Merge pull request #1143 from opendatalab/release-0.10.3

Release 0.10.3

magic_pdf/dict2md/ocr_mkcontent.py

@@ -5,7 +5,6 @@ from loguru import logger
 from magic_pdf.config.make_content_config import DropMode, MakeMode
 from magic_pdf.config.ocr_content_type import BlockType, ContentType
 from magic_pdf.libs.commons import join_path
-from magic_pdf.libs.language import detect_lang
 from magic_pdf.libs.markdown_utils import ocr_escape_special_markdown_char
 from magic_pdf.para.para_split_v3 import ListLineTag
 
@@ -30,6 +29,13 @@ def ocr_mk_mm_markdown_with_para_and_pagination(pdf_info_dict: list,
     for page_info in pdf_info_dict:
         paras_of_layout = page_info.get('para_blocks')
         if not paras_of_layout:
+            markdown_with_para_and_pagination.append({
+                'page_no':
+                    page_no,
+                'md_content':
+                    '',
+            })
+            page_no += 1
             continue
         page_markdown = ocr_mk_markdown_with_para_core_v2(
             paras_of_layout, 'mm', img_buket_path)
@@ -136,14 +142,11 @@ def merge_para_with_text(para_block):
             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 j, span in enumerate(line['spans']):
 
             span_type = span['type']
@@ -157,27 +160,18 @@ def merge_para_with_text(para_block):
 
             content = content.strip()
             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
-                    if span_type in [ContentType.Text, ContentType.InterlineEquation]:
-                        para_text += content  # 中文/日语/韩文语境下，content间不需要空格分隔
-                    elif span_type == ContentType.InlineEquation:
-                        para_text += f' {content} '
-                else:
-                    if span_type in [ContentType.Text, ContentType.InlineEquation]:
-                        # 如果span是line的最后一个且末尾带有-连字符，那么末尾不应该加空格,同时应该把-删除
-                        if j == len(line['spans'])-1 and __is_hyphen_at_line_end(content):
-                            para_text += content[:-1]
-                        elif len(content) == 1 and content not in ['A', 'I', 'a', 'i'] and not content.isdigit():
-                            para_text += content
-                        else:  # 西方文本语境下 content间需要空格分隔
-                            para_text += f'{content} '
-                    elif span_type == ContentType.InterlineEquation:
-                        para_text += content
+                if span_type in [ContentType.Text, ContentType.InlineEquation]:
+                    # 如果span是line的最后一个且末尾带有-连字符，那么末尾不应该加空格,同时应该把-删除
+                    if j == len(line['spans'])-1 and __is_hyphen_at_line_end(content):
+                        para_text += content[:-1]
+                    else:  # content间需要空格分隔
+                        para_text += f'{content} '
+                elif span_type == ContentType.InterlineEquation:
+                    para_text += content
             else:
                 continue
     # 连写字符拆分
-    para_text = __replace_ligatures(para_text)
+    # para_text = __replace_ligatures(para_text)
 
     return para_text
 

magic_pdf/filter/pdf_meta_scan.py

@@ -8,7 +8,7 @@ from loguru import logger
 from magic_pdf.config.drop_reason import DropReason
 from magic_pdf.libs.commons import get_top_percent_list, mymax
 from magic_pdf.libs.language import detect_lang
-from magic_pdf.libs.pdf_check import detect_invalid_chars
+from magic_pdf.libs.pdf_check import detect_invalid_chars_by_pymupdf
 
 scan_max_page = 50
 junk_limit_min = 10
@@ -323,7 +323,7 @@ def get_language(doc: fitz.Document):
 
 def check_invalid_chars(pdf_bytes):
     """乱码检测."""
-    return detect_invalid_chars(pdf_bytes)
+    return detect_invalid_chars_by_pymupdf(pdf_bytes)
 
 
 def pdf_meta_scan(pdf_bytes: bytes):

magic_pdf/libs/pdf_check.py

-from io import BytesIO
-import re
 import fitz
 import numpy as np
 from loguru import logger
-from pdfminer.high_level import extract_text
+# import re
+# from io import BytesIO
+# from pdfminer.high_level import extract_text
 
 
 def calculate_sample_count(total_page: int):
@@ -14,7 +14,7 @@ def calculate_sample_count(total_page: int):
     return select_page_cnt
 
