{"id":1119,"date":"2026-07-02T06:24:54","date_gmt":"2026-07-02T06:24:54","guid":{"rendered":"https:\/\/blog.nimail.cn\/?p=1119"},"modified":"2026-07-02T06:24:54","modified_gmt":"2026-07-02T06:24:54","slug":"%e5%91%8a%e5%88%ab%e6%89%8b%e5%8a%a8%e5%bd%95%e5%85%a5-%e5%9b%be%e7%89%87%e8%bd%acexcel%e9%ab%98%e6%95%88%e6%96%b9%e6%a1%88%e5%85%a8%e8%a7%a3%e6%9e%90","status":"publish","type":"post","link":"https:\/\/blog.nimail.cn\/best-articles\/%e5%91%8a%e5%88%ab%e6%89%8b%e5%8a%a8%e5%bd%95%e5%85%a5-%e5%9b%be%e7%89%87%e8%bd%acexcel%e9%ab%98%e6%95%88%e6%96%b9%e6%a1%88%e5%85%a8%e8%a7%a3%e6%9e%90\/","title":{"rendered":"\u544a\u522b\u624b\u52a8\u5f55\u5165\uff01\u56fe\u7247\u8f6cExcel\u9ad8\u6548\u65b9\u6848\u5168\u89e3\u6790"},"content":{"rendered":"<h2 class=\"mt-4 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class=\"table table-bordered table-hover w-100 bg-white rounded mb-4\" style=\"width:100%;max-width:100%;\">\n<thead class=\"table-dark\">\n<tr>\n<th>\u5904\u7406\u73af\u8282<\/th>\n<th>\u4f20\u7edf\u4eba\u5de5\u65b9\u5f0f<\/th>\n<th>\u667a\u80fd\u8bc6\u522b\u65b9\u6848<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u884c\u5217\u5bf9\u9f50<\/td>\n<td>\u8017\u65f6\u6781\u957f\uff0c\u6613\u9519\u4f4d<\/td>\n<td><span class=\"badge bg-success\">\u81ea\u52a8\u5438\u9644<\/span> \u6beb\u79d2\u7ea7\u5b8c\u6210<\/td>\n<\/tr>\n<tr>\n<td>\u590d\u6742\u8868\u5934<\/td>\n<td>\u9700\u624b\u52a8\u5408\u5e76\u5355\u5143\u683c<\/td>\n<td><span class=\"badge bg-primary\">\u667a\u80fd\u89e3\u6790<\/span> \u4fdd\u7559\u539f\u59cb\u5c42\u7ea7<\/td>\n<\/tr>\n<tr>\n<td>\u6279\u91cf\u6548\u7387<\/td>\n<td>\u5355\u65e5\u4e0a\u965050\u5f20<\/td>\n<td><span class=\"badge bg-info\">\u5e76\u53d1\u5904\u7406<\/span> \u8f7b\u677e\u4e0a\u5343\u5f20<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u5f53\u7136\uff0c\u5982\u679c\u4f60\u662f\u91cd\u5ea6\u6280\u672f\u7528\u6237\uff0c\u5b8c\u5168\u53ef\u4ee5\u7528\u811a\u672c\u63a5\u7ba1\u6574\u4e2a\u6d41\u7a0b\u3002\u4e0b\u9762\u8fd9\u6bb5\u57fa\u4e8ePython\u7684\u7b80\u6613\u5b9e\u73b0\uff0c\u5c55\u793a\u4e86\u5982\u4f55\u8c03\u7528\u7b2c\u4e09\u65b9\u5e93\u5b8c\u6210<strong>\u56fe\u7247\u751f\u6210\u8868\u683c<\/strong>\u7684\u6838\u5fc3\u52a8\u4f5c\u3002\u867d\u7136\u751f\u4ea7\u73af\u5883\u9700\u8981\u52a0\u9519\u8bef\u91cd\u8bd5\u548c\u7cbe\u5ea6\u6821\u9a8c\uff0c\u4f46\u8dd1\u901a\u57fa\u7840\u94fe\u8def\u53ea\u9700\u8981\u8fd9\u51e0\u884c\u4ee3\u7801\uff1a<\/p>\n<div class=\"card shadow-sm mb-4\">\n<div class=\"card-body p-3\">\n<pre class=\"bg-light p-3 rounded