{"id":948060,"date":"2024-12-27T00:00:10","date_gmt":"2024-12-26T16:00:10","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/948060.html"},"modified":"2024-12-27T00:00:11","modified_gmt":"2024-12-26T16:00:11","slug":"python-%e5%a6%82%e4%bd%95%e4%b8%a2%e5%bc%83%e5%83%8f%e7%b4%a0","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/948060.html","title":{"rendered":"python \u5982\u4f55\u4e22\u5f03\u50cf\u7d20"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25083555\/e86f17fb-6943-401c-88a4-bba6131c8a99.webp\" alt=\"python \u5982\u4f55\u4e22\u5f03\u50cf\u7d20\" \/><\/p>\n<p><p> <strong>\u5728Python\u4e2d\u4e22\u5f03\u50cf\u7d20\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff0c\u5982\u4f7f\u7528\u56fe\u50cf\u5904\u7406\u5e93\u3001\u8c03\u6574\u56fe\u50cf\u5927\u5c0f\u3001\u4fee\u6539\u50cf\u7d20\u503c\u7b49\u3002\u5177\u4f53\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528OpenCV\u8fdb\u884c\u50cf\u7d20\u5904\u7406\u3001\u901a\u8fc7PIL\u5e93\u4fee\u6539\u56fe\u50cf\u3001\u5229\u7528NumPy\u6570\u7ec4\u64cd\u4f5c\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u4e22\u5f03\u50cf\u7d20\uff0c\u5e76\u4ee5OpenCV\u4e3a\u4f8b\u8fdb\u884c\u8be6\u7ec6\u63cf\u8ff0\u3002<\/strong><\/p>\n<\/p>\n<p><p>\u4e00\u3001\u4f7f\u7528OPENCV\u8fdb\u884c\u50cf\u7d20\u5904\u7406<\/p>\n<\/p>\n<p><p>OpenCV\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u5728Python\u4e2d\uff0cOpenCV\u7684\u4f7f\u7528\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8f7b\u677e\u5730\u5bf9\u56fe\u50cf\u8fdb\u884c\u50cf\u7d20\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u8bfb\u53d6\u4e0e\u663e\u793a\u56fe\u50cf<\/strong><\/p>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u8bfb\u53d6\u56fe\u50cf\u5e76\u663e\u793a\u3002OpenCV\u63d0\u4f9b\u4e86<code>cv2.imread()<\/code>\u51fd\u6570\u6765\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\uff0c\u800c<code>cv2.imshow()<\/code>\u51fd\u6570\u5219\u7528\u4e8e\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;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<\/li>\n<li>\n<p><strong>\u8c03\u6574\u56fe\u50cf\u5927\u5c0f<\/strong><\/p>\n<\/p>\n<p><p>\u8c03\u6574\u56fe\u50cf\u5927\u5c0f\u662f\u4e22\u5f03\u50cf\u7d20\u7684\u5e38\u89c1\u65b9\u6cd5\u4e4b\u4e00\u3002OpenCV\u7684<code>cv2.resize()<\/code>\u51fd\u6570\u53ef\u4ee5\u6539\u53d8\u56fe\u50cf\u7684\u5c3a\u5bf8\uff0c\u4ece\u800c\u4e22\u5f03\u591a\u4f59\u7684\u50cf\u7d20\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8c03\u6574\u56fe\u50cf\u5927\u5c0f<\/p>\n<p>resized_image = cv2.resize(image, (new_width, new_height))<\/p>\n<h2><strong>\u663e\u793a\u8c03\u6574\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imshow(&#39;Resized