_strip_pages_ratio = narrow_strip_pages_count / len(img_sz_list)
+
+    return narrow_strip_pages_ratio < 0.5
+
+
+def classify(total_page: int, page_width, page_height, img_sz_list: list, text_len_list: list, img_num_list: list,
+             text_layout_list: list, invalid_chars: bool):
+    """
+    这里的图片和页面长度单位是pts
+    :param total_page:
+    :param text_len_list:
+    :param page_width:
+    :param page_height:
+    :param img_sz_list:
+    :param pdf_path:
+    :return:
+    """
+    results = {
+        'by_image_area': classify_by_area(total_page, page_width, page_height, img_sz_list, text_len_list),
+        'by_text_len': classify_by_text_len(text_len_list, total_page),
+        'by_avg_words': classify_by_avg_words(text_len_list),
+        'by_img_num': classify_by_img_num(img_sz_list, img_num_list),
+        'by_text_layout': classify_by_text_layout(text_layout_list),
+        'by_img_narrow_strips': classify_by_img_narrow_strips(page_width, page_height, img_sz_list),
+        'by_invalid_chars': invalid_chars,
+    }
+
+    if all(results.values()):
+        return True, results
+    elif not any(results.values()):
+        return False, results
+    else:
+        logger.warning(
+            f"pdf is not classified by area and text_len, by_image_area: {results['by_image_area']},"
+            f" by_text: {results['by_text_len']}, by_avg_words: {results['by_avg_words']}, by_img_num: {results['by_img_num']},"
+            f" by_text_layout: {results['by_text_layout']}, by_img_narrow_strips: {results['by_img_narrow_strips']},"
+            f" by_invalid_chars: {results['by_invalid_chars']}",
+            file=sys.stderr)  # 利用这种情况可以快速找出来哪些pdf比较特殊，针对性修正分类算法
+        return False, results
+
+
+@click.command()
+@click.option("--json-file", type=str, help="pdf信息")
+def main(json_file):
+    if json_file is None:
+        print("json_file is None", file=sys.stderr)
+        exit(0)
+    try:
+        with open(json_file, "r") as f:
+            for l in f:
+                if l.strip() == "":
+                    continue
+                o = json.loads(l)
+                total_page = o["total_page"]
+                page_width = o["page_width_pts"]
+                page_height = o["page_height_pts"]
+                img_sz_list = o["image_info_per_page"]
+                text_len_list = o['text_len_per_page']
+                text_layout_list = o['text_layout_per_page']
+                pdf_path = o['pdf_path']
+                is_encrypted = o['is_encrypted']
+                is_needs_password = o['is_needs_password']
+                if is_encrypted or total_page == 0 or is_needs_password:  # 加密的，需要密码的，没有页面的，都不处理
+                    continue
+                tag = classify(total_page, page_width, page_height, img_sz_list, text_len_list, text_layout_list)
+                o['is_text_pdf'] = tag
+                print(json.dumps(o, ensure_ascii=False))
+    except Exception as e:
+        print("ERROR: ", e, file=sys.stderr)
+
+
+if __name__ == "__main__":
+    main()
+    # false = False
+    # true = True
+    # null = None
+    # o = 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1.6","title":"","author":"","subject":"","keywords":"","creator":"Adobe Acrobat 7.0","producer":"Adobe Acrobat 7.0 Image Conversion Plug-in","creationDate":"D:20080404141457+01'00'","modDate":"D:20080404144821+01'00'","trapped":"","encryption":null}}
+    # o = json.loads(json.dumps(o))
+    # total_page = o["total_page"]
+    # page_width = o["page_width_pts"]
+    # page_height = o["page_height_pts"]
+    # img_sz_list = o["image_info_per_page"]
+    # text_len_list = o['text_len_per_page']
+    # pdf_path = o['pdf_path']
+    # is_encrypted = o['is_encrypted']
+    # is_needs_password = o['is_needs_password']
+    # if is_encrypted or total_page == 0 or is_needs_password:  # 加密的，需要密码的，没有页面的，都不处理
+    #     print("加密的")
+    #     exit(0)
+    # tag = classify(pdf_path, total_page, page_width, page_height, img_sz_list, text_len_list)
+    # o['is_text_pdf'] = tag
+    # print(json.dumps(o, ensure_ascii=False))

magic_pdf/filter/pdf_meta_scan.py

+"""
+输入： s3路径，每行一个
+输出： pdf文件元信息，包括每一页上的所有图片的长宽高，bbox位置
+"""
+import sys
+import click
+
+from magic_pdf.libs.commons import read_file, mymax, get_top_percent_list
+from magic_pdf.libs.commons import fitz
+from loguru import logger
+from collections import Counter
+
+from magic_pdf.libs.drop_reason import DropReason
+from magic_pdf.libs.language import detect_lang
+from magic_pdf.libs.pdf_check import detect_invalid_chars
+
+scan_max_page = 50
+junk_limit_min = 10
+
+
+def calculate_max_image_area_per_page(result: list, page_width_pts, page_height_pts):
+    max_image_area_per_page = [mymax([(x1 - x0) * (y1 - y0) for x0, y0, x1, y1, _ in page_img_sz]) for page_img_sz in
+                               result]
+    page_area = int(page_width_pts) * int(page_height_pts)
+    max_image_area_per_page = [area / page_area for area in max_image_area_per_page]
+    max_image_area_per_page = [area for area in max_image_area_per_page if area > 0.6]
+    return max_image_area_per_page
+
+
+def process_image(page, junk_img_bojids=[]):
+    page_result = []  # 存每个页面里的多张图四元组信息
+    items = page.get_images()
+    dedup = set()
+    for img in items:
+        # 这里返回的是图片在page上的实际展示的大小。返回一个数组，每个元素第一部分是
+        img_bojid = img[0]  # 在pdf文件中是全局唯一的，如果这个图反复出现在pdf里那么就可能是垃圾信息，例如水印、页眉页脚等
+        if img_bojid in junk_img_bojids:  # 如果是垃圾图像，就跳过
+            continue
+        recs = page.get_image_rects(img, transform=True)
+        if recs:
+            rec = recs[0][0]
+            x0, y0, x1, y1 = map(int, rec)
+            width = x1 - x0
+            height = y1 - y0
+            if (x0, y0, x1, y1, img_bojid) in dedup:  # 这里面会出现一些重复的bbox，无需重复出现，需要去掉
+                continue
+            if not all([width, height]):  # 长和宽任何一个都不能是0，否则这个图片不可见，没有实际意义
+                continue
+            dedup.add((x0, y0, x1, y1, img_bojid))
+            page_result.append([x0, y0, x1, y1, img_bojid])
+    return page_result
+
+
+def get_image_info(doc: fitz.Document, page_width_pts, page_height_pts) -> list:
+    """
+    返回每个页面里的图片的四元组，每个页面多个图片。
+    :param doc:
+    :return:
+    """
+    # 使用 Counter 计数 img_bojid 的出现次数
+    img_bojid_counter = Counter(img[0] for page in doc for img in page.get_images())
+    # 找出出现次数超过 len(doc) 半数的 img_bojid
+
+    junk_limit = max(len(doc) * 0.5, junk_limit_min)  # 对一些页数比较少的进行豁免
+
+    junk_img_bojids = [img_bojid for img_bojid, count in img_bojid_counter.items() if count >= junk_limit]
+
+    #todo 加个判断，用前十页就行，这些垃圾图片需要满足两个条件，不止出现的次数要足够多，而且图片占书页面积的比例要足够大，且图与图大小都差不多
+    #有两种扫描版，一种文字版，这里可能会有误判
+    #扫描版1：每页都有所有扫描页图片，特点是图占比大，每页展示1张
+    #扫描版2，每页存储的扫描页图片数量递增，特点是图占比大，每页展示1张，需要清空junklist跑前50页图片信息用于分类判断
+    #文字版1.每页存储所有图片，特点是图片占页面比例不大，每页展示可能为0也可能不止1张 这种pdf需要拿前10页抽样检测img大小和个数，如果符合需要清空junklist
+    imgs_len_list = [len(page.get_images()) for page in doc]
+
+    special_limit_pages = 10
+
+    # 统一用前十页结果做判断
+    result = []
+    break_loop = False
+    for i, page in enumerate(doc):
+        if break_loop:
+            break
+        if i >= special_limit_pages:
+            break
+        page_result = process_image(page)  # 这里不传junk_img_bojids，拿前十页所有图片信息用于后续分析
+        result.append(page_result)
+        for item in result:
+            if not any(item):  # 如果任何一页没有图片，说明是个文字版，需要判断是否为特殊文字版
+                if max(imgs_len_list) == min(imgs_len_list) and max(
+                        imgs_len_list) >= junk_limit_min:  # 如果是特殊文字版，就把junklist置空并break
+                    junk_img_bojids = []
+                else:  # 不是特殊文字版，是个普通文字版，但是存在垃圾图片，不置空junklist
+                    pass
+                break_loop = True
+                break
+    if not break_loop:
+        # 获取前80%的元素
+        top_eighty_percent = get_top_percent_list(imgs_len_list, 0.8)
+        # 检查前80%的元素是否都相等
+        if len(set(top_eighty_percent)) == 1 and max(imgs_len_list) >= junk_limit_min:
+
+            # # 如果前10页跑完都有图，根据每页图片数量是否相等判断是否需要清除junklist
+            # if max(imgs_len_list) == min(imgs_len_list) and max(imgs_len_list) >= junk_limit_min:
+
+            #前10页都有图，且每页数量一致，需要检测图片大小占页面的比例判断是否需要清除junklist
+            max_image_area_per_page = calculate_max_image_area_per_page(result, page_width_pts, page_height_pts)
+            if len(max_image_area_per_page) < 0.8 * special_limit_pages:  # 前10页不全是大图，说明可能是个文字版pdf，把垃圾图片list置空
+                junk_img_bojids = []
+            else:  # 前10页都有图，而且80%都是大图，且每页图片数量一致并都很多，说明是扫描版1，不需要清空junklist
+                pass
+        else:  # 每页图片数量不一致，需要清掉junklist全量跑前50页图片
+            junk_img_bojids = []
+
+    #正式进入取前50页图片的信息流程
+    result = []
+    for i, page in enumerate(doc):
+        if i >= scan_max_page:
+            break
+        page_result = process_image(page, junk_img_bojids)
+        # logger.info(f"page {i} img_len: {len(page_result)}")
+        result.append(page_result)
+
+    return result, junk_img_bojids
+
+
+def get_pdf_page_size_pts(doc: fitz.Document):
+    page_cnt = len(doc)
+    l: int = min(page_cnt, 50)
+    #把所有宽度和高度塞到两个list 分别取中位数（中间遇到了个在纵页里塞横页的pdf，导致宽高互换了）
+    page_width_list = []
+    page_height_list = []
+    for i in range(l):
+        page = doc[i]
+        page_rect = page.rect
+        page_width_list.append(page_rect.width)
+        page_height_list.append(page_rect.height)
+
+    page_width_list.sort()
+    page_height_list.sort()
+
+    median_width = page_width_list[len(page_width_list) // 2]
+    median_height = page_height_list[len(page_height_list) // 2]
+
+    return median_width, median_height
+
+
+def get_pdf_textlen_per_page(doc: fitz.Document):
+    text_len_lst = []
+    for page in doc:
+        # 拿包含img和text的所有blocks
+        # text_block = page.get_text("blocks")
+        # 拿所有text的blocks
+        # text_block = page.get_text("words")
+        # text_block_len = sum([len(t[4]) for t in text_block])
+        #拿所有text的str
+        text_block = page.get_text("text")
+        text_block_len = len(text_block)
+        # logger.info(f"page {page.number} text_block_len: {text_block_len}")
+        text_len_lst.append(text_block_len)
+
+    return text_len_lst
+
+
+def get_pdf_text_layout_per_page(doc: fitz.Document):
+    """
+    根据PDF文档的每一页文本布局，判断该页的文本布局是横向、纵向还是未知。
+
+    Args:
+        doc (fitz.Document): PDF文档对象。
+
+    Returns:
+        List[str]: 每一页的文本布局（横向、纵向、未知）。
+
+    """
+    text_layout_list = []
+
+    for page_id, page in enumerate(doc):
+        if page_id >= scan_max_page:
+            break
+        # 创建每一页的纵向和横向的文本行数计数器
+        vertical_count = 0
+        horizontal_count = 0
+        text_dict = page.get_text("dict")
+        if "blocks" in text_dict:
+            for block in text_dict["blocks"]:
+                if 'lines' in block:
+                    for line in block["lines"]:
+                        # 获取line的bbox顶点坐标
+                        x0, y0, x1, y1 = line['bbox']
+                        # 计算bbox的宽高
+                        width = x1 - x0
+                        height = y1 - y0
+                        # 计算bbox的面积
+                        area = width * height
+                        font_sizes = []
+                        for span in line['spans']:
+                            if 'size' in span:
+                                font_sizes.append(span['size'])
+                        if len(font_sizes) > 0:
+                            average_font_size = sum(font_sizes) / len(font_sizes)
+                        else:
+                            average_font_size = 10  # 有的line拿不到font_size，先定一个阈值100
+                        if area <= average_font_size ** 2:  # 判断bbox的面积是否小于平均字体大小的平方,单字无法计算是横向还是纵向
+                            continue
+                        else:
+                            if 'wmode' in line:  # 通过wmode判断文本方向
+                                if line['wmode'] == 1:  # 判断是否为竖向文本
+                                    vertical_count += 1
+                                elif line['wmode'] == 0:  # 判断是否为横向文本
+                                    horizontal_count += 1
+                        #     if 'dir' in line:  # 通过旋转角度计算判断文本方向
+                        #         # 获取行的 "dir" 值
+                        #         dir_value = line['dir']
+                        #         cosine, sine = dir_value
+                        #         # 计算角度
+                        #         angle = math.degrees(math.acos(cosine))
+                        #
+                        #         # 判断是否为横向文本
+                        #         if abs(angle - 0) < 0.01 or abs(angle - 180) < 0.01:
+                        #             # line_text = ' '.join(span['text'] for span in line['spans'])
+                        #             # print('This line is horizontal:', line_text)
+                        #             horizontal_count += 1
+                        #         # 判断是否为纵向文本
+                        #         elif abs(angle - 90) < 0.01 or abs(angle - 270) < 0.01:
+                        #             # line_text = ' '.join(span['text'] for span in line['spans'])
+                        #             # print('This line is vertical:', line_text)
+                        #             vertical_count += 1
+        # print(f"page_id: {page_id}, vertical_count: {vertical_count}, horizontal_count: {horizontal_count}")
+        # 判断每一页的文本布局
+        if vertical_count == 0 and horizontal_count == 0:  # 该页没有文本，无法判断
+            text_layout_list.append("unknow")
+            continue
+        else:
+            if vertical_count > horizontal_count:  # 该页的文本纵向行数大于横向的
+                text_layout_list.append("vertical")
+            else:  # 该页的文本横向行数大于纵向的
+                text_layout_list.append("horizontal")
+        # logger.info(f"page_id: {page_id}, vertical_count: {vertical_count}, horizontal_count: {horizontal_count}")
+    return text_layout_list
+
+
+'''定义一个自定义异常用来抛出单页svg太多的pdf'''
+
+
+class PageSvgsTooManyError(Exception):
+    def __init__(self, message="Page SVGs are too many"):
+        self.message = message
+        super().__init__(self.message)
+
+
+def get_svgs_per_page(doc: fitz.Document):
+    svgs_len_list = []
+    for page_id, page in enumerate(doc):
+        # svgs = page.get_drawings()
+        svgs = page.get_cdrawings()  # 切换成get_cdrawings，效率更高
+        len_svgs = len(svgs)
+        if len_svgs >= 3000:
+            raise PageSvgsTooManyError()
+        else:
+            svgs_len_list.append(len_svgs)
+        # logger.info(f"page_id: {page_id}, svgs_len: {len(svgs)}")
+    return svgs_len_list
+
+
+def get_imgs_per_page(doc: fitz.Document):
+    imgs_len_list = []
+    for page_id, page in enumerate(doc):
+        imgs = page.get_images()
+        imgs_len_list.append(len(imgs))
+        # logger.info(f"page_id: {page}, imgs_len: {len(imgs)}")
+
+    return imgs_len_list
+
+
+def get_language(doc: fitz.Document):
+    """
+    获取PDF文档的语言。
+    Args:
+        doc (fitz.Document): PDF文档对象。
+    Returns:
+        str: 文档语言，如 "en-US"。
+    """
+    language_lst = []
+    for page_id, page in enumerate(doc):
+        if page_id >= scan_max_page:
+            break
+        # 拿所有text的str
+        text_block = page.get_text("text")
+        page_language = detect_lang(text_block)
+        language_lst.append(page_language)
+
+        # logger.info(f"page_id: {page_id}, page_language: {page_language}")
+
+    # 统计text_language_list中每种语言的个数
+    count_dict = Counter(language_lst)
+    # 输出text_language_list中出现的次数最多的语言
+    language = max(count_dict, key=count_dict.get)
+    return language
+
+
+def check_invalid_chars(pdf_bytes):
+    """
+    乱码检测
+    """
+    return detect_invalid_chars(pdf_bytes)
+
+
+def pdf_meta_scan(pdf_bytes: bytes):
+    """
+    :param s3_pdf_path:
+    :param pdf_bytes: pdf文件的二进制数据
+    几个维度来评价：是否加密，是否需要密码，纸张大小，总页数，是否文字可提取
+    """
+    doc = fitz.open("pdf", pdf_bytes)
+    is_needs_password = doc.needs_pass
+    is_encrypted = doc.is_encrypted
+    total_page = len(doc)
+    if total_page == 0:
+        logger.warning(f"drop this pdf, drop_reason: {DropReason.EMPTY_PDF}")
+        result = {"_need_drop": True, "_drop_reason": DropReason.EMPTY_PDF}
+        return result
+    else:
+        page_width_pts, page_height_pts = get_pdf_page_size_pts(doc)
+        # logger.info(f"page_width_pts: {page_width_pts}, page_height_pts: {page_height_pts}")
+
+        # svgs_per_page = get_svgs_per_page(doc)
+        # logger.info(f"svgs_per_page: {svgs_per_page}")
+        imgs_per_page = get_imgs_per_page(doc)
+        # logger.info(f"imgs_per_page: {imgs_per_page}")
+
+        image_info_per_page, junk_img_bojids = get_image_info(doc, page_width_pts, page_height_pts)
+        # logger.info(f"image_info_per_page: {image_info_per_page}, junk_img_bojids: {junk_img_bojids}")
+        text_len_per_page = get_pdf_textlen_per_page(doc)
+        # logger.info(f"text_len_per_page: {text_len_per_page}")
+        text_layout_per_page = get_pdf_text_layout_per_page(doc)
+        # logger.info(f"text_layout_per_page: {text_layout_per_page}")
+        text_language = get_language(doc)
+        # logger.info(f"text_language: {text_language}")
+        invalid_chars = check_invalid_chars(pdf_bytes)
+        # logger.info(f"invalid_chars: {invalid_chars}")
+
+        # 最后输出一条json
+        res = {
+            "is_needs_password": is_needs_password,
+            "is_encrypted": is_encrypted,
+            "total_page": total_page,
+            "page_width_pts": int(page_width_pts),
+            "page_height_pts": int(page_height_pts),
+            "image_info_per_page": image_info_per_page,
+            "text_len_per_page": text_len_per_page,
+            "text_layout_per_page": text_layout_per_page,
+            "text_language": text_language,
+            # "svgs_per_page": svgs_per_page,
+            "imgs_per_page": imgs_per_page,  # 增加每页img数量list
+            "junk_img_bojids": junk_img_bojids,  # 增加垃圾图片的bojid list
+            "invalid_chars": invalid_chars,
+            "metadata": doc.metadata
+        }
+        # logger.info(json.dumps(res, ensure_ascii=False))
+        return res
+
+
+@click.command()
+@click.option('--s3-pdf-path', help='s3上pdf文件的路径')
+@click.option('--s3-profile', help='s3上的profile')
+def main(s3_pdf_path: str, s3_profile: str):
+    """
+
+    """
+    try:
+        file_content = read_file(s3_pdf_path, s3_profile)
+        pdf_meta_scan(file_content)
+    except Exception as e:
+        print(f"ERROR: {s3_pdf_path}, {e}", file=sys.stderr)
+        logger.exception(e)
+
+
+if __name__ == '__main__':
+    main()
+    # "D:\project/20231108code-clean\pdf_cost_time\竖排例子\净空法师-大乘无量寿.pdf"
+    # "D:\project/20231108code-clean\pdf_cost_time\竖排例子\三国演义_繁体竖排版.pdf"
+    # "D:\project/20231108code-clean\pdf_cost_time\scihub\scihub_86800000\libgen.scimag86880000-86880999.zip_10.1021/acsami.1c03109.s002.pdf"
+    # "D:/project/20231108code-clean/pdf_cost_time/scihub/scihub_18600000/libgen.scimag18645000-18645999.zip_10.1021/om3006239.pdf"
+    # file_content = read_file("D:/project/20231108code-clean/pdf_cost_time/scihub/scihub_31000000/libgen.scimag31098000-31098999.zip_10.1109/isit.2006.261791.pdf","")
+    # file_content = read_file("D:\project/20231108code-clean\pdf_cost_time\竖排例子\净空法师_大乘无量寿.pdf","")
+    # doc = fitz.open("pdf", file_content)
+    # text_layout_lst = get_pdf_text_layout_per_page(doc)
+    # print(text_layout_lst)

