{"id":1010608,"date":"2024-12-27T11:22:39","date_gmt":"2024-12-27T03:22:39","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1010608.html"},"modified":"2024-12-27T11:22:41","modified_gmt":"2024-12-27T03:22:41","slug":"python%e5%a6%82%e4%bd%95%e5%ae%9e%e7%8e%b0%e5%9b%be%e5%83%8f%e9%94%90%e5%8c%96","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1010608.html","title":{"rendered":"python\u5982\u4f55\u5b9e\u73b0\u56fe\u50cf\u9510\u5316"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25085049\/dc4236d8-af02-422d-a4fe-25651207c664.webp\" alt=\"python\u5982\u4f55\u5b9e\u73b0\u56fe\u50cf\u9510\u5316\" \/><\/p>\n<p><p> \u4e00\u3001\u56fe\u50cf\u9510\u5316\u6982\u8ff0<\/p>\n<\/p>\n<p><p><strong>\u56fe\u50cf\u9510\u5316\u662f\u56fe\u50cf\u5904\u7406\u4e2d\u7684\u4e00\u79cd\u6280\u672f\uff0c\u7528\u4e8e\u589e\u5f3a\u56fe\u50cf\u4e2d\u7684\u8fb9\u7f18\u7ec6\u8282\u3001\u63d0\u9ad8\u56fe\u50cf\u7684\u6e05\u6670\u5ea6\u548c\u5bf9\u6bd4\u5ea6\u3001\u6539\u5584\u89c6\u89c9\u611f\u53d7\u3002<\/strong>\u5176\u4e2d\u4e00\u79cd\u5e38\u7528\u7684\u65b9\u6cd5\u662f\u901a\u8fc7\u5377\u79ef\u64cd\u4f5c\u5b9e\u73b0\u7684\u3002\u5377\u79ef\u64cd\u4f5c\u901a\u8fc7\u5bf9\u56fe\u50cf\u5e94\u7528\u7279\u5b9a\u7684\u6ee4\u6ce2\u5668\u6765\u589e\u5f3a\u56fe\u50cf\u7684\u7ec6\u8282\u3002\u53ef\u4ee5\u4f7f\u7528Python\u4e2d\u7684OpenCV\u5e93\u6765\u5b9e\u73b0\u56fe\u50cf\u9510\u5316\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Python\u5b9e\u73b0\u56fe\u50cf\u9510\u5316\uff0c\u5e76\u63a2\u8ba8\u5b9e\u73b0\u8fc7\u7a0b\u4e2d\u6d89\u53ca\u7684\u5173\u952e\u6280\u672f\u3002<\/p>\n<\/p>\n<p><p>Python\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u7f16\u7a0b\u8bed\u8a00\uff0c\u5b83\u6709\u8bb8\u591a\u5e93\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u3002OpenCV\u662f\u5176\u4e2d\u6700\u6d41\u884c\u7684\u4e00\u4e2a\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u901a\u8fc7OpenCV\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u5bf9\u56fe\u50cf\u8fdb\u884c\u9510\u5316\u5904\u7406\u3002\u9510\u5316\u7684\u6838\u5fc3\u601d\u60f3\u662f\u901a\u8fc7\u5377\u79ef\u64cd\u4f5c\u6765\u589e\u5f3a\u56fe\u50cf\u7684\u8fb9\u7f18\u7ec6\u8282\u3002\u5377\u79ef\u64cd\u4f5c\u7684\u5173\u952e\u5728\u4e8e\u9009\u62e9\u5408\u9002\u7684\u6ee4\u6ce2\u5668\u6216\u5377\u79ef\u6838\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001\u56fe\u50cf\u9510\u5316\u7684\u57fa\u672c\u539f\u7406<\/p>\n<\/p>\n<ol>\n<li>\u9510\u5316\u6ee4\u6ce2\u5668<\/li>\n<\/ol>\n<p><p>\u56fe\u50cf\u9510\u5316\u4e3b\u8981\u4f9d\u8d56\u4e8e\u9510\u5316\u6ee4\u6ce2\u5668\u3002\u9510\u5316\u6ee4\u6ce2\u5668\u662f\u4e00\u79cd\u5377\u79ef\u6838\uff0c\u7528\u4e8e\u589e\u5f3a\u56fe\u50cf\u7684\u7ec6\u8282\u548c\u8fb9\u7f18\u3002\u5e38\u7528\u7684\u9510\u5316\u6ee4\u6ce2\u5668\u6709\u62c9\u666e\u62c9\u65af\u6ee4\u6ce2\u5668\u3001Sobel\u6ee4\u6ce2\u5668\u3001\u548cUnsharp