Image&#39;, resized_image)<\/p>\n<p>cv2.waitKey(0)<\/p>\n<p>cv2.destroyAllWindows()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u8bbe\u7f6e\u65b0\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6\uff0c\u53ef\u4ee5\u6709\u6548\u5730\u4e22\u5f03\u4e0d\u9700\u8981\u7684\u50cf\u7d20\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u50cf\u7d20\u5316\u5904\u7406<\/strong><\/p>\n<\/p>\n<p><p>\u50cf\u7d20\u5316\u5904\u7406\u662f\u901a\u8fc7\u964d\u4f4e\u56fe\u50cf\u7684\u5206\u8fa8\u7387\u6765\u8fbe\u5230\u4e22\u5f03\u50cf\u7d20\u7684\u6548\u679c\u3002\u53ef\u4ee5\u901a\u8fc7\u7f29\u5c0f\u56fe\u50cf\u7136\u540e\u653e\u5927\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u7f29\u5c0f\u56fe\u50cf<\/p>\n<p>small_image = cv2.resize(image, (small_width, small_height), interpolation=cv2.INTER_LINEAR)<\/p>\n<h2><strong>\u653e\u5927\u56fe\u50cf<\/strong><\/h2>\n<p>pixelated_image = cv2.resize(small_image, (image.shape[1], image.shape[0]), interpolation=cv2.INTER_NEAREST)<\/p>\n<h2><strong>\u663e\u793a\u50cf\u7d20\u5316\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imshow(&#39;Pixelated Image&#39;, pixelated_image)<\/p>\n<p>cv2.waitKey(0)<\/p>\n<p>cv2.destroyAllWindows()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5728\u964d\u4f4e\u56fe\u50cf\u7ec6\u8282\u7684\u540c\u65f6\u4e22\u5f03\u591a\u4f59\u7684\u50cf\u7d20\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n<p><p>\u4e8c\u3001\u901a\u8fc7PIL\u5e93\u4fee\u6539\u56fe\u50cf<\/p>\n<\/p>\n<p><p>PIL\uff08Pillow\uff09\u662fPython\u7684\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u63d0\u4f9b\u4e86\u7b80\u5355\u6613\u7528\u7684\u63a5\u53e3\u6765\u5bf9\u56fe\u50cf\u8fdb\u884c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u8bfb\u53d6\u4e0e\u663e\u793a\u56fe\u50cf<\/strong><\/p>\n<\/p>\n<p><p>\u4f7f\u7528PIL\u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7<code>Image.open()<\/code>\u51fd\u6570\u6765\u8bfb\u53d6\u56fe\u50cf\uff0c\u5e76\u901a\u8fc7<code>show()<\/code>\u65b9\u6cd5\u6765\u663e\u793a\u56fe\u50cf\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from PIL import Image<\/p>\n<h2><strong>\u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n<p>image = Image.open(&#39;image.jpg&#39;)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n<p>image.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u8c03\u6574\u56fe\u50cf\u5927\u5c0f<\/strong><\/p>\n<\/p>\n<p><p>PIL\u5e93\u63d0\u4f9b\u4e86<code>resize()<\/code>\u65b9\u6cd5\u6765\u8c03\u6574\u56fe\u50cf\u5927\u5c0f\uff0c\u8fd9\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u4e22\u5f03\u591a\u4f59\u7684\u50cf\u7d20\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8c03\u6574\u56fe\u50cf\u5927\u5c0f<\/p>\n<p>resized_image = image.resize((new_width, new_height))<\/p>\n<h2><strong>\u663e\u793a\u8c03\u6574\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>resized_image.