magic_pdf/integrations/rag/api.py

+import os
+from pathlib import Path
+
+from loguru import logger
+
+from magic_pdf.integrations.rag.type import (ElementRelation, LayoutElements,
+                                             Node)
+from magic_pdf.integrations.rag.utils import inference
+
+
+class RagPageReader:
+
+    def __init__(self, pagedata: LayoutElements):
+        self.o = [
+            Node(
+                category_type=v.category_type,
+                text=v.text,
+                image_path=v.image_path,
+                anno_id=v.anno_id,
+                latex=v.latex,
+                html=v.html,
+            ) for v in pagedata.layout_dets
+        ]
+
+        self.pagedata = pagedata
+
+    def __iter__(self):
+        return iter(self.o)
+
+    def get_rel_map(self) -> list[ElementRelation]:
+        return self.pagedata.extra.element_relation
+
+
+class RagDocumentReader:
+
+    def __init__(self, ragdata: list[LayoutElements]):
+        self.o = [RagPageReader(v) for v in ragdata]
+
+    def __iter__(self):
+        return iter(self.o)
+
+
+class DataReader:
+
+    def __init__(self, path_or_directory: str, method: str, output_dir: str):
+        self.path_or_directory = path_or_directory
+        self.method = method
+        self.output_dir = output_dir
+        self.pdfs = []
+        if os.path.isdir(path_or_directory):
+            for doc_path in Path(path_or_directory).glob('*.pdf'):
+                self.pdfs.append(doc_path)
+        else:
+            assert path_or_directory.endswith('.pdf')
+            self.pdfs.append(Path(path_or_directory))
+
+    def get_documents_count(self) -> int:
+        """Returns the number of documents in the directory."""
+        return len(self.pdfs)
+
+    def get_document_result(self, idx: int) -> RagDocumentReader | None:
+        """
+        Args:
+            idx (int): the index of documents under the
+                directory path_or_directory
+
+        Returns:
+            RagDocumentReader | None: RagDocumentReader is an iterable object,
+            more details @RagDocumentReader
+        """
+        if idx >= self.get_documents_count() or idx < 0:
+            logger.error(f'invalid idx: {idx}')
+            return None
+        res = inference(str(self.pdfs[idx]), self.output_dir, self.method)
+        if res is None:
+            logger.warning(f'failed to inference pdf {self.pdfs[idx]}')
+            return None
+        return RagDocumentReader(res)
+
+    def get_document_filename(self, idx: int) -> Path:
+        """get the filename of the document."""
+        return self.pdfs[idx]

magic_pdf/integrations/rag/type.py

+from enum import Enum
+
+from pydantic import BaseModel, Field
+
+
+# rag
+class CategoryType(Enum):  # py310 not support StrEnum
+    text = 'text'
+    title = 'title'
+    interline_equation = 'interline_equation'
+    image = 'image'
+    image_body = 'image_body'
+    image_caption = 'image_caption'
+    table = 'table'
+    table_body = 'table_body'
+    table_caption = 'table_caption'
+    table_footnote = 'table_footnote'
+
+
+class ElementRelType(Enum):
+    sibling = 'sibling'
+
+
+class PageInfo(BaseModel):
+    page_no: int = Field(description='the index of page, start from zero',
+                         ge=0)
+    height: int = Field(description='the height of page', gt=0)
+    width: int = Field(description='the width of page', ge=0)
+    image_path: str | None = Field(description='the image of this page',
+                                   default=None)
+
+
+class ContentObject(BaseModel):
+    category_type: CategoryType = Field(description='类别')
+    poly: list[float] = Field(
+        description=('Coordinates, need to convert back to PDF coordinates,'
+                     ' order is top-left, top-right, bottom-right, bottom-left'
+                     ' x,y coordinates'))
+    ignore: bool = Field(description='whether ignore this object',
+                         default=False)
+    text: str | None = Field(description='text content of the object',
+                             default=None)
+    image_path: str | None = Field(description='path of embedded image',
+                                   default=None)
+    order: int = Field(description='the order of this object within a page',
+                       default=-1)
+    anno_id: int = Field(description='unique id', default=-1)
+    latex: str | None = Field(description='latex result', default=None)
+    html: str | None = Field(description='html result', default=None)
+
+
+class ElementRelation(BaseModel):
+    source_anno_id: int = Field(description='unique id of the source object',
+                                default=-1)
+    target_anno_id: int = Field(description='unique id of the target object',
+                                default=-1)
+    relation: ElementRelType = Field(
+        description='the relation between source and target element')
+
+
+class LayoutElementsExtra(BaseModel):
+    element_relation: list[ElementRelation] = Field(
+        description='the relation between source and target element')
+
+
+class LayoutElements(BaseModel):
+    layout_dets: list[ContentObject] = Field(
+        description='layout element details')
+    page_info: PageInfo = Field(description='page info')
+    extra: LayoutElementsExtra = Field(description='extra information')
+
+
+# iter data format
+class Node(BaseModel):
+    category_type: CategoryType = Field(description='类别')
+    text: str | None = Field(description='text content of the object',
+                             default=None)
+    image_path: str | None = Field(description='path of embedded image',
+                                   default=None)
+    anno_id: int = Field(description='unique id', default=-1)
+    latex: str | None = Field(description='latex result', default=None)
+    html: str | None = Field(description='html result', default=None)

magic_pdf/integrations/rag/utils.py

+import json
+import os
+from pathlib import Path
+
+from loguru import logger
+
+import magic_pdf.model as model_config
+from magic_pdf.dict2md.ocr_mkcontent import merge_para_with_text
+from magic_pdf.integrations.rag.type import (CategoryType, ContentObject,
+                                             ElementRelation, ElementRelType,
+                                             LayoutElements,
+                                             LayoutElementsExtra, PageInfo)
+from magic_pdf.libs.ocr_content_type import BlockType, ContentType
+from magic_pdf.rw.AbsReaderWriter import AbsReaderWriter
+from magic_pdf.rw.DiskReaderWriter import DiskReaderWriter
+from magic_pdf.tools.common import do_parse, prepare_env
+
+
+def convert_middle_json_to_layout_elements(
+    json_data: dict,
+    output_dir: str,
+) -> list[LayoutElements]:
+    uniq_anno_id = 0
+
+    res: list[LayoutElements] = []
+    for page_no, page_data in enumerate(json_data['pdf_info']):
+        order_id = 0
+        page_info = PageInfo(
+            height=int(page_data['page_size'][1]),
+            width=int(page_data['page_size'][0]),
+            page_no=page_no,
+        )
+        layout_dets: list[ContentObject] = []
+        extra_element_relation: list[ElementRelation] = []
+
+        for para_block in page_data['para_blocks']:
+            para_text = ''
+            para_type = para_block['type']
+
+            if para_type == BlockType.Text:
+                para_text = merge_para_with_text(para_block)
+                x0, y0, x1, y1 = para_block['bbox']
+                content = ContentObject(
+                    anno_id=uniq_anno_id,
+                    category_type=CategoryType.text,
+                    text=para_text,
+                    order=order_id,
+                    poly=[x0, y0, x1, y0, x1, y1, x0, y1],
+                )
+                uniq_anno_id += 1
+                order_id += 1
+                layout_dets.append(content)
+
+            elif para_type == BlockType.Title:
+                para_text = merge_para_with_text(para_block)
+                x0, y0, x1, y1 = para_block['bbox']
+                content = ContentObject(
+                    anno_id=uniq_anno_id,
+                    category_type=CategoryType.title,
+                    text=para_text,
+                    order=order_id,
+                    poly=[x0, y0, x1, y0, x1, y1, x0, y1],
+                )
+                uniq_anno_id += 1
+                order_id += 1
+                layout_dets.append(content)
+
+            elif para_type == BlockType.InterlineEquation:
+                para_text = merge_para_with_text(para_block)
+                x0, y0, x1, y1 = para_block['bbox']
+                content = ContentObject(
+                    anno_id=uniq_anno_id,
+                    category_type=CategoryType.interline_equation,
+                    text=para_text,
+                    order=order_id,
+                    poly=[x0, y0, x1, y0, x1, y1, x0, y1],
+                )
+                uniq_anno_id += 1
+                order_id += 1
+                layout_dets.append(content)
+
+            elif para_type == BlockType.Image:
+                body_anno_id = -1
+                caption_anno_id = -1
+
+                for block in para_block['blocks']:
+                    if block['type'] == BlockType.ImageBody:
+                        for line in block['lines']:
+                            for span in line['spans']:
+                                if span['type'] == ContentType.Image:
+                                    x0, y0, x1, y1 = block['bbox']
+                                    content = ContentObject(
+                                        anno_id=uniq_anno_id,
+                                        category_type=CategoryType.image_body,
+                                        image_path=os.path.join(
+                                            output_dir, span['image_path']),
+                                        order=order_id,
+                                        poly=[x0, y0, x1, y0, x1, y1, x0, y1],
+                                    )
+                                    body_anno_id = uniq_anno_id
+                                    uniq_anno_id += 1
+                                    order_id += 1
+                                    layout_dets.append(content)
+
+                for block in para_block['blocks']:
+                    if block['type'] == BlockType.ImageCaption:
+                        para_text += merge_para_with_text(block)
+                        x0, y0, x1, y1 = block['bbox']
+                        content = ContentObject(
+                            anno_id=uniq_anno_id,
+                            category_type=CategoryType.image_caption,
+                            text=para_text,
+                            order=order_id,
+                            poly=[x0, y0, x1, y0, x1, y1, x0, y1],
+                        )
+                        caption_anno_id = uniq_anno_id
+                        uniq_anno_id += 1
+                        order_id += 1
+                        layout_dets.append(content)
+
+                if body_anno_id > 0 and caption_anno_id > 0:
+                    element_relation = ElementRelation(
+                        relation=ElementRelType.sibling,
+                        source_anno_id=body_anno_id,
+                        target_anno_id=caption_anno_id,
+                    )
+                    extra_element_relation.append(element_relation)
+
+            elif para_type == BlockType.Table:
+                body_anno_id, caption_anno_id, footnote_anno_id = -1, -1, -1
+
+                for block in para_block['blocks']:
+                    if block['type'] == BlockType.TableCaption:
+                        para_text += merge_para_with_text(block)
+                        x0, y0, x1, y1 = block['bbox']
+                        content = ContentObject(
+                            anno_id=uniq_anno_id,
+                            category_type=CategoryType.table_caption,
+                            text=para_text,
+                            order=order_id,
+                            poly=[x0, y0, x1, y0, x1, y1, x0, y1],
+                        )
+                        caption_anno_id = uniq_anno_id
+                        uniq_anno_id += 1
+                        order_id += 1
+                        layout_dets.append(content)
+
+                for block in para_block['blocks']:
+                    if block['type'] == BlockType.TableBody:
+                        for line in block['lines']:
+                            for span in line['spans']:
+                                if span['type'] == ContentType.Table:
+                                    x0, y0, x1, y1 = para_block['bbox']
+                                    content = ContentObject(
+                                        anno_id=uniq_anno_id,
+                                        category_type=CategoryType.table_body,
+                                        order=order_id,
+                                        poly=[x0, y0, x1, y0, x1, y1, x0, y1],
+                                    )
+                                    body_anno_id = uniq_anno_id
+                                    uniq_anno_id += 1
+                                    order_id += 1
+                                    # if processed by table model
+                                    if span.get('latex', ''):
+                                        content.latex = span['latex']
+                                    else:
+                                        content.image_path = os.path.join(
+                                            output_dir, span['image_path'])
+                                    layout_dets.append(content)
+
+                for block in para_block['blocks']:
+                    if block['type'] == BlockType.TableFootnote:
+                        para_text += merge_para_with_text(block)
+                        x0, y0, x1, y1 = block['bbox']
+                        content = ContentObject(
+                            anno_id=uniq_anno_id,
+                            category_type=CategoryType.table_footnote,
+                            text=para_text,
+                            order=order_id,
+                            poly=[x0, y0, x1, y0, x1, y1, x0, y1],
+                        )
+                        footnote_anno_id = uniq_anno_id
+                        uniq_anno_id += 1
+                        order_id += 1
+                        layout_dets.append(content)
+
+                if caption_anno_id != -1 and body_anno_id != -1:
+                    element_relation = ElementRelation(
+                        relation=ElementRelType.sibling,
+                        source_anno_id=body_anno_id,
+                        target_anno_id=caption_anno_id,
+                    )
+                    extra_element_relation.append(element_relation)
+
+                if footnote_anno_id != -1 and body_anno_id != -1:
+                    element_relation = ElementRelation(
+                        relation=ElementRelType.sibling,
+                        source_anno_id=body_anno_id,
+                        target_anno_id=footnote_anno_id,
+                    )
+                    extra_element_relation.append(element_relation)
+
+        res.append(
+            LayoutElements(
+                page_info=page_info,
+                layout_dets=layout_dets,
+                extra=LayoutElementsExtra(
+                    element_relation=extra_element_relation),
+            ))
+
+    return res
+
+
+def inference(path, output_dir, method):
+    model_config.__use_inside_model__ = True
+    model_config.__model_mode__ = 'full'
+    if output_dir == '':
+        if os.path.isdir(path):
+            output_dir = os.path.join(path, 'output')
+        else:
+            output_dir = os.path.join(os.path.dirname(path), 'output')
+
+    local_image_dir, local_md_dir = prepare_env(output_dir,
+                                                str(Path(path).stem), method)
+
+    def read_fn(path):
+        disk_rw = DiskReaderWriter(os.path.dirname(path))
+        return disk_rw.read(os.path.basename(path), AbsReaderWriter.MODE_BIN)
+
+    def parse_doc(doc_path: str):
+        try:
+            file_name = str(Path(doc_path).stem)
+            pdf_data = read_fn(doc_path)
+            do_parse(
+                output_dir,
+                file_name,
+                pdf_data,
+                [],
+                method,
+                False,
+                f_draw_span_bbox=False,
+                f_draw_layout_bbox=False,
+                f_dump_md=False,
+                f_dump_middle_json=True,
+                f_dump_model_json=False,
+                f_dump_orig_pdf=False,
+                f_dump_content_list=False,
+                f_draw_model_bbox=False,
+            )
+
+            middle_json_fn = os.path.join(local_md_dir,
+                                          f'{file_name}_middle.json')
+            with open(middle_json_fn) as fd:
+                jso = json.load(fd)
+            os.remove(middle_json_fn)
+            return convert_middle_json_to_layout_elements(jso, local_image_dir)
+
+        except Exception as e:
+            logger.exception(e)
+
+    return parse_doc(path)
+
+
+if __name__ == '__main__':
+    import pprint
+
+    base_dir = '/opt/data/pdf/resources/samples/'
+    if 0:
+        with open(base_dir + 'json_outputs/middle.json') as f:
+            d = json.load(f)
+        result = convert_middle_json_to_layout_elements(d, '/tmp')
+        pprint.pp(result)
+    if 0:
+        with open(base_dir + 'json_outputs/middle.3.json') as f:
+            d = json.load(f)
+        result = convert_middle_json_to_layout_elements(d, '/tmp')
+        pprint.pp(result)
+
+    if 1:
+        res = inference(
+            base_dir + 'samples/pdf/one_page_with_table_image.pdf',
+            '/tmp/output',
+            'ocr',
+        )
+        pprint.pp(res)