Masking\uff08USM\uff09\u7b49\u3002\u8fd9\u4e9b\u6ee4\u6ce2\u5668\u901a\u8fc7\u5bf9\u56fe\u50cf\u8fdb\u884c\u5377\u79ef\u8fd0\u7b97\uff0c\u7a81\u51fa\u56fe\u50cf\u4e2d\u7684\u8fb9\u7f18\u3002<\/p>\n<\/p>\n<p><p>\u62c9\u666e\u62c9\u65af\u6ee4\u6ce2\u5668\u662f\u4e00\u79cd\u5e38\u7528\u7684\u4e8c\u9636\u5bfc\u6570\u6ee4\u6ce2\u5668\uff0c\u7528\u4e8e\u68c0\u6d4b\u56fe\u50cf\u4e2d\u7684\u8fb9\u7f18\u3002\u5b83\u901a\u8fc7\u8ba1\u7b97\u50cf\u7d20\u7684\u4e8c\u9636\u5bfc\u6570\u6765\u589e\u5f3a\u8fb9\u7f18\u3002Sobel\u6ee4\u6ce2\u5668\u662f\u4e00\u79cd\u4e00\u9636\u5bfc\u6570\u6ee4\u6ce2\u5668\uff0c\u901a\u5e38\u7528\u4e8e\u68c0\u6d4b\u6c34\u5e73\u548c\u5782\u76f4\u65b9\u5411\u7684\u8fb9\u7f18\u3002Unsharp Masking \u662f\u4e00\u79cd\u901a\u8fc7\u5c06\u6a21\u7cca\u56fe\u50cf\u4ece\u539f\u59cb\u56fe\u50cf\u4e2d\u51cf\u53bb\u6765\u589e\u5f3a\u56fe\u50cf\u7ec6\u8282\u7684\u6280\u672f\u3002<\/p>\n<\/p>\n<ol start=\"2\">\n<li>\u5377\u79ef\u64cd\u4f5c<\/li>\n<\/ol>\n<p><p>\u5377\u79ef\u662f\u56fe\u50cf\u5904\u7406\u4e2d\u7684\u4e00\u79cd\u91cd\u8981\u64cd\u4f5c\u3002\u5b83\u901a\u8fc7\u5728\u56fe\u50cf\u4e0a\u5e94\u7528\u5377\u79ef\u6838\u6765\u5b9e\u73b0\u6ee4\u6ce2\u5668\u7684\u6548\u679c\u3002\u5377\u79ef\u6838\u662f\u4e00\u4e2a\u5c0f\u77e9\u9635\uff0c\u5b83\u5728\u56fe\u50cf\u4e0a\u6ed1\u52a8\uff0c\u9010\u4e2a\u50cf\u7d20\u5730\u5e94\u7528\u6ee4\u6ce2\u5668\u3002\u901a\u8fc7\u5377\u79ef\u64cd\u4f5c\uff0c\u53ef\u4ee5\u5b9e\u73b0\u56fe\u50cf\u7684\u5e73\u6ed1\u3001\u9510\u5316\u3001\u8fb9\u7f18\u68c0\u6d4b\u7b49\u6548\u679c\u3002<\/p>\n<\/p>\n<p><p>\u5728\u56fe\u50cf\u9510\u5316\u4e2d\uff0c\u5377\u79ef\u64cd\u4f5c\u901a\u8fc7\u589e\u5f3a\u50cf\u7d20\u4e4b\u95f4\u7684\u5bf9\u6bd4\u5ea6\u6765\u7a81\u51fa\u8fb9\u7f18\u3002\u901a\u5e38\uff0c\u5377\u79ef\u6838\u7684\u4e2d\u5fc3\u5143\u7d20\u4e3a\u6b63\u503c\uff0c\u5468\u56f4\u5143\u7d20\u4e3a\u8d1f\u503c\uff0c\u8fd9\u6837\u53ef\u4ee5\u589e\u5f3a\u8fb9\u7f18\u7684\u5bf9\u6bd4\u5ea6\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u9510\u5316<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5OpenCV<\/li>\n<\/ol>\n<p><p>\u5728\u5f00\u59cb\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u9510\u5316\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5OpenCV\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u901a\u8fc7pip\u5b89\u88c5OpenCV\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install