{"id":53742,"date":"2025-02-16T11:11:52","date_gmt":"2025-02-16T03:11:52","guid":{"rendered":"https:\/\/fwq.ai\/blog\/53742\/"},"modified":"2025-02-16T11:11:52","modified_gmt":"2025-02-16T03:11:52","slug":"5%e4%b8%aa%e6%96%87%e6%9c%ac-%e8%a1%a8%e6%a0%bc%e6%8f%90%e5%8f%96python%e5%8c%85","status":"publish","type":"post","link":"https:\/\/fwq.ai\/blog\/53742\/","title":{"rendered":"5\u4e2a\u6587\u672c\/\u8868\u683c\u63d0\u53d6Python\u5305"},"content":{"rendered":"<p>\u5728\u5f53\u4eca\u7684\u6570\u5b57\u65f6\u4ee3\uff0c\u4ece\u975e\u7ed3\u6784\u5316\u6570\u636e\u4e2d\u63d0\u53d6\u6709\u610f\u4e49\u7684\u4fe1\u606f\u5bf9\u4e8e\u5404\u79cd\u5e94\u7528\u81f3\u5173\u91cd\u8981\u3002\u4ece PDF \u7b49\u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\u548c\u8868\u683c\u5728\u6570\u636e\u5206\u6790\u3001\u4fe1\u606f\u68c0\u7d22\u548c\u81ea\u52a8\u5316\u4efb\u52a1\u4e2d\u53d1\u6325\u7740\u91cd\u8981\u4f5c\u7528\u3002<\/p>\n<p>\u5728\u8fd9\u7bc7\u535a\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u6df1\u5165\u7814\u7a76 Python \u4e2d\u7684\u6587\u672c\u548c\u8868\u683c\u63d0\u53d6\u4e16\u754c\uff0c\u63a2\u7d22\u53ef\u4ee5\u7b80\u5316\u8fd9\u4e9b\u8fc7\u7a0b\u7684\u4e0d\u540c\u5305\u3002<\/p>\n<h2>0\u3001\u5149\u5b66\u5b57\u7b26\u8bc6\u522b (OCR)<\/h2>\n<p>\u5728\u6df1\u5165\u7814\u7a76\u63d0\u53d6\u5305\u4e4b\u524d\uff0c\u8ba9\u6211\u4eec\u5148\u4e86\u89e3\u4e00\u4e0b\u5149\u5b66\u5b57\u7b26\u8bc6\u522b (OCR) \u7684\u57fa\u672c\u6982\u5ff5\u3002<\/p>\n<p>OCR \u662f\u4e00\u79cd\u4f7f\u8ba1\u7b97\u673a\u80fd\u591f\u8bc6\u522b\u548c\u63d0\u53d6\u56fe\u50cf\u6216\u626b\u63cf\u6587\u6863\u4e2d\u7684\u6587\u672c\u7684\u6280\u672f\u3002\u5b83\u6d89\u53ca\u4e00\u7cfb\u5217\u6b65\u9aa4\uff0c\u5305\u62ec\u56fe\u50cf\u9884\u5904\u7406\u3001\u5b57\u7b26\u5206\u5272\u548c\u5b57\u7b26\u8bc6\u522b\u3002<\/p>\n<p>\u6587\u672c\u68c0\u6d4b\u548c\u6587\u672c\u8bc6\u522b\u662f\u4e24\u4e2a\u57fa\u672c\u7ec4\u4ef6\uff0c\u5b83\u4eec\u534f\u540c\u5de5\u4f5c\u4ee5\u5728 OCR \u4e2d\u4ece\u56fe\u50cf\u6216\u626b\u63cf\u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\u3002\u8ba9\u6211\u4eec\u8be6\u7ec6\u63a2\u8ba8\u6bcf\u4e2a\u90e8\u5206\uff1a<\/p>\n<p>\u6587\u672c\u68c0\u6d4b\u6d89\u53ca\u5b9a\u4f4d\u56fe\u50cf\u6216\u6587\u6863\u4e2d\u5305\u542b\u6587\u672c\u7684\u533a\u57df\u6216\u8fb9\u754c\u6846\u3002\u6b64\u6b65\u9aa4\u5bf9\u4e8e\u786e\u5b9a\u9700\u8981\u6267\u884c\u6587\u672c\u63d0\u53d6\u7684\u5173\u6ce8\u533a\u57df\u81f3\u5173\u91cd\u8981\u3002\u4ee5\u4e0b\u662f\u6587\u672c\u68c0\u6d4b\u8fc7\u7a0b\u7684\u6982\u8ff0\uff1a<\/p>\n<ul>\n<li>\u5bf9\u8c61\u5b9a\u4f4d\uff1a\u5e94\u7528\u5bf9\u8c61\u5b9a\u4f4d\u7b97\u6cd5\u6765\u8bc6\u522b\u56fe\u50cf\u4e2d\u53ef\u80fd\u5305\u542b\u6587\u672c\u7684\u6f5c\u5728\u533a\u57df\u3002\u8fd9\u4e9b\u7b97\u6cd5\u5206\u6790\u89c6\u89c9\u7279\u5f81\uff0c\u4f8b\u5982\u8fb9\u7f18\u3001\u89d2\u548c\u7eb9\u7406\u56fe\u6848\uff0c\u4ee5\u786e\u5b9a\u53ef\u80fd\u5305\u542b\u6587\u672c\u7684\u533a\u57df\u3002<\/li>\n<li>\u8fb9\u754c\u6846\u751f\u6210\uff1a\u4e00\u65e6\u8bc6\u522b\u51fa\u6f5c\u5728\u7684\u6587\u672c\u533a\u57df\uff0c\u5c31\u4f1a\u5728\u8fd9\u4e9b\u533a\u57df\u5468\u56f4\u751f\u6210\u8fb9\u754c\u6846\u3002\u8fd9\u4e9b\u8fb9\u754c\u6846\u5b9a\u4e49\u4e86\u56fe\u50cf\u4e2d\u6587\u672c\u7684\u7a7a\u95f4\u8303\u56f4\uff0c\u5e76\u63d0\u4f9b\u4e86\u4e00\u79cd\u9694\u79bb\u548c\u63d0\u53d6\u6587\u672c\u4ee5\u4f9b\u8fdb\u4e00\u6b65\u5904\u7406\u7684\u65b9\u6cd5\u3002<\/li>\n<\/ul>\n<p>\u4e00\u65e6\u68c0\u6d4b\u5230\u6587\u672c\u533a\u57df\uff0c\u4e0b\u4e00\u6b65\u5c31\u662f\u6267\u884c\u6587\u672c\u8bc6\u522b\uff0c\u8fd9\u6d89\u53ca\u5c06\u68c0\u6d4b\u5230\u7684\u6587\u672c\u533a\u57df\u8f6c\u6362\u4e3a\u673a\u5668\u53ef\u8bfb\u7684\u6587\u672c\u3002\u4ee5\u4e0b\u662f\u6587\u672c\u8bc6\u522b\u8fc7\u7a0b\u7684\u6982\u8ff0\uff1a<\/p>\n<ul>\n<li>\u5b57\u7b26\u5206\u5272\uff1a\u5728\u6b64\u6b65\u9aa4\u4e2d\uff0c\u8fdb\u4e00\u6b65\u5206\u6790\u6587\u672c\u533a\u57df\u4ee5\u5206\u5272\u5355\u4e2a\u5b57\u7b26\u6216\u6587\u672c\u884c\u3002\u8fd9\u79cd\u5206\u5272\u5bf9\u4e8e\u5c06\u6587\u672c\u5206\u6210\u53ef\u4ee5\u5355\u72ec\u8bc6\u522b\u7684\u8f83\u5c0f\u5355\u5143\u662f\u5fc5\u8981\u7684\u3002<\/li>\n<li>\u7279\u5f81\u63d0\u53d6\uff1a\u5bf9\u4e8e\u6bcf\u4e2a\u5206\u5272\u7684\u5b57\u7b26\u6216\u6587\u672c\u884c\uff0c\u63d0\u53d6\u8fb9\u7f18\u3001\u89d2\u6216\u7eb9\u7406\u56fe\u6848\u7b49\u7279\u5f81\u3002\u8fd9\u4e9b\u7279\u5f81\u6709\u52a9\u4e8e\u4ee5\u6709\u610f\u4e49\u7684\u65b9\u5f0f\u8868\u793a\u6587\u672c\u5355\u5143\u7684\u89c6\u89c9\u7279\u5f81\u3002<\/li>\n<li>\u5b57\u7b26\u8bc6\u522b\uff1a\u63d0\u53d6\u7684\u7279\u5f81\u7528\u4f5c\u5b57\u7b26\u8bc6\u522b\u7b97\u6cd5\u7684\u8f93\u5165\uff0c\u4f8b\u5982\u673a\u5668\u5b66\u4e60\u6a21\u578b\u6216\u6a21\u5f0f\u5339\u914d\u6280\u672f\u3002\u8be5\u7b97\u6cd5\u5c06\u7279\u5f81\u4e0e\u9884\u5148\u8bad\u7ec3\u7684\u5b57\u7b26\u6216\u5b57\u4f53\u96c6\u8fdb\u884c\u6bd4\u8f83\uff0c\u5e76\u786e\u5b9a\u6bcf\u4e2a\u7247\u6bb5\u6700\u53ef\u80fd\u7684\u5b57\u7b26\u3002<\/li>\n<li>\u6587\u672c\u7ec4\u5408\uff1a\u4e00\u65e6\u5b57\u7b26\u88ab\u5355\u