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Unverified Commit 0d83fb77 authored by Xiaomeng Zhao's avatar Xiaomeng Zhao Committed by GitHub
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Merge pull request #743 from myhloli/para-split-v3 

refactor(para_split_v3): merge list and index block detection
parents 702b6ac9 244b8684
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Showing with 111 additions and 82 deletions
magic_pdf/libs/draw_bbox.py
View file @ 0d83fb77
...@@ -237,6 +237,8 @@ def draw_span_bbox(pdf_info, pdf_bytes, out_path, filename): ...@@ -237,6 +237,8 @@ def draw_span_bbox(pdf_info, pdf_bytes, out_path, filename):
BlockType.Text, BlockType.Text,
BlockType.Title, BlockType.Title,
BlockType.InterlineEquation, BlockType.InterlineEquation,
BlockType.List,
BlockType.Index,
]: ]:
for line in block['lines']: for line in block['lines']:
for span in line['spans']: for span in line['spans']:
......
magic_pdf/para/para_split_v3.py
View file @ 0d83fb77
...@@ -15,6 +15,9 @@ class ListLineTag: ...@@ -15,6 +15,9 @@ class ListLineTag:
def __process_blocks(blocks): def __process_blocks(blocks):
# 对所有block预处理
# 1.通过title和interline_equation将block分组
# 2.bbox边界根据line信息重置
result = [] result = []
current_group = [] current_group = []
...@@ -47,11 +50,15 @@ def __process_blocks(blocks): ...@@ -47,11 +50,15 @@ def __process_blocks(blocks):
return result return result
def __is_list_block(block): def __is_list_or_index_block(block):
# 一个block如果是list block 应该同时满足以下特征 # 一个block如果是list block 应该同时满足以下特征
# 1.block内有多个line 2.block 内有多个line左侧顶格写 3.block内有多个line 右侧不顶格（狗牙状） # 1.block内有多个line 2.block 内有多个line左侧顶格写 3.block内有多个line 右侧不顶格（狗牙状）
# 1.block内有多个line 2.block 内有多个line左侧顶格写 3.多个line以endflag结尾 # 1.block内有多个line 2.block 内有多个line左侧顶格写 3.多个line以endflag结尾
# 1.block内有多个line 2.block 内有多个line左侧顶格写 3.block内有多个line 左侧不顶格 # 1.block内有多个line 2.block 内有多个line左侧顶格写 3.block内有多个line 左侧不顶格
# index block 是一种特殊的list block
# 一个block如果是index block 应该同时满足以下特征
# 1.block内有多个line 2.block 内有多个line两侧均顶格写 3.line的开头或者结尾均为数字
if len(block['lines']) >= 3: if len(block['lines']) >= 3:
first_line = block['lines'][0] first_line = block['lines'][0]
line_height = first_line['bbox'][3] - first_line['bbox'][1] line_height = first_line['bbox'][3] - first_line['bbox'][1]
...@@ -60,7 +67,19 @@ def __is_list_block(block): ...@@ -60,7 +67,19 @@ def __is_list_block(block):
left_close_num = 0 left_close_num = 0
left_not_close_num = 0 left_not_close_num = 0
right_not_close_num = 0 right_not_close_num = 0
right_close_num = 0
lines_text_list = [] 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']: for line in block['lines']:
line_text = "" line_text = ""
...@@ -73,110 +92,118 @@ def __is_list_block(block): ...@@ -73,110 +92,118 @@ def __is_list_block(block):
lines_text_list.append(line_text) 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 # 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 left_close_num += 1
elif line['bbox'][0] - block['bbox_fs'][0] > line_height: elif line['bbox'][0] - block['bbox_fs'][0] > line_height:
# logger.info(f"{line_text}, {block['bbox_fs']}, {line['bbox']}") # logger.info(f"{line_text}, {block['bbox_fs']}, {line['bbox']}")
left_not_close_num += 1 left_not_close_num += 1
# 计算右侧是否不顶格，拍脑袋用0.3block宽度做阈值 # 计算右侧是否顶格
closed_area = 0.3 * block_weight if abs(block['bbox_fs'][2] - line['bbox'][2]) < line_height:
# closed_area = 5 * line_height right_close_num += 1
if block['bbox_fs'][2] - line['bbox'][2] > closed_area: else:
right_not_close_num += 1 # 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
closed_area = 0.3 * block_weight
# closed_area = 5 * line_height
if block['bbox_fs'][2] - line['bbox'][2] > closed_area:
right_not_close_num += 1
# 判断lines_text_list中的元素是否有超过80%都以LIST_END_FLAG结尾 # 判断lines_text_list中的元素是否有超过80%都以LIST_END_FLAG结尾
line_end_flag = False line_end_flag = False
if len(lines_text_list) > 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
if num_end_count / len(lines_text_list) >= 0.8:
line_end_flag = True
if 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
return True
else:
return False
else:
return False
def __is_index_block(block):
# 一个block如果是index block 应该同时满足以下特征
# 1.block内有多个line 2.block 内有多个line两侧均顶格写 3.line的开头或者结尾均为数字
if len(block['lines']) >= 3:
first_line = block['lines'][0]
line_height = first_line['bbox'][3] - first_line['bbox'][1]
left_close_num = 0
right_close_num = 0
lines_text_list = []
for line in block['lines']:
# 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:
left_close_num += 1
# 计算右侧是否不顶格
if abs(block['bbox_fs'][2] - line['bbox'][2]) < line_height / 2:
right_close_num += 1
line_text = ""
for span in line['spans']:
span_type = span['type']
if span_type == ContentType.Text:
line_text += span['content'].strip()
lines_text_list.append(line_text)
# 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 # 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 line_num_flag = False
num_start_count = 0
num_end_count = 0
flag_end_count = 0
if len(lines_text_list) > 0: if len(lines_text_list) > 0:
num_start_count = 0
num_end_count = 0
for line_text in lines_text_list: for line_text in lines_text_list:
if len(line_text) > 0: if len(line_text) > 0:
if line_text[-1] in LIST_END_FLAG:
flag_end_count += 1
if line_text[0].isdigit(): if line_text[0].isdigit():
num_start_count += 1 num_start_count += 1
if line_text[-1].isdigit(): if line_text[-1].isdigit():
num_end_count += 1 num_end_count += 1
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: if num_start_count / len(lines_text_list) >= 0.8 or num_end_count / len(lines_text_list) >= 0.8:
line_num_flag = True 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']: for line in block['lines']:
line[ListLineTag.IS_LIST_START_LINE] = True line[ListLineTag.IS_LIST_START_LINE] = True
return BlockType.Index
return 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: else:
return False return BlockType.Text
else: else:
return False return BlockType.Text
def __merge_2_text_blocks(block1, block2): def __merge_2_text_blocks(block1, block2):
if len(block1['lines']) > 0: if len(block1['lines']) > 0:
first_line = block1['lines'][0] first_line = block1['lines'][0]
line_height = first_line['bbox'][3] - first_line['bbox'][1] 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] last_line = block2['lines'][-1]
if len(last_line['spans']) > 0: if len(last_line['spans']) > 0:
last_span = last_line['spans'][-1] last_span = last_line['spans'][-1]
line_height = last_line['bbox'][3] - last_line['bbox'][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']: if block1['page_num'] != block2['page_num']:
for line in block1['lines']: for line in block1['lines']:
for span in line['spans']: for span in line['spans']:
...@@ -189,7 +216,6 @@ def __merge_2_text_blocks(block1, block2): ...@@ -189,7 +216,6 @@ def __merge_2_text_blocks(block1, block2):
def __merge_2_list_blocks(block1, block2): def __merge_2_list_blocks(block1, block2):
if block1['page_num'] != block2['page_num']: if block1['page_num'] != block2['page_num']:
for line in block1['lines']: for line in block1['lines']:
for span in line['spans']: for span in line['spans']:
...@@ -206,16 +232,15 @@ def __para_merge_page(blocks): ...@@ -206,16 +232,15 @@ def __para_merge_page(blocks):
for text_blocks_group in page_text_blocks_groups: for text_blocks_group in page_text_blocks_groups:
if len(text_blocks_group) > 0: if len(text_blocks_group) > 0:
# 需要先在合并前对所有block判断是否为list block # 需要先在合并前对所有block判断是否为list or index block
for block in text_blocks_group: for block in text_blocks_group:
if __is_list_block(block): block_type = __is_list_or_index_block(block)
block['type'] = BlockType.List block['type'] = block_type
elif __is_index_block(block): # logger.info(f"{block['type']}:{block}")
block['type'] = BlockType.Index
if len(text_blocks_group) > 1: if len(text_blocks_group) > 1:
# 倒序遍历 # 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] current_block = text_blocks_group[i]
# 检查是否有前一个块 # 检查是否有前一个块
...@@ -224,10 +249,12 @@ def __para_merge_page(blocks): ...@@ -224,10 +249,12 @@ def __para_merge_page(blocks):