magic_pdf/layout/bbox_sort.py

+# 定义这里的bbox是一个list [x0, y0, x1, y1, block_content, idx_x, idx_y, content_type, ext_x0, ext_y0, ext_x1, ext_y1], 初始时候idx_x, idx_y都是None
+# 其中x0, y0代表左上角坐标，x1, y1代表右下角坐标，坐标原点在左上角。
+
+
+
+from magic_pdf.layout.layout_spiler_recog import get_spilter_of_page
+from magic_pdf.libs.boxbase import _is_in, _is_in_or_part_overlap, _is_vertical_full_overlap
+from magic_pdf.libs.commons import mymax
+
+X0_IDX = 0
+Y0_IDX = 1
+X1_IDX = 2
+Y1_IDX = 3
+CONTENT_IDX = 4
+IDX_X = 5
+IDX_Y = 6
+CONTENT_TYPE_IDX = 7
+
+X0_EXT_IDX = 8
+Y0_EXT_IDX = 9
+X1_EXT_IDX = 10
+Y1_EXT_IDX = 11
+
+
+def prepare_bboxes_for_layout_split(image_info, image_backup_info, table_info, inline_eq_info, interline_eq_info, text_raw_blocks: dict, page_boundry, page):
+    """
+    text_raw_blocks:结构参考test/assets/papre/pymu_textblocks.json
+    把bbox重新组装成一个list，每个元素[x0, y0, x1, y1, block_content, idx_x, idx_y, content_type, ext_x0, ext_y0, ext_x1, ext_y1], 初始时候idx_x, idx_y都是None. 对于图片、公式来说，block_content是图片的地址， 对于段落来说，block_content是pymupdf里的block结构
+    """
+    all_bboxes = []
+    
+    for image in image_info:
+        box = image['bbox']
+        # 由于没有实现横向的栏切分，因此在这里先过滤掉一些小的图片。这些图片有可能影响layout，造成没有横向栏切分的情况下，layout切分不准确。例如 scihub_76500000/libgen.scimag76570000-76570999.zip_10.1186/s13287-019-1355-1
+        # 把长宽都小于50的去掉
+        if abs(box[0]-box[2]) < 50 and abs(box[1]-box[3]) < 50:
+            continue
+        all_bboxes.append([box[0], box[1], box[2], box[3], None, None, None, 'image', None, None, None, None])
+        
+    for table in table_info:
+        box = table['bbox']
+        all_bboxes.append([box[0], box[1], box[2], box[3], None, None, None, 'table', None, None, None, None])
+    
+    """由于公式与段落混合，因此公式不再参与layout划分，无需加入all_bboxes"""
+    # 加入文本block
+    text_block_temp = []
+    for block in text_raw_blocks:
+        bbox = block['bbox']
+        text_block_temp.append([bbox[0], bbox[1], bbox[2], bbox[3], None, None, None, 'text', None, None, None, None])
+        
+    text_block_new = resolve_bbox_overlap_for_layout_det(text_block_temp)   
+    text_block_new = filter_lines_bbox(text_block_new) # 去掉线条bbox，有可能让layout探测陷入无限循环
+    
+        
+    """找出会影响layout的色块、横向分割线"""
+    spilter_bboxes = get_spilter_of_page(page, [b['bbox'] for b in image_info]+[b['bbox'] for b in image_backup_info], [b['bbox'] for b in table_info], )
+    # 还要去掉存在于spilter_bboxes里的text_block
+    if len(spilter_bboxes) > 0:
+        text_block_new = [box for box in text_block_new if not any([_is_in_or_part_overlap(box[:4], spilter_bbox) for spilter_bbox in spilter_bboxes])]
+        
+    for bbox in text_block_new:
+        all_bboxes.append([bbox[0], bbox[1], bbox[2], bbox[3], None, None, None, 'text', None, None, None, None]) 
+        
+    for bbox in spilter_bboxes:
+        all_bboxes.append([bbox[0], bbox[1], bbox[2], bbox[3], None, None, None, 'spilter', None, None, None, None])
+    
+     
+    return all_bboxes
+
+def resolve_bbox_overlap_for_layout_det(bboxes:list):
+    """
+    1. 去掉bbox互相包含的，去掉被包含的
+    2. 上下方向上如果有重叠，就扩大大box范围，直到覆盖小box
+    """
+    def _is_in_other_bbox(i:int):
+        """
+        判断i个box是否被其他box有所包含
+        """
+        for j in range(0, len(bboxes)):
+            if j!=i and _is_in(bboxes[i][:4], bboxes[j][:4]):
+                return True
+            # elif j!=i and _is_bottom_full_overlap(bboxes[i][:4], bboxes[j][:4]):
+            #     return True
+            
+        return False
+    
+    # 首先去掉被包含的bbox
+    new_bbox_1 = []
+    for i in range(0, len(bboxes)):
+        if not _is_in_other_bbox(i):
+            new_bbox_1.append(bboxes[i])
+            
+    # 其次扩展大的box
+    new_box = []
+    new_bbox_2 = []
+    len_1 = len(new_bbox_2)
+    while True:
+        merged_idx = []
+        for i in range(0, len(new_bbox_1)):
+            if i in merged_idx:
+                continue
+            for j in range(i+1, len(new_bbox_1)):
+                if j in merged_idx:
+                    continue
+                bx1 = new_bbox_1[i]
+                bx2 = new_bbox_1[j]
+                if i!=j and _is_vertical_full_overlap(bx1[:4], bx2[:4]):
+                    merged_box = min([bx1[0], bx2[0]]), min([bx1[1], bx2[1]]), max([bx1[2], bx2[2]]), max([bx1[3], bx2[3]])
+                    new_bbox_2.append(merged_box)
+                    merged_idx.append(i)
+                    merged_idx.append(j)
+                    
+        for i in range(0, len(new_bbox_1)): # 没有合并的加入进来
+            if i not in merged_idx:
+                new_bbox_2.append(new_bbox_1[i])        
+
+        if len(new_bbox_2)==0 or len_1==len(new_bbox_2):
+            break
+        else:
+            len_1 = len(new_bbox_2)
+            new_box = new_bbox_2
+            new_bbox_1, new_bbox_2 = new_bbox_2, []
+                        
+    return new_box
+
+
+def filter_lines_bbox(bboxes: list):
+    """
+    过滤掉bbox为空的行
+    """
+    new_box = []
+    for box in bboxes:
+        x0, y0, x1, y1 = box[0], box[1], box[2], box[3]
+        if abs(x0-x1)<=1 or abs(y0-y1)<=1:
+            continue
+        else:
+            new_box.append(box)
+    return new_box
+
+
+################################################################################
+# 第一种排序算法
+# 以下是基于延长线遮挡做的一个算法
+#
+################################################################################
+def find_all_left_bbox(this_bbox, all_bboxes) -> list:
+    """
+    寻找this_bbox左边的所有bbox
+    """
+    left_boxes = [box for box in all_bboxes if box[X1_IDX] <= this_bbox[X0_IDX]]
+    return left_boxes
+
+
+def find_all_top_bbox(this_bbox, all_bboxes) -> list:
+    """
+    寻找this_bbox上面的所有bbox
+    """
+    top_boxes = [box for box in all_bboxes if box[Y1_IDX] <= this_bbox[Y0_IDX]]
+    return top_boxes
+
+
+def get_and_set_idx_x(this_bbox, all_bboxes) -> int:
+    """
+    寻找this_bbox在all_bboxes中的遮挡深度 idx_x
+    """
+    if this_bbox[IDX_X] is not None:
+        return this_bbox[IDX_X]
+    else:
+        all_left_bboxes = find_all_left_bbox(this_bbox, all_bboxes)
+        if len(all_left_bboxes) == 0:
+            this_bbox[IDX_X] = 0
+        else:
+            all_left_bboxes_idx = [get_and_set_idx_x(bbox, all_bboxes) for bbox in all_left_bboxes]
+            max_idx_x = mymax(all_left_bboxes_idx)
+            this_bbox[IDX_X] = max_idx_x + 1
+        return this_bbox[IDX_X]
+
+
+def get_and_set_idx_y(this_bbox, all_bboxes) -> int:
+    """
+    寻找this_bbox在all_bboxes中y方向的遮挡深度 idx_y
+    """
+    if this_bbox[IDX_Y] is not None:
+        return this_bbox[IDX_Y]
+    else:
+        all_top_bboxes = find_all_top_bbox(this_bbox, all_bboxes)
+        if len(all_top_bboxes) == 0:
+            this_bbox[IDX_Y] = 0
+        else:
+            all_top_bboxes_idx = [get_and_set_idx_y(bbox, all_bboxes) for bbox in all_top_bboxes]
+            max_idx_y = mymax(all_top_bboxes_idx)
+            this_bbox[IDX_Y] = max_idx_y + 1
+        return this_bbox[IDX_Y]
+
+
+def bbox_sort(all_bboxes: list):
+    """
+    排序
+    """
+    all_bboxes_idx_x = [get_and_set_idx_x(bbox, all_bboxes) for bbox in all_bboxes]
+    all_bboxes_idx_y = [get_and_set_idx_y(bbox, all_bboxes) for bbox in all_bboxes]
+    all_bboxes_idx = [(idx_x, idx_y) for idx_x, idx_y in zip(all_bboxes_idx_x, all_bboxes_idx_y)]
+
+    all_bboxes_idx = [idx_x_y[0] * 100000 + idx_x_y[1] for idx_x_y in all_bboxes_idx]  # 变换成一个点，保证能够先X，X相同时按Y排序
+    all_bboxes_idx = list(zip(all_bboxes_idx, all_bboxes))
+    all_bboxes_idx.sort(key=lambda x: x[0])
+    sorted_bboxes = [bbox for idx, bbox in all_bboxes_idx]
+    return sorted_bboxes
+
+
+################################################################################
+# 第二种排序算法
+# 下面的算法在计算idx_x和idx_y的时候不考虑延长线，而只考虑实际的长或者宽被遮挡的情况
+#
+################################################################################
+
+def find_left_nearest_bbox(this_bbox, all_bboxes) -> list:
+    """
+    在all_bboxes里找到所有右侧高度和this_bbox有重叠的bbox
+    """
+    left_boxes = [box for box in all_bboxes if box[X1_IDX] <= this_bbox[X0_IDX] and any([
+         box[Y0_IDX] < this_bbox[Y0_IDX] < box[Y1_IDX], box[Y0_IDX] < this_bbox[Y1_IDX] < box[Y1_IDX],
+         this_bbox[Y0_IDX] < box[Y0_IDX] < this_bbox[Y1_IDX], this_bbox[Y0_IDX] < box[Y1_IDX] < this_bbox[Y1_IDX],
+         box[Y0_IDX]==this_bbox[Y0_IDX] and box[Y1_IDX]==this_bbox[Y1_IDX]])]
+        
+    # 然后再过滤一下，找到水平上距离this_bbox最近的那个
+    if len(left_boxes) > 0:
+        left_boxes.sort(key=lambda x: x[X1_IDX], reverse=True)
+        left_boxes = [left_boxes[0]]
+    else:
+        left_boxes = []
+    return left_boxes
+
+
+def get_and_set_idx_x_2(this_bbox, all_bboxes):
+    """
+    寻找this_bbox在all_bboxes中的被直接遮挡的深度 idx_x
+    这个遮挡深度不考虑延长线，而是被实际的长或者宽遮挡的情况
+    """
+    if this_bbox[IDX_X] is not None:
+        return this_bbox[IDX_X]
+    else:
+        left_nearest_bbox = find_left_nearest_bbox(this_bbox, all_bboxes)
+        if len(left_nearest_bbox) == 0:
+            this_bbox[IDX_X] = 0
+        else:
+            left_idx_x = get_and_set_idx_x_2(left_nearest_bbox[0], all_bboxes)
+            this_bbox[IDX_X] = left_idx_x + 1
+        return this_bbox[IDX_X]
+
+
+def find_top_nearest_bbox(this_bbox, all_bboxes) -> list:
+    """
+    在all_bboxes里找到所有下侧宽度和this_bbox有重叠的bbox
+    """
+    top_boxes = [box for box in all_bboxes if box[Y1_IDX] <= this_bbox[Y0_IDX] and any([
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+         this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    # 然后再过滤一下，找到水平上距离this_bbox最近的那个
+    if len(top_boxes) > 0:
+        top_boxes.sort(key=lambda x: x[Y1_IDX], reverse=True)
+        top_boxes = [top_boxes[0]]
+    else:
+        top_boxes = []
+    return top_boxes
+
+
+def get_and_set_idx_y_2(this_bbox, all_bboxes):
+    """
+    寻找this_bbox在all_bboxes中的被直接遮挡的深度 idx_y
+    这个遮挡深度不考虑延长线，而是被实际的长或者宽遮挡的情况
+    """
+    if this_bbox[IDX_Y] is not None:
+        return this_bbox[IDX_Y]
+    else:
+        top_nearest_bbox = find_top_nearest_bbox(this_bbox, all_bboxes)
+        if len(top_nearest_bbox) == 0:
+            this_bbox[IDX_Y] = 0
+        else:
+            top_idx_y = get_and_set_idx_y_2(top_nearest_bbox[0], all_bboxes)
+            this_bbox[IDX_Y] = top_idx_y + 1
+        return this_bbox[IDX_Y]
+
+
+def paper_bbox_sort(all_bboxes: list, page_width, page_height):
+    all_bboxes_idx_x = [get_and_set_idx_x_2(bbox, all_bboxes) for bbox in all_bboxes]
+    all_bboxes_idx_y = [get_and_set_idx_y_2(bbox, all_bboxes) for bbox in all_bboxes]
+    all_bboxes_idx = [(idx_x, idx_y) for idx_x, idx_y in zip(all_bboxes_idx_x, all_bboxes_idx_y)]
+
+    all_bboxes_idx = [idx_x_y[0] * 100000 + idx_x_y[1] for idx_x_y in all_bboxes_idx]  # 变换成一个点，保证能够先X，X相同时按Y排序
+    all_bboxes_idx = list(zip(all_bboxes_idx, all_bboxes))
+    all_bboxes_idx.sort(key=lambda x: x[0])
+    sorted_bboxes = [bbox for idx, bbox in all_bboxes_idx]
+    return sorted_bboxes
+
+################################################################################
+"""
+第三种排序算法, 假设page的最左侧为X0，最右侧为X1，最上侧为Y0，最下侧为Y1
+这个排序算法在第二种算法基础上增加对bbox的预处理步骤。预处理思路如下：
+1. 首先在水平方向上对bbox进行扩展。扩展方法是：
+    - 对每个bbox，找到其左边最近的bbox（也就是y方向有重叠），然后将其左边界扩展到左边最近bbox的右边界(x1+1),这里加1是为了避免重叠。如果没有左边的bbox，那么就将其左边界扩展到page的最左侧X0。
+    - 对每个bbox，找到其右边最近的bbox（也就是y方向有重叠），然后将其右边界扩展到右边最近bbox的左边界(x0-1),这里减1是为了避免重叠。如果没有右边的bbox，那么就将其右边界扩展到page的最右侧X1。
+    - 经过上面2个步骤，bbox扩展到了水平方向的最大范围。[左最近bbox.x1+1, 右最近bbox.x0-1]
+    
+2. 合并所有的连续水平方向的bbox, 合并方法是：
+    - 对bbox进行y方向排序，然后从上到下遍历所有bbox，如果当前bbox和下一个bbox的x0, x1等于X0, X1，那么就合并这两个bbox。
+    
+3. 然后在垂直方向上对bbox进行扩展。扩展方法是：
+    - 首先从page上切割掉合并后的水平bbox, 得到几个新的block
+    针对每个block
+    - x0: 扎到位于左侧x=x0延长线的左侧所有的bboxes, 找到最大的x1,让x0=x1+1。如果没有，则x0=X0
+    - x1: 找到位于右侧x=x1延长线右侧所有的bboxes， 找到最小的x0, 让x1=x0-1。如果没有，则x1=X1
+    随后在垂直方向上合并所有的连续的block，方法如下：
+    - 对block进行x方向排序，然后从左到右遍历所有block，如果当前block和下一个block的x0, x1相等，那么就合并这两个block。
+    如果垂直切分后所有小bbox都被分配到了一个block, 那么分割就完成了。这些合并后的block打上标签'GOOD_LAYOUT’
+    如果在某个垂直方向上无法被完全分割到一个block，那么就将这个block打上标签'BAD_LAYOUT'。
+    至此完成，一个页面的预处理，天然的block要么属于'GOOD_LAYOUT'，要么属于'BAD_LAYOUT'。针对含有'BAD_LAYOUT'的页面，可以先按照自上而下，自左到右进行天然排序，也可以先过滤掉这种书籍。
+    (完成条件下次加强：进行水平方向切分，把混乱的layout部分尽可能切割出去)
+"""
+################################################################################
+def find_left_neighbor_bboxes(this_bbox, all_bboxes) -> list:
+    """
+    在all_bboxes里找到所有右侧高度和this_bbox有重叠的bbox
+    这里使用扩展之后的bbox
+    """
+    left_boxes = [box for box in all_bboxes if box[X1_EXT_IDX] <= this_bbox[X0_EXT_IDX] and any([
+         box[Y0_EXT_IDX] < this_bbox[Y0_EXT_IDX] < box[Y1_EXT_IDX], box[Y0_EXT_IDX] < this_bbox[Y1_EXT_IDX] < box[Y1_EXT_IDX],
+         this_bbox[Y0_EXT_IDX] < box[Y0_EXT_IDX] < this_bbox[Y1_EXT_IDX], this_bbox[Y0_EXT_IDX] < box[Y1_EXT_IDX] < this_bbox[Y1_EXT_IDX],
+         box[Y0_EXT_IDX]==this_bbox[Y0_EXT_IDX] and box[Y1_EXT_IDX]==this_bbox[Y1_EXT_IDX]])]
+        
+    # 然后再过滤一下，找到水平上距离this_bbox最近的那个
+    if len(left_boxes) > 0:
+        left_boxes.sort(key=lambda x: x[X1_EXT_IDX], reverse=True)
+        left_boxes = left_boxes
+    else:
+        left_boxes = []
+    return left_boxes
+
+def find_top_neighbor_bboxes(this_bbox, all_bboxes) -> list:
+    """
+    在all_bboxes里找到所有下侧宽度和this_bbox有重叠的bbox
+    这里使用扩展之后的bbox
+    """
+    top_boxes = [box for box in all_bboxes if box[Y1_EXT_IDX] <= this_bbox[Y0_EXT_IDX] and any([