opencv-python<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728Python\u4e2d\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u3002<\/p>\n<\/p>\n<ol start=\"2\">\n<li>\u8bfb\u53d6\u548c\u663e\u793a\u56fe\u50cf<\/li>\n<\/ol>\n<p><p>\u5728\u8fdb\u884c\u56fe\u50cf\u9510\u5316\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u8bfb\u53d6\u56fe\u50cf\u5e76\u663e\u793a\u3002\u53ef\u4ee5\u4f7f\u7528OpenCV\u7684<code>cv2.imread()<\/code>\u51fd\u6570\u8bfb\u53d6\u56fe\u50cf\uff0c\u4f7f\u7528<code>cv2.imshow()<\/code>\u51fd\u6570\u663e\u793a\u56fe\u50cf\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import cv2<\/p>\n<h2><strong>\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n<p>image = cv2.imread(&#39;path_to_image.jpg&#39;)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imshow(&#39;Original Image&#39;, image)<\/p>\n<p>cv2.w<a href=\"https:\/\/docs.pingcode.com\/blog\/59162.html\" target=\"_blank\">AI<\/a>tKey(0)<\/p>\n<p>cv2.destroyAllWindows()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u5e94\u7528\u62c9\u666e\u62c9\u65af\u6ee4\u6ce2\u5668<\/li>\n<\/ol>\n<p><p>\u62c9\u666e\u62c9\u65af\u6ee4\u6ce2\u5668\u662f\u4e00\u79cd\u5e38\u7528\u7684\u9510\u5316\u6ee4\u6ce2\u5668\uff0c\u5b83\u53ef\u4ee5\u901a\u8fc7\u589e\u5f3a\u56fe\u50cf\u4e2d\u7684\u8fb9\u7f18\u6765\u63d0\u9ad8\u56fe\u50cf\u7684\u6e05\u6670\u5ea6\u3002\u53ef\u4ee5\u4f7f\u7528OpenCV\u7684<code>cv2.Laplacian()<\/code>\u51fd\u6570\u6765\u5e94\u7528\u62c9\u666e\u62c9\u65af\u6ee4\u6ce2\u5668\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5e94\u7528\u62c9\u666e\u62c9\u65af\u6ee4\u6ce2\u5668<\/p>\n<p>laplacian = cv2.Laplacian(image, cv2.CV_64F)<\/p>\n<h2><strong>\u663e\u793a\u9510\u5316\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imshow(&#39;Laplacian Sharpened Image&#39;, laplacian)<\/p>\n<p>cv2.waitKey(0)<\/p>\n<p>cv2.destroyAllWindows()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"4\">\n<li>\u5e94\u7528Sobel\u6ee4\u6ce2\u5668<\/li>\n<\/ol>\n<p><p>Sobel\u6ee4\u6ce2\u5668\u662f\u4e00\u79cd\u5e38\u7528\u7684\u8fb9\u7f18\u68c0\u6d4b\u6ee4\u6ce2\u5668\uff0c\u53ef\u4ee5\u7528\u4e8e\u56fe\u50cf\u9510\u5316\u3002\u53ef\u4ee5\u4f7f\u7528OpenCV\u7684<code>cv2.Sobel()<\/code>\u51fd\u6570\u6765\u5e94\u7528Sobel\u6ee4\u6ce2\u5668\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5e94\u7528Sobel\u6ee4\u6ce2\u5668<\/p>\n<p>sobel_x = cv2.Sobel(image, cv2.CV_64F, 1, 0, ksize=3)<\/p>\n<p>sobel_y = cv2.Sobel(image, cv2.CV_64F, 