 
-def extract_pages(src_pdf_bytes: bytes):
+def extract_pages(src_pdf_bytes: bytes) -> fitz.Document:
     pdf_docs = fitz.open("pdf", src_pdf_bytes)
     total_page = len(pdf_docs)
     if total_page == 0:
@@ -33,30 +33,57 @@ def extract_pages(src_pdf_bytes: bytes):
     return sample_docs
 
 
-def detect_invalid_chars(src_pdf_bytes: bytes) -> bool:
-    """"
-    检测PDF中是否包含非法字符
+# def detect_invalid_chars(src_pdf_bytes: bytes) -> bool:
+#     """"
+#     检测PDF中是否包含非法字符
+#     """
+#     '''pdfminer比较慢,需要先随机抽取10页左右的sample'''
+#     sample_docs = extract_pages(src_pdf_bytes)
+#     sample_pdf_bytes = sample_docs.tobytes()
+#     sample_pdf_file_like_object = BytesIO(sample_pdf_bytes)
+#     text = extract_text(sample_pdf_file_like_object)
+#     text = text.replace("\n", "")
+#     # logger.info(text)
+#     '''乱码文本用pdfminer提取出来的文本特征是(cid:xxx)'''
+#     cid_pattern = re.compile(r'\(cid:\d+\)')
+#     matches = cid_pattern.findall(text)
+#     cid_count = len(matches)
+#     cid_len = sum(len(match) for match in matches)
+#     text_len = len(text)
+#     if text_len == 0:
+#         cid_chars_radio = 0
+#     else:
+#         cid_chars_radio = cid_count/(cid_count + text_len - cid_len)
+#     logger.info(f"cid_count: {cid_count}, text_len: {text_len}, cid_chars_radio: {cid_chars_radio}")
+#     '''当一篇文章存在5%以上的文本是乱码时,认为该文档为乱码文档'''
+#     if cid_chars_radio > 0.05:
+#         return False  # 乱码文档
+#     else:
+#         return True   # 正常文档
+
+
+def count_replacement_characters(text: str) -> int:
+    """
+    统计字符串中 0xfffd 字符的数量。
     """
-    '''pdfminer比较慢,需要先随机抽取10页左右的sample'''
+    return text.count('\ufffd')
+
+
+def detect_invalid_chars_by_pymupdf(src_pdf_bytes: bytes) -> bool:
     sample_docs = extract_pages(src_pdf_bytes)
-    sample_pdf_bytes = sample_docs.tobytes()
-    sample_pdf_file_like_object = BytesIO(sample_pdf_bytes)
-    text = extract_text(sample_pdf_file_like_object)
-    text = text.replace("\n", "")
-    # logger.info(text)
-    '''乱码文本用pdfminer提取出来的文本特征是(cid:xxx)'''
-    cid_pattern = re.compile(r'\(cid:\d+\)')
-    matches = cid_pattern.findall(text)
-    cid_count = len(matches)
-    cid_len = sum(len(match) for match in matches)
-    text_len = len(text)
+    doc_text = ""
+    for page in sample_docs:
+        page_text = page.get_text('text', flags=fitz.TEXT_PRESERVE_WHITESPACE | fitz.TEXT_MEDIABOX_CLIP)
+        doc_text += page_text
+    text_len = len(doc_text)
+    uffd_count = count_replacement_characters(doc_text)
     if text_len == 0:
-        cid_chars_radio = 0
+        uffd_chars_radio = 0
     else:
-        cid_chars_radio = cid_count/(cid_count + text_len - cid_len)
-    logger.info(f"cid_count: {cid_count}, text_len: {text_len}, cid_chars_radio: {cid_chars_radio}")
-    '''当一篇文章存在5%以上的文本是乱码时,认为该文档为乱码文档'''
-    if cid_chars_radio > 0.05:
+        uffd_chars_radio = uffd_count / text_len
+    logger.info(f"uffd_count: {uffd_count}, text_len: {text_len}, uffd_chars_radio: {uffd_chars_radio}")
+    '''当一篇文章存在1%以上的文本是乱码时,认为该文档为乱码文档'''
+    if uffd_chars_radio > 0.01:
         return False  # 乱码文档
     else:
-        return True   # 正常文档
+        return True   # 正常文档
\ No newline at end of file