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u50cf\u7d20\u5316\u5904\u7406<\/strong><\/p>\n<\/p>\n<p><p>\u4e0eOpenCV\u7c7b\u4f3c\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u7f29\u5c0f\u7136\u540e\u653e\u5927\u56fe\u50cf\u6765\u5b9e\u73b0\u50cf\u7d20\u5316\u5904\u7406\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u7f29\u5c0f\u56fe\u50cf<\/p>\n<p>small_image = image.resize((small_width, small_height), Image.LINEAR)<\/p>\n<h2><strong>\u653e\u5927\u56fe\u50cf<\/strong><\/h2>\n<p>pixelated_image = small_image.resize(image.size, Image.NEAREST)<\/p>\n<h2><strong>\u663e\u793a\u50cf\u7d20\u5316\u56fe\u50cf<\/strong><\/h2>\n<p>pixelated_image.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n<p><p>\u4e09\u3001\u5229\u7528NUMPY\u6570\u7ec4\u64cd\u4f5c<\/p>\n<\/p>\n<p><p>NumPy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u7ec4\u5904\u7406\u5e93\uff0c\u53ef\u4ee5\u76f4\u63a5\u5bf9\u56fe\u50cf\u7684\u50cf\u7d20\u8fdb\u884c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u8bfb\u53d6\u56fe\u50cf\u5e76\u8f6c\u6362\u4e3a\u6570\u7ec4<\/strong><\/p>\n<\/p>\n<p><p>\u4f7f\u7528OpenCV\u8bfb\u53d6\u56fe\u50cf\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u5176\u8f6c\u6362\u4e3aNumPy\u6570\u7ec4\uff0c\u4ee5\u4fbf\u8fdb\u884c\u50cf\u7d20\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import cv2<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u8bfb\u53d6\u56fe\u50cf\u5e76\u8f6c\u6362\u4e3a\u6570\u7ec4<\/strong><\/h2>\n<p>image = cv2.imread(&#39;image.jpg&#39;)<\/p>\n<p>image_array = np.array(image)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u4fee\u6539\u50cf\u7d20\u503c<\/strong><\/p>\n<\/p>\n<p><p>\u901a\u8fc7NumPy\u6570\u7ec4\uff0c\u6211\u4eec\u53ef\u4ee5\u76f4\u63a5\u4fee\u6539\u56fe\u50cf\u7684\u50cf\u7d20\u503c\uff0c\u4ee5\u8fbe\u5230\u4e22\u5f03\u50cf\u7d20\u7684\u6548\u679c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5c06\u56fe\u50cf\u4e2d\u7684\u67d0\u4e9b\u50cf\u7d20\u8bbe\u4e3a\u9ed1\u8272<\/p>\n<p>image_array[100:200, 100:200] = [0, 0, 0]<\/p>\n<h2><strong>\u663e\u793a\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>modified_image = cv2.cvtColor(image_array, cv2.COLOR_BGR2RGB)<\/p>\n<p>cv2.imshow(&#39;Modified Image&#39;, modified_image)<\/p>\n<p>cv2.waitKey(0)<\/p>\n<p>cv2.destroyAllWindows()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u968f\u673a\u4e22\u5f03\u50cf\u7d20<\/strong><\/p>\n<\/p>\n<p><p>\u6211\u4eec\u8fd8\u53ef\u4ee5\u901a\u8fc7\u968f\u673a\u9009\u62e9\u50cf\u7d20\u5e76\u4fee\u6539\u5176\u503c\u6765\u5b9e\u73b0\u968f\u673a\u4e22\u5f03\u50cf\u7d20\u7684\u6548\u679c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u63a9\u7801<\/p>\n<p>mask = np.random.choice([0, 1], size=image_array.shape[:2], p=[0.1, 0.9])<\/p>\n<h2><strong>\u5c06\u63a9\u7801\u5e94\u7528\u4e8e\u56fe\u50cf<\/strong><\/h2>\n<p>image_array[mask == 0] = [0, 0, 0]<\/p>\n<h2><strong>\u663e\u793a\u968f\u673a\u4e22\u5f03\u50cf\u7d20\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>random_discard_image = cv2.cvtColor(image_array, cv2.COLOR_BGR2RGB)<\/p>\n<p>cv2.imshow(&#39;Random Discard