0, 1, ksize=3)<\/p>\n<p>sobel = cv2.addWeighted(sobel_x, 0.5, sobel_y, 0.5, 0)<\/p>\n<h2><strong>\u663e\u793a\u9510\u5316\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imshow(&#39;Sobel Sharpened Image&#39;, sobel)<\/p>\n<p>cv2.waitKey(0)<\/p>\n<p>cv2.destroyAllWindows()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"5\">\n<li>\u5e94\u7528Unsharp Masking<\/li>\n<\/ol>\n<p><p>Unsharp Masking \u662f\u4e00\u79cd\u901a\u8fc7\u6a21\u7cca\u56fe\u50cf\u589e\u5f3a\u7ec6\u8282\u7684\u6280\u672f\u3002\u53ef\u4ee5\u901a\u8fc7\u5c06\u6a21\u7cca\u56fe\u50cf\u4ece\u539f\u59cb\u56fe\u50cf\u4e2d\u51cf\u53bb\u6765\u5b9e\u73b0Unsharp Masking\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6a21\u7cca\u56fe\u50cf<\/p>\n<p>blurred = cv2.GaussianBlur(image, (9, 9), 10)<\/p>\n<h2><strong>Unsharp Masking<\/strong><\/h2>\n<p>unsharp_mask = cv2.addWeighted(image, 1.5, blurred, -0.5, 0)<\/p>\n<h2><strong>\u663e\u793a\u9510\u5316\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imshow(&#39;Unsharp Masking Image&#39;, unsharp_mask)<\/p>\n<p>cv2.waitKey(0)<\/p>\n<p>cv2.destroyAllWindows()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u56db\u3001\u56fe\u50cf\u9510\u5316\u7684\u5e94\u7528\u573a\u666f<\/p>\n<\/p>\n<ol>\n<li>\u533b\u5b66\u5f71\u50cf\u5904\u7406<\/li>\n<\/ol>\n<p><p>\u5728\u533b\u5b66\u5f71\u50cf\u4e2d\uff0c\u56fe\u50cf\u9510\u5316\u53ef\u4ee5\u7528\u4e8e\u589e\u5f3a\u75c5\u53d8\u533a\u57df\u7684\u7ec6\u8282\uff0c\u5e2e\u52a9\u533b\u751f\u66f4\u51c6\u786e\u5730\u8bca\u65ad\u75c5\u60c5\u3002\u901a\u8fc7\u56fe\u50cf\u9510\u5316\uff0c\u53ef\u4ee5\u63d0\u9ad8\u533b\u5b66\u5f71\u50cf\u7684\u5bf9\u6bd4\u5ea6\u548c\u6e05\u6670\u5ea6\uff0c\u4f7f\u5f97\u75c5\u53d8\u533a\u57df\u66f4\u52a0\u660e\u663e\u3002<\/p>\n<\/p>\n<ol start=\"2\">\n<li>\u8ba1\u7b97\u673a\u89c6\u89c9<\/li>\n<\/ol>\n<p><p>\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u4e2d\uff0c\u56fe\u50cf\u9510\u5316\u53ef\u4ee5\u7528\u4e8e\u589e\u5f3a\u56fe\u50cf\u7279\u5f81\uff0c\u5e2e\u52a9\u8ba1\u7b97\u673a\u66f4\u597d\u5730\u8bc6\u522b\u548c\u5206\u7c7b\u56fe\u50cf\u3002\u901a\u8fc7\u56fe\u50cf\u9510\u5316\uff0c\u53ef\u4ee5\u63d0\u9ad8\u56fe\u50cf\u7684\u8fb9\u7f18\u7ec6\u8282\uff0c\u4f7f\u5f97\u8ba1\u7b97\u673a\u89c6\u89c9\u7b97\u6cd5\u80fd\u591f\u66f4\u51c6\u786e\u5730\u63d0\u53d6\u7279\u5f81\u3002<\/p>\n<\/p>\n<ol