+        box[X0_EXT_IDX] < this_bbox[X0_EXT_IDX] < box[X1_EXT_IDX], box[X0_EXT_IDX] < this_bbox[X1_EXT_IDX] < box[X1_EXT_IDX],
+         this_bbox[X0_EXT_IDX] < box[X0_EXT_IDX] < this_bbox[X1_EXT_IDX], this_bbox[X0_EXT_IDX] < box[X1_EXT_IDX] < this_bbox[X1_EXT_IDX],
+        box[X0_EXT_IDX]==this_bbox[X0_EXT_IDX] and box[X1_EXT_IDX]==this_bbox[X1_EXT_IDX]])]
+    # 然后再过滤一下，找到水平上距离this_bbox最近的那个
+    if len(top_boxes) > 0:
+        top_boxes.sort(key=lambda x: x[Y1_EXT_IDX], reverse=True)
+        top_boxes = top_boxes
+    else:
+        top_boxes = []
+    return top_boxes
+
+def get_and_set_idx_x_2_ext(this_bbox, all_bboxes):
+    """
+    寻找this_bbox在all_bboxes中的被直接遮挡的深度 idx_x
+    这个遮挡深度不考虑延长线，而是被实际的长或者宽遮挡的情况
+    """
+    if this_bbox[IDX_X] is not None:
+        return this_bbox[IDX_X]
+    else:
+        left_nearest_bbox = find_left_neighbor_bboxes(this_bbox, all_bboxes)
+        if len(left_nearest_bbox) == 0:
+            this_bbox[IDX_X] = 0
+        else:
+            left_idx_x = [get_and_set_idx_x_2(b, all_bboxes) for b in left_nearest_bbox]
+            this_bbox[IDX_X] = mymax(left_idx_x) + 1
+        return this_bbox[IDX_X]
+   
+def get_and_set_idx_y_2_ext(this_bbox, all_bboxes):
+    """
+    寻找this_bbox在all_bboxes中的被直接遮挡的深度 idx_y
+    这个遮挡深度不考虑延长线，而是被实际的长或者宽遮挡的情况
+    """
+    if this_bbox[IDX_Y] is not None:
+        return this_bbox[IDX_Y]
+    else:
+        top_nearest_bbox = find_top_neighbor_bboxes(this_bbox, all_bboxes)
+        if len(top_nearest_bbox) == 0:
+            this_bbox[IDX_Y] = 0
+        else:
+            top_idx_y = [get_and_set_idx_y_2_ext(b, all_bboxes) for b in top_nearest_bbox]
+            this_bbox[IDX_Y] = mymax(top_idx_y) + 1
+        return this_bbox[IDX_Y]
+ 
+def _paper_bbox_sort_ext(all_bboxes: list):
+    all_bboxes_idx_x = [get_and_set_idx_x_2_ext(bbox, all_bboxes) for bbox in all_bboxes]
+    all_bboxes_idx_y = [get_and_set_idx_y_2_ext(bbox, all_bboxes) for bbox in all_bboxes]
+    all_bboxes_idx = [(idx_x, idx_y) for idx_x, idx_y in zip(all_bboxes_idx_x, all_bboxes_idx_y)]
+
+    all_bboxes_idx = [idx_x_y[0] * 100000 + idx_x_y[1] for idx_x_y in all_bboxes_idx]  # 变换成一个点，保证能够先X，X相同时按Y排序
+    all_bboxes_idx = list(zip(all_bboxes_idx, all_bboxes))
+    all_bboxes_idx.sort(key=lambda x: x[0])
+    sorted_bboxes = [bbox for idx, bbox in all_bboxes_idx]
+    return sorted_bboxes
+
+# ===============================================================================================
+def find_left_bbox_ext_line(this_bbox, all_bboxes) -> list:
+    """
+    寻找this_bbox左边的所有bbox, 使用延长线
+    """
+    left_boxes = [box for box in all_bboxes if box[X1_IDX] <= this_bbox[X0_IDX]]
+    if len(left_boxes):
+        left_boxes.sort(key=lambda x: x[X1_IDX], reverse=True)
+        left_boxes = left_boxes[0]
+    else:
+        left_boxes = None
+    
+    return left_boxes
+
+def find_right_bbox_ext_line(this_bbox, all_bboxes) -> list:
+    """
+    寻找this_bbox右边的所有bbox, 使用延长线
+    """
+    right_boxes = [box for box in all_bboxes if box[X0_IDX] >= this_bbox[X1_IDX]]
+    if len(right_boxes):
+        right_boxes.sort(key=lambda x: x[X0_IDX])
+        right_boxes = right_boxes[0]
+    else:
+        right_boxes = None
+    return right_boxes
+
+# =============================================================================================
+
+def find_left_nearest_bbox_direct(this_bbox, all_bboxes) -> list:
+    """
+    在all_bboxes里找到所有右侧高度和this_bbox有重叠的bbox， 不用延长线并且不能像
+    """
+    left_boxes = [box for box in all_bboxes if box[X1_IDX] <= this_bbox[X0_IDX] and any([
+         box[Y0_IDX] < this_bbox[Y0_IDX] < box[Y1_IDX], box[Y0_IDX] < this_bbox[Y1_IDX] < box[Y1_IDX],
+         this_bbox[Y0_IDX] < box[Y0_IDX] < this_bbox[Y1_IDX], this_bbox[Y0_IDX] < box[Y1_IDX] < this_bbox[Y1_IDX],
+         box[Y0_IDX]==this_bbox[Y0_IDX] and box[Y1_IDX]==this_bbox[Y1_IDX]])]
+        
+    # 然后再过滤一下，找到水平上距离this_bbox最近的那个——x1最大的那个
+    if len(left_boxes) > 0:
+        left_boxes.sort(key=lambda x: x[X1_EXT_IDX] if x[X1_EXT_IDX] else x[X1_IDX], reverse=True)
+        left_boxes = left_boxes[0]
+    else:
+        left_boxes = None
+    return left_boxes
+
+def find_right_nearst_bbox_direct(this_bbox, all_bboxes) -> list:
+    """
+    找到在this_bbox右侧且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    right_bboxes = [box for box in all_bboxes if box[X0_IDX] >= this_bbox[X1_IDX] and any([
+        this_bbox[Y0_IDX] < box[Y0_IDX] < this_bbox[Y1_IDX], this_bbox[Y0_IDX] < box[Y1_IDX] < this_bbox[Y1_IDX],
+        box[Y0_IDX] < this_bbox[Y0_IDX] < box[Y1_IDX], box[Y0_IDX] < this_bbox[Y1_IDX] < box[Y1_IDX],
+        box[Y0_IDX]==this_bbox[Y0_IDX] and box[Y1_IDX]==this_bbox[Y1_IDX]])]
+    
+    if len(right_bboxes)>0:
+        right_bboxes.sort(key=lambda x: x[X0_EXT_IDX] if x[X0_EXT_IDX] else x[X0_IDX])
+        right_bboxes = right_bboxes[0]
+    else:
+        right_bboxes = None
+    return right_bboxes
+
+def reset_idx_x_y(all_boxes:list)->list:
+    for box in all_boxes:
+        box[IDX_X] = None
+        box[IDX_Y] = None
+        
+    return all_boxes
+
+# ===================================================================================================
+def find_top_nearest_bbox_direct(this_bbox, bboxes_collection) -> list:
+    """
+    找到在this_bbox上方且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    top_bboxes = [box for box in bboxes_collection if box[Y1_IDX] <= this_bbox[Y0_IDX] and any([
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+         this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    # 然后再过滤一下，找到上方距离this_bbox最近的那个
+    if len(top_bboxes) > 0:
+        top_bboxes.sort(key=lambda x: x[Y1_IDX], reverse=True)
+        top_bboxes = top_bboxes[0]
+    else:
+        top_bboxes = None
+    return top_bboxes
+
+def find_bottom_nearest_bbox_direct(this_bbox, bboxes_collection) -> list:
+    """
+    找到在this_bbox下方且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    bottom_bboxes = [box for box in bboxes_collection if box[Y0_IDX] >= this_bbox[Y1_IDX] and any([
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+         this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    # 然后再过滤一下，找到水平上距离this_bbox最近的那个
+    if len(bottom_bboxes) > 0:
+        bottom_bboxes.sort(key=lambda x: x[Y0_IDX])
+        bottom_bboxes = bottom_bboxes[0]
+    else:
+        bottom_bboxes = None
+    return bottom_bboxes
+
+def find_boundry_bboxes(bboxes:list) -> tuple:
+    """
+    找到bboxes的边界——找到所有bbox里最小的(x0, y0), 最大的(x1, y1)
+    """
+    x0, y0, x1, y1 = bboxes[0][X0_IDX], bboxes[0][Y0_IDX], bboxes[0][X1_IDX], bboxes[0][Y1_IDX]
+    for box in bboxes:
+        x0 = min(box[X0_IDX], x0)
+        y0 = min(box[Y0_IDX], y0)
+        x1 = max(box[X1_IDX], x1)
+        y1 = max(box[Y1_IDX], y1)
+        
+    return x0, y0, x1, y1
+    
+
+def extend_bbox_vertical(bboxes:list, boundry_x0, boundry_y0, boundry_x1, boundry_y1) -> list:
+    """
+    在垂直方向上扩展能够直接垂直打通的bbox,也就是那些上下都没有其他box的bbox
+    """
+    for box in bboxes:
+        top_nearest_bbox = find_top_nearest_bbox_direct(box, bboxes)
+        bottom_nearest_bbox = find_bottom_nearest_bbox_direct(box, bboxes)
+        if top_nearest_bbox is None and bottom_nearest_bbox is None: # 独占一列
+            box[X0_EXT_IDX] = box[X0_IDX]
+            box[Y0_EXT_IDX] = boundry_y0
+            box[X1_EXT_IDX] = box[X1_IDX]
+            box[Y1_EXT_IDX] = boundry_y1
+        # else:
+        #     if top_nearest_bbox is None:
+        #         box[Y0_EXT_IDX] = boundry_y0
+        #     else:
+        #         box[Y0_EXT_IDX] = top_nearest_bbox[Y1_IDX] + 1
+        #     if bottom_nearest_bbox is None:
+        #         box[Y1_EXT_IDX] = boundry_y1
+        #     else:
+        #         box[Y1_EXT_IDX] = bottom_nearest_bbox[Y0_IDX] - 1
+        #     box[X0_EXT_IDX] = box[X0_IDX]
+        #     box[X1_EXT_IDX] = box[X1_IDX]
+    return bboxes
+    
+
+# ===================================================================================================
+
+def paper_bbox_sort_v2(all_bboxes: list, page_width:int, page_height:int):
+    """
+    增加预处理行为的排序:
+    return:
+    [
+        {
+            "layout_bbox": [x0, y0, x1, y1],
+            "layout_label":"GOOD_LAYOUT/BAD_LAYOUT",
+            "content_bboxes": [] #每个元素都是[x0, y0, x1, y1, block_content, idx_x, idx_y, content_type, ext_x0, ext_y0, ext_x1, ext_y1], 并且顺序就是阅读顺序
+        }
+    ]
+    """
+    sorted_layouts = [] # 最后的返回结果
+    page_x0, page_y0, page_x1, page_y1 = 1, 1, page_width-1, page_height-1
+    
+    all_bboxes = paper_bbox_sort(all_bboxes) # 大致拍下序
+    # 首先在水平方向上扩展独占一行的bbox
+    for bbox in all_bboxes:
+        left_nearest_bbox = find_left_nearest_bbox_direct(bbox, all_bboxes) # 非扩展线
+        right_nearest_bbox = find_right_nearst_bbox_direct(bbox, all_bboxes)
+        if left_nearest_bbox is None and right_nearest_bbox is None: # 独占一行
+            bbox[X0_EXT_IDX] = page_x0
+            bbox[Y0_EXT_IDX] = bbox[Y0_IDX]
+            bbox[X1_EXT_IDX] = page_x1
+            bbox[Y1_EXT_IDX] = bbox[Y1_IDX]
+            
+    # 此时独占一行的被成功扩展到指定的边界上，这个时候利用边界条件合并连续的bbox，成为一个group
+    if len(all_bboxes)==1:
+        return [{"layout_bbox": [page_x0, page_y0, page_x1, page_y1], "layout_label":"GOOD_LAYOUT", "content_bboxes": all_bboxes}]
+    if len(all_bboxes)==0:
+        return []
+    
+    """
+    然后合并所有连续水平方向的bbox.
+    
+    """
+    all_bboxes.sort(key=lambda x: x[Y0_IDX])
+    h_bboxes = []
+    h_bbox_group = []
+    v_boxes = []
+
+    for bbox in all_bboxes:
+        if bbox[X0_IDX] == page_x0 and bbox[X1_IDX] == page_x1:
+            h_bbox_group.append(bbox)
+        else:
+            if len(h_bbox_group)>0:
+                h_bboxes.append(h_bbox_group) 
+                h_bbox_group = []
+    # 最后一个group
+    if len(h_bbox_group)>0:
+        h_bboxes.append(h_bbox_group)
+
+    """
+    现在h_bboxes里面是所有的group了，每个group都是一个list
+    对h_bboxes里的每个group进行计算放回到sorted_layouts里
+    """
+    for gp in h_bboxes:
+        gp.sort(key=lambda x: x[Y0_IDX])
+        block_info = {"layout_label":"GOOD_LAYOUT", "content_bboxes": gp}
+        # 然后计算这个group的layout_bbox，也就是最小的x0,y0, 最大的x1,y1
+        x0, y0, x1, y1 = gp[0][X0_EXT_IDX], gp[0][Y0_EXT_IDX], gp[-1][X1_EXT_IDX], gp[-1][Y1_EXT_IDX]
+        block_info["layout_bbox"] = [x0, y0, x1, y1]
+        sorted_layouts.append(block_info)
+        
+    # 接下来利用这些连续的水平bbox的layout_bbox的y0, y1，从水平上切分开其余的为几个部分
+    h_split_lines = [page_y0]
+    for gp in h_bboxes:
+        layout_bbox = gp['layout_bbox']
+        y0, y1 = layout_bbox[1], layout_bbox[3]
+        h_split_lines.append(y0)
+        h_split_lines.append(y1)
+    h_split_lines.append(page_y1)
+    
+    unsplited_bboxes = []
+    for i in range(0, len(h_split_lines), 2):
+        start_y0, start_y1 = h_split_lines[i:i+2]
+        # 然后找出[start_y0, start_y1]之间的其他bbox，这些组成一个未分割板块
+        bboxes_in_block = [bbox for bbox in all_bboxes if bbox[Y0_IDX]>=start_y0 and bbox[Y1_IDX]<=start_y1]
+        unsplited_bboxes.append(bboxes_in_block)
+    # ================== 至此，水平方向的 已经切分排序完毕====================================
+    """
+    接下来针对每个非水平的部分切分垂直方向的
+    此时，只剩下了无法被完全水平打通的bbox了。对这些box，优先进行垂直扩展，然后进行垂直切分.
+    分3步：
+    1. 先把能完全垂直打通的隔离出去当做一个layout
+    2. 其余的先垂直切分
+    3. 垂直切分之后的部分再尝试水平切分
+    4. 剩下的不能被切分的各个部分当成一个layout
+    """
+    # 对每部分进行垂直切分
+    for bboxes_in_block in unsplited_bboxes:
+        # 首先对这个block的bbox进行垂直方向上的扩展
+        boundry_x0, boundry_y0, boundry_x1, boundry_y1 = find_boundry_bboxes(bboxes_in_block) 
+        # 进行垂直方向上的扩展
+        extended_vertical_bboxes = extend_bbox_vertical(bboxes_in_block, boundry_x0, boundry_y0, boundry_x1, boundry_y1)
+        # 然后对这个block进行垂直方向上的切分
+        extend_bbox_vertical.sort(key=lambda x: x[X0_IDX]) # x方向上从小到大，代表了从左到右读取
+        v_boxes_group = []
+        for bbox in extended_vertical_bboxes:
+            if bbox[Y0_IDX]==boundry_y0 and bbox[Y1_IDX]==boundry_y1:
+                v_boxes_group.append(bbox)
+            else:
+                if len(v_boxes_group)>0:
+                    v_boxes.append(v_boxes_group)
+                    v_boxes_group = []
+                    
+        if len(v_boxes_group)>0:
+            
+            v_boxes.append(v_boxes_group)
+            
+        # 把连续的垂直部分加入到sorted_layouts里。注意这个时候已经是连续的垂直部分了，因为上面已经做了
+        for gp in v_boxes:
+            gp.sort(key=lambda x: x[X0_IDX])
+            block_info = {"layout_label":"GOOD_LAYOUT", "content_bboxes": gp}
+            # 然后计算这个group的layout_bbox，也就是最小的x0,y0, 最大的x1,y1
+            x0, y0, x1, y1 = gp[0][X0_EXT_IDX], gp[0][Y0_EXT_IDX], gp[-1][X1_EXT_IDX], gp[-1][Y1_EXT_IDX]
+            block_info["layout_bbox"] = [x0, y0, x1, y1]
+            sorted_layouts.append(block_info)
+            
+        # 在垂直方向上，划分子块，也就是用贯通的垂直线进行切分。这些被切分出来的块，极大可能是可被垂直切分的，如果不能完全的垂直切分，那么尝试水平切分。都不能的则当成一个layout
+        v_split_lines = [boundry_x0]
+        for gp in v_boxes:
+            layout_bbox = gp['layout_bbox']
+            x0, x1 = layout_bbox[0], layout_bbox[2]
+            v_split_lines.append(x0)
+            v_split_lines.append(x1)
+        v_split_lines.append(boundry_x1)
+        
+    reset_idx_x_y(all_bboxes)
+    all_boxes = _paper_bbox_sort_ext(all_bboxes)
+    return all_boxes
+            
+    
+    
+    
+    
+
+
+