if current_block['type'] == 'text' and prev_block['type'] == 'text': if current_block['type'] == 'text' and prev_block['type'] == 'text':
__merge_2_text_blocks(current_block, prev_block) __merge_2_text_blocks(current_block, prev_block)
if current_block['type'] == BlockType.List and prev_block['type'] == BlockType.List: elif (
__merge_2_list_blocks(current_block, prev_block) (current_block['type'] == BlockType.List and prev_block['type'] == BlockType.List) or
if current_block['type'] == BlockType.Index and prev_block['type'] == BlockType.Index: (current_block['type'] == BlockType.Index and prev_block['type'] == BlockType.Index)
):
__merge_2_list_blocks(current_block, prev_block) __merge_2_list_blocks(current_block, prev_block)
else: else:
continue continue
...@@ -249,7 +276,7 @@ def para_split(pdf_info_dict, debug_mode=False): ...@@ -249,7 +276,7 @@ def para_split(pdf_info_dict, debug_mode=False):
if __name__ == '__main__': 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, 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[474.3399963378906, 395.9229736328125, 493.80181884765625, 409.6080017089844], 'content': '2.51', 'type': 'text', 'score': 1.0}, {'bbox': [493.80181884765625, 398.0705871582031, 574.8645629882812, 408.0306091308594], 'content': ' 个百分点，公司毛', 'type': 'text', 'score': 1.0}], 'index': 34}, {'bbox': [201.88999938964844, 411.5229797363281, 279.6589050292969, 425.2080078125], 'spans': [{'bbox': [201.88999938964844, 413.67059326171875, 271.7195739746094, 423.630615234375], 'content': '利率明显改善。', 'type': 'text', 'score': 1.0}, {'bbox': [271.7300109863281, 411.5229797363281, 279.6589050292969, 425.2080078125], 'content': ' ', 'type': 'text', 'score': 1.0}], 'index': 35}], 'index': 33, 'page_num': 'page_0'}, {'type': 'text', 'bbox': [199, 427, 577, 503], 'lines': [{'bbox': [201.88999938964844, 429.2705993652344, 574.9743041992188, 439.2306213378906], 'spans': [{'bbox': [201.88999938964844, 429.2705993652344, 574.9743041992188, 439.2306213378906], 'content': '降本增效成效显著，管理、销售费用率下降。报告期内，公司注重内控管理、人员能', 'type': 'text', 'score': 1.0}], 'index': 36}, {'bbox': [201.88999938964844, 442.7229919433594, 575.1400146484375, 456.40802001953125], 'spans': [{'bbox': [201.88999938964844, 444.87060546875, 530.7092895507812, 454.83062744140625], 'content': '效提升，加强管理方式优化及费用控制，公司运营管理方面降本增效明显。', 'type': 'text', 'score': 1.0}, {'bbox': [530.3800048828125, 442.7229919433594, 552.600830078125, 456.40802001953125], 'content': '2024', 'type': 'text', 'score': 1.0}, {'bbox': [552.600830078125, 444.87060546875, 575.1400146484375, 454.83062744140625], 'content': ' 年上', 'type': 'text', 'score': 1.0}], 'index': 37}, {'bbox': [201.88999938964844, 458.3229675292969, 575.1334838867188, 472.00799560546875], 'spans': [{'bbox': [201.88999938964844, 460.4705810546875, 310.71295166015625, 470.43060302734375], 'content': '半年，公司销售费用率为', 'type': 'text', 'score': 1.0}, {'bbox': [312, 459, 348, 471], 'score': 0.91, 'content': '16.39\\%', 'type': 'inline_equation'}, {'bbox': [347.3500061035156, 460.4705810546875, 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'score': 1.0}], 'index': 40}], 'index': 38, 'page_num': 'page_0'}, {'type': 'text', 'bbox': [199, 505, 577, 628], 'lines': [{'bbox': [201.88999938964844, 505.1727600097656, 575.0682983398438, 518.8876953125], 'spans': [{'bbox': [201.88999938964844, 507.27056884765625, 241.9491424560547, 517.2305908203125], 'content': '公司加大', 'type': 'text', 'score': 1.0}, {'bbox': [245.2100067138672, 505.1727600097656, 255.1788787841797, 518.8876953125], 'content': 'AI', 'type': 'text', 'score': 1.0}, {'bbox': [255.1788787841797, 507.27056884765625, 328.44818115234375, 517.2305908203125], 'content': ' 投入力度，医疗', 'type': 'text', 'score': 1.0}, {'bbox': [331.75, 505.1727600097656, 341.7189025878906, 518.8876953125], 'content': 'AI', 'type': 'text', 'score': 1.0}, {'bbox': [341.7189025878906, 507.27056884765625, 575.0682983398438, 517.2305908203125], 'content': ' 产品落地情况良好。