{"id":979016,"date":"2024-12-27T06:42:45","date_gmt":"2024-12-26T22:42:45","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/979016.html"},"modified":"2024-12-27T06:42:48","modified_gmt":"2024-12-26T22:42:48","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e6%88%aa%e5%8f%96%e5%9b%be%e7%89%87","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/979016.html","title":{"rendered":"\u5982\u4f55\u7528python\u622a\u53d6\u56fe\u7247"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24205040\/78292b92-852e-4170-9238-3750577d4fb6.webp\" alt=\"\u5982\u4f55\u7528python\u622a\u53d6\u56fe\u7247\" \/><\/p>\n<p><p> <strong>\u4f7f\u7528Python\u622a\u53d6\u56fe\u7247\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u4e3b\u8981\u5305\u62ec\u4f7f\u7528PIL\u5e93\u3001OpenCV\u5e93\u3001\u4ee5\u53caPillow\u5e93\u3002PIL\u5e93\u63d0\u4f9b\u4e86\u57fa\u672c\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3001OpenCV\u652f\u6301\u591a\u79cd\u56fe\u50cf\u5904\u7406\u64cd\u4f5c\u3001Pillow\u662fPIL\u7684\u5347\u7ea7\u7248\uff0c\u62e5\u6709\u66f4\u597d\u7684\u529f\u80fd\u548c\u517c\u5bb9\u6027\u3002<\/strong>\u5176\u4e2d\uff0cPillow\u5e93\u56e0\u5176\u6613\u7528\u6027\u548c\u529f\u80fd\u4e30\u5bcc\u6027\uff0c\u5e38\u88ab\u7528\u4e8e\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u3002\u4e0b\u9762\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5e93\u6765\u622a\u53d6\u56fe\u7247\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001\u4f7f\u7528Pillow\u5e93\u622a\u53d6\u56fe\u7247<\/p>\n<\/p>\n<p><p>Pillow\u5e93\u662fPython\u4e2d\u975e\u5e38\u6d41\u884c\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u56fe\u50cf\u64cd\u4f5c\u529f\u80fd\u3002\u4f7f\u7528Pillow\u5e93\u622a\u53d6\u56fe\u7247\u7684\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5\u548c\u5bfc\u5165Pillow\u5e93<\/li>\n<\/ol>\n<p><p>\u5728\u4f7f\u7528Pillow\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5\u5b83\u3002\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u8f7b\u677e\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install Pillow<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165\u6240\u9700\u7684\u6a21\u5757\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from PIL import Image<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u6253\u5f00\u5e76\u622a\u53d6\u56fe\u7247<\/li>\n<\/ol>\n<p><p>\u4f7f\u7528Pillow\u5e93\u6253\u5f00\u56fe\u50cf\u6587\u4ef6\uff0c\u5e76\u8c03\u7528<code>crop()<\/code>\u65b9\u6cd5\u8fdb\u884c\u622a\u53d6\u3002<code>crop()<\/code>\u65b9\u6cd5\u9700\u8981\u4e00\u4e2a\u5143\u7ec4\u53c2\u6570\uff0c\u5b9a\u4e49\u4e86\u622a\u53d6\u533a\u57df\u7684\u5de6\u3001\u4e0a\u3001\u53f3\u3001\u4e0b\u5750\u6807\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6253\u5f00\u56fe\u50cf<\/p>\n<p>image = Image.open(&#39;example.jpg&#39;)<\/p>\n<h2><strong>\u5b9a\u4e49\u622a\u53d6\u533a\u57df (left, upper, right, lower)<\/strong><\/h2>\n<p>crop_area = (100, 100, 400, 400)<\/p>\n<h2><strong>\u622a\u53d6\u56fe\u50cf<\/strong><\/h2>\n<p>cropped_image = image.crop(crop_area)<\/p>\n<h2><strong>\u663e\u793a\u6216\u4fdd\u5b58\u622a\u53d6\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cropped_image.show()  # \u663e\u793a<\/p>\n<p>cropped_image.save(&#39;cropped_example.jpg&#39;)  # \u4fdd\u5b58<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u6ce8\u610f\u4e8b\u9879<\/li>\n<\/ol>\n<p><p>\u5728\u4f7f\u7528Pillow\u622a\u53d6\u56fe\u50cf\u65f6\uff0c\u9700\u8981\u786e\u4fdd\u5750\u6807\u503c\u5728\u56fe\u50cf\u8303\u56f4\u5185\uff0c\u5426\u5219\u4f1a\u5f15\u53d1\u9519\u8bef\u3002\u540c\u65f6\uff0c\u622a\u53d6\u540e\u7684\u56fe\u50cf\u53ef\u4ee5\u518d\u6b21\u8fdb\u884c\u5176\u4ed6\u5904\u7406\uff0c\u5982\u8c03\u6574\u5927\u5c0f\u3001\u65cb\u8f6c\u7b49\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001\u4f7f\u7528OpenCV\u5e93\u622a\u53d6\u56fe\u7247<\/p>\n<\/p>\n<p><p>OpenCV\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u652f\u6301\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00\uff0c\u9002\u7528\u4e8e\u5b9e\u65f6\u56fe\u50cf\u5904\u7406\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528OpenCV\u622a\u53d6\u56fe\u7247\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5\u548c\u5bfc\u5165OpenCV\u5e93<\/li>\n<\/ol>\n<p><p>\u4e0ePillow\u7c7b\u4f3c\uff0c\u9996\u5148\u9700\u8981\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\u5bfc\u5165OpenCV\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import cv2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u6253\u5f00\u5e76\u622a\u53d6\u56fe\u7247<\/li>\n<\/ol>\n<p><p>\u4f7f\u7528OpenCV\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\uff0c\u5e76\u901a\u8fc7\u6570\u7ec4\u5207\u7247\u5b9e\u73b0\u56fe\u50cf\u622a\u53d6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8bfb\u53d6\u56fe\u50cf<\/p>\n<p>image = cv2.imread(&#39;example.jpg&#39;)<\/p>\n<h2><strong>\u5b9a\u4e49\u622a\u53d6\u533a\u57df (y_start:y_end, x_start:x_end)<\/strong><\/h2>\n<p>crop_area = image[100:400, 100:400]<\/p>\n<h2><strong>\u663e\u793a\u6216\u4fdd\u5b58\u622a\u53d6\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imshow(&#39;Cropped Image&#39;, crop_area)  # \u663e\u793a<\/p>\n<p>cv2.imwrite(&#39;cropped_example.jpg&#39;, crop_area)  # \u4fdd\u5b58<\/p>\n<h2><strong>\u7b49\u5f85\u5173\u95ed\u7a97\u53e3<\/strong><\/h2>\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>\u6ce8\u610f\u4e8b\u9879<\/li>\n<\/ol>\n<p><p>OpenCV\u4f7f\u7528BGR\u683c\u5f0f\u5904\u7406\u56fe\u50cf\uff0c\u56e0\u6b64\u5728\u5904\u7406\u989c\u8272\u901a\u9053\u65f6\u9700\u6ce8\u610f\u3002\u540c\u65f6\uff0cOpenCV\u5904\u7406\u56fe\u50cf\u7684\u901f\u5ea6\u8f83\u5feb\uff0c\u9002\u5408\u5904\u7406\u5927\u578b\u56fe\u50cf\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001\u4f7f\u7528PIL\u5e93\u622a\u53d6\u56fe\u7247<\/p>\n<\/p>\n<p><p>\u867d\u7136PIL\u5e93\u5df2\u7ecf\u4e0d\u518d\u66f4\u65b0\uff0c\u4f46\u5b83\u4f9d\u7136\u662f\u8bb8\u591a\u9057\u7559\u9879\u76ee\u4e2d\u5e38\u7528\u7684\u56fe\u50cf\u5904\u7406\u5de5\u5177\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528PIL\u5e93\u622a\u53d6\u56fe\u7247\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5\u548c\u5bfc\u5165PIL\u5e93<\/li>\n<\/ol>\n<p><p>PIL\u5e93\u4e0d\u518d\u5355\u72ec\u63d0\u4f9b\u5b89\u88c5\u5305\uff0c\u5efa\u8bae\u4f7f\u7528Pillow\u4f5c\u4e3a\u66ff\u4ee3\u3002\u4f46\u5982\u679c\u9879\u76ee\u4e2d\u4ecd\u4f7f\u7528PIL\uff0c\u5bfc\u5165\u65b9\u5f0f\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from PIL import Image<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u6253\u5f00\u5e76\u622a\u53d6\u56fe\u7247<\/li>\n<\/ol>\n<p><p>\u4e0ePillow\u7c7b\u4f3c\uff0cPIL\u63d0\u4f9b\u4e86<code>crop()<\/code>\u65b9\u6cd5\u8fdb\u884c\u56fe\u50cf\u622a\u53d6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6253\u5f00\u56fe\u50cf<\/p>\n<p>image = Image.open(&#39;example.jpg&#39;)<\/p>\n<h2><strong>\u5b9a\u4e49\u622a\u53d6\u533a\u57df (left, upper, right, lower)<\/strong><\/h2>\n<p>crop_area = (100, 100, 400, 400)<\/p>\n<h2><strong>\u622a\u53d6\u56fe\u50cf<\/strong><\/h2>\n<p>cropped_image = image.crop(crop_area)<\/p>\n<h2><strong>\u663e\u793a\u6216\u4fdd\u5b58\u622a\u53d6\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cropped_image.show()  # \u663e\u793a<\/p>\n<p>cropped_image.save(&#39;cropped_example.jpg&#39;)  # \u4fdd\u5b58<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u6ce8\u610f\u4e8b\u9879<\/li>\n<\/ol>\n<p><p>PIL\u7684\u4f7f\u7528\u65b9\u6cd5\u4e0ePillow\u51e0\u4e4e\u76f8\u540c\uff0c\u4f46\u5efa\u8bae\u4f7f\u7528Pillow\u4ee5\u83b7\u53d6\u66f4\u597d\u7684\u6027\u80fd\u548c\u65b0\u529f\u80fd\u652f\u6301\u3002<\/p>\n<\/p>\n<p><p>\u56db\u3001\u4f7f\u7528Matplotlib\u5e93\u622a\u53d6\u56fe\u7247<\/p>\n<\/p>\n<p><p>\u867d\u7136Matplotlib\u4e3b\u8981\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\uff0c\u4f46\u4e5f\u53ef\u4ee5\u7528\u4e8e\u7b80\u5355\u7684\u56fe\u50cf\u5904\u7406\u4efb\u52a1\uff0c\u5982\u622a\u53d6\u56fe\u50cf\u3002<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5\u548c\u5bfc\u5165Matplotlib\u5e93<\/li>\n<\/ol>\n<p><pre><code class=\"language-bash\">pip install matplotlib<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<p>import matplotlib.image as mpimg<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u6253\u5f00\u5e76\u622a\u53d6\u56fe\u7247<\/li>\n<\/ol>\n<p><p>\u901a\u8fc7Matplotlib\u8bfb\u53d6\u56fe\u50cf\u5e76\u622a\u53d6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8bfb\u53d6\u56fe\u50cf<\/p>\n<p>image = mpimg.imread(&#39;example.jpg&#39;)<\/p>\n<h2><strong>\u5b9a\u4e49\u622a\u53d6\u533a\u57df (y_start:y_end, x_start:x_end)<\/strong><\/h2>\n<p>crop_area = image[100:400, 