magic_pdf/layout/layout_det_utils.py

+from magic_pdf.layout.bbox_sort import X0_EXT_IDX, X0_IDX, X1_EXT_IDX, X1_IDX, Y0_IDX, Y1_EXT_IDX, Y1_IDX
+from magic_pdf.libs.boxbase import _is_bottom_full_overlap, _left_intersect, _right_intersect
+
+
+def find_all_left_bbox_direct(this_bbox, all_bboxes) -> list:
+    """
+    在all_bboxes里找到所有右侧垂直方向上和this_bbox有重叠的bbox， 不用延长线
+    并且要考虑两个box左右相交的情况，如果相交了，那么右侧的box就不算最左侧。
+    """
+    left_boxes = [box for box in all_bboxes if box[X1_IDX] <= this_bbox[X0_IDX] 
+         and any([
+         box[Y0_IDX] < this_bbox[Y0_IDX] < box[Y1_IDX], box[Y0_IDX] < this_bbox[Y1_IDX] < box[Y1_IDX],
+         this_bbox[Y0_IDX] < box[Y0_IDX] < this_bbox[Y1_IDX], this_bbox[Y0_IDX] < box[Y1_IDX] < this_bbox[Y1_IDX],
+         box[Y0_IDX]==this_bbox[Y0_IDX] and box[Y1_IDX]==this_bbox[Y1_IDX]]) or _left_intersect(box[:4], this_bbox[:4])]
+        
+    # 然后再过滤一下，找到水平上距离this_bbox最近的那个——x1最大的那个
+    if len(left_boxes) > 0:
+        left_boxes.sort(key=lambda x: x[X1_EXT_IDX] if x[X1_EXT_IDX] else x[X1_IDX], reverse=True)
+        left_boxes = left_boxes[0]
+    else:
+        left_boxes = None
+    return left_boxes
+
+def find_all_right_bbox_direct(this_bbox, all_bboxes) -> list:
+    """
+    找到在this_bbox右侧且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    right_bboxes = [box for box in all_bboxes if box[X0_IDX] >= this_bbox[X1_IDX] 
+        and any([
+        this_bbox[Y0_IDX] < box[Y0_IDX] < this_bbox[Y1_IDX], this_bbox[Y0_IDX] < box[Y1_IDX] < this_bbox[Y1_IDX],
+        box[Y0_IDX] < this_bbox[Y0_IDX] < box[Y1_IDX], box[Y0_IDX] < this_bbox[Y1_IDX] < box[Y1_IDX],
+        box[Y0_IDX]==this_bbox[Y0_IDX] and box[Y1_IDX]==this_bbox[Y1_IDX]]) or _right_intersect(this_bbox[:4], box[:4])]
+    
+    if len(right_bboxes)>0:
+        right_bboxes.sort(key=lambda x: x[X0_EXT_IDX] if x[X0_EXT_IDX] else x[X0_IDX])
+        right_bboxes = right_bboxes[0]
+    else:
+        right_bboxes = None
+    return right_bboxes
+
+def find_all_top_bbox_direct(this_bbox, all_bboxes) -> list:
+    """
+    找到在this_bbox上侧且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    top_bboxes = [box for box in all_bboxes if box[Y1_IDX] <= this_bbox[Y0_IDX] and any([
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+        this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    
+    if len(top_bboxes)>0:
+        top_bboxes.sort(key=lambda x: x[Y1_EXT_IDX] if x[Y1_EXT_IDX] else x[Y1_IDX], reverse=True)
+        top_bboxes = top_bboxes[0]
+    else:
+        top_bboxes = None
+    return top_bboxes
+
+def find_all_bottom_bbox_direct(this_bbox, all_bboxes) -> list:
+    """
+    找到在this_bbox下侧且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    bottom_bboxes = [box for box in all_bboxes if box[Y0_IDX] >= this_bbox[Y1_IDX] and any([
+        this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    
+    if len(bottom_bboxes)>0:
+        bottom_bboxes.sort(key=lambda x:  x[Y0_IDX])
+        bottom_bboxes = bottom_bboxes[0]
+    else:
+        bottom_bboxes = None
+    return bottom_bboxes
+
+# ===================================================================================================================
+def find_bottom_bbox_direct_from_right_edge(this_bbox, all_bboxes) -> list:
+    """
+    找到在this_bbox下侧且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    bottom_bboxes = [box for box in all_bboxes if box[Y0_IDX] >= this_bbox[Y1_IDX] and any([
+        this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    
+    if len(bottom_bboxes)>0:
+        # y0最小， X1最大的那个,也就是box上边缘最靠近this_bbox的那个,并且还最靠右
+        bottom_bboxes.sort(key=lambda x: x[Y0_IDX])
+        bottom_bboxes = [box for box in bottom_bboxes if box[Y0_IDX]==bottom_bboxes[0][Y0_IDX]]
+        # 然后再y1相同的情况下，找到x1最大的那个
+        bottom_bboxes.sort(key=lambda x: x[X1_IDX], reverse=True)
+        bottom_bboxes = bottom_bboxes[0]
+    else:
+        bottom_bboxes = None
+    return bottom_bboxes
+
+def find_bottom_bbox_direct_from_left_edge(this_bbox, all_bboxes) -> list:
+    """
+    找到在this_bbox下侧且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    bottom_bboxes = [box for box in all_bboxes if box[Y0_IDX] >= this_bbox[Y1_IDX] and any([
+        this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    
+    if len(bottom_bboxes)>0:
+        # y0最小， X0最小的那个
+        bottom_bboxes.sort(key=lambda x: x[Y0_IDX])
+        bottom_bboxes = [box for box in bottom_bboxes if box[Y0_IDX]==bottom_bboxes[0][Y0_IDX]]
+        # 然后再y0相同的情况下，找到x0最小的那个
+        bottom_bboxes.sort(key=lambda x: x[X0_IDX])
+        bottom_bboxes = bottom_bboxes[0]
+    else:
+        bottom_bboxes = None
+    return bottom_bboxes
+
+def find_top_bbox_direct_from_left_edge(this_bbox, all_bboxes) -> list:
+    """
+    找到在this_bbox上侧且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    top_bboxes = [box for box in all_bboxes if box[Y1_IDX] <= this_bbox[Y0_IDX] and any([
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+        this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    
+    if len(top_bboxes)>0:
+        # y1最大， X0最小的那个
+        top_bboxes.sort(key=lambda x: x[Y1_IDX], reverse=True)
+        top_bboxes = [box for box in top_bboxes if box[Y1_IDX]==top_bboxes[0][Y1_IDX]]
+        # 然后再y1相同的情况下，找到x0最小的那个
+        top_bboxes.sort(key=lambda x: x[X0_IDX])
+        top_bboxes = top_bboxes[0]
+    else:
+        top_bboxes = None
+    return top_bboxes
+
+def find_top_bbox_direct_from_right_edge(this_bbox, all_bboxes) -> list:
+    """
+    找到在this_bbox上侧且距离this_bbox距离最近的bbox.必须是直接遮挡的那种
+    """
+    top_bboxes = [box for box in all_bboxes if box[Y1_IDX] <= this_bbox[Y0_IDX] and any([
+        box[X0_IDX] < this_bbox[X0_IDX] < box[X1_IDX], box[X0_IDX] < this_bbox[X1_IDX] < box[X1_IDX],
+        this_bbox[X0_IDX] < box[X0_IDX] < this_bbox[X1_IDX], this_bbox[X0_IDX] < box[X1_IDX] < this_bbox[X1_IDX],
+        box[X0_IDX]==this_bbox[X0_IDX] and box[X1_IDX]==this_bbox[X1_IDX]])]
+    
+    if len(top_bboxes)>0:
+        # y1最大， X1最大的那个
+        top_bboxes.sort(key=lambda x: x[Y1_IDX], reverse=True)
+        top_bboxes = [box for box in top_bboxes if box[Y1_IDX]==top_bboxes[0][Y1_IDX]]
+        # 然后再y1相同的情况下，找到x1最大的那个
+        top_bboxes.sort(key=lambda x: x[X1_IDX], reverse=True)
+        top_bboxes = top_bboxes[0]
+    else:
+        top_bboxes = None
+    return top_bboxes
+    
+# ===================================================================================================================
+
+def get_left_edge_bboxes(all_bboxes) -> list:
+    """
+    返回最左边的bbox
+    """
+    left_bboxes = [box for box in all_bboxes if find_all_left_bbox_direct(box, all_bboxes) is None]
+    return left_bboxes
+    
+def get_right_edge_bboxes(all_bboxes) -> list:
+    """
+    返回最右边的bbox
+    """
+    right_bboxes = [box for box in all_bboxes if find_all_right_bbox_direct(box, all_bboxes) is None]
+    return right_bboxes
+
+def fix_vertical_bbox_pos(bboxes:list):
+    """
+    检查这批bbox在垂直方向是否有轻微的重叠，如果重叠了，就把重叠的bbox往下移动一点
+    在x方向上必须一个包含或者被包含，或者完全重叠，不能只有部分重叠
+    """
+    bboxes.sort(key=lambda x: x[Y0_IDX]) # 从上向下排列
+    for i in range(0, len(bboxes)):
+        for j in range(i+1, len(bboxes)):
+            if _is_bottom_full_overlap(bboxes[i][:4], bboxes[j][:4]):
+                # 如果两个bbox有部分重叠，那么就把下面的bbox往下移动一点
+                bboxes[j][Y0_IDX] = bboxes[i][Y1_IDX] + 2 # 2是个经验值
+                break
+    return bboxes