72ec\u8bc6\u522b\uff0c\u5b83\u4eec\u5c31\u4f1a\u6839\u636e\u5176\u5728\u6587\u672c\u533a\u57df\u5185\u7684\u7a7a\u95f4\u6392\u5217\u7ec4\u5408\u5e76\u7ec4\u7ec7\u6210\u5355\u8bcd\u3001\u53e5\u5b50\u6216\u6bb5\u843d\u3002\u6b64\u7ec4\u5408\u6b65\u9aa4\u53ef\u786e\u4fdd\u8bc6\u522b\u7684\u5b57\u7b26\u6309\u6b63\u786e\u7684\u987a\u5e8f\u6392\u5217\uff0c\u4ee5\u5f62\u6210\u8fde\u8d2f\u4e14\u6709\u610f\u4e49\u7684\u6587\u672c\u3002<\/li>\n<li>\u540e\u5904\u7406\uff1a\u5728\u6587\u672c\u8bc6\u522b\u6b65\u9aa4\u4e4b\u540e\uff0c\u53ef\u4ee5\u5e94\u7528\u5176\u4ed6\u540e\u5904\u7406\u6280\u672f\u6765\u7ec6\u5316\u8bc6\u522b\u7684\u6587\u672c\u3002\u8fd9\u53ef\u4ee5\u5305\u62ec\u8bed\u8a00\u5efa\u6a21\u3001\u62fc\u5199\u68c0\u67e5\u548c\u4e0a\u4e0b\u6587\u5206\u6790\uff0c\u4ee5\u63d0\u9ad8\u63d0\u53d6\u6587\u672c\u7684\u51c6\u786e\u6027\u548c\u8fde\u8d2f\u6027\u3002<\/li>\n<\/ul>\n<blockquote><p>\n  \u6587\u672c\u63d0\u53d6\u5305\n<\/p><\/blockquote>\n<h2>1\u3001Pytesseract<\/h2>\n<p>Pytesseract \u662f\u4e00\u4e2a\u6d41\u884c\u7684 Python \u5e93\uff0c\u53ef\u7528\u4f5c Google \u7684 Tesseract OCR \u5f15\u64ce\u7684\u5305\u88c5\u5668\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u754c\u9762\u6765\u4ece\u56fe\u50cf\u548c\u626b\u63cf\u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\u3002\u5b83\u53ef\u4ee5\u8bfb\u53d6\u6240\u6709\u7c7b\u578b\u7684\u56fe\u50cf\uff0c\u5982 jpeg\u3001png\u3001gif\u3001bmp\u3001tiff \u7b49\u3002<\/p>\n<p>\u4ece\u56fe\u50cf\u4e2d\u63d0\u53d6\u6587\u672c\u7684\u51fd\u6570\uff1a<\/p>\n<pre><code>text = pytesseract.image_to_string(imagePath, **args)<\/code><\/pre>\n<p>\u5176\u4ed6\u53ef\u9009\u53c2\u6570\uff1a<\/p>\n<ul>\n<li>lang \u2014 \u6587\u672c\u7684\u8bed\u8a00\uff08\u4f8b\u5982 lang = \u2018eng+fra\u2019\uff09<\/li>\n<li>config \u2014 OCR \u914d\u7f6e\uff08\u4f8b\u5982 config = \u2018-c retain_interword_spaces=1\u2019\uff09<\/li>\n<li>output_type \u2014 \u6307\u5b9a\u8f93\u51fa\u7684\u7c7b\u578b\uff0c\u9ed8\u8ba4\u4e3a\u5b57\u7b26\u4e32\uff08\u4f8b\u5982 output_type = Output.STRING\uff09<\/li>\n<\/ul>\n<p>config \u53c2\u6570\u5141\u8bb8\u4f60\u81ea\u5b9a\u4e49 Tesseract OCR \u5f15\u64ce\u7684\u884c\u4e3a\u548c\u6027\u80fd\u3002\u5b83\u4f7f\u4f60\u80fd\u591f\u4f20\u9012\u5176\u4ed6\u914d\u7f6e\u9009\u9879\u6765\u5f71\u54cd\u6587\u672c\u63d0\u53d6\u8fc7\u7a0b\u3002<\/p>\n<p>\u4f8b\u5982\uff0c\u8981\u4ece\u4e0b\u56fe\u4e2d\u63d0\u53d6\u952e\u503c\u5bf9\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>-c retain_interword_spaces = 