公司继续加大研发投入力度，尤', 'type': 'text', 'score': 1.0}], 'index': 41}, {'bbox': [201.88999938964844, 520.7230224609375, 575.057861328125, 534.4080200195312], 'spans': [{'bbox': [201.88999938964844, 522.87060546875, 241.83958435058594, 532.8306274414062], 'content': '其是医疗', 'type': 'text', 'score': 1.0}, {'bbox': [244.97000122070312, 520.7230224609375, 254.45889282226562, 534.4080200195312], 'content': 'AI', 'type': 'text', 'score': 1.0}, {'bbox': [254.45889282226562, 522.87060546875, 407.5176696777344, 532.8306274414062], 'content': ' 投入力度。报告期内，公司新申请', 'type': 'text', 'score': 1.0}, {'bbox': [410.8299865722656, 520.7230224609375, 421.8876953125, 534.4080200195312], 'content': '26', 'type': 'text', 'score': 1.0}, {'bbox': [421.8876953125, 522.87060546875, 575.057861328125, 532.8306274414062], 'content': ' 项发明专利，主要集中在医疗数据', 'type': 'text', 'score': 1.0}], 'index': 42}, {'bbox': [201.88999938964844, 536.322998046875, 574.8896484375, 550.0079956054688], 'spans': [{'bbox': [201.88999938964844, 538.4705810546875, 231.77001953125, 548.4306030273438], 'content': '利用和', 'type': 'text', 'score': 1.0}, {'bbox': [234.77000427246094, 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'content': '。依托公司', 'type': 'text', 'score': 1.0}], 'index': 43}, {'bbox': [201.88999938964844, 551.9229736328125, 574.925048828125, 565.6080322265625], 'spans': [{'bbox': [201.88999938964844, 551.9229736328125, 211.25889587402344, 565.6080322265625], 'content': 'AI', 'type': 'text', 'score': 1.0}, {'bbox': [211.25889587402344, 554.0706176757812, 332.65252685546875, 564.0306396484375], 'content': ' 技术的积累，公司推出医疗', 'type': 'text', 'score': 1.0}, {'bbox': [335.2300109863281, 551.9229736328125, 344.5989074707031, 565.6080322265625], 'content': 'AI', 'type': 'text', 'score': 1.0}, {'bbox': [344.5989074707031, 554.0706176757812, 574.925048828125, 564.0306396484375], 'content': ' 应用开发平台，打造全院智慧化服务接入底座，实现', 'type': 'text', 'score': 1.0}], 'index': 44}, {'bbox': [201.88999938964844, 567.552978515625, 574.8896484375, 581.238037109375], 'spans': [{'bbox': [201.88999938964844, 569.7006225585938, 291.7491149902344, 579.66064453125], 'content': '多技术框架、多业务', 'type': 'text', 'score': 1.0}, {'bbox': 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574.8896484375, 579.66064453125], 'content': '三生大模', 'type': 'text', 'score': 1.0}], 'index': 45}, {'bbox': [201.88999938964844, 583.1529541015625, 575.1400146484375, 596.8380126953125], 'spans': [{'bbox': [201.88999938964844, 585.3005981445312, 211.85000610351562, 595.2606201171875], 'content': '型', 'type': 'text', 'score': 1.0}, {'bbox': [211.85000610351562, 584.8434448242188, 215.16676330566406, 595.9706420898438], 'content': '”', 'type': 'text', 'score': 1.0}, {'bbox': [215.2100067138672, 585.3005981445312, 540.5800170898438, 595.2606201171875], 'content': '，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, 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'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 # 调用函数
groups = __process_blocks(input_blocks) groups = __process_blocks(input_blocks)
for group_index, group in enumerate(groups): for group_index, group in enumerate(groups):
......
magic_pdf/pdf_parse_union_core_v2.py
View file @ 0d83fb77
...@@ -360,7 +360,7 @@ def parse_page_core(pdf_docs, magic_model, page_id, pdf_bytes_md5, imageWriter, ...@@ -360,7 +360,7 @@ def parse_page_core(pdf_docs, magic_model, page_id, pdf_bytes_md5, imageWriter,
need_drop, drop_reason) need_drop, drop_reason)
'''将span填入blocks中''' '''将span填入blocks中'''
block_with_spans, spans = fill_spans_in_blocks(all_bboxes, spans, 0.3) block_with_spans, spans = fill_spans_in_blocks(all_bboxes, spans, 0.5)
'''对block进行fix操作''' '''对block进行fix操作'''
fix_blocks = fix_block_spans(block_with_spans, img_blocks, table_blocks) fix_blocks = fix_block_spans(block_with_spans, img_blocks, table_blocks)
......
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