100:400]<\/p>\n<h2><strong>\u663e\u793a\u622a\u53d6\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>plt.imshow(crop_area)<\/p>\n<p>plt.axis(&#39;off&#39;)  # \u4e0d\u663e\u793a\u5750\u6807\u8f74<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u6ce8\u610f\u4e8b\u9879<\/li>\n<\/ol>\n<p><p>Matplotlib\u5728\u5904\u7406\u56fe\u50cf\u65f6\uff0c\u901a\u5e38\u4f7f\u7528RGB\u683c\u5f0f\uff0c\u56e0\u6b64\u5728\u4e0e\u5176\u4ed6\u5e93\u534f\u540c\u4f7f\u7528\u65f6\u9700\u6ce8\u610f\u683c\u5f0f\u8f6c\u6362\u3002<\/p>\n<\/p>\n<p><p>\u4e94\u3001\u603b\u7ed3<\/p>\n<\/p>\n<p><p>Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5e93\u548c\u65b9\u6cd5\u6765\u622a\u53d6\u56fe\u7247\uff0c\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u53ef\u4ee5\u63d0\u9ad8\u5f00\u53d1\u6548\u7387\u548c\u56fe\u50cf\u5904\u7406\u6548\u679c\u3002<strong>Pillow\u5e93\u662f\u5904\u7406\u56fe\u50cf\u7684\u9996\u9009\u5de5\u5177\uff0c\u56e0\u5176\u7b80\u5355\u6613\u7528\u548c\u529f\u80fd\u5168\u9762<\/strong>\uff0c\u800cOpenCV\u5219\u9002\u5408\u9700\u8981\u9ad8\u6027\u80fd\u548c\u590d\u6742\u64cd\u4f5c\u7684\u573a\u666f\u3002\u65e0\u8bba\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\uff0c\u4e86\u89e3\u6bcf\u4e2a\u5de5\u5177\u7684\u7279\u70b9\u548c\u9650\u5236\u662f\u786e\u4fdd\u6210\u529f\u5b9e\u73b0\u56fe\u50cf\u622a\u53d6\u7684\u5173\u952e\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u7528Python\u622a\u53d6\u56fe\u7247\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u4ec0\u4e48\uff1f<\/strong><br \/>\u622a\u53d6\u56fe\u7247\u7684\u57fa\u672c\u6b65\u9aa4\u5305\u62ec\uff1a\u9996\u5148\uff0c\u4f7f\u7528\u5408\u9002\u7684\u5e93\uff0c\u4f8b\u5982Pillow\u6216OpenCV\uff0c\u6765\u6253\u5f00\u548c\u52a0\u8f7d\u56fe\u7247\u3002\u63a5\u7740\uff0c\u786e\u5b9a\u622a\u53d6\u533a\u57df\u7684\u5750\u6807\u548c\u5c3a\u5bf8\uff0c\u6700\u540e\u8c03\u7528\u76f8\u5e94\u7684\u51fd\u6570\u8fdb\u884c\u622a\u53d6\u5e76\u4fdd\u5b58\u5904\u7406\u540e\u7684\u56fe\u7247\u3002\u5177\u4f53\u7684\u4ee3\u7801\u5b9e\u73b0\u4e5f\u4f1a\u56e0\u6240\u4f7f\u7528\u7684\u5e93\u800c\u6709\u6240\u4e0d\u540c\u3002<\/p>\n<p><strong>Python\u622a\u53d6\u56fe\u7247\u65f6\uff0c\u5982\u4f55\u9009\u62e9\u622a\u53d6\u533a\u57df\uff1f<\/strong><br \/>\u9009\u62e9\u622a\u53d6\u533a\u57df\u65f6\uff0c\u9700\u8981\u660e\u786e\u4f60\u60f3\u8981\u622a\u53d6\u7684\u90e8\u5206\u7684\u5750\u6807\u3002\u901a\u5e38\uff0c\u5750\u6807\u7684\u683c\u5f0f\u4e3a\uff08\u5de6\u4e0a\u89d2x, \u5de6\u4e0a\u89d2y, \u5bbd\u5ea6, \u9ad8\u5ea6\uff09\u3002\u53ef\u4ee5\u901a\u8fc7\u56fe\u50cf\u67e5\u770b\u5de5\u5177\u83b7\u53d6\u8fd9\u4e9b\u5750\u6807\uff0c\u786e\u4fdd\u622a\u53d6\u7684\u533a\u57df\u7b26\u5408\u4f60\u7684\u9700\u6c42\u3002<\/p>\n<p><strong>\u4f7f\u7528Python\u622a\u53d6\u56fe\u7247\u540e\uff0c\u5982\u4f55\u4fdd\u5b58\u5904\u7406\u597d\u7684\u56fe\u7247\uff1f<\/strong><br 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