1<\/code> \u9009\u9879\uff0c\u8be5\u9009\u9879\u5728\u6587\u672c\u63d0\u53d6\u671f\u95f4\u4fdd\u7559\u5355\u8bcd\u95f4\u7a7a\u683c\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0cPytesseract \u6267\u884c\u6587\u672c\u8bc6\u522b\u65f6\u4e0d\u8003\u8651\u5404\u4e2a\u5355\u8bcd\u4e4b\u95f4\u7684\u95f4\u8ddd\u3002\u8fd9\u53ef\u80fd\u5bfc\u81f4\u63d0\u53d6\u7684\u6587\u672c\u4f5c\u4e3a\u8fde\u7eed\u5b57\u7b26\u4e32\u8fd4\u56de\uff0c\u800c\u8bc6\u522b\u7684\u5355\u8bcd\u4e4b\u95f4\u6ca1\u6709\u4efb\u4f55\u7a7a\u683c\u3002<\/p>\n<p>  \u4f7f\u7528\u548c\u4e0d\u4f7f\u7528\u914d\u7f6e\u9009\u9879\u65f6 Pytesseract \u63d0\u53d6\u7684\u6587\u672c\u8f93\u51fa\u7684\u5dee\u5f02 <\/p>\n<p>\u5f53\u4f60\u5728 Pytesseract \u7684\u914d\u7f6e\u5b57\u7b26\u4e32\u4e2d\u5305\u542b <code>-c retain_interword_spaces=1<\/code> \u53c2\u6570\u65f6\uff0c\u5b83\u4f1a\u6307\u793a Pytesseract \u4fdd\u7559\u539f\u59cb\u6587\u672c\u4e2d\u7684\u5355\u8bcd\u95f4\u7a7a\u683c\u3002\u8fd9\u610f\u5473\u7740\u63d0\u53d6\u7684\u6587\u672c\u5c06\u5305\u62ec\u8bc6\u522b\u5355\u8bcd\u4e4b\u95f4\u7684\u7a7a\u683c\uff0c\u4fdd\u6301\u539f\u59cb\u5355\u8bcd\u8fb9\u754c\u3002<\/p>\n<p>  \u4e0d\u4f7f\u7528\u914d\u7f6e\u53c2\u6570  \u4f7f\u7528\u914d\u7f6e\u53c2\u6570 <\/p>\n<h2>2\u3001PyMuPDF (Fitz)<\/h2>\n<p>PyMuPDF\uff0c\u4e5f\u79f0\u4e3a Fitz\uff0c\u662f MuPDF \u5e93\u7684 Python \u7ed1\u5b9a\u3002\u5b83\u63d0\u4f9b\u4e86\u5904\u7406 PDF \u6587\u6863\u7684\u5168\u9762\u529f\u80fd\uff0c\u5305\u62ec\u6587\u672c\u63d0\u53d6\u3002PyMuPDF \u5141\u8bb8\u4f60\u8bbf\u95ee PDF \u6587\u4ef6\u4e2d\u7684\u6587\u672c\u5185\u5bb9\u3001\u5143\u6570\u636e\u548c\u6ce8\u91ca\u3002\u5176\u5e7f\u6cdb\u7684\u529f\u80fd\u4f7f\u5176\u6210\u4e3a\u4ece\u7b80\u5355\u548c\u590d\u6742\u7684 PDF \u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\u7684\u591a\u529f\u80fd\u9009\u62e9\u3002<\/p>\n<p>\u63d0\u53d6\u6587\u672c\u7684\u51fd\u6570\uff1a<\/p>\n<pre><code>get_text(option)<\/code><\/pre>\n<p>\u6211\u4eec\u53ef\u4ee5\u4ece\u591a\u4e2a\u53ef\u7528\u9009\u9879\u4e2d\u9009\u62e9\u4e00\u4e2a\u9009\u9879\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0c\u9009\u62e9\u201c\u6587\u672c\u201d\u9009\u9879\u3002\u9009\u9879\u5217\u8868\u5982\u4e0b\u3002<\/p>\n<p>\u9009\u9879\uff1a<\/p>\n<ul>\n<li>text\uff1a\uff08\u9ed8\u8ba4\uff09\u5e26\u6362\u884c\u7b26\u7684\u7eaf\u6587\u672c\u3002\u6ca1\u6709\u683c\u5f0f\uff0c\u6ca1\u6709\u6587\u672c\u4f4d\u7f6e\u8be6\u7ec6\u4fe1\u606f\uff0c\u6ca1\u6709\u56fe\u50cf\u3002<\/li>\n<li>blocks\uff1a\u751f\u6210\u6587\u672c\u5757\u5217\u8868\uff08= \u6bb5\u843d\uff09\u3002<\/li>\n<li>words\uff1a\u751f\u6210\u5355\u8bcd\u5217\u8868\uff08\u4e0d\u5305\u542b\u7a7a\u683c\u7684\u5b57\u7b26\u4e32\uff09\u3002<\/li>\n<li>html\uff1a\u751f\u6210 