magic_pdf/model/pp_structure_v2.py

@@ -18,11 +18,31 @@ def region_to_bbox(region):
 
 
 class CustomPaddleModel:
-    def __init__(self, ocr: bool = False, show_log: bool = False, lang=None):
+    def __init__(self,
+                 ocr: bool = False,
+                 show_log: bool = False,
+                 lang=None,
+                 det_db_box_thresh=0.3,
+                 use_dilation=True,
+                 det_db_unclip_ratio=1.8
+    ):
         if lang is not None:
-            self.model = PPStructure(table=False, ocr=ocr, show_log=show_log, lang=lang)
+            self.model = PPStructure(table=False,
+                                     ocr=True,
+                                     show_log=show_log,
+                                     lang=lang,
+                                     det_db_box_thresh=det_db_box_thresh,
+                                     use_dilation=use_dilation,
+                                     det_db_unclip_ratio=det_db_unclip_ratio,
+            )
         else:
-            self.model = PPStructure(table=False, ocr=ocr, show_log=show_log)
+            self.model = PPStructure(table=False,
+                                     ocr=True,
+                                     show_log=show_log,
+                                     det_db_box_thresh=det_db_box_thresh,
+                                     use_dilation=use_dilation,
+                                     det_db_unclip_ratio=det_db_unclip_ratio,
+            )
 
     def __call__(self, img):
         try:

magic_pdf/model/sub_modules/ocr/paddleocr/ocr_utils.py

+import cv2
 import numpy as np
 from loguru import logger
-
+from io import BytesIO
+from PIL import Image
+import base64
 from magic_pdf.libs.boxbase import __is_overlaps_y_exceeds_threshold
 from magic_pdf.pre_proc.ocr_dict_merge import merge_spans_to_line
 
+from ppocr.utils.utility import check_and_read
+
+
+def img_decode(content: bytes):
+    np_arr = np.frombuffer(content, dtype=np.uint8)
+    return cv2.imdecode(np_arr, cv2.IMREAD_UNCHANGED)
+
+
+def check_img(img):
+    if isinstance(img, bytes):
+        img = img_decode(img)
+    if isinstance(img, str):
+        image_file = img
+        img, flag_gif, flag_pdf = check_and_read(image_file)
+        if not flag_gif and not flag_pdf:
+            with open(image_file, 'rb') as f:
+                img_str = f.read()
+                img = img_decode(img_str)
+            if img is None:
+                try:
+                    buf = BytesIO()
+                    image = BytesIO(img_str)
+                    im = Image.open(image)
+                    rgb = im.convert('RGB')
+                    rgb.save(buf, 'jpeg')
+                    buf.seek(0)
+                    image_bytes = buf.read()
+                    data_base64 = str(base64.b64encode(image_bytes),
+                                      encoding="utf-8")
+                    image_decode = base64.b64decode(data_base64)
+                    img_array = np.frombuffer(image_decode, np.uint8)
+                    img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
+                except:
+                    logger.error("error in loading image:{}".format(image_file))
+                    return None
+        if img is None:
+            logger.error("error in loading image:{}".format(image_file))
+            return None
+    if isinstance(img, np.ndarray) and len(img.shape) == 2:
+        img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+
+    return img
+
 
 def bbox_to_points(bbox):
     """ 将bbox格式转换为四个顶点的数组 """

magic_pdf/model/sub_modules/ocr/paddleocr/ppocr_273_mod.py

 import copy
 import time
-
 import cv2
 import numpy as np
+
 from paddleocr import PaddleOCR
-from paddleocr.paddleocr import check_img, logger
-from paddleocr.ppocr.utils.utility import alpha_to_color, binarize_img
-from paddleocr.tools.infer.predict_system import sorted_boxes
-from paddleocr.tools.infer.utility import get_rotate_crop_image, get_minarea_rect_crop
+from ppocr.utils.logging import get_logger
+from ppocr.utils.utility import alpha_to_color, binarize_img
+from tools.infer.predict_system import sorted_boxes
+from tools.infer.utility import get_rotate_crop_image, get_minarea_rect_crop
+
+from magic_pdf.model.sub_modules.ocr.paddleocr.ocr_utils import update_det_boxes, merge_det_boxes, check_img
 