magic_pdf/layout/layout_sort.py

+"""对pdf上的box进行layout识别，并对内部组成的box进行排序."""
+
+from loguru import logger
+
+from magic_pdf.layout.bbox_sort import (CONTENT_IDX, CONTENT_TYPE_IDX,
+                                        X0_EXT_IDX, X0_IDX, X1_EXT_IDX, X1_IDX,
+                                        Y0_EXT_IDX, Y0_IDX, Y1_EXT_IDX, Y1_IDX,
+                                        paper_bbox_sort)
+from magic_pdf.layout.layout_det_utils import (
+    find_all_bottom_bbox_direct, find_all_left_bbox_direct,
+    find_all_right_bbox_direct, find_all_top_bbox_direct,
+    find_bottom_bbox_direct_from_left_edge,
+    find_bottom_bbox_direct_from_right_edge,
+    find_top_bbox_direct_from_left_edge, find_top_bbox_direct_from_right_edge,
+    get_left_edge_bboxes, get_right_edge_bboxes)
+from magic_pdf.libs.boxbase import get_bbox_in_boundary
+
+LAYOUT_V = 'V'
+LAYOUT_H = 'H'
+LAYOUT_UNPROC = 'U'
+LAYOUT_BAD = 'B'
+
+
+def _is_single_line_text(bbox):
+    """检查bbox里面的文字是否只有一行."""
+    return True  # TODO
+    box_type = bbox[CONTENT_TYPE_IDX]
+    if box_type != 'text':
+        return False
+    paras = bbox[CONTENT_IDX]['paras']
+    text_content = ''
+    for para_id, para in paras.items():  # 拼装内部的段落文本
+        is_title = para['is_title']
+        if is_title != 0:
+            text_content += f"## {para['text']}"
+        else:
+            text_content += para['text']
+        text_content += '\n\n'
+
+    return bbox[CONTENT_TYPE_IDX] == 'text' and len(text_content.split('\n\n')) <= 1
+
+
+def _horizontal_split(bboxes: list, boundary: tuple, avg_font_size=20) -> list:
+    """
+    对bboxes进行水平切割
+    方法是：找到左侧和右侧都没有被直接遮挡的box，然后进行扩展，之后进行切割
+    return:
+        返回几个大的Layout区域 [[x0, y0, x1, y1, "h|u|v"], ], h代表水平，u代表未探测的，v代表垂直布局
+    """
+    sorted_layout_blocks = []  # 这是要最终返回的值
+
+    bound_x0, bound_y0, bound_x1, bound_y1 = boundary
+    all_bboxes = get_bbox_in_boundary(bboxes, boundary)
+    # all_bboxes = paper_bbox_sort(all_bboxes, abs(bound_x1-bound_x0), abs(bound_y1-bound_x0)) # 大致拍下序, 这个是基于直接遮挡的。
+    """
+    首先在水平方向上扩展独占一行的bbox
+
+    """
+    last_h_split_line_y1 = bound_y0  # 记录下上次的水平分割线
+    for i, bbox in enumerate(all_bboxes):
+        left_nearest_bbox = find_all_left_bbox_direct(bbox, all_bboxes)  # 非扩展线
+        right_nearest_bbox = find_all_right_bbox_direct(bbox, all_bboxes)
+        if left_nearest_bbox is None and right_nearest_bbox is None:  # 独占一行
+            """
+            然而，如果只是孤立的一行文字，那么就还要满足以下几个条件才可以：
+            1. bbox和中心线相交。或者
+            2. 上方或者下方也存在同类水平的独占一行的bbox。 或者
+            3. TODO 加强条件：这个bbox上方和下方是同一列column，那么就不能算作独占一行
+            """
+            # 先检查这个bbox里是否只包含一行文字
+            # is_single_line = _is_single_line_text(bbox)
+            """
+            这里有个点需要注意，当页面内容不是居中的时候，第一次调用传递的是page的boundary，这个时候mid_x就不是中心线了.
+            所以这里计算出最紧致的boundary，然后再计算mid_x
+            """
+            boundary_real_x0, boundary_real_x1 = min(
+                [bbox[X0_IDX] for bbox in all_bboxes]
+            ), max([bbox[X1_IDX] for bbox in all_bboxes])
+            mid_x = (boundary_real_x0 + boundary_real_x1) / 2
+            # 检查这个box是否内容在中心线有交
+            # 必须跨过去2个字符的宽度
+            is_cross_boundary_mid_line = (
+                min(mid_x - bbox[X0_IDX], bbox[X1_IDX] - mid_x) > avg_font_size * 2
+            )
+            """
+            检查条件2
+            """
+            is_belong_to_col = False
+            """
+            检查是否能被上方col吸收，方法是：
+            1. 上方非空且不是独占一行的，并且
+            2. 从上个水平分割的最大y=y1开始到当前bbox,最左侧的bbox的[min_x0, max_x1],能够覆盖当前box的[x0, x1]
+            """
+            """
+            以迭代的方式向上找，查找范围是[bound_x0, last_h_sp, bound_x1, bbox[Y0_IDX]]
+            """
+            # 先确定上方的y0, y0
+            b_y0, b_y1 = last_h_split_line_y1, bbox[Y0_IDX]
+            # 然后从box开始逐个向上找到所有与box在x上有交集的box
+            box_to_check = [bound_x0, b_y0, bound_x1, b_y1]
+            bbox_in_bound_check = get_bbox_in_boundary(all_bboxes, box_to_check)
+
+            bboxes_on_top = []
+            virtual_box = bbox
+            while True:
+                b_on_top = find_all_top_bbox_direct(virtual_box, bbox_in_bound_check)
+                if b_on_top is not None:
+                    bboxes_on_top.append(b_on_top)
+                    virtual_box = [
+                        min([virtual_box[X0_IDX], b_on_top[X0_IDX]]),
+                        min(virtual_box[Y0_IDX], b_on_top[Y0_IDX]),
+                        max([virtual_box[X1_IDX], b_on_top[X1_IDX]]),
+                        b_y1,
+                    ]
+                else:
+                    break
+
+            # 随后确定这些box的最小x0, 最大x1
+            if len(bboxes_on_top) > 0 and len(bboxes_on_top) != len(
+                bbox_in_bound_check
+            ):  # virtual_box可能会膨胀到占满整个区域，这实际上就不能属于一个col了。
+                min_x0, max_x1 = virtual_box[X0_IDX], virtual_box[X1_IDX]
+                # 然后采用一种比较粗糙的方法，看min_x0，max_x1是否与位于[bound_x0, last_h_sp, bound_x1, bbox[Y0_IDX]]之间的box有相交
+
+                if not any(
+                    [
+                        b[X0_IDX] <= min_x0 - 1 <= b[X1_IDX]
+                        or b[X0_IDX] <= max_x1 + 1 <= b[X1_IDX]
+                        for b in bbox_in_bound_check
+                    ]
+                ):
+                    # 其上，下都不能被扩展成行，暂时只检查一下上方 TODO
+                    top_nearest_bbox = find_all_top_bbox_direct(bbox, bboxes)
+                    bottom_nearest_bbox = find_all_bottom_bbox_direct(bbox, bboxes)
+                    if not any(
+                        [
+                            top_nearest_bbox is not None
+                            and (
+                                find_all_left_bbox_direct(top_nearest_bbox, bboxes)
+                                is None
+                                and find_all_right_bbox_direct(top_nearest_bbox, bboxes)
+                                is None
+                            ),
+                            bottom_nearest_bbox is not None
+                            and (
+                                find_all_left_bbox_direct(bottom_nearest_bbox, bboxes)
+                                is None
+                                and find_all_right_bbox_direct(
+                                    bottom_nearest_bbox, bboxes
+                                )
+                                is None
+                            ),
+                            top_nearest_bbox is None or bottom_nearest_bbox is None,
+                        ]
+                    ):
+                        is_belong_to_col = True
+
+            # 检查是否能被下方col吸收 TODO
+            """
+            这里为什么没有is_cross_boundary_mid_line的条件呢？
+            确实有些杂志左右两栏宽度不是对称的。
+            """
+            if not is_belong_to_col or is_cross_boundary_mid_line:
+                bbox[X0_EXT_IDX] = bound_x0
+                bbox[Y0_EXT_IDX] = bbox[Y0_IDX]
+                bbox[X1_EXT_IDX] = bound_x1
+                bbox[Y1_EXT_IDX] = bbox[Y1_IDX]
+                last_h_split_line_y1 = bbox[Y1_IDX]  # 更新这条线
+            else:
+                continue
+    """
+    此时独占一行的被成功扩展到指定的边界上，这个时候利用边界条件合并连续的bbox，成为一个group
+    然后合并所有连续水平方向的bbox.
+    """
+    all_bboxes.sort(key=lambda x: x[Y0_IDX])
+    h_bboxes = []
+    h_bbox_group = []
+
+    for bbox in all_bboxes:
+        if bbox[X0_EXT_IDX] == bound_x0 and bbox[X1_EXT_IDX] == bound_x1:
+            h_bbox_group.append(bbox)
+        else:
+            if len(h_bbox_group) > 0:
+                h_bboxes.append(h_bbox_group)
+                h_bbox_group = []
+    # 最后一个group
+    if len(h_bbox_group) > 0:
+        h_bboxes.append(h_bbox_group)
+    """
+    现在h_bboxes里面是所有的group了，每个group都是一个list
+    对h_bboxes里的每个group进行计算放回到sorted_layouts里
+    """
+    h_layouts = []
+    for gp in h_bboxes:
+        gp.sort(key=lambda x: x[Y0_IDX])
+        # 然后计算这个group的layout_bbox，也就是最小的x0,y0, 最大的x1,y1
+        x0, y0, x1, y1 = (
+            gp[0][X0_EXT_IDX],
+            gp[0][Y0_EXT_IDX],
+            gp[-1][X1_EXT_IDX],
+            gp[-1][Y1_EXT_IDX],
+        )
+        h_layouts.append([x0, y0, x1, y1, LAYOUT_H])  # 水平的布局
+    """
+    接下来利用这些连续的水平bbox的layout_bbox的y0, y1，从水平上切分开其余的为几个部分
+    """
+    h_split_lines = [bound_y0]
+    for gp in h_bboxes:  # gp是一个list[bbox_list]
+        y0, y1 = gp[0][1], gp[-1][3]
+        h_split_lines.append(y0)
+        h_split_lines.append(y1)
+    h_split_lines.append(bound_y1)
+
+    unsplited_bboxes = []
+    for i in range(0, len(h_split_lines), 2):
+        start_y0, start_y1 = h_split_lines[i : i + 2]
+        # 然后找出[start_y0, start_y1]之间的其他bbox，这些组成一个未分割板块
+        bboxes_in_block = [
+            bbox
+            for bbox in all_bboxes
+            if bbox[Y0_IDX] >= start_y0 and bbox[Y1_IDX] <= start_y1
+        ]
+        unsplited_bboxes.append(bboxes_in_block)
+    # 接着把未处理的加入到h_layouts里
+    for bboxes_in_block in unsplited_bboxes:
+        if len(bboxes_in_block) == 0:
+            continue
+        x0, y0, x1, y1 = (
+            bound_x0,
+            min([bbox[Y0_IDX] for bbox in bboxes_in_block]),
+            bound_x1,
+            max([bbox[Y1_IDX] for bbox in bboxes_in_block]),
+        )
+        h_layouts.append([x0, y0, x1, y1, LAYOUT_UNPROC])
+
+    h_layouts.sort(key=lambda x: x[1])  # 按照y0排序, 也就是从上到下的顺序
+    """
+    转换成如下格式返回
+    """
+    for layout in h_layouts:
+        sorted_layout_blocks.append(
+            {
+                'layout_bbox': layout[:4],
+                'layout_label': layout[4],
+                'sub_layout': [],
+            }
+        )
+    return sorted_layout_blocks
+
+
+###############################################################################################
+#
+#  垂直方向的处理
+#
+#
+###############################################################################################
+def _vertical_align_split_v1(bboxes: list, boundary: tuple) -> list:
+    """
+    计算垂直方向上的对齐， 并分割bboxes成layout。负责对一列多行的进行列维度分割。
+    如果不能完全分割，剩余部分作为layout_lable为u的layout返回
+    -----------------------
+    |     |           |
+    |     |           |
+    |     |           |
+    |     |           |
+    -------------------------
+    此函数会将：以上布局将会切分出来2列
+    """
+    sorted_layout_blocks = []  # 这是要最终返回的值
+    new_boundary = [boundary[0], boundary[1], boundary[2], boundary[3]]
+
+    v_blocks = []
+    """
+    先从左到右切分
+    """
+    while True:
+        all_bboxes = get_bbox_in_boundary(bboxes, new_boundary)
+        left_edge_bboxes = get_left_edge_bboxes(all_bboxes)
+        if len(left_edge_bboxes) == 0:
+            break
+        right_split_line_x1 = max([bbox[X1_IDX] for bbox in left_edge_bboxes]) + 1
+        # 然后检查这条线能不与其他bbox的左边界相交或者重合
+        if any(
+            [bbox[X0_IDX] <= right_split_line_x1 <= bbox[X1_IDX] for bbox in all_bboxes]
+        ):
+            # 垂直切分线与某些box发生相交，说明无法完全垂直方向切分。
+            break
+        else:  # 说明成功分割出一列
+            # 找到左侧边界最靠左的bbox作为layout的x0
+            layout_x0 = min(
+                [bbox[X0_IDX] for bbox in left_edge_bboxes]
+            )  # 这里主要是为了画出来有一定间距
+            v_blocks.append(
+                [
+                    layout_x0,
+                    new_boundary[1],
+                    right_split_line_x1,
+                    new_boundary[3],
+                    LAYOUT_V,
+                ]
+            )
+            new_boundary[0] = right_split_line_x1  # 更新边界
+    """
+    再从右到左切， 此时如果还是无法完全切分，那么剩余部分作为layout_lable为u的layout返回
+    """
+    unsplited_block = []
+    while True:
+        all_bboxes = get_bbox_in_boundary(bboxes, new_boundary)
+        right_edge_bboxes = get_right_edge_bboxes(all_bboxes)
+        if len(right_edge_bboxes) == 0:
+            break
+        left_split_line_x0 = min([bbox[X0_IDX] for bbox in right_edge_bboxes]) - 1
+        # 然后检查这条线能不与其他bbox的左边界相交或者重合
+        if any(
+            [bbox[X0_IDX] <= left_split_line_x0 <= bbox[X1_IDX] for bbox in all_bboxes]
+        ):
+            # 这里是余下的
+            unsplited_block.append(
+                [
+                    new_boundary[0],
+                    new_boundary[1],
+                    new_boundary[2],
+                    new_boundary[3],
+                    LAYOUT_UNPROC,
+                ]
+            )
+            break
+        else:
+            # 找到右侧边界最靠右的bbox作为layout的x1
+            layout_x1 = max([bbox[X1_IDX] for bbox in right_edge_bboxes])
+            v_blocks.append(
+                [
+                    left_split_line_x0,
+                    new_boundary[1],
+                    layout_x1,
+                    new_boundary[3],
+                    LAYOUT_V,
+                ]
+            )
+            new_boundary[2] = left_split_line_x0  # 更新右边界
+    """
+    最后拼装成layout格式返回
+    """
+    for block in v_blocks:
+        sorted_layout_blocks.append(
+            {
+                'layout_bbox': block[:4],
+                'layout_label': block[4],
+                'sub_layout': [],
+            }
+        )
+    for block in unsplited_block:
+        sorted_layout_blocks.append(
+            {
+                'layout_bbox': block[:4],
+                'layout_label': block[4],
+                'sub_layout': [],
+            }
+        )
+
+    # 按照x0排序
+    sorted_layout_blocks.sort(key=lambda x: x['layout_bbox'][0])
+    return sorted_layout_blocks
+
+
+def _vertical_align_split_v2(bboxes: list, boundary: tuple) -> list:
+    """改进的
+    _vertical_align_split算法，原算法会因为第二列的box由于左侧没有遮挡被认为是左侧的一部分，导致整个layout多列被识别为一列。
+    利用从左上角的box开始向下看的方法，不断扩展w_x0, w_x1，直到不能继续向下扩展，或者到达边界下边界。"""
+    sorted_layout_blocks = []  # 这是要最终返回的值
+    new_boundary = [boundary[0], boundary[1], boundary[2], boundary[3]]
+    bad_boxes = []  # 被割中的box
+    v_blocks = []
+    while True:
+        all_bboxes = get_bbox_in_boundary(bboxes, new_boundary)
+        if len(all_bboxes) == 0:
+            break
+        left_top_box = min(
+            all_bboxes, key=lambda x: (x[X0_IDX], x[Y0_IDX])
+        )  # 这里应该加强，检查一下必须是在第一列的 TODO
+        start_box = [
+            left_top_box[X0_IDX],
+            left_top_box[Y0_IDX],
+            left_top_box[X1_IDX],
+            left_top_box[Y1_IDX],
+        ]
+        w_x0, w_x1 = left_top_box[X0_IDX], left_top_box[X1_IDX]
+        """
+        然后沿着这个box线向下找最近的那个box, 然后扩展w_x0, w_x1
+        扩展之后，宽度会增加，随后用x=w_x1来检测在边界内是否有box与相交，如果相交，那么就说明不能再扩展了。
+        当不能扩展的时候就要看是否到达下边界：
+        1. 达到，那么更新左边界继续分下一个列
+        2. 没有达到，那么此时开始从右侧切分进入下面的循环里
+        """
+        while left_top_box is not None:  # 向下去找
+            virtual_box = [w_x0, left_top_box[Y0_IDX], w_x1, left_top_box[Y1_IDX]]
+            left_top_box = find_bottom_bbox_direct_from_left_edge(
+                virtual_box, all_bboxes
+            )
+            if left_top_box:
+                w_x0, w_x1 = min(virtual_box[X0_IDX], left_top_box[X0_IDX]), max(
+                    [virtual_box[X1_IDX], left_top_box[X1_IDX]]
+                )
+        # 万一这个初始的box在column中间，那么还要向上看
+        start_box = [
+            w_x0,
+            start_box[Y0_IDX],
+            w_x1,
+            start_box[Y1_IDX],
+        ]  # 扩展一下宽度更鲁棒
+        left_top_box = find_top_bbox_direct_from_left_edge(start_box, all_bboxes)
+        while left_top_box is not None:  # 向上去找
+            virtual_box = [w_x0, left_top_box[Y0_IDX], w_x1, left_top_box[Y1_IDX]]
+            left_top_box = find_top_bbox_direct_from_left_edge(virtual_box, all_bboxes)
+            if left_top_box:
+                w_x0, w_x1 = min(virtual_box[X0_IDX], left_top_box[X0_IDX]), max(
+                    [virtual_box[X1_IDX], left_top_box[X1_IDX]]
+                )
+
+        # 检查相交
+        if any([bbox[X0_IDX] <= w_x1 + 1 <= bbox[X1_IDX] for bbox in all_bboxes]):
+            for b in all_bboxes:
+                if b[X0_IDX] <= w_x1 + 1 <= b[X1_IDX]:
+                    bad_boxes.append([b[X0_IDX], b[Y0_IDX], b[X1_IDX], b[Y1_IDX]])
+            break
+        else:  # 说明成功分割出一列
+            v_blocks.append([w_x0, new_boundary[1], w_x1, new_boundary[3], LAYOUT_V])
+            new_boundary[0] = w_x1  # 更新边界
+    """
+    接着开始从右上角的box扫描
+    """
+    w_x0, w_x1 = 0, 0
+    unsplited_block = []
+    while True:
+        all_bboxes = get_bbox_in_boundary(bboxes, new_boundary)
+        if len(all_bboxes) == 0:
+            break
+        # 先找到X1最大的
+        bbox_list_sorted = sorted(
+            all_bboxes, key=lambda bbox: bbox[X1_IDX], reverse=True
+        )
+        # Then, find the boxes with the smallest Y0 value