HTML \u683c\u5f0f\u7684\u5185\u5bb9\u3002<\/li>\n<li>dict \/ json\uff1a\u4e0e HTML \u4fe1\u606f\u7ea7\u522b\u76f8\u540c\uff0c\u4f46\u4ee5 Python \u5b57\u5178\u6216 JSON \u5b57\u7b26\u4e32\u5f62\u5f0f\u63d0\u4f9b\u3002<\/li>\n<li>rawdict \/ rawjson\uff1a\u201cdict\u201d\/\u201cjson\u201d\u7684\u8d85\u96c6\u3002\u5b83\u8fd8\u63d0\u4f9b\u5b57\u7b26\u8be6\u7ec6\u4fe1\u606f\u3002<\/li>\n<\/ul>\n<p>\u4e0b\u9762\u7ed9\u51fa\u4e86\u6309\u6bb5\u843d\u63d0\u53d6\u6587\u672c\u7684\u793a\u4f8b\uff1a<\/p>\n<p>  \u5757\u683c\u5f0f\u7684\u793a\u4f8b\u8f93\u5165\u548c\u8f93\u51fa <\/p>\n<p>\u4e0a\u9762\u7684\u4ee3\u7801\u5c06\u8fd4\u56de\u4e00\u4e2a\u5143\u7ec4\u5217\u8868\uff1a<\/p>\n<ul>\n<li>\u6bcf\u4e2a\u5143\u7ec4\u88ab\u89c6\u4e3a\u4e00\u4e2a\u5757\u3002<\/li>\n<li>\u5143\u7ec4\u5305\u542b\uff1a\uff08X0\u3001Y0\u3001X1\u3001Y1\u3001\u201c\u5757\u4e2d\u7684\u884c\u201d\u3001block_no\u3001block_type\uff09<\/li>\n<li>\u524d\u56db\u9879\u662f\u8fb9\u754c\u6846\u5750\u6807<\/li>\n<li>\u7b2c\u4e94\u9879\u662f\u6587\u672c\u672c\u8eab\uff08\u591a\u884c\u7531\u6362\u884c\u7b26\u6216\u201c\\n\u201d\u5206\u9694\uff09<\/li>\n<li>\u7b2c\u516d\u9879\u662f\u5757\u7f16\u53f7<\/li>\n<li>\u7b2c\u4e03\u9879\u662f\u5757\u7c7b\u578b\uff080 \u8868\u793a\u6587\u672c\uff0c1 \u8868\u793a\u56fe\u50cf\uff09<\/li>\n<\/ul>\n<p>Fitz \u4ee5\u81ea\u7136\u9605\u8bfb\u987a\u5e8f\u8bfb\u53d6 pdf\u3002\u5982\u679c PDF \u88ab\u5206\u6210 2 \u5217\uff0cFitz \u4e0d\u4f1a\u6c34\u5e73\u8bfb\u53d6\u6574\u884c\uff0c\u800c\u662f\u5148\u8bfb\u53d6\u7b2c\u4e00\u5217\uff0c\u7136\u540e\u5f00\u59cb\u4ee5\u81ea\u7136\u9605\u8bfb\u987a\u5e8f\u8bfb\u53d6\u7b2c\u4e8c\u5217\uff1a<\/p>\n<p>  \u4ee5\u81ea\u7136\u9605\u8bfb\u987a\u5e8f\u8f93\u51fa\u6587\u672c <\/p>\n<p>Fitz \u7684\u5c40\u9650\u6027\uff1a<\/p>\n<ul>\n<li>\u4ec5\u9002\u7528\u4e8e\u673a\u5668\u751f\u6210\u7684 PDF\uff0c\u4e0d\u9002\u7528\u4e8e\u626b\u63cf\u7684 PDF<\/li>\n<li>\u8be5\u5e93\u9700\u8981\u5b89\u88c5\u975e Python \u8f6f\u4ef6\uff08MuPDF\uff09\u3002<\/li>\n<\/ul>\n<h2>3\u3001pdfplumber<\/h2>\n<p>\u4ee5\u4e0b\u6bcf\u4e2a\u5c5e\u6027\u90fd\u8fd4\u56de\u5339\u914d\u5bf9\u8c61\u7684 Python \u5217\u8868\uff1a<\/p>\n<ul>\n<li>chars \u2014 \u6bcf\u4e2a\u4ee3\u8868\u4e00\u4e2a\u6587\u672c\u5b57\u7b26\u3002<\/li>\n<li>lines \u2014 \u6bcf\u4e2a\u4ee3\u8868\u4e00\u6761\u4e00\u7ef4\u7ebf\u3002<\/li>\n<li>rects \u2014 \u6bcf\u4e2a\u8868\u793a\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u5f62\u3002<\/li>\n<li>curves \u2014 \u6bcf\u4e2a\u8868\u793a\u4efb\u4f55\u4e00\u7cfb\u5217\u65e0\u6cd5\u200b\u200b\u8bc6\u522b\u4e3a\u7ebf\u6216\u77e9\u5f62\u7684\u8fde\u63a5\u70b9\u3002<\/li>\n<li>images \u2014 \u6bcf\u4e2a\u8868\u793a\u4e00\u5f20\u56fe\u7247\u3002<\/li>\n<li>annots \u2014 \u6bcf\u4e2a\u8868\u793a\u4e00\u4e2a PDF \u6ce8\u91ca<\/li>\n<li>hyperlinks \u2014 \u6bcf\u4e2a\u8868\u793a\u4e00\u4e2a\u5b50\u7c7b\u578b\u4e3a Link \u7684 PDF \u6ce8\u91ca\uff0c\u5e76\u5177\u6709 URI \u64cd\u4f5c\u5c5e\u6027<\/li>\n<\/ul>\n<p>\u5728\u4e0a\u56fe\u4e2d\uff0c\u4f60\u53ef\u4ee5\u770b\u5230\u952e\u4ee5\u7c97\u4f53\u663e\u793a\u3002\u56e0\u6b64\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u6587\u672c\u7684\u5b57\u4f53\u5c5e\u6027\u4ece\u4e0a\u56fe\u4e2d\u63d0\u53d6\u952e\u3002\u4ee3\u7801\u7247\u6bb5\u5982\u4e0b\u6240\u793a\uff1a<\/p>\n<pre><code>boldKey = []\nwith pdfplumber.open(pdfPath) as pdf:\ntext = pdf.pages[0]\n# filter only those words which have object type as char, Bold in fontname property\nbold_text = text.filter(lambda obj: (obj[\"object_type\"] == \"char\" and \"Bold\" in obj[\"fontname\"]))\nboldKey.append(bold_text.extract_text())\nboldKey = boldKey[0].split(\"\\n\")\nprint(boldKey)<\/code><\/pre>\n<p>  \u63d0\u53d6\u7684\u7c97\u4f53\u5173\u952e\u5b57\u5217\u8868 <\/p>\n<p>\u8868\u683c\u98ce\u683c\uff1a<\/p>\n<ul>\n<li>Stream \u2014 Stream \u53ef\u7528\u4e8e\u89e3\u6790\u5355\u5143\u683c\u4e4b\u95f4\u6709\u7a7a\u683c\u7684\u8868\u683c\uff0c\u4ee5\u6a21\u62df\u8868\u683c\u7ed3\u6784\u3002<\/li>\n<\/ul>\n<ul>\n<li>Lattice \u2014 Lattice \u672c\u8d28\u4e0a\u66f4\u5177\u786e\u5b9a\u6027\uff0c\u4e0d\u4f9d\u8d56\u4e8e\u731c\u6d4b\u3002\u5b83\u53ef\u7528\u4e8e\u89e3\u6790\u5355\u5143\u683c\u4e4b\u95f4\u6709\u5206\u754c\u7ebf\u7684\u8868\u683c\u3002<\/li>\n<\/ul>\n<blockquote><p>\n  \u8868\u683c\u63d0\u53d6\u5305\n<\/p><\/blockquote>\n<h2>4\u3001Camelot<\/h2>\n<p>Camelot \u662f\u4e00\u4e2a\u4e13\u95e8\u4e3a\u4ece PDF \u6587\u6863\u4e2d\u63d0\u53d6\u8868\u683c\u800c\u8bbe\u8ba1\u7684 Python \u5e93\u3002\u5b83\u5229\u7528\u5148\u8fdb\u7684\u6280\u672f\uff08\u5305\u62ec\u8ba1\u7b97\u673a\u89c6\u89c9\u7b97\u6cd5\uff09\u6765\u51c6\u786e\u68c0\u6d4b\u548c\u63d0\u53d6\u8868\u683c\u3002Camelot \u63d0\u4f9b\u4e86\u4e0d\u540c\u7684\u8868\u683c\u63d0\u53d6\u65b9\u6cd5\uff0c\u4f8b\u5982 Lattice \u548c Stream\uff0c\u4ee5\u5904\u7406\u4e0d\u540c\u7c7b\u578b\u7684\u8868\u683c\u7ed3\u6784\u3002\u6bcf\u4e2a\u8868\u90fd\u91c7\u7528 pandas DataFrame \u683c\u5f0f\uff0c\u53ef\u65e0\u7f1d\u96c6\u6210\u5230 ETL \u548c\u6570\u636e\u5206\u6790\u5de5\u4f5c\u6d41\u4e2d\u3002\u6211\u4eec\u53ef\u4ee5\u5c06\u8868\u5bfc\u51fa\u4e3a\u591a\u79cd\u683c\u5f0f\uff0c\u5305\u62ec CSV\u3001JSON\u3001Excel \u548c HTML\u3002<\/p>\n<p>\u63d0\u53d6\u8868\u683c\u7684\u51fd\u6570\uff1a<\/p>\n<pre><code>tables = camelot.read_pdf(filePath, **args)<\/code><\/pre>\n<p>\u5176\u4ed6\u53c2\u6570\u662f<\/p>\n<ul>\n<li>pages \u2014 \u4ece PDF \u8bfb\u53d6\u7684\u9875\u6570\uff08\u9ed8\u8ba4\u503c\uff1a&#8217;1&#8217;\uff09<\/li>\n<li>flavor \u2014 \u89e3\u6790\u65b9\u6cd5\uff08\u9ed8\u8ba4\u503c\uff1a&#8217;lattice&#8217;\uff09<\/li>\n<\/ul>\n<h2>5\u3001Tabula<\/h2>\n<p>Tabula \u662f\u4e00\u79cd\u6d41\u884c\u7684\u5f00\u6e90\u5de5\u5177\uff0c\u53ef\u4ee5\u4ece PDF \u6587\u4ef6\u4e2d\u63d0\u53d6\u8868\u683c\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7528\u6237\u53cb\u597d\u7684\u754c\u9762\uff0c\u65e2\u53ef\u4ee5\u4f5c\u4e3a\u547d\u4ee4\u884c\u5b9e\u7528\u7a0b\u5e8f\uff0c\u4e5f\u53ef\u4ee5\u4f5c\u4e3a Python \u5e93\u3002Tabula \u7684\u7b97\u6cd5\u53ef\u4ee5\u667a\u80fd\u5730\u5206\u6790 PDF \u5e03\u5c40\uff0c\u4ee5\u6709\u6548\u5730\u8bc6\u522b\u548c\u63d0\u53d6\u8868\u683c\u3002 Tabula-py \u662f tabula-java \u7684\u7b80\u5355 Python \u5305\u88c5\u5668\uff0c\u53ef\u4ee5\u8bfb\u53d6 PDF \u4e2d\u7684\u8868\u683c\u3002\u4f60\u53ef\u4ee5\u4ece PDF \u4e2d\u8bfb\u53d6\u8868\u683c\u5e76\u5c06\u5176\u8f6c\u6362\u4e3a Pandas \u6570\u636e\u6846\u3002Tabula-py \u8fd8\u5141\u8bb8\u4f60\u5c06 PDF \u6587\u4ef6\u8f6c\u6362\u4e3a CSV\u3001TSV \u6216 JSON \u6587\u4ef6\u3002<\/p>\n<p>\u63d0\u53d6\u8868\u683c\u7684\u51fd\u6570\uff1a<\/p>\n<pre><code>dfs = tabula.read_pdf(filePath, **args)<\/code><\/pre>\n<p>\u5176\u4ed6\u53c2\u6570\uff1a<\/p>\n<ul>\n<li>pages \u2014 \u4ece PDF \u8bfb\u53d6\u7684\u9875\u6570\uff08\u9ed8\u8ba4\u503c\uff1a\u20181\u2019\uff09<\/li>\n<\/ul>\n<h2>6\u3001\u7ed3\u675f\u8bed<\/h2>\n<p>\u4ece\u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\u548c\u8868\u683c\u662f\u8bb8\u591a\u6570\u636e\u9a71\u52a8\u5e94\u7528\u7a0b\u5e8f\u4e2d\u7684\u57fa\u672c\u4efb\u52a1\u3002\u5728\u8fd9\u7bc7\u535a\u6587\u4e2d\uff0c\u6211\u4eec\u63a2\u7d22\u4e86\u5404\u79cd\u6709\u52a9\u4e8e\u4ece PDF \u4e2d\u63d0\u53d6\u6587\u672c\u548c\u8868\u683c\u7684 Python \u5305\u3002\u6211\u4eec\u4ecb\u7ecd\u4e86\u6587\u672c\u63d0\u53d6\u5305\uff0c\u5982 pytesseract\u3001PyMuPDF (Fitz) \u548c pdfplumber\u3002\u5bf9\u4e8e\u8868\u683c\u63d0\u53d6\uff0c\u6211\u4eec\u8ba8\u8bba\u4e86 Camelot \u548c