{"id":993575,"date":"2024-12-27T08:47:12","date_gmt":"2024-12-27T00:47:12","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/993575.html"},"modified":"2024-12-27T08:47:15","modified_gmt":"2024-12-27T00:47:15","slug":"%e7%bc%96%e7%a8%8bpython%e5%a6%82%e4%bd%95%e7%bc%a9%e6%94%be%e5%9b%be%e7%89%87","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/993575.html","title":{"rendered":"\u7f16\u7a0bpython\u5982\u4f55\u7f29\u653e\u56fe\u7247"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25070917\/59bc9620-6af7-4725-9536-353cc5869084.webp\" alt=\"\u7f16\u7a0bpython\u5982\u4f55\u7f29\u653e\u56fe\u7247\" \/><\/p>\n<p><p> \u5f00\u5934\u6bb5\u843d\uff1a<br \/><strong>\u5728Python\u4e2d\u7f29\u653e\u56fe\u7247\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528PIL\u5e93\u3001OpenCV\u5e93\u3001scikit-image\u5e93<\/strong>\u3002\u8fd9\u4e9b\u5e93\u90fd\u63d0\u4f9b\u4e86\u7b80\u5355\u800c\u5f3a\u5927\u7684\u529f\u80fd\u6765\u5904\u7406\u56fe\u50cf\u7f29\u653e\u3002\u4f7f\u7528PIL\u5e93\u4e2d\u7684Image\u6a21\u5757\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u56fe\u7247\u7f29\u653e\uff1bOpenCV\u5e93\u5219\u63d0\u4f9b\u4e86\u66f4\u9ad8\u6548\u7684\u56fe\u50cf\u5904\u7406\u80fd\u529b\uff0c\u9002\u5408\u9700\u8981\u5904\u7406\u5927\u91cf\u56fe\u50cf\u7684\u573a\u666f\uff1b\u800cscikit-image\u5e93\u5219\u63d0\u4f9b\u4e86\u79d1\u5b66\u8ba1\u7b97\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528PIL\u5e93\u4e2d\u7684Image\u6a21\u5757\u6765\u7f29\u653e\u56fe\u7247\u3002\u901a\u8fc7Image\u6a21\u5757\u7684<code>resize()<\/code>\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u6307\u5b9a\u76ee\u6807\u5c3a\u5bf8\u7f29\u653e\u56fe\u7247\uff0c\u540c\u65f6\u53ef\u4ee5\u8bbe\u7f6e\u63d2\u503c\u53c2\u6570\u6765\u63a7\u5236\u7f29\u653e\u8d28\u91cf\u3002\u4f8b\u5982\uff0c\u4f7f\u7528<code>Image.ANTIALIAS<\/code>\u53ef\u4ee5\u83b7\u5f97\u9ad8\u8d28\u91cf\u7684\u7f29\u653e\u6548\u679c\u3002\u63a5\u4e0b\u6765\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8Python\u4e2d\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5e93\u8fdb\u884c\u56fe\u7247\u7684\u7f29\u653e\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001PIL\u5e93\u7684\u4f7f\u7528<\/p>\n<\/p>\n<p><p>PIL\uff08Python Imaging Library\uff09\u662fPython\u4e2d\u5904\u7406\u56fe\u50cf\u7684\u4e00\u4e2a\u7ecf\u5178\u5e93\uff0c\u867d\u7136PIL\u672c\u8eab\u5df2\u7ecf\u505c\u6b62\u66f4\u65b0\uff0c\u4f46\u5176\u5206\u652f\u9879\u76eePillow\u4f9d\u7136\u6d3b\u8dc3\uff0c\u5e76\u4e14\u662fPython\u4e2d\u5904\u7406\u56fe\u50cf\u7684\u5e38\u7528\u5de5\u5177\u3002<\/p>\n<\/p>\n<p><p>1\u3001\u5b89\u88c5\u548c\u5bfc\u5165Pillow<br \/>\u8981\u4f7f\u7528PIL\u5e93\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5Pillow\u3002\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u8fdb\u884c\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\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165\u6240\u9700\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<p><p>2\u3001\u7f29\u653e\u56fe\u7247\u7684\u57fa\u672c\u6b65\u9aa4<br \/>\u4f7f\u7528Pillow\u7f29\u653e\u56fe\u7247\u7684\u57fa\u672c\u6b65\u9aa4\u5305\u62ec\u6253\u5f00\u56fe\u50cf\u6587\u4ef6\u3001\u8c03\u7528<code>resize()<\/code>\u65b9\u6cd5\u8fdb\u884c\u7f29\u653e\u3001\u4fdd\u5b58\u7f29\u653e\u540e\u7684\u56fe\u50cf\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6253\u5f00\u56fe\u50cf\u6587\u4ef6<\/p>\n<p>image = Image.open(&#39;example.jpg&#39;)<\/p>\n<h2><strong>\u5b9a\u4e49\u7f29\u653e\u540e\u7684\u5c3a\u5bf8<\/strong><\/h2>\n<p>new_size = (800, 600)<\/p>\n<h2><strong>\u8fdb\u884c\u7f29\u653e<\/strong><\/h2>\n<p>resized_image = image.resize(new_size, Image.ANTIALIAS)<\/p>\n<h2><strong>\u4fdd\u5b58\u7f29\u653e\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>resized_image.save(&#39;example_resized.jpg&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c<code>Image.ANTIALIAS<\/code>\u53c2\u6570\u7528\u4e8e\u63d0\u9ad8\u56fe\u50cf\u7f29\u653e\u8d28\u91cf\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001OpenCV\u5e93\u7684\u4f7f\u7528<\/p>\n<\/p>\n<p><p>OpenCV\uff08Open Source Computer Vision Library\uff09\u662f\u4e00\u4e2a\u5f00\u6e90\u8ba1\u7b97\u673a\u89c6\u89c9\u548c<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u8f6f\u4ef6\u5e93\uff0c\u63d0\u4f9b\u4e86\u591a\u79cd\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002<\/p>\n<\/p>\n<p><p>1\u3001\u5b89\u88c5\u548c\u5bfc\u5165OpenCV<br \/>\u5728\u5f00\u59cb\u4f7f\u7528OpenCV\u4e4b\u524d\uff0c\u9700\u8981\u5b89\u88c5\u76f8\u5e94\u7684Python\u5e93\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\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165OpenCV\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import cv2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>2\u3001\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u7f29\u653e<br \/>OpenCV\u63d0\u4f9b\u4e86<code>cv2.resize()<\/code>\u51fd\u6570\u7528\u4e8e\u8c03\u6574\u56fe\u50cf\u5c3a\u5bf8\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528OpenCV\u7f29\u653e\u56fe\u50cf\u7684\u793a\u4f8b\uff1a<\/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\u7f29\u653e\u6bd4\u4f8b<\/strong><\/h2>\n<p>scale_percent = 50 # \u7f29\u5c0f50%<\/p>\n<h2><strong>\u8ba1\u7b97\u7f29\u653e\u540e\u7684\u5c3a\u5bf8<\/strong><\/h2>\n<p>width = int(image.shape[1] * scale_percent \/ 100)<\/p>\n<p>height = int(image.shape[0] * scale_percent \/ 100)<\/p>\n<p>new_size = (width, height)<\/p>\n<h2><strong>\u8fdb\u884c\u7f29\u653e<\/strong><\/h2>\n<p>resized_image = cv2.resize(image, new_size, interpolation=cv2.INTER_AREA)<\/p>\n<h2><strong>\u4fdd\u5b58\u7f29\u653e\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imwrite(&#39;example_resized.jpg&#39;, resized_image)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u91cc\uff0c<code>cv2.INTER_AREA<\/code>\u662f\u4e00\u4e2a\u63d2\u503c\u65b9\u6cd5\uff0c\u901a\u5e38\u7528\u4e8e\u7f29\u5c0f\u56fe\u50cf\u65f6\u4ee5\u83b7\u5f97\u66f4\u597d\u7684\u8d28\u91cf\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001scikit-image\u5e93\u7684\u4f7f\u7528<\/p>\n<\/p>\n<p><p>scikit-image\u662f\u4e00\u4e2a\u7528\u4e8e\u56fe\u50cf\u5904\u7406\u7684Python\u5e93\uff0c\u57fa\u4e8eNumPy\u6784\u5efa\uff0c\u4e13\u6ce8\u4e8e\u79d1\u5b66\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><p>1\u3001\u5b89\u88c5\u548c\u5bfc\u5165scikit-image<br \/>\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u5b89\u88c5scikit-image\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install scikit-image<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u7136\u540e\u5728\u811a\u672c\u4e2d\u5bfc\u5165\u6240\u9700\u6a21\u5757\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from skimage import io, transform<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>2\u3001\u4f7f\u7528scikit-image\u8fdb\u884c\u56fe\u50cf\u7f29\u653e<br \/>\u4f7f\u7528scikit-image\u7684<code>transform.resize()<\/code>\u51fd\u6570\u53ef\u4ee5\u8f7b\u677e\u8c03\u6574\u56fe\u50cf\u5c3a\u5bf8\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8bfb\u53d6\u56fe\u50cf<\/p>\n<p>image = io.imread(&#39;example.jpg&#39;)<\/p>\n<h2><strong>\u5b9a\u4e49\u7f29\u653e\u540e\u7684\u5c3a\u5bf8<\/strong><\/h2>\n<p>new_size = (600, 800)<\/p>\n<h2><strong>\u8fdb\u884c\u7f29\u653e<\/strong><\/h2>\n<p>resized_image = transform.resize(image, new_size, anti_aliasing=True)<\/p>\n<h2><strong>\u4fdd\u5b58\u7f29\u653e\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>io.imsave(&#39;example_resized.jpg&#39;, (resized_image * 255).astype(&#39;uint8&#39;))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u91cc\u7684<code>anti_aliasing=True<\/code>\u53c2\u6570\u7528\u4e8e\u51cf\u5c11\u7f29\u653e\u65f6\u7684\u952f\u9f7f\u6548\u5e94\uff0c\u4ece\u800c\u63d0\u9ad8\u56fe\u50cf\u8d28\u91cf\u3002<\/p>\n<\/p>\n<p><p>\u56db\u3001\u9009\u62e9\u5408\u9002\u7684\u5e93\u548c\u65b9\u6cd5<\/p>\n<\/p>\n<p><p>\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\u548c\u65b9\u6cd5\u5bf9\u4e8e\u56fe\u50cf\u5904\u7406\u975e\u5e38\u91cd\u8981\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5efa\u8bae\uff1a<\/p>\n<\/p>\n<p><p>1\u3001\u5904\u7406\u5927\u6279\u91cf\u56fe\u50cf<br \/>\u5982\u679c\u9700\u8981\u9ad8\u6548\u5904\u7406\u5927\u91cf\u56fe\u50cf\uff0cOpenCV\u7531\u4e8e\u5176\u5e95\u5c42C\/C++\u5b9e\u73b0\u548c\u591a\u7ebf\u7a0b\u5904\u7406\u80fd\u529b\uff0c\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n<p><p>2\u3001\u9700\u8981\u9ad8\u8d28\u91cf\u7f29\u653e<br \/>\u5982\u679c\u56fe\u50cf\u8d28\u91cf\u662f\u9996\u8981\u8003\u8651\u56e0\u7d20\uff0c\u53ef\u4ee5\u4f7f\u7528Pillow\u7684<code>Image.ANTIALIAS<\/code>\u6216scikit-image\u7684<code>anti_aliasing=True<\/code>\u53c2\u6570\u8fdb\u884c\u9ad8\u8d28\u91cf\u7f29\u653e\u3002<\/p>\n<\/p>\n<p><p>3\u3001\u79d1\u5b66\u8ba1\u7b97\u4e0e\u5206\u6790<br \/>\u5bf9\u4e8e\u9700\u8981\u79d1\u5b66\u8ba1\u7b97\u548c\u5206\u6790\u7684\u56fe\u50cf\u5904\u7406\u4efb\u52a1\uff0cscikit-image\u7531\u4e8e\u5176\u4e0eNumPy\u7684\u7d27\u5bc6\u96c6\u6210\uff0c\u662f\u4e00\u4e2a\u7406\u60f3\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n<p><p>\u4e94\u3001\u56fe\u50cf\u7f29\u653e\u6ce8\u610f\u4e8b\u9879<\/p>\n<\/p>\n<p><p>\u5728\u8fdb\u884c\u56fe\u50cf\u7f29\u653e\u65f6\uff0c\u6709\u4e00\u4e9b\u91cd\u8981\u7684\u6ce8\u610f\u4e8b\u9879\u9700\u8981\u8003\u8651\uff1a<\/p>\n<\/p>\n<p><p>1\u3001\u4fdd\u6301\u56fe\u50cf\u6bd4\u4f8b<br \/>\u5728\u7f29\u653e\u56fe\u50cf\u65f6\uff0c\u901a\u5e38\u9700\u8981\u4fdd\u6301\u56fe\u50cf\u7684\u957f\u5bbd\u6bd4\u4f8b\uff0c\u4ee5\u907f\u514d\u56fe\u50cf\u5931\u771f\u3002\u8fd9\u53ef\u4ee5\u901a\u8fc7\u8ba1\u7b97\u65b0\u7684\u5c3a\u5bf8\u65f6\u4fdd\u6301\u6bd4\u4f8b\u4e00\u81f4\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><p>2\u3001\u9009\u62e9\u5408\u9002\u7684\u63d2\u503c\u65b9\u6cd5<br \/>\u4e0d\u540c\u7684\u63d2\u503c\u65b9\u6cd5\u4f1a\u5f71\u54cd\u7f29\u653e\u540e\u7684\u56fe\u50cf\u8d28\u91cf\u3002\u4e00\u822c\u6765\u8bf4\uff0c<code>Image.ANTIALIAS<\/code>\u548c<code>cv2.INTER_AREA<\/code>\u9002\u5408\u7f29\u5c0f\u56fe\u50cf\uff0c<code>cv2.INTER_LINEAR<\/code>\u9002\u5408\u653e\u5927\u56fe\u50cf\u3002<\/p>\n<\/p>\n<p><p>3\u3001\u5904\u7406\u8fb9\u754c\u6548\u5e94<br \/>\u5728\u7f29\u653e\u8fc7\u7a0b\u4e2d\uff0c\u8fb9\u754c\u6548\u5e94\u53ef\u80fd\u5bfc\u81f4\u56fe\u50cf\u51fa\u73b0\u952f\u9f7f\u6216\u6a21\u7cca\u3002\u53ef\u4ee5\u901a\u8fc7\u9009\u62e9\u5408\u9002\u7684\u63d2\u503c\u65b9\u6cd5\u548c\u4f7f\u7528\u6297\u952f\u9f7f\u9009\u9879\u6765\u51cf\u8f7b\u8fd9\u79cd\u5f71\u54cd\u3002<\/p>\n<\/p>\n<p><p>\u603b\u7ed3\u6765\u8bf4\uff0cPython\u63d0\u4f9b\u4e86\u591a\u79cd\u56fe\u50cf\u7f29\u653e\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u6bcf\u79cd\u65b9\u6848\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u5e94\u7528\u573a\u666f\u3002\u901a\u8fc7\u5bf9\u6bd4Pillow\u3001OpenCV\u548cscikit-image\u7684\u4e0d\u540c\u529f\u80fd\u548c\u7279\u70b9\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u6700\u9002\u5408\u7684\u5de5\u5177\u8fdb\u884c\u56fe\u50cf\u7f29\u653e\u3002\u65e0\u8bba\u662f\u5904\u7406\u5927\u6279\u91cf\u56fe\u50cf\u3001\u8ffd\u6c42\u9ad8\u8d28\u91cf\u7f29\u653e\uff0c\u8fd8\u662f\u8fdb\u884c\u79d1\u5b66\u8ba1\u7b97\uff0cPython\u751f\u6001\u7cfb\u7edf\u4e2d\u7684\u8fd9\u4e9b\u5e93\u90fd\u80fd\u6ee1\u8db3\u4e0d\u540c\u7684\u56fe\u50cf\u5904\u7406\u9700\u6c42\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u7f29\u653e\u56fe\u7247\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u7f29\u653e\u56fe\u7247\uff0c\u5982PIL\uff08Pillow\uff09\u548cOpenCV\u7b49\u3002\u4f7f\u7528Pillow\u5e93\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7<code>Image.open()<\/code>\u52a0\u8f7d\u56fe\u7247\uff0c\u7136\u540e\u4f7f\u7528<code>resize()<\/code>\u65b9\u6cd5\u6765\u8c03\u6574\u56fe\u7247\u7684\u5927\u5c0f\u3002\u4f8b\u5982\uff1a  <\/p>\n<pre><code class=\"language-python\">from PIL import Image\n\nimg = Image.open(&#39;example.jpg&#39;)\nimg = img.resize((width, height))\nimg.save(&#39;resized_example.jpg&#39;)\n<\/code><\/pre>\n<p>\u8fd9\u79cd\u65b9\u6cd5\u4e0d\u4ec5\u7b80\u5355\uff0c\u800c\u4e14\u80fd\u591f\u7075\u6d3b\u5904\u7406\u4e0d\u540c\u7684\u7f29\u653e\u6bd4\u4f8b\u3002<\/p>\n<p><strong>\u7f29\u653e\u56fe\u7247\u65f6\u5e94\u8be5\u6ce8\u610f\u54ea\u4e9b\u53c2\u6570\uff1f<\/strong><br \/>\u5728\u7f29\u653e\u56fe\u7247\u65f6\uff0c\u4fdd\u6301\u56fe\u7247\u7684\u5bbd\u9ad8\u6bd4\u662f\u975e\u5e38\u91cd\u8981\u7684\uff0c\u4ee5\u907f\u514d\u56fe\u7247\u53d8\u5f62\u3002\u60a8\u53ef\u4ee5\u8ba1\u7b97\u65b0\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6\uff0c\u4f7f\u5f97\u6bd4\u4f8b\u4fdd\u6301\u4e00\u81f4\u3002\u6b64\u5916\uff0c\u9009\u62e9\u5408\u9002\u7684\u63d2\u503c\u65b9\u6cd5\uff08\u5982NEAREST\u3001BILINEAR\u3001BICUBIC\u7b49\uff09\u4e5f\u4f1a\u5f71\u54cd\u7f29\u653e\u540e\u7684\u56fe\u7247\u8d28\u91cf\u3002<\/p>\n<p><strong>\u6709\u54ea\u4e9b\u5e93\u53ef\u4ee5\u9009\u62e9\u6765\u7f29\u653e\u56fe\u7247\uff1f<\/strong><br \/>Python\u4e2d\u5e38\u7528\u6765\u7f29\u653e\u56fe\u7247\u7684\u5e93\u5305\u62ecPillow\u3001OpenCV\u548cscikit-image\u3002Pillow\u662f\u4e00\u4e2a\u7b80\u5355\u6613\u7528\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u9002\u5408\u4e8e\u57fa\u672c\u7684\u56fe\u50cf\u64cd\u4f5c\uff1bOpenCV\u5219\u63d0\u4f9b\u4e86\u66f4\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\uff0c\u9002\u5408\u4e8e\u590d\u6742\u7684\u4efb\u52a1\uff1b\u800cscikit-image\u5219\u662f\u4e00\u4e2a\u4e13\u95e8\u7528\u4e8e\u56fe\u50cf\u5904\u7406\u7684\u5e93\uff0c\u9002\u5408\u4e8e\u79d1\u5b66\u8ba1\u7b97\u548c\u56fe\u50cf\u5206\u6790\u3002\u6839\u636e\u9879\u76ee\u9700\u6c42\uff0c\u53ef\u4ee5\u9009\u62e9\u6700\u9002\u5408\u7684\u5e93\u6765\u5b8c\u6210\u7f29\u653e\u4efb\u52a1\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5f00\u5934\u6bb5\u843d\uff1a\u5728Python\u4e2d\u7f29\u653e\u56fe\u7247\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528PIL\u5e93\u3001OpenCV\u5e93\u3001scikit-image\u5e93\u3002\u8fd9\u4e9b\u5e93\u90fd\u63d0 [&hellip;]","protected":false},"author":3,"featured_media":993588,"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\/993575"}],"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=993575"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/993575\/revisions"}],"predecessor-version":[{"id":993591,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/993575\/revisions\/993591"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/993588"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=993575"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=993575"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=993575"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}