w-100 mb-0\" style=\"width:100%;max-width:100%;\"><code class=\"language-python\"># \u4f9d\u8d56\u5b89\u88c5\uff1apip install ddddocr pandas openpyxl\nimport ddddocr\nimport pandas as pd\nfrom PIL import Image\nimport io\n\ndef extract_table_from_image(image_path):\n    # \u521d\u59cb\u5316OCR\u5f15\u64ce\n    ocr = ddddocr.DdddOcr(show_ad=False)\n    with open(image_path, 'rb') as f:\n        img_bytes = f.read()\n    \n    # \u83b7\u53d6\u8bc6\u522b\u7ed3\u679c\uff08\u7b80\u5316\u7248\uff0c\u5b9e\u9645\u9700\u7ed3\u5408\u5750\u6807\u805a\u7c7b\u7b97\u6cd5\u91cd\u6784\u8868\u683c\uff09\n    result = ocr.table_recognition(img_bytes)\n    return result\n\n# \u5bfc\u51fa\u4e3axlsx\nif __name__ == '__main__':\n    df = pd.DataFrame(extract_table_from_image('data.jpg'))\n    df.to_excel('output.xlsx', index=False)\n    print(\"\u2705 jpg\u8f6cexcel \u6210\u529f\")<\/code><\/pre>\n<\/p><\/div>\n<\/div>\n<p>\u8fd9\u5957\u903b\u8f91\u8dd1\u901a\u540e\uff0c\u4f60\u4f1a\u53d1\u73b0<strong>\u600e\u4e48\u628a\u56fe\u7247\u8f6c\u6210excel<\/strong>\u6839\u672c\u4e0d\u662f\u6280\u672f\u74f6\u9888\uff0c\u800c\u662f\u5de5\u4f5c\u6d41\u8bbe\u8ba1\u95ee\u9898\u3002\u65e0\u8bba\u662f\u5904\u7406\u65e5\u5e38\u62a5\u9500\u5355\u91cc\u7684<strong>\u56fe\u7247\u8f6c\u8868\u683c\u514d\u8d39<\/strong>\u9700\u6c42\uff0c\u8fd8\u662f\u5e94\u5bf9\u7d27\u6025\u7684<strong>\u8868\u683c\u63d0\u53d6<\/strong>\u4efb\u52a1\uff0c\u63d0\u524d\u642d\u597d\u6846\u67b6\u603b\u6bd4\u4e34\u65f6\u6293\u778e\u5f3a\u3002\u73b0\u5728\u5f88\u591a<strong>\u56fe\u7247\u63d0\u53d6\u8868\u683c<\/strong>\u670d\u52a1\u90fd\u5728\u5377\u8bc6\u522b\u7387\uff0c\u9009\u4e00\u4e2a\u54cd\u5e94\u5feb\u3001\u6392\u7248\u8fd8\u539f\u5ea6\u9ad8\u7684\u5e73\u53f0\uff0c\u76f4\u63a5\u62d6\u62fd\u4e0a\u4f20\u5c31\u80fd\u62ff\u5230\u5e72\u51c0\u7684\u6570\u636e\u6e90\u3002\u9047\u5230\u5e26\u6c34\u5370\u6216\u6a21\u7cca\u7684<strong>\u56fe\u7247\u8868\u683c\u8f6c\u6362excel<\/strong>\u539f\u56fe\uff0c\u8bb0\u5f97\u5148\u7528\u4fee\u56fe\u8f6f\u4ef6\u62c9\u9ad8\u5bf9\u6bd4\u5ea6\uff0c\u8bc6\u522b\u6548\u679c\u4f1a\u76f4\u7ebf\u4e0a\u5347\u3002\u641e\u5b9a<strong>\u56fe\u7247\u8f6c\u6362\u6210excel<\/strong>\u540e\uff0c\u76f4\u63a5\u4e0b\u8f7d\u5373\u53ef\u3002\u5bf9\u4e8e\u4e60\u60ef\u7528\u547d\u4ee4\u884c\u7684\u5927\u4f6c\uff0c\u5199\u4e2a\u722c\u866b\u914d\u5408<strong>\u56fe\u7247\u8f6c\u8868\u683c<\/strong>\u63a5\u53e3\uff0c\u751a\u81f3\u80fd\u5b9e\u73b0\u5b9a\u65f6\u540c\u6b65\u3002\u6bd5\u7adf<strong>jpg to 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