Tabula\uff0c\u5b83\u4eec\u63d0\u4f9b\u4e86\u4ece PDF \u6587\u6863\u4e2d\u63d0\u53d6\u8868\u683c\u7684\u6709\u6548\u65b9\u6cd5\u3002<\/p>\n<p>\u901a\u8fc7\u5229\u7528\u8fd9\u4e9b\u5305\uff0c\u4f60\u53ef\u4ee5\u81ea\u52a8\u6267\u884c\u4ece PDF \u6587\u4ef6\u4e2d\u63d0\u53d6\u6709\u4ef7\u503c\u4fe1\u606f\u7684\u8fc7\u7a0b\uff0c\u4ece\u800c\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u5e76\u5b9e\u73b0\u5bf9\u975e\u7ed3\u6784\u5316\u6570\u636e\u7684\u66f4\u6df1\u5165\u5206\u6790\u3002<\/p>\n<hr>\n","protected":false},"excerpt":{"rendered":"<p>\u5728\u5f53\u4eca\u7684\u6570\u5b57\u65f6\u4ee3\uff0c\u4ece\u975e\u7ed3\u6784\u5316\u6570\u636e\u4e2d\u63d0\u53d6\u6709\u610f\u4e49\u7684\u4fe1\u606f\u5bf9\u4e8e\u5404\u79cd\u5e94\u7528\u81f3\u5173\u91cd\u8981\u3002\u4ece PDF \u7b49\u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\u548c\u8868\u683c\u5728\u6570\u636e\u5206\u6790\u3001\u4fe1\u606f\u68c0\u7d22\u548c\u81ea\u52a8\u5316\u4efb\u52a1\u4e2d\u53d1\u6325\u7740\u91cd\u8981\u4f5c\u7528\u3002 \u5728\u8fd9\u7bc7\u535a\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u6df1\u5165\u7814\u7a76 Python \u4e2d\u7684\u6587\u672c\u548c\u8868\u683c\u63d0\u53d6\u4e16\u754c\uff0c\u63a2\u7d22\u53ef\u4ee5\u7b80\u5316\u8fd9\u4e9b\u8fc7\u7a0b\u7684\u4e0d\u540c\u5305\u3002 0\u3001\u5149\u5b66\u5b57\u7b26\u8bc6\u522b (OCR) \u5728\u6df1\u5165\u7814\u7a76\u63d0\u53d6\u5305\u4e4b\u524d\uff0c\u8ba9\u6211\u4eec\u5148\u4e86\u89e3\u4e00\u4e0b\u5149\u5b66\u5b57\u7b26\u8bc6\u522b (OCR) \u7684\u57fa\u672c\u6982\u5ff5\u3002 OCR 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\u540e\u5904\u7406\uff1a\u5728\u6587\u672c\u8bc6\u522b\u6b65\u9aa4\u4e4b\u540e\uff0c\u53ef\u4ee5\u5e94\u7528\u5176\u4ed6\u540e\u5904\u7406\u6280\u672f\u6765\u7ec6\u5316\u8bc6\u522b\u7684\u6587\u672c\u3002\u8fd9\u53ef\u4ee5\u5305\u62ec\u8bed\u8a00\u5efa\u6a21\u3001\u62fc\u5199\u68c0\u67e5\u548c\u4e0a\u4e0b\u6587\u5206\u6790\uff0c\u4ee5\u63d0\u9ad8\u63d0\u53d6\u6587\u672c\u7684\u51c6\u786e\u6027\u548c\u8fde\u8d2f\u6027\u3002 \u6587\u672c\u63d0\u53d6\u5305 1\u3001Pytesseract Pytesseract \u662f\u4e00\u4e2a\u6d41\u884c\u7684 Python \u5e93\uff0c\u53ef\u7528\u4f5c Google \u7684 Tesseract OCR \u5f15\u64ce\u7684\u5305\u88c5\u5668\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u754c\u9762\u6765\u4ece\u56fe\u50cf\u548c\u626b\u63cf\u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\u3002\u5b83\u53ef\u4ee5\u8bfb\u53d6\u6240\u6709\u7c7b\u578b\u7684\u56fe\u50cf\uff0c\u5982 jpeg\u3001png\u3001gif\u3001bmp\u3001tiff \u7b49\u3002 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