Image&#39;, random_discard_image)<\/p>\n<p>cv2.waitKey(0)<\/p>\n<p>cv2.destroyAllWindows()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u7075\u6d3b\u5730\u4e22\u5f03\u56fe\u50cf\u4e2d\u7684\u50cf\u7d20\u3002\u65e0\u8bba\u662f\u4f7f\u7528OpenCV\u3001PIL\u8fd8\u662fNumPy\uff0c\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\uff0c\u9009\u62e9\u9002\u5408\u81ea\u5df1\u7684\u65b9\u6cd5\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u4e22\u5f03\u56fe\u50cf\u4e2d\u7684\u7279\u5b9a\u50cf\u7d20\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528PIL\uff08Python Imaging Library\uff09\u6216OpenCV\u5e93\u6765\u5904\u7406\u56fe\u50cf\u3002\u5982\u679c\u60a8\u60f3\u4e22\u5f03\u7279\u5b9a\u7684\u50cf\u7d20\uff0c\u53ef\u4ee5\u901a\u8fc7\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u56fe\u50cf\u5e76\u590d\u5236\u60a8\u60f3\u8981\u4fdd\u7559\u7684\u50cf\u7d20\u6765\u5b9e\u73b0\u3002\u5177\u4f53\u6b65\u9aa4\u5305\u62ec\u52a0\u8f7d\u56fe\u50cf\u3001\u904d\u5386\u50cf\u7d20\u5e76\u6839\u636e\u6761\u4ef6\u9009\u62e9\u6027\u5730\u6dfb\u52a0\u5230\u65b0\u56fe\u50cf\u4e2d\u3002<\/p>\n<p><strong>\u6709\u54ea\u4e9b\u5e93\u53ef\u4ee5\u7528\u4e8e\u4e22\u5f03\u56fe\u50cf\u4e2d\u7684\u50cf\u7d20\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u6700\u5e38\u7528\u7684\u5e93\u5305\u62ecPIL\uff08Pillow\uff09\u548cOpenCV\u3002Pillow\u662f\u4e00\u4e2a\u53cb\u597d\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u9002\u5408\u7b80\u5355\u7684\u56fe\u50cf\u64cd\u4f5c\uff1b\u800cOpenCV\u5219\u63d0\u4f9b\u4e86\u66f4\u4e3a\u9ad8\u7ea7\u7684\u529f\u80fd\uff0c\u9002\u5408\u590d\u6742\u7684\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u3002\u6839\u636e\u60a8\u7684\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\uff0c\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u4e22\u5f03\u4e0d\u9700\u8981\u7684\u50cf\u7d20\u3002<\/p>\n<p><strong>\u4e22\u5f03\u50cf\u7d20\u540e\u5982\u4f55\u4fdd\u5b58\u5904\u7406\u540e\u7684\u56fe\u50cf\uff1f<\/strong><br \/>\u5728\u5904\u7406\u5b8c\u56fe\u50cf\u5e76\u4e22\u5f03\u4e86\u4e0d\u9700\u8981\u7684\u50cf\u7d20\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528PIL\u4e2d\u7684<code>save()<\/code>\u65b9\u6cd5\u6216OpenCV\u4e2d\u7684<code>imwrite()<\/code>\u51fd\u6570\u5c06\u5904\u7406\u540e\u7684\u56fe\u50cf\u4fdd\u5b58\u5230\u6587\u4ef6\u3002\u786e\u4fdd\u5728\u4fdd\u5b58\u65f6\u9009\u62e9\u9002\u5f53\u7684\u6587\u4ef6\u683c\u5f0f\uff0c\u4f8b\u5982JPEG\u6216PNG\uff0c\u4ee5\u4fbf\u4e8e\u540e\u7eed\u4f7f\u7528\u548c\u5206\u4eab\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u4e22\u5f03\u50cf\u7d20\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff0c\u5982\u4f7f\u7528\u56fe\u50cf\u5904\u7406\u5e93\u3001\u8c03\u6574\u56fe\u50cf\u5927\u5c0f\u3001\u4fee\u6539\u50cf\u7d20\u503c\u7b49\u3002\u5177\u4f53\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528 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