+        bigest_x1 = bbox_list_sorted[0][X1_IDX]
+        boxes_with_bigest_x1 = [
+            bbox for bbox in bbox_list_sorted if bbox[X1_IDX] == bigest_x1
+        ]  # 也就是最靠右的那些
+        right_top_box = min(
+            boxes_with_bigest_x1, key=lambda bbox: bbox[Y0_IDX]
+        )  # y0最小的那个
+        start_box = [
+            right_top_box[X0_IDX],
+            right_top_box[Y0_IDX],
+            right_top_box[X1_IDX],
+            right_top_box[Y1_IDX],
+        ]
+        w_x0, w_x1 = right_top_box[X0_IDX], right_top_box[X1_IDX]
+
+        while right_top_box is not None:
+            virtual_box = [w_x0, right_top_box[Y0_IDX], w_x1, right_top_box[Y1_IDX]]
+            right_top_box = find_bottom_bbox_direct_from_right_edge(
+                virtual_box, all_bboxes
+            )
+            if right_top_box:
+                w_x0, w_x1 = min([w_x0, right_top_box[X0_IDX]]), max(
+                    [w_x1, right_top_box[X1_IDX]]
+                )
+        # 在向上扫描
+        start_box = [
+            w_x0,
+            start_box[Y0_IDX],
+            w_x1,
+            start_box[Y1_IDX],
+        ]  # 扩展一下宽度更鲁棒
+        right_top_box = find_top_bbox_direct_from_right_edge(start_box, all_bboxes)
+        while right_top_box is not None:
+            virtual_box = [w_x0, right_top_box[Y0_IDX], w_x1, right_top_box[Y1_IDX]]
+            right_top_box = find_top_bbox_direct_from_right_edge(
+                virtual_box, all_bboxes
+            )
+            if right_top_box:
+                w_x0, w_x1 = min([w_x0, right_top_box[X0_IDX]]), max(
+                    [w_x1, right_top_box[X1_IDX]]
+                )
+
+        # 检查是否与其他box相交， 垂直切分线与某些box发生相交，说明无法完全垂直方向切分。
+        if any([bbox[X0_IDX] <= w_x0 - 1 <= bbox[X1_IDX] for bbox in all_bboxes]):
+            unsplited_block.append(
+                [
+                    new_boundary[0],
+                    new_boundary[1],
+                    new_boundary[2],
+                    new_boundary[3],
+                    LAYOUT_UNPROC,
+                ]
+            )
+            for b in all_bboxes:
+                if b[X0_IDX] <= w_x0 - 1 <= b[X1_IDX]:
+                    bad_boxes.append([b[X0_IDX], b[Y0_IDX], b[X1_IDX], b[Y1_IDX]])
+            break
+        else:  # 说明成功分割出一列
+            v_blocks.append([w_x0, new_boundary[1], w_x1, new_boundary[3], LAYOUT_V])
+            new_boundary[2] = w_x0
+    """转换数据结构"""
+    for block in v_blocks:
+        sorted_layout_blocks.append(
+            {
+                'layout_bbox': block[:4],
+                'layout_label': block[4],
+                'sub_layout': [],
+            }
+        )
+
+    for block in unsplited_block:
+        sorted_layout_blocks.append(
+            {
+                'layout_bbox': block[:4],
+                'layout_label': block[4],
+                'sub_layout': [],
+                'bad_boxes': bad_boxes,  # 记录下来，这个box是被割中的
+            }
+        )
+
+    # 按照x0排序
+    sorted_layout_blocks.sort(key=lambda x: x['layout_bbox'][0])
+    return sorted_layout_blocks
+
+
+def _try_horizontal_mult_column_split(bboxes: list, boundary: tuple) -> list:
+    """
+    尝试水平切分，如果切分不动，那就当一个BAD_LAYOUT返回
+    ------------------
+    |        |       |
+    ------------------
+    |    |       |   |   <-  这里是此函数要切分的场景
+    ------------------
+    |        |       |
+    |        |       |
+    """
+    pass
+
+
+def _vertical_split(bboxes: list, boundary: tuple) -> list:
+    """
+    从垂直方向进行切割，分block
+    这个版本里，如果垂直切分不动，那就当一个BAD_LAYOUT返回
+
+                                --------------------------
+                                    |        |       |
+                                    |        |       |
+                                | |
+    这种列是此函数要切分的  ->    | |
+                                | |
+                                    |        |       |
+                                    |        |       |
+                                -------------------------
+    """
+    sorted_layout_blocks = []  # 这是要最终返回的值
+
+    bound_x0, bound_y0, bound_x1, bound_y1 = boundary
+    all_bboxes = get_bbox_in_boundary(bboxes, boundary)
+    """
+    all_bboxes = fix_vertical_bbox_pos(all_bboxes) # 垂直方向解覆盖
+    all_bboxes = fix_hor_bbox_pos(all_bboxes)  # 水平解覆盖
+
+    这两行代码目前先不执行，因为公式检测，表格检测还不是很成熟，导致非常多的textblock参与了运算，时间消耗太大。
+    这两行代码的作用是：
+    如果遇到互相重叠的bbox, 那么会把面积较小的box进行压缩，从而避免重叠。对布局切分来说带来正反馈。
+    """
+
+    # all_bboxes = paper_bbox_sort(all_bboxes, abs(bound_x1-bound_x0), abs(bound_y1-bound_x0)) # 大致拍下序, 这个是基于直接遮挡的。
+    """
+    首先在垂直方向上扩展独占一行的bbox
+
+    """
+    for bbox in all_bboxes:
+        top_nearest_bbox = find_all_top_bbox_direct(bbox, all_bboxes)  # 非扩展线
+        bottom_nearest_bbox = find_all_bottom_bbox_direct(bbox, all_bboxes)
+        if (
+            top_nearest_bbox is None
+            and bottom_nearest_bbox is None
+            and not any(
+                [
+                    b[X0_IDX] < bbox[X1_IDX] < b[X1_IDX]
+                    or b[X0_IDX] < bbox[X0_IDX] < b[X1_IDX]
+                    for b in all_bboxes
+                ]
+            )
+        ):  # 独占一列, 且不和其他重叠
+            bbox[X0_EXT_IDX] = bbox[X0_IDX]
+            bbox[Y0_EXT_IDX] = bound_y0
+            bbox[X1_EXT_IDX] = bbox[X1_IDX]
+            bbox[Y1_EXT_IDX] = bound_y1
+        """
+    此时独占一列的被成功扩展到指定的边界上，这个时候利用边界条件合并连续的bbox，成为一个group
+    然后合并所有连续垂直方向的bbox.
+    """
+    all_bboxes.sort(key=lambda x: x[X0_IDX])
+    # fix: 这里水平方向的列不要合并成一个行，因为需要保证返回给下游的最小block，总是可以无脑从上到下阅读文字。
+    v_bboxes = []
+    for box in all_bboxes:
+        if box[Y0_EXT_IDX] == bound_y0 and box[Y1_EXT_IDX] == bound_y1:
+            v_bboxes.append(box)
+    """
+    现在v_bboxes里面是所有的group了，每个group都是一个list
+    对v_bboxes里的每个group进行计算放回到sorted_layouts里
+    """
+    v_layouts = []
+    for vbox in v_bboxes:
+        # gp.sort(key=lambda x: x[X0_IDX])
+        # 然后计算这个group的layout_bbox，也就是最小的x0,y0, 最大的x1,y1
+        x0, y0, x1, y1 = (
+            vbox[X0_EXT_IDX],
+            vbox[Y0_EXT_IDX],
+            vbox[X1_EXT_IDX],
+            vbox[Y1_EXT_IDX],
+        )
+        v_layouts.append([x0, y0, x1, y1, LAYOUT_V])  # 垂直的布局
+    """
+    接下来利用这些连续的垂直bbox的layout_bbox的x0, x1，从垂直上切分开其余的为几个部分
+    """
+    v_split_lines = [bound_x0]
+    for gp in v_bboxes:
+        x0, x1 = gp[X0_IDX], gp[X1_IDX]
+        v_split_lines.append(x0)
+        v_split_lines.append(x1)
+    v_split_lines.append(bound_x1)
+
+    unsplited_bboxes = []
+    for i in range(0, len(v_split_lines), 2):
+        start_x0, start_x1 = v_split_lines[i : i + 2]
+        # 然后找出[start_x0, start_x1]之间的其他bbox，这些组成一个未分割板块
+        bboxes_in_block = [
+            bbox
+            for bbox in all_bboxes
+            if bbox[X0_IDX] >= start_x0 and bbox[X1_IDX] <= start_x1
+        ]
+        unsplited_bboxes.append(bboxes_in_block)
+    # 接着把未处理的加入到v_layouts里
+    for bboxes_in_block in unsplited_bboxes:
+        if len(bboxes_in_block) == 0:
+            continue
+        x0, y0, x1, y1 = (
+            min([bbox[X0_IDX] for bbox in bboxes_in_block]),
+            bound_y0,
+            max([bbox[X1_IDX] for bbox in bboxes_in_block]),
+            bound_y1,
+        )
+        v_layouts.append(
+            [x0, y0, x1, y1, LAYOUT_UNPROC]
+        )  # 说明这篇区域未能够分析出可靠的版面
+
+    v_layouts.sort(key=lambda x: x[0])  # 按照x0排序, 也就是从左到右的顺序
+
+    for layout in v_layouts:
+        sorted_layout_blocks.append(
+            {
+                'layout_bbox': layout[:4],
+                'layout_label': layout[4],
+                'sub_layout': [],
+            }
+        )
+    """
+    至此，垂直方向切成了2种类型，其一是独占一列的，其二是未处理的。
+    下面对这些未处理的进行垂直方向切分，这个切分要切出来类似“吕”这种类型的垂直方向的布局
+    """
+    for i, layout in enumerate(sorted_layout_blocks):
+        if layout['layout_label'] == LAYOUT_UNPROC:
+            x0, y0, x1, y1 = layout['layout_bbox']
+            v_split_layouts = _vertical_align_split_v2(bboxes, [x0, y0, x1, y1])
+            sorted_layout_blocks[i] = {
+                'layout_bbox': [x0, y0, x1, y1],
+                'layout_label': LAYOUT_H,
+                'sub_layout': v_split_layouts,
+            }
+            layout['layout_label'] = LAYOUT_H  # 被垂线切分成了水平布局
+
+    return sorted_layout_blocks
+
+
+def split_layout(bboxes: list, boundary: tuple, page_num: int) -> list:
+    """
+    把bboxes切割成layout
+    return:
+    [
+        {
+            "layout_bbox": [x0,y0,x1,y1],
+            "layout_label":"u|v|h|b", 未处理|垂直|水平|BAD_LAYOUT
+            "sub_layout":[] #每个元素都是[
+                                            x0,y0,
+                                            x1,y1,
+                                            block_content,
+                                            idx_x,idx_y,
+                                            content_type,
+                                            ext_x0,ext_y0,
+                                            ext_x1,ext_y1
+                                        ], 并且顺序就是阅读顺序
+        }
+    ]
+    example:
+    [
+        {
+            "layout_bbox": [0, 0, 100, 100],
+            "layout_label":"u|v|h|b",
+            "sub_layout":[
+
+            ]
+        },
+        {
+            "layout_bbox": [0, 0, 100, 100],
+            "layout_label":"u|v|h|b",
+            "sub_layout":[
+                {
+                    "layout_bbox": [0, 0, 100, 100],
+                    "layout_label":"u|v|h|b",
+                    "content_bboxes":[
+                        [],
+                        [],
+                        []
+                    ]
+                },
+                {
+                    "layout_bbox": [0, 0, 100, 100],
+                    "layout_label":"u|v|h|b",
+                    "sub_layout":[
+
+                    ]
+                }
+        }
+    ]
+    """
+    sorted_layouts = []  # 最终返回的结果
+
+    boundary_x0, boundary_y0, boundary_x1, boundary_y1 = boundary
+    if len(bboxes) <= 1:
+        return [
+            {
+                'layout_bbox': [boundary_x0, boundary_y0, boundary_x1, boundary_y1],
+                'layout_label': LAYOUT_V,
+                'sub_layout': [],
+            }
+        ]
+    """
+    接下来按照先水平后垂直的顺序进行切分
+    """
+    bboxes = paper_bbox_sort(
+        bboxes, boundary_x1 - boundary_x0, boundary_y1 - boundary_y0
+    )
+    sorted_layouts = _horizontal_split(bboxes, boundary)  # 通过水平分割出来的layout
+    for i, layout in enumerate(sorted_layouts):
+        x0, y0, x1, y1 = layout['layout_bbox']
+        layout_type = layout['layout_label']
+        if layout_type == LAYOUT_UNPROC:  # 说明是非独占单行的，这些需要垂直切分
+            v_split_layouts = _vertical_split(bboxes, [x0, y0, x1, y1])
+            """
+            最后这里有个逻辑问题：如果这个函数只分离出来了一个column layout，那么这个layout分割肯定超出了算法能力范围。因为我们假定的是传进来的
+            box已经把行全部剥离了，所以这里必须十多个列才可以。如果只剥离出来一个layout，并且是多个box，那么就说明这个layout是无法分割的，标记为LAYOUT_UNPROC
+            """
+            layout_label = LAYOUT_V
+            if len(v_split_layouts) == 1:
+                if len(v_split_layouts[0]['sub_layout']) == 0:
+                    layout_label = LAYOUT_UNPROC
+                    # logger.warning(f"WARNING: pageno={page_num}, 无法分割的layout: ", v_split_layouts)
+            """
+            组合起来最终的layout
+            """
+            sorted_layouts[i] = {
+                'layout_bbox': [x0, y0, x1, y1],
+                'layout_label': layout_label,
+                'sub_layout': v_split_layouts,
+            }
+            layout['layout_label'] = LAYOUT_H
+    """
+    水平和垂直方向都切分完毕了。此时还有一些未处理的，这些未处理的可能是因为水平和垂直方向都无法切分。
+    这些最后调用_try_horizontal_mult_block_split做一次水平多个block的联合切分，如果也不能切分最终就当做BAD_LAYOUT返回
+    """
+    # TODO
+
+    return sorted_layouts
+
+
+def get_bboxes_layout(all_boxes: list, boundary: tuple, page_id: int):
+    """
+    对利用layout排序之后的box，进行排序
+    return:
+    [
+        {
+            "layout_bbox": [x0, y0, x1, y1],
+            "layout_label":"u|v|h|b", 未处理|垂直|水平|BAD_LAYOUT
+        }，
+    ]
+    """
+
+    def _preorder_traversal(layout):
+        """对sorted_layouts的叶子节点，也就是len(sub_layout)==0的节点进行排序。排序按照前序遍历的顺序，也就是从上到
+        下，从左到右的顺序."""
+        sorted_layout_blocks = []
+        for layout in layout:
+            sub_layout = layout['sub_layout']
+            if len(sub_layout) == 0:
+                sorted_layout_blocks.append(layout)
+            else:
+                s = _preorder_traversal(sub_layout)
+                sorted_layout_blocks.extend(s)
+        return sorted_layout_blocks
+
+    # -------------------------------------------------------------------------------------------------------------------------
+    sorted_layouts = split_layout(
+        all_boxes, boundary, page_id
+    )  # 先切分成layout，得到一个Tree
+    total_sorted_layout_blocks = _preorder_traversal(sorted_layouts)
+    return total_sorted_layout_blocks, sorted_layouts
+
+
+def get_columns_cnt_of_layout(layout_tree):
+    """获取一个layout的宽度."""
+    max_width_list = [0]  # 初始化一个元素，防止max,min函数报错
+
+    for items in layout_tree:  # 针对每一层（横切）计算列数，横着的算一列
+        layout_type = items['layout_label']
+        sub_layouts = items['sub_layout']
+        if len(sub_layouts) == 0:
+            max_width_list.append(1)
+        else:
+            if layout_type == LAYOUT_H:
+                max_width_list.append(1)
+            else:
+                width = 0
+                for sub_layout in sub_layouts:
+                    if len(sub_layout['sub_layout']) == 0:
+                        width += 1
+                    else:
+                        for lay in sub_layout['sub_layout']:
+                            width += get_columns_cnt_of_layout([lay])
+                max_width_list.append(width)
+
+    return max(max_width_list)
+
+
+def sort_with_layout(bboxes: list, page_width, page_height) -> (list, list):
+    """输入是一个bbox的list.
+
+    获取到输入之后，先进行layout切分，然后对这些bbox进行排序。返回排序后的bboxes
+    """
+
+    new_bboxes = []
+    for box in bboxes:
+        # new_bboxes.append([box[0], box[1], box[2], box[3], None, None, None, 'text', None, None, None, None])
+        new_bboxes.append(
+            [
+                box[0],
+                box[1],
+                box[2],
+                box[3],
+                None,
+                None,
+                None,
+                'text',
+                None,
+                None,
+                None,
+                None,
+                box[4],
+            ]
+        )
+
+    layout_bboxes, _ = get_bboxes_layout(
+        new_bboxes, tuple([0, 0, page_width, page_height]), 0
+    )
+    if any([lay['layout_label'] == LAYOUT_UNPROC for lay in layout_bboxes]):
+        logger.warning('drop this pdf, reason: 复杂版面')
+        return None, None
+
+    sorted_bboxes = []
+    # 利用layout bbox每次框定一些box，然后排序
+    for layout in layout_bboxes:
+        lbox = layout['layout_bbox']
+        bbox_in_layout = get_bbox_in_boundary(new_bboxes, lbox)
+        sorted_bbox = paper_bbox_sort(
+            bbox_in_layout, lbox[2] - lbox[0], lbox[3] - lbox[1]
+        )
+        sorted_bboxes.extend(sorted_bbox)
+
+    return sorted_bboxes, layout_bboxes
+
+
+def sort_text_block(text_block, layout_bboxes):
+    """对一页的text_block进行排序."""
+    sorted_text_bbox = []
+    all_text_bbox = []
+    # 做一个box=>text的映射
+    box_to_text = {}
+    for blk in text_block:
+        box = blk['bbox']
+        box_to_text[(box[0], box[1], box[2], box[3])] = blk
+        all_text_bbox.append(box)
+
+    # text_blocks_to_sort = []
+    # for box in box_to_text.keys():
+    #     text_blocks_to_sort.append([box[0], box[1], box[2], box[3], None, None, None, 'text', None, None, None, None])
+
+    # 按照layout_bboxes的顺序，对text_block进行排序
+    for layout in layout_bboxes:
+        layout_box = layout['layout_bbox']
+        text_bbox_in_layout = get_bbox_in_boundary(
+            all_text_bbox,
+            [
+                layout_box[0] - 1,
+                layout_box[1] - 1,
+                layout_box[2] + 1,
+                layout_box[3] + 1,
+            ],
+        )
+        # sorted_bbox = paper_bbox_sort(text_bbox_in_layout, layout_box[2]-layout_box[0], layout_box[3]-layout_box[1])
+        text_bbox_in_layout.sort(
+            key=lambda x: x[1]
+        )  # 一个layout内部的box，按照y0自上而下排序
+        # sorted_bbox = [[b] for b in text_blocks_to_sort]
+        for sb in text_bbox_in_layout:
+            sorted_text_bbox.append(box_to_text[(sb[0], sb[1], sb[2], sb[3])])
+
+    return sorted_text_bbox

