diff --git a/magic_pdf/para/para_split_v3.py b/magic_pdf/para/para_split_v3.py index 989adfe0..7a26b2d8 100644 --- a/magic_pdf/para/para_split_v3.py +++ b/magic_pdf/para/para_split_v3.py @@ -69,6 +69,17 @@ def __is_list_or_index_block(block): right_not_close_num = 0 right_close_num = 0 lines_text_list = [] + + multiple_para_flag = False + last_line = block['lines'][-1] + # 如果首行左边不顶格而右边顶格,末行左边顶格而右边不顶格 （第一行可能可以右边不顶格） + if (first_line['bbox'][0] - block['bbox_fs'][0] > line_height / 2 and + # block['bbox_fs'][2] - first_line['bbox'][2] < line_height and + abs(last_line['bbox'][0] - block['bbox_fs'][0]) < line_height / 2 and + block['bbox_fs'][2] - last_line['bbox'][2] > line_height + ): + multiple_para_flag = True + for line in block['lines']: line_text = "" @@ -81,14 +92,14 @@ def __is_list_or_index_block(block): lines_text_list.append(line_text) # 计算line左侧顶格数量是否大于2，是否顶格用abs(block['bbox_fs'][0] - line['bbox'][0]) < line_height/2 来判断 - if abs(block['bbox_fs'][0] - line['bbox'][0]) < line_height/2: + if abs(block['bbox_fs'][0] - line['bbox'][0]) < line_height / 2: left_close_num += 1 elif line['bbox'][0] - block['bbox_fs'][0] > line_height: # logger.info(f"{line_text}, {block['bbox_fs']}, {line['bbox']}") left_not_close_num += 1 # 计算右侧是否顶格 - if abs(block['bbox_fs'][2] - line['bbox'][2]) < line_height / 2: + if abs(block['bbox_fs'][2] - line['bbox'][2]) < line_height: right_close_num += 1 else: # 右侧不顶格情况下是否有一段距离，拍脑袋用0.3block宽度做阈值 @@ -101,35 +112,73 @@ def __is_list_or_index_block(block): line_end_flag = False # 判断lines_text_list中的元素是否有超过80%都以数字开头或都以数字结尾 line_num_flag = False + num_start_count = 0 + num_end_count = 0 + flag_end_count = 0 if len(lines_text_list) > 0: - num_start_count = 0 - num_end_count = 0 for line_text in lines_text_list: if len(line_text) > 0: if line_text[-1] in LIST_END_FLAG: - num_end_count += 1 + flag_end_count += 1 if line_text[0].isdigit(): num_start_count += 1 if line_text[-1].isdigit(): num_end_count += 1 - if num_end_count / len(lines_text_list) >= 0.8: + if flag_end_count / len(lines_text_list) >= 0.8: line_end_flag = True if num_start_count / len(lines_text_list) >= 0.8 or num_end_count / len(lines_text_list) >= 0.8: line_num_flag = True - if left_close_num >= 2 and right_close_num >= 2 and line_num_flag: + # 有的目录右侧不贴边, 目前认为左边或者右边有一边全贴边，且符合数字规则极为index + if ((left_close_num/len(block['lines']) >= 0.8 or right_close_num/len(block['lines']) >= 0.8) + and line_num_flag + ): for line in block['lines']: line[ListLineTag.IS_LIST_START_LINE] = True return BlockType.Index - elif left_close_num >= 2 and (right_not_close_num >= 2 or line_end_flag or left_not_close_num > 2): - for line in block['lines']: - if abs(block['bbox_fs'][0] - line['bbox'][0]) < line_height / 2: - line[ListLineTag.IS_LIST_START_LINE] = True - if abs(block['bbox_fs'][2] - line['bbox'][2]) > line_height: - line[ListLineTag.IS_LIST_END_LINE] = True + elif left_close_num >= 2 and ( + right_not_close_num >= 2 or line_end_flag or left_not_close_num >= 2) and not multiple_para_flag: + # 处理一种特殊的没有缩进的list，所有行都贴左边，通过右边的空隙判断是否是item尾 + if left_close_num / len(block['lines']) > 0.9: + # 这种是每个item只有一行，且左边都贴边的短item list + if flag_end_count == 0 and right_close_num / len(block['lines']) < 0.5: + for line in block['lines']: + if abs(block['bbox_fs'][0] - line['bbox'][0]) < line_height / 2: + line[ListLineTag.IS_LIST_START_LINE] = True + # 这种是大部分line item 都有结束标识符的情况，按结束标识符区分不同item + elif line_end_flag: + for i, line in enumerate(block['lines']): + if lines_text_list[i][-1] in LIST_END_FLAG: + line[ListLineTag.IS_LIST_END_LINE] = True + if i + 1 < len(block['lines']): + block['lines'][i+1][ListLineTag.IS_LIST_START_LINE] = True + # line item基本没有结束标识符，而且也没有缩进，按右侧空隙判断哪些是item end + else: + line_start_flag = False + for i, line in enumerate(block['lines']): + if line_start_flag: + line[ListLineTag.IS_LIST_START_LINE] = True + line_start_flag = False + elif abs(block['bbox_fs'][2] - line['bbox'][2]) > line_height: + line[ListLineTag.IS_LIST_END_LINE] = True + line_start_flag = True + # 一种有缩进的特殊有序list,start line 左侧不贴边且以数字开头，end line 以 IS_LIST_END_LINE 结尾且数量和start line 一致 + elif num_start_count == flag_end_count: # 简单一点先不考虑左侧不贴边的情况 + for i, line in enumerate(block['lines']): + if lines_text_list[i][0].isdigit(): + line[ListLineTag.IS_LIST_START_LINE] = True + if lines_text_list[i][-1] in LIST_END_FLAG: + line[ListLineTag.IS_LIST_END_LINE] = True + else: + # 正常有缩进的list处理 + for line in block['lines']: + if abs(block['bbox_fs'][0] - line['bbox'][0]) < line_height / 2: + line[ListLineTag.IS_LIST_START_LINE] = True + if abs(block['bbox_fs'][2] - line['bbox'][2]) > line_height: + line[ListLineTag.IS_LIST_END_LINE] = True return BlockType.List else: @@ -142,12 +191,19 @@ def __merge_2_text_blocks(block1, block2): if len(block1['lines']) > 0: first_line = block1['lines'][0] line_height = first_line['bbox'][3] - first_line['bbox'][1] - if abs(block1['bbox_fs'][0] - first_line['bbox'][0]) < line_height/2: + block1_weight = block1['bbox'][2] - block1['bbox'][0] + block2_weight = block2['bbox'][2] - block2['bbox'][0] + min_block_weight = min(block1_weight, block2_weight) + if abs(block1['bbox_fs'][0] - first_line['bbox'][0]) < line_height / 2: last_line = block2['lines'][-1] if len(last_line['spans']) > 0: last_span = last_line['spans'][-1] line_height = last_line['bbox'][3] - last_line['bbox'][1] - if abs(block2['bbox_fs'][2] - last_line['bbox'][2]) < line_height and not last_span['content'].endswith(LINE_STOP_FLAG): + if (abs(block2['bbox_fs'][2] - last_line['bbox'][2]) < line_height and + not last_span['content'].endswith(LINE_STOP_FLAG) and + # 两个block宽度差距超过2倍也不合并 + abs(block1_weight - block2_weight) < min_block_weight + ): if block1['page_num'] != block2['page_num']: for line in block1['lines']: for span in line['spans']: @@ -160,7 +216,6 @@ def __merge_2_text_blocks(block1, block2): def __merge_2_list_blocks(block1, block2): - if block1['page_num'] != block2['page_num']: for line in block1['lines']: for span in line['spans']: @@ -185,7 +240,7 @@ def __para_merge_page(blocks): if len(text_blocks_group) > 1: # 倒序遍历 - for i in range(len(text_blocks_group)-1, -1, -1): + for i in range(len(text_blocks_group) - 1, -1, -1): current_block = text_blocks_group[i] # 检查是否有前一个块 @@ -221,7 +276,7 @@ def para_split(pdf_info_dict, debug_mode=False): if __name__ == '__main__': - input_blocks = [{'type': 'text', 'bbox': [19, 79, 285, 95], 'lines': [{'bbox': [21.360000610351562, 81.50750732421875, 287.69000244140625, 93.62750244140625], 'spans': [{'bbox': [21.360000610351562, 81.62750244140625, 170.3000030517578, 93.62750244140625], 'content': '嘉和美康（688246）/计算机', 'type': 'text', 'score': 1.0}, {'bbox': [170.3000030517578, 81.62750244140625, 176.3000030517578, 93.62750244140625], 'content': ' ', 'type': 'text', 'score': 1.0}, {'bbox': [181.22000122070312, 81.50750732421875, 281.8052062988281, 93.50750732421875], 'content': '证券研究报告/公司点评', 'type': 'text', 'score': 1.0}, {'bbox': [281.69000244140625, 81.50750732421875, 287.69000244140625, 93.50750732421875], 'content': ' ', 'type': 'text', 'score': 1.0}], 'index': 0}], 'index': 0, 'page_num': 'page_0', 'bbox_fs': [21.360000610351562, 81.50750732421875, 287.69000244140625, 93.62750244140625]}, {'type': 'title', 'bbox': [18, 109, 124, 123], 'lines': [{'bbox': [21.360000610351562, 