-from magic_pdf.model.sub_modules.ocr.paddleocr.ocr_utils import update_det_boxes, merge_det_boxes
+logger = get_logger()
 
 
 class ModifiedPaddleOCR(PaddleOCR):

magic_pdf/model/sub_modules/table/tablemaster/tablemaster_paddle.py

@@ -2,8 +2,8 @@ import os
 
 import cv2
 import numpy as np
-from paddleocr.ppstructure.table.predict_table import TableSystem
-from paddleocr.ppstructure.utility import init_args
+from ppstructure.table.predict_table import TableSystem
+from ppstructure.utility import init_args
 from PIL import Image
 
 from magic_pdf.config.constants import *  # noqa: F403

magic_pdf/para/para_split_v3.py

 import copy
 
+from loguru import logger
+
 from magic_pdf.config.constants import CROSS_PAGE, LINES_DELETED
 from magic_pdf.config.ocr_content_type import BlockType, ContentType
+from magic_pdf.libs.language import detect_lang
 
 LINE_STOP_FLAG = (
     '.',
@@ -125,6 +128,9 @@ def __is_list_or_index_block(block):
 
             # 添加所有文本，包括空行，保持与block['lines']长度一致
             lines_text_list.append(line_text)
+            block_text = ''.join(lines_text_list)
+            block_lang = detect_lang(block_text)
+            # logger.info(f"block_lang: {block_lang}")
 
             # 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:
@@ -136,13 +142,16 @@ def __is_list_or_index_block(block):
             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
-                # block宽的阈值可以小些，block窄的阈值要大
-
-                if block_weight_radio >= 0.5:
+                # 类中文没有超长单词的情况，可以用统一的阈值
+                if block_lang in ['zh', 'ja', 'ko']:
                     closed_area = 0.26 * block_weight
                 else:
-                    closed_area = 0.36 * block_weight
+                    # 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
+                    # block宽的阈值可以小些，block窄的阈值要大
+                    if block_weight_radio >= 0.5:
+                        closed_area = 0.26 * block_weight
+                    else:
+                        closed_area = 0.36 * block_weight
                 if block['bbox_fs'][2] - line['bbox'][2] > closed_area:
                     right_not_close_num += 1
 

magic_pdf/pdf_parse_union_core_v2.py

@@ -30,22 +30,14 @@ try:
         torchtext.disable_torchtext_deprecation_warning()
 except ImportError:
     pass
-from magic_pdf.model.sub_modules.model_init import AtomModelSingleton
 
+from magic_pdf.model.sub_modules.model_init import AtomModelSingleton
 from magic_pdf.para.para_split_v3 import para_split
-
-from magic_pdf.pre_proc.construct_page_dict import \
-    ocr_construct_page_component_v2
+from magic_pdf.pre_proc.construct_page_dict import ocr_construct_page_component_v2
 from magic_pdf.pre_proc.cut_image import ocr_cut_image_and_table
-
-from magic_pdf.pre_proc.ocr_detect_all_bboxes import \
-    ocr_prepare_bboxes_for_layout_split_v2
-from magic_pdf.pre_proc.ocr_dict_merge import (fill_spans_in_blocks,
-                                               fix_block_spans_v2,
-                                               fix_discarded_block)
-from magic_pdf.pre_proc.ocr_span_list_modify import (
-    get_qa_need_list_v2, remove_overlaps_low_confidence_spans,
-    remove_overlaps_min_spans)
+from magic_pdf.pre_proc.ocr_detect_all_bboxes import ocr_prepare_bboxes_for_layout_split_v2
+from magic_pdf.pre_proc.ocr_dict_merge import fill_spans_in_blocks, fix_block_spans_v2, fix_discarded_block
+from magic_pdf.pre_proc.ocr_span_list_modify import get_qa_need_list_v2, remove_overlaps_low_confidence_spans, remove_overlaps_min_spans
 
 
 def __replace_STX_ETX(text_str: str):
@@ -65,10 +57,18 @@ def __replace_STX_ETX(text_str: str):
     return text_str
 