start=\"3\">\n<li>\u6444\u5f71\u548c\u56fe\u50cf\u7f16\u8f91<\/li>\n<\/ol>\n<p><p>\u5728\u6444\u5f71\u548c\u56fe\u50cf\u7f16\u8f91\u4e2d\uff0c\u56fe\u50cf\u9510\u5316\u53ef\u4ee5\u7528\u4e8e\u63d0\u9ad8\u56fe\u50cf\u7684\u6e05\u6670\u5ea6\u548c\u89c6\u89c9\u6548\u679c\u3002\u901a\u8fc7\u56fe\u50cf\u9510\u5316\uff0c\u53ef\u4ee5\u589e\u5f3a\u7167\u7247\u7684\u7ec6\u8282\u548c\u5bf9\u6bd4\u5ea6\uff0c\u4f7f\u5f97\u7167\u7247\u66f4\u52a0\u751f\u52a8\u548c\u5438\u5f15\u4eba\u3002<\/p>\n<\/p>\n<p><p>\u4e94\u3001\u603b\u7ed3<\/p>\n<\/p>\n<p><p>\u56fe\u50cf\u9510\u5316\u662f\u56fe\u50cf\u5904\u7406\u4e2d\u7684\u4e00\u79cd\u91cd\u8981\u6280\u672f\uff0c\u53ef\u4ee5\u7528\u4e8e\u589e\u5f3a\u56fe\u50cf\u7684\u7ec6\u8282\u548c\u8fb9\u7f18\uff0c\u63d0\u9ad8\u56fe\u50cf\u7684\u6e05\u6670\u5ea6\u548c\u5bf9\u6bd4\u5ea6\u3002\u901a\u8fc7\u4f7f\u7528Python\u4e2d\u7684OpenCV\u5e93\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5b9e\u73b0\u56fe\u50cf\u9510\u5316\u3002\u672c\u6587\u4ecb\u7ecd\u4e86\u56fe\u50cf\u9510\u5316\u7684\u57fa\u672c\u539f\u7406\u3001\u5e38\u7528\u7684\u9510\u5316\u6ee4\u6ce2\u5668\u3001\u4ee5\u53ca\u5982\u4f55\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u9510\u5316\u3002\u6b64\u5916\uff0c\u8fd8\u4ecb\u7ecd\u4e86\u56fe\u50cf\u9510\u5316\u5728\u533b\u5b66\u5f71\u50cf\u5904\u7406\u3001\u8ba1\u7b97\u673a\u89c6\u89c9\u3001\u6444\u5f71\u548c\u56fe\u50cf\u7f16\u8f91\u4e2d\u7684\u5e94\u7528\u3002\u901a\u8fc7\u638c\u63e1\u56fe\u50cf\u9510\u5316\u6280\u672f\uff0c\u53ef\u4ee5\u5728\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\u4e2d\u83b7\u5f97\u66f4\u597d\u7684\u6548\u679c\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u56fe\u50cf\u9510\u5316\u7684\u57fa\u672c\u6982\u5ff5\u662f\u4ec0\u4e48\uff1f<\/strong><br \/>\u56fe\u50cf\u9510\u5316\u662f\u4e00\u79cd\u56fe\u50cf\u5904\u7406\u6280\u672f\uff0c\u7528\u4e8e\u589e\u5f3a\u56fe\u50cf\u7684\u8fb9\u7f18\u548c\u7ec6\u8282\uff0c\u4f7f\u56fe\u50cf\u770b\u8d77\u6765\u66f4\u52a0\u6e05\u6670\u3002\u901a\u8fc7\u589e\u52a0\u5bf9\u6bd4\u5ea6\u548c\u7ec6\u8282\uff0c\u9510\u5316\u53ef\u4ee5\u6539\u5584\u89c6\u89c9\u6548\u679c\uff0c\u5e2e\u52a9\u89c2\u4f17\u66f4\u597d\u5730\u8bc6\u522b\u56fe\u50cf\u4e2d\u7684\u5bf9\u8c61\u3002\u5e38\u7528\u7684\u9510\u5316\u6280\u672f\u5305\u62ec\u62c9\u666e\u62c9\u65af\u7b97\u5b50\u3001\u9ad8\u901a\u6ee4\u6ce2\u7b49\u3002<\/p>\n<p><strong>\u4f7f\u7528Python\u8fdb\u884c\u56fe\u50cf\u9510\u5316\u6709\u54ea\u4e9b\u5e38\u7528\u5e93\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u5e38\u7528\u7684\u56fe\u50cf\u5904\u7406\u5e93\u5305\u62ecPIL\uff08Pillow\uff09\u3001OpenCV\u548cscikit-image\u3002Pillow\u63d0\u4f9b\u4e86\u7b80\u5355\u6613\u7528\u7684\u63a5\u53e3\uff0c\u9002\u5408\u57fa\u672c\u7684\u56fe\u50cf\u5904\u7406\u4efb\u52a1\uff1bOpenCV\u5219\u529f\u80fd\u5f3a\u5927\uff0c\u9002\u5408\u590d\u6742\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\uff1b\u800cscikit-image\u5219\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u7b97\u6cd5\u548c\u5de5\u5177\uff0c\u4e13\u6ce8\u4e8e\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n<p><strong>\u5728Python\u4e2d\u5982\u4f55\u5b9e\u73b0\u56fe\u50cf\u9510\u5316\uff1f<\/strong><br \/>\u53ef\u4ee5\u901a\u8fc7\u5e94\u7528\u5377\u79ef\u6ee4\u6ce2\u5668\u6765\u5b9e\u73b0\u56fe\u50cf\u9510\u5316\u3002\u5e38\u89c1\u7684\u65b9\u6cd5\u662f\u4f7f\u7528\u4e00\u4e2a\u9510\u5316\u6838\uff08\u5982\u62c9\u666e\u62c9\u65af\u7b97\u5b50\uff09\uff0c\u901a\u8fc7numpy\u5e93\u8fdb\u884c\u5377\u79ef\u64cd\u4f5c\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<pre><code class=\"language-python\">import cv2\nimport numpy as np\n\n# \u8bfb\u53d6\u56fe\u50cf\nimage = cv2.imread(&#39;image.jpg&#39;)\n\n# \u5b9a\u4e49\u9510\u5316\u5185\u6838\nsharpening_filter = np.array([[0, -1, 0],\n                              [-1, 5, -1],\n                              [0, -1, 0]])\n\n# \u5e94\u7528\u5377\u79ef\nsharpened_image = cv2.filter2D(image, -1, sharpening_filter)\n\n# \u663e\u793a\u7ed3\u679c\ncv2.imshow(&#39;Original Image&#39;, image)\ncv2.imshow(&#39;Sharpened Image&#39;, sharpened_image)\ncv2.waitKey(0)\ncv2.destroyAllWindows()\n<\/code><\/pre>\n<p>\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u7b80\u5355\u5730\u5c06\u9510\u5316\u6548\u679c\u5e94\u7528\u4e8e\u56fe\u50cf\uff0c\u63d0\u5347\u5176\u6e05\u6670\u5ea6\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u4e00\u3001\u56fe\u50cf\u9510\u5316\u6982\u8ff0 \u56fe\u50cf\u9510\u5316\u662f\u56fe\u50cf\u5904\u7406\u4e2d\u7684\u4e00\u79cd\u6280\u672f\uff0c\u7528\u4e8e\u589e\u5f3a\u56fe\u50cf\u4e2d\u7684\u8fb9\u7f18\u7ec6\u8282\u3001\u63d0\u9ad8\u56fe\u50cf\u7684\u6e05\u6670\u5ea6\u548c\u5bf9\u6bd4\u5ea6\u3001\u6539\u5584\u89c6\u89c9 [&hellip;]","protected":false},"author":3,"featured_media":1010616,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1010608"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1010608"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1010608\/revisions"}],"predecessor-version":[{"id":1010618,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1010608\/revisions\/1010618"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1010616"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1010608"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1010608"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1010608"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}