101.70799255371094, 98.47967529296875, 116.21743774414062], 'spans': [{'bbox': [21.360000610351562, 101.70799255371094, 98.47967529296875, 116.21743774414062], 'content': '[Table_Industry] ', 'type': 'text', 'score': 1.0}], 'index': 1}, {'bbox': [21.1200008392334, 110.3074951171875, 129.5640106201172, 122.3074951171875], 'spans': [{'bbox': [21.1200008392334, 110.3074951171875, 129.5640106201172, 122.3074951171875], 'content': '评级：买入（维持）', 'type': 'text', 'score': 1.0}], 'index': 2}], 'index': 1.5, 'page_num': 'page_0'}, {'type': 'text', 'bbox': [20, 126, 117, 137], 'lines': [{'bbox': [21.1200008392334, 127.40557861328125, 116.18000030517578, 136.40557861328125], 'spans': [{'bbox': [21.1200008392334, 127.40557861328125, 116.18000030517578, 136.40557861328125], 'content': '市场价格：16.62 元/股', 'type': 'text', 'score': 1.0}], 'index': 3}], 'index': 3, 'page_num': 'page_0', 'bbox_fs': [21.1200008392334, 127.40557861328125, 116.18000030517578, 136.40557861328125]}, {'type': 'text', 'bbox': [19, 144, 158, 172], 'lines': [{'bbox': [21.1200008392334, 144.1099853515625, 86.88600158691406, 156.50299072265625], 'spans': [{'bbox': [21.1200008392334, 146.005615234375, 84.33599853515625, 155.005615234375], 'content': '分析师：闻学臣', 'type': 'text', 'score': 1.0}, {'bbox': [84.38400268554688, 144.1099853515625, 86.88600158691406, 156.50299072265625], 'content': ' ', 'type': 'text', 'score': 1.0}], 'index': 4}, {'bbox': [21.1200008392334, 159.7099609375, 157.9219970703125, 172.10296630859375], 'spans': [{'bbox': [21.1200008392334, 161.6055908203125, 84.33599853515625, 170.6055908203125], 'content': '执业证书编号：', 'type': 'text', 'score': 1.0}, {'bbox': [84.50399780273438, 159.7099609375, 155.45095825195312, 172.10296630859375], 'content': 'S0740519090007', 'type': 'text', 'score': 1.0}, {'bbox': [155.4199981689453, 159.7099609375, 157.9219970703125, 172.10296630859375], 'content': ' ', 'type': 'text', 'score': 1.0}], 'index': 5}], 'index': 4.5, 'page_num': 'page_0', 'bbox_fs': [21.1200008392334, 144.1099853515625, 157.9219970703125, 172.10296630859375]}, {'type': 'text', 'bbox': [18, 194, 157, 241], 'lines': [{'bbox': [21.1200008392334, 193.86497497558594, 86.88600158691406, 206.23097229003906], 'spans': [{'bbox': [21.1200008392334, 195.80560302734375, 84.33599853515625, 204.80560302734375], 'content': '分析师：何柄谕', 'type': 'text', 'score': 1.0}, {'bbox': [84.38400268554688, 193.86497497558594, 86.88600158691406, 206.23097229003906], 'content': ' ', 'type': 'text', 'score': 1.0}], 'index': 6}, {'bbox': [21.1200008392334, 211.07000732421875, 157.9219970703125, 223.4630126953125], 'spans': [{'bbox': 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'，以大模型为底座的多业务场景得到落地验证并且应用效果良好，比如新型', 'type': 'text', 'score': 1.0}, {'bbox': [543.219970703125, 583.1529541015625, 552.5888671875, 596.8380126953125], 'content': 'AI', 'type': 'text', 'score': 1.0}, {'bbox': [552.5888671875, 585.3005981445312, 575.1400146484375, 595.2606201171875], 'content': ' 产品', 'type': 'text', 'score': 1.0}], 'index': 46}, {'bbox': [201.88999938964844, 600.9005737304688, 575.1082763671875, 610.860595703125], 'spans': [{'bbox': [201.88999938964844, 600.9005737304688, 575.1082763671875, 610.860595703125], 'content': '可以将医务人员曾经数小时的病历书写工作缩减至半小时内完成，大幅提升书写内容', 'type': 'text', 'score': 1.0}], 'index': 47}, {'bbox': [201.88999938964844, 614.4027709960938, 304.618896484375, 628.1177368164062], 'spans': [{'bbox': [201.88999938964844, 616.5006103515625, 301.7195129394531, 626.4606323242188], 'content': '的准确率及工作效率。', 'type': 'text', 'score': 1.0}, {'bbox': [301.8500061035156, 614.4027709960938, 304.618896484375, 628.1177368164062], 