 
+def __replace_0xfffd(text_str: str):
+    """Replace \ufffd, as these characters become garbled when extracted using pymupdf."""
+    if text_str:
+        s = text_str.replace('\ufffd', " ")
+        return s
+    return text_str
+
 def chars_to_content(span):
     # 检查span中的char是否为空
     if len(span['chars']) == 0:
-        span['content'] = ''
+        pass
+        # span['content'] = ''
     else:
         # 先给chars按char['bbox']的中心点的x坐标排序
         span['chars'] = sorted(span['chars'], key=lambda x: (x['bbox'][0] + x['bbox'][2]) / 2)
@@ -83,22 +83,24 @@ def chars_to_content(span):
             if char['bbox'][0] - span['chars'][span['chars'].index(char) - 1]['bbox'][2] > char_avg_width:
                 content += ' '
             content += char['c']
-        span['content'] = __replace_STX_ETX(content)
+
+        span['content'] = __replace_0xfffd(content)
 
     del span['chars']
 
 
 LINE_STOP_FLAG = ('.', '!', '?', '。', '！', '？', ')', '）', '"', '”', ':', '：', ';', '；', ']', '】', '}', '}', '>', '》', '、', ',', '，', '-', '—', '–',)
+LINE_START_FLAG = ('(', '（', '"', '“', '【', '{', '《', '<', '「', '『', '【', '[',)
+
+
 def fill_char_in_spans(spans, all_chars):
 
+    # 简单从上到下排一下序
+    spans = sorted(spans, key=lambda x: x['bbox'][1])
+
     for char in all_chars:
         for span in spans:
-            # 判断char是否属于LINE_STOP_FLAG
-            if char['c'] in LINE_STOP_FLAG:
-                char_is_line_stop_flag = True
-            else:
-                char_is_line_stop_flag = False
-            if calculate_char_in_span(char['bbox'], span['bbox'], char_is_line_stop_flag):
+            if calculate_char_in_span(char['bbox'], span['bbox'], char['c']):
                 span['chars'].append(char)
                 break
 
@@ -106,13 +108,16 @@ def fill_char_in_spans(spans, all_chars):
 
     for span in spans:
         chars_to_content(span)
-        if len(span['content']) == 0:
+        # 有的span中虽然没有字但有一两个空的占位符，用宽高和content长度过滤
+        if len(span['content']) * span['height'] < span['width'] * 0.5:
+            # logger.info(f"maybe empty span: {len(span['content'])}, {span['height']}, {span['width']}")
             empty_spans.append(span)
+        del span['height'], span['width']
     return empty_spans
 
 
 # 使用鲁棒性更强的中心点坐标判断
-def calculate_char_in_span(char_bbox, span_bbox, char_is_line_stop_flag):
+def calculate_char_in_span(char_bbox, span_bbox, char, span_height_radio=0.33):
     char_center_x = (char_bbox[0] + char_bbox[2]) / 2
     char_center_y = (char_bbox[1] + char_bbox[3]) / 2
     span_center_y = (span_bbox[1] + span_bbox[3]) / 2
@@ -121,18 +126,26 @@ def calculate_char_in_span(char_bbox, span_bbox, char_is_line_stop_flag):
     if (
         span_bbox[0] < char_center_x < span_bbox[2]
         and span_bbox[1] < char_center_y < span_bbox[3]
-        and abs(char_center_y - span_center_y) < span_height / 4  # 字符的中轴和span的中轴高度差不能超过1/4span高度
+        and abs(char_center_y - span_center_y) < span_height * span_height_radio  # 字符的中轴和span的中轴高度差不能超过1/4span高度
     ):
         return True
     else:
         # 如果char是LINE_STOP_FLAG，就不用中心点判定，换一种方案（左边界在span区域内，高度判定和之前逻辑一致）
         # 主要是给结尾符号一个进入span的机会，这个char还应该离span右边界较近
-        if char_is_line_stop_flag:
+        if char in LINE_STOP_FLAG:
             if (
                 (span_bbox[2] - span_height) < char_bbox[0] < span_bbox[2]
                 and char_center_x > span_bbox[0]
                 and span_bbox[1] < char_center_y < span_bbox[3]
-                and abs(char_center_y - span_center_y) < span_height / 4
+                and abs(char_center_y - span_center_y) < span_height * span_height_radio
+            ):
+                return True
+        elif char in LINE_START_FLAG:
+            if (
+                span_bbox[0] < char_bbox[2] < (span_bbox[0] + span_height)
+                and char_center_x < span_bbox[2]
+                and span_bbox[1] < char_center_y < span_bbox[3]
+                and abs(char_center_y - span_center_y) < span_height * span_height_radio
             ):
                 return True
         else:
@@ -141,12 +154,14 @@ def calculate_char_in_span(char_bbox, span_bbox, char_is_line_stop_flag):
 