magic_pdf/layout/layout_spiler_recog.py

+"""
+找到能分割布局的水平的横线、色块
+"""
+
+import os
+from magic_pdf.libs.commons import fitz
+from magic_pdf.libs.boxbase import _is_in_or_part_overlap
+
+
+def __rect_filter_by_width(rect, page_w, page_h):
+    mid_x = page_w/2
+    if rect[0]< mid_x < rect[2]:
+        return True
+    return False
+
+
+def __rect_filter_by_pos(rect, image_bboxes, table_bboxes):
+    """
+    不能出现在table和image的位置
+    """
+    for box in image_bboxes:
+        if _is_in_or_part_overlap(rect, box):
+            return False
+    
+    for box in table_bboxes:
+        if _is_in_or_part_overlap(rect, box):
+            return False
+    
+    return True
+
+
+def __debug_show_page(page, bboxes1: list,bboxes2: list,bboxes3: list,):
+    save_path = "./tmp/debug.pdf"
+    if os.path.exists(save_path):
+        # 删除已经存在的文件
+        os.remove(save_path)
+    # 创建一个新的空白 PDF 文件
+    doc = fitz.open('')
+
+    width = page.rect.width
+    height = page.rect.height
+    new_page = doc.new_page(width=width, height=height)
+    
+    shape = new_page.new_shape()
+    for bbox in bboxes1:
+        # 原始box画上去
+        rect = fitz.Rect(*bbox[0:4])
+        shape = new_page.new_shape()
+        shape.draw_rect(rect)
+        shape.finish(color=fitz.pdfcolor['red'], fill=fitz.pdfcolor['blue'], fill_opacity=0.2)
+        shape.finish()
+        shape.commit()
+        
+    for bbox in bboxes2:
+        # 原始box画上去
+        rect = fitz.Rect(*bbox[0:4])
+        shape = new_page.new_shape()
+        shape.draw_rect(rect)
+        shape.finish(color=None, fill=fitz.pdfcolor['yellow'], fill_opacity=0.2)
+        shape.finish()
+        shape.commit()
+        
+    for bbox in bboxes3:
+        # 原始box画上去
+        rect = fitz.Rect(*bbox[0:4])
+        shape = new_page.new_shape()
+        shape.draw_rect(rect)
+        shape.finish(color=fitz.pdfcolor['red'], fill=None)
+        shape.finish()
+        shape.commit()
+        
+    parent_dir = os.path.dirname(save_path)
+    if not os.path.exists(parent_dir):
+        os.makedirs(parent_dir)
+
+    doc.save(save_path)
+    doc.close() 
+    
+def get_spilter_of_page(page, image_bboxes, table_bboxes):
+    """
+    获取到色块和横线
+    """
+    cdrawings = page.get_cdrawings()
+    
+    spilter_bbox = []
+    for block in cdrawings:
+        if 'fill' in block:
+            fill = block['fill']
+        if 'fill' in block and block['fill'] and block['fill']!=(1.0,1.0,1.0):
+            rect = block['rect']
+            if __rect_filter_by_width(rect, page.rect.width, page.rect.height) and __rect_filter_by_pos(rect, image_bboxes, table_bboxes):
+                spilter_bbox.append(list(rect))
+    
+    """过滤、修正一下这些box。因为有时候会有一些矩形，高度为0或者为负数，造成layout计算无限循环。如果是负高度或者0高度，统一修正为高度为1"""
+    for box in spilter_bbox:
+        if box[3]-box[1] <= 0:
+            box[3] = box[1] + 1
+            
+    #__debug_show_page(page, spilter_bbox, [], [])
+    
+    return spilter_bbox

magic_pdf/layout/mcol_sort.py

+"""
+This is an advanced PyMuPDF utility for detecting multi-column pages.
+It can be used in a shell script, or its main function can be imported and
+invoked as descript below.
+
+Features
+---------
+- Identify text belonging to (a variable number of) columns on the page.
+- Text with different background color is handled separately, allowing for
+  easier treatment of side remarks, comment boxes, etc.
+- Uses text block detection capability to identify text blocks and
+  uses the block bboxes as primary structuring principle.
+- Supports ignoring footers via a footer margin parameter.
+- Returns re-created text boundary boxes (integer coordinates), sorted ascending
+  by the top, then by the left coordinates.
+
+Restrictions
+-------------
+- Only supporting horizontal, left-to-right text
+- Returns a list of text boundary boxes - not the text itself. The caller is
+  expected to extract text from within the returned boxes.
+- Text written above images is ignored altogether (option).
+- This utility works as expected in most cases. The following situation cannot
+  be handled correctly:
+    * overlapping (non-disjoint) text blocks
+    * image captions are not recognized and are handled like normal text
+
+Usage
+------
+- As a CLI shell command use
+
+  python multi_column.py input.pdf footer_margin
+
+  Where footer margin is the height of the bottom stripe to ignore on each page.
+  This code is intended to be modified according to your need.
+
+- Use in a Python script as follows:
+
+  ----------------------------------------------------------------------------------
+  from multi_column import column_boxes
+
+  # for each page execute
+  bboxes = column_boxes(page, footer_margin=50, no_image_text=True)
+
+  # bboxes is a list of fitz.IRect objects, that are sort ascending by their y0,
+  # then x0 coordinates. Their text content can be extracted by all PyMuPDF
+  # get_text() variants, like for instance the following:
+  for rect in bboxes:
+      print(page.get_text(clip=rect, sort=True))
+  ----------------------------------------------------------------------------------
+"""
+import sys
+from magic_pdf.libs.commons import fitz
+
+
+def column_boxes(page, footer_margin=50, header_margin=50, no_image_text=True):
+    """Determine bboxes which wrap a column."""
+    paths = page.get_drawings()
+    bboxes = []
+
+    # path rectangles
+    path_rects = []
+
+    # image bboxes
+    img_bboxes = []
+
+    # bboxes of non-horizontal text
+    # avoid when expanding horizontal text boxes
+    vert_bboxes = []
+
+    # compute relevant page area
+    clip = +page.rect
+    clip.y1 -= footer_margin  # Remove footer area
+    clip.y0 += header_margin  # Remove header area
+
+    def can_extend(temp, bb, bboxlist):
+        """Determines whether rectangle 'temp' can be extended by 'bb'
+        without intersecting any of the rectangles contained in 'bboxlist'.
+
+        Items of bboxlist may be None if they have been removed.
+
+        Returns:
+            True if 'temp' has no intersections with items of 'bboxlist'.
+        """
+        for b in bboxlist:
+            if not intersects_bboxes(temp, vert_bboxes) and (
+                b == None or b == bb or (temp & b).is_empty
+            ):
+                continue
+            return False
+
+        return True
+
+    def in_bbox(bb, bboxes):
+        """Return 1-based number if a bbox contains bb, else return 0."""
+        for i, bbox in enumerate(bboxes):
+            if bb in bbox:
+                return i + 1
+        return 0
+
+    def intersects_bboxes(bb, bboxes):
+        """Return True if a bbox intersects bb, else return False."""
+        for bbox in bboxes:
+            if not (bb & bbox).is_empty:
+                return True
+        return False
+
+    def extend_right(bboxes, width, path_bboxes, vert_bboxes, img_bboxes):
+        """Extend a bbox to the right page border.
+
+        Whenever there is no text to the right of a bbox, enlarge it up
+        to the right page border.
+
+        Args:
+            bboxes: (list[IRect]) bboxes to check
+            width: (int) page width
+            path_bboxes: (list[IRect]) bboxes with a background color
+            vert_bboxes: (list[IRect]) bboxes with vertical text
+            img_bboxes: (list[IRect]) bboxes of images
+        Returns:
+            Potentially modified bboxes.
+        """
+        for i, bb in enumerate(bboxes):
+            # do not extend text with background color
+            if in_bbox(bb, path_bboxes):
+                continue
+
+            # do not extend text in images
+            if in_bbox(bb, img_bboxes):
+                continue
+
+            # temp extends bb to the right page border
+            temp = +bb
+            temp.x1 = width
+
+            # do not cut through colored background or images
+            if intersects_bboxes(temp, path_bboxes + vert_bboxes + img_bboxes):
+                continue
+
+            # also, do not intersect other text bboxes
+            check = can_extend(temp, bb, bboxes)
+            if check:
+                bboxes[i] = temp  # replace with enlarged bbox
+
+        return [b for b in bboxes if b != None]
+
+    def clean_nblocks(nblocks):
+        """Do some elementary cleaning."""
+
+        # 1. remove any duplicate blocks.
+        blen = len(nblocks)
+        if blen < 2:
+            return nblocks
+        start = blen - 1
+        for i in range(start, -1, -1):
+            bb1 = nblocks[i]
+            bb0 = nblocks[i - 1]
+            if bb0 == bb1:
+                del nblocks[i]
+
+        # 2. repair sequence in special cases:
+        # consecutive bboxes with almost same bottom value are sorted ascending
+        # by x-coordinate.
+        y1 = nblocks[0].y1  # first bottom coordinate
+        i0 = 0  # its index
+        i1 = -1  # index of last bbox with same bottom
+
+        # Iterate over bboxes, identifying segments with approx. same bottom value.
+        # Replace every segment by its sorted version.
+        for i in range(1, len(nblocks)):
+            b1 = nblocks[i]
+            if abs(b1.y1 - y1) > 10:  # different bottom
+                if i1 > i0:  # segment length > 1? Sort it!
+                    nblocks[i0 : i1 + 1] = sorted(
+                        nblocks[i0 : i1 + 1], key=lambda b: b.x0
+                    )
+                y1 = b1.y1  # store new bottom value
+                i0 = i  # store its start index
+            i1 = i  # store current index
+        if i1 > i0:  # segment waiting to be sorted
+            nblocks[i0 : i1 + 1] = sorted(nblocks[i0 : i1 + 1], key=lambda b: b.x0)
+        return nblocks
+
+    # extract vector graphics
+    for p in paths:
+        path_rects.append(p["rect"].irect)
+    path_bboxes = path_rects
+
+    # sort path bboxes by ascending top, then left coordinates
+    path_bboxes.sort(key=lambda b: (b.y0, b.x0))
+
+    # bboxes of images on page, no need to sort them
+    for item in page.get_images():
+        img_bboxes.extend(page.get_image_rects(item[0]))
+
+    # blocks of text on page
+    blocks = page.get_text(
+        "dict",
+        flags=fitz.TEXTFLAGS_TEXT,
+        clip=clip,
+    )["blocks"]
+
+    # Make block rectangles, ignoring non-horizontal text
+    for b in blocks:
+        bbox = fitz.IRect(b["bbox"])  # bbox of the block
+
+        # ignore text written upon images
+        if no_image_text and in_bbox(bbox, img_bboxes):
+            continue
+
+        # confirm first line to be horizontal
+        line0 = b["lines"][0]  # get first line
+        if line0["dir"] != (1, 0):  # only accept horizontal text
+            vert_bboxes.append(bbox)
+            continue
+
+        srect = fitz.EMPTY_IRECT()
+        for line in b["lines"]:
+            lbbox = fitz.IRect(line["bbox"])
+            text = "".join([s["text"].strip() for s in line["spans"]])
+            if len(text) > 1:
+                srect |= lbbox
+        bbox = +srect
+
+        if not bbox.is_empty:
+            bboxes.append(bbox)
+
+    # Sort text bboxes by ascending background, top, then left coordinates
+    bboxes.sort(key=lambda k: (in_bbox(k, path_bboxes), k.y0, k.x0))
+
+    # Extend bboxes to the right where possible
+    bboxes = extend_right(
+        bboxes, int(page.rect.width), path_bboxes, vert_bboxes, img_bboxes
+    )
+
+    # immediately return of no text found
+    if bboxes == []:
+        return []
+
+    # --------------------------------------------------------------------
+    # Join bboxes to establish some column structure
+    # --------------------------------------------------------------------
+    # the final block bboxes on page
+    nblocks = [bboxes[0]]  # pre-fill with first bbox
+    bboxes = bboxes[1:]  # remaining old bboxes
+
+    for i, bb in enumerate(bboxes):  # iterate old bboxes
+        check = False  # indicates unwanted joins
+
+        # check if bb can extend one of the new blocks
+        for j in range(len(nblocks)):
+            nbb = nblocks[j]  # a new block
+
+            # never join across columns
+            if bb == None or nbb.x1 < bb.x0 or bb.x1 < nbb.x0:
+                continue
+
+            # never join across different background colors
+            if in_bbox(nbb, path_bboxes) != in_bbox(bb, path_bboxes):
+                continue
+
+            temp = bb | nbb  # temporary extension of new block
+            check = can_extend(temp, nbb, nblocks)
+            if check == True:
+                break
+
+        if not check:  # bb cannot be used to extend any of the new bboxes
+            nblocks.append(bb)  # so add it to the list
+            j = len(nblocks) - 1  # index of it
+            temp = nblocks[j]  # new bbox added
+
+        # check if some remaining bbox is contained in temp
+        check = can_extend(temp, bb, bboxes)
+        if check == False:
+            nblocks.append(bb)
+        else:
+            nblocks[j] = temp
+        bboxes[i] = None
+
+    # do some elementary cleaning
+    nblocks = clean_nblocks(nblocks)
+
+    # return identified text bboxes
+    return nblocks
+
+
+if __name__ == "__main__":
+    """Only for debugging purposes, currently.
+
+    Draw red borders around the returned text bboxes and insert
+    the bbox number.
+    Then save the file under the name "input-blocks.pdf".
+    """
+
+    # get the file name
+    filename = sys.argv[1]
+
+    # check if footer margin is given
+    if len(sys.argv) > 2:
+        footer_margin = int(sys.argv[2])
+    else:  # use default vaue
+        footer_margin = 50
+
+    # check if header margin is given
+    if len(sys.argv) > 3:
+        header_margin = int(sys.argv[3])
+    else:  # use default vaue
+        header_margin = 50
+
+    # open document
+    doc = fitz.open(filename)
+
+    # iterate over the pages
+    for page in doc:
+        # remove any geometry issues
+        page.wrap_contents()
+
+        # get the text bboxes
+        bboxes = column_boxes(page, footer_margin=footer_margin, header_margin=header_margin)
+
+        # prepare a canvas to draw rectangles and text
+        shape = page.new_shape()
+
+        # iterate over the bboxes
+        for i, rect in enumerate(bboxes):
+            shape.draw_rect(rect)  # draw a border
+
+            # write sequence number
+            shape.insert_text(rect.tl + (5, 15), str(i), color=fitz.pdfcolor["red"])
+
+        # finish drawing / text with color red
+        shape.finish(color=fitz.pdfcolor["red"])
+        shape.commit()  # store to the page
+
+    # save document with text bboxes
+    doc.ez_save(filename.replace(".pdf", "-blocks.pdf"))
\ No newline at end of file