'content': ' ', 'type': 'text', 'score': 1.0}], 'index': 48}], 'index': 44.5, 'page_num': 'page_0'}, {'type': 'text', 'bbox': [200, 646, 577, 690], 'lines': [{'bbox': [201.88999938964844, 645.552978515625, 574.8973999023438, 659.238037109375], 'spans': [{'bbox': [201.88999938964844, 647.7006225585938, 310.00994873046875, 657.66064453125], 'content': '投资建议：我们预计公司', 'type': 'text', 'score': 1.0}, {'bbox': [312.5299987792969, 645.552978515625, 384.72003173828125, 659.238037109375], 'content': '2024/2025/2026', 'type': 'text', 'score': 1.0}, {'bbox': [384.72003173828125, 647.7006225585938, 447.2890625, 657.66064453125], 'content': ' 年收入分别为', 'type': 'text', 'score': 1.0}, {'bbox': [449.8299865722656, 645.552978515625, 526.9088745117188, 659.238037109375], 'content': '9.03/11.48/14.47 ', 'type': 'text', 'score': 1.0}, {'bbox': [526.9000244140625, 647.7006225585938, 574.8973999023438, 657.66064453125], 'content': '亿元，净利', 'type': 'text', 'score': 1.0}], 'index': 49}, {'bbox': [201.88999938964844, 661.1529541015625, 574.98876953125, 674.8380126953125], 'spans': [{'bbox': [201.88999938964844, 663.3005981445312, 241.7300262451172, 673.2606201171875], 'content': '润分别为', 'type': 'text', 'score': 1.0}, {'bbox': [241.85000610351562, 661.1529541015625, 311.3388977050781, 674.8380126953125], 'content': ' 0.95/1.20/1.60 ', 'type': 'text', 'score': 1.0}, {'bbox': [311.3299865722656, 663.3005981445312, 361.239501953125, 673.2606201171875], 'content': '亿元，对应', 'type': 'text', 'score': 1.0}, {'bbox': [364.989990234375, 661.1529541015625, 378.35333251953125, 674.8380126953125], 'content': 'PE', 'type': 'text', 'score': 1.0}, {'bbox': [378.35333251953125, 663.3005981445312, 411.8995361328125, 673.2606201171875], 'content': ' 分别为', 'type': 'text', 'score': 1.0}, {'bbox': [411.9100036621094, 661.1529541015625, 481.42193603515625, 674.8380126953125], 'content': ' 24.1/19.0/14.3', 'type': 'text', 'score': 1.0}, {'bbox': [481.42193603515625, 663.3005981445312, 574.98876953125, 673.2606201171875], 'content': ' 倍。考虑公司业绩高', 'type': 'text', 'score': 1.0}], 'index': 50}, {'bbox': [201.88999938964844, 676.802734375, 431.35888671875, 690.5177001953125], 'spans': [{'bbox': [201.88999938964844, 678.9005737304688, 371.7577209472656, 688.860595703125], 'content': '增长以及估值处于较低水平，给予公司', 'type': 'text', 'score': 1.0}, {'bbox': [371.8299865722656, 678.4434204101562, 375.1467590332031, 689.5706176757812], 'content': '“', 'type': 'text', 'score': 1.0}, {'bbox': [375.19000244140625, 678.9005737304688, 395.1099853515625, 688.860595703125], 'content': '买入', 'type': 'text', 'score': 1.0}, {'bbox': [395.1099853515625, 678.4434204101562, 398.4267578125, 689.5706176757812], 'content': '”', 'type': 'text', 'score': 1.0}, {'bbox': [398.4700012207031, 678.9005737304688, 428.45953369140625, 688.860595703125], 'content': '评级。', 'type': 'text', 'score': 1.0}, {'bbox': [428.5899963378906, 676.802734375, 431.35888671875, 690.5177001953125], 'content': ' ', 'type': 'text', 'score': 1.0}], 'index': 51}], 'index': 50, 'page_num': 'page_0'}, {'type': 'text', 'bbox': [200, 708, 404, 721], 'lines': [{'bbox': [201.88999938964844, 708.0027465820312, 404.9588928222656, 721.7177124023438], 'spans': [{'bbox': [201.88999938964844, 710.1005859375, 402.00811767578125, 720.0606079101562], 'content': '风险提示：业务发展不及预期，政策推进缓慢', 'type': 'text', 'score': 1.0}, {'bbox': [402.19000244140625, 708.0027465820312, 404.9588928222656, 721.7177124023438], 'content': ' ', 'type': 'text', 'score': 1.0}], 'index': 52}], 'index': 52, 'page_num': 'page_0'}] + input_blocks = [] # 调用函数 groups = __process_blocks(input_blocks) for group_index, group in enumerate(groups):