 def txt_spans_extract_v2(pdf_page, spans, all_bboxes, all_discarded_blocks, lang):
 
-    text_blocks_raw = pdf_page.get_text('rawdict', flags=fitz.TEXTFLAGS_TEXT)['blocks']
+    text_blocks_raw = pdf_page.get_text('rawdict', flags=fitz.TEXT_PRESERVE_WHITESPACE | fitz.TEXT_MEDIABOX_CLIP)['blocks']
 
-    # @todo: 拿到char之后把倾斜角度较大的先删一遍
     all_pymu_chars = []
     for block in text_blocks_raw:
         for line in block['lines']:
+            cosine, sine = line['dir']
+            if abs (cosine) < 0.9 or abs(sine) > 0.1:
+                continue
             for span in line['spans']:
                 all_pymu_chars.extend(span['chars'])
 
@@ -157,6 +172,7 @@ def txt_spans_extract_v2(pdf_page, spans, all_bboxes, all_discarded_blocks, lang
             continue
         span_height = span['bbox'][3] - span['bbox'][1]
         span['height'] = span_height
+        span['width'] = span['bbox'][2] - span['bbox'][0]
         span_height_list.append(span_height)
     if len(span_height_list) == 0:
         return spans
@@ -174,15 +190,13 @@ def txt_spans_extract_v2(pdf_page, spans, all_bboxes, all_discarded_blocks, lang
             if block[7] in [BlockType.ImageBody, BlockType.TableBody, BlockType.InterlineEquation]:
                 continue
             if calculate_overlap_area_in_bbox1_area_ratio(span['bbox'], block[0:4]) > 0.5:
-                if span['height'] > median_span_height * 3 and span['height'] > (span['bbox'][2] - span['bbox'][0]) * 3:
+                if span['height'] > median_span_height * 3 and span['height'] > span['width'] * 3:
                     vertical_spans.append(span)
                 elif block in all_bboxes:
                     useful_spans.append(span)
                 else:
                     unuseful_spans.append(span)
 
-                del span['height']
-
                 break
 
     """垂直的span框直接用pymu的line进行填充"""
@@ -232,6 +246,7 @@ def txt_spans_extract_v2(pdf_page, spans, all_bboxes, all_discarded_blocks, lang
             if ocr_res and len(ocr_res) > 0:
                 if len(ocr_res[0]) > 0:
                     ocr_text, ocr_score = ocr_res[0][0]
+                    # logger.info(f"ocr_text: {ocr_text}, ocr_score: {ocr_score}")
                     if ocr_score > 0.5 and len(ocr_text) > 0:
                         span['content'] = ocr_text
                         span['score'] = ocr_score

requirements.txt

@@ -4,10 +4,10 @@ click>=8.1.7
 fast-langdetect==0.2.0
 loguru>=0.6.0
 numpy>=1.21.6,<2.0.0
-pdfminer.six==20231228
 pydantic>=2.7.2,<2.8.0
 PyMuPDF>=1.24.9
 scikit-learn>=1.0.2
 torch>=2.2.2,<=2.3.1
 transformers
+# pdfminer.six==20231228
 # The requirements.txt must ensure that only necessary external dependencies are introduced. If there are new dependencies to add, please contact the project administrator.