refactor(pdf_check): improve character detection using PyMuPDF

- Replace pdfminer with PyMuPDF for character detection
- Implement new method detect_invalid_chars_by_pymupdf
- Update check_invalid_chars in pdf_meta_scan.py to use new method
- Add __replace_0xfffd function in pdf_parse_union_core_v2.py to handle special characters
- Remove unused imports and update requirements.txt

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/pdf_parse_union_core_v2.py

@@ -57,6 +57,13 @@ 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:
@@ -76,7 +83,8 @@ 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']
 
@@ -140,7 +148,7 @@ 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.TEXT_PRESERVE_WHITESPACE | fitz.TEXT_MEDIABOX_CLIP | fitz.TEXT_CID_FOR_UNKNOWN_UNICODE)['blocks']
+    text_blocks_raw = pdf_page.get_text('rawdict', flags=fitz.TEXT_PRESERVE_WHITESPACE | fitz.TEXT_MEDIABOX_CLIP)['blocks']
 
     all_pymu_chars = []
     for block in text_blocks_raw:

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.