{"id":1145155,"date":"2025-01-08T23:05:50","date_gmt":"2025-01-08T15:05:50","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1145155.html"},"modified":"2025-01-08T23:05:52","modified_gmt":"2025-01-08T15:05:52","slug":"%e5%a6%82%e4%bd%95%e5%b0%86%e4%ba%8c%e7%bb%b4%e7%9f%a9%e9%98%b5%e8%b5%8b%e5%80%bc%e7%bb%99%e4%b8%89%e7%bb%b4python","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1145155.html","title":{"rendered":"\u5982\u4f55\u5c06\u4e8c\u7ef4\u77e9\u9635\u8d4b\u503c\u7ed9\u4e09\u7ef4python"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24181907\/40200c17-141c-42fd-85de-3c78902d05b4.webp\" alt=\"\u5982\u4f55\u5c06\u4e8c\u7ef4\u77e9\u9635\u8d4b\u503c\u7ed9\u4e09\u7ef4python\" \/><\/p>\n<p><p> <strong>\u8981\u5c06\u4e8c\u7ef4\u77e9\u9635\u8d4b\u503c\u7ed9\u4e09\u7ef4Python\u6570\u7ec4\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u3001\u901a\u8fc7\u6269\u5c55\u7ef4\u5ea6\u3001\u5e7f\u64ad\u6216\u76f4\u63a5\u5d4c\u5957\u7b49\u65b9\u6cd5<\/strong>\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f\u4f7f\u7528NumPy\u5e93\u4e2d\u7684<code>np.newaxis<\/code>\u6216<code>np.expand_dims<\/code>\u51fd\u6570\u6765\u6269\u5c55\u4e8c\u7ef4\u77e9\u9635\u7684\u7ef4\u5ea6\uff0c\u4f7f\u5176\u6210\u4e3a\u4e09\u7ef4\u6570\u7ec4\u4e2d\u7684\u4e00\u4e2a\u5207\u7247\u3002\u4f7f\u7528NumPy\u7684\u4f18\u52bf\u5728\u4e8e\u5176\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u548c\u4e30\u5bcc\u7684\u51fd\u6570\u5e93\u3002\u63a5\u4e0b\u6765\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8\u51e0\u79cd\u4e0d\u540c\u7684\u65b9\u6cd5\uff0c\u5e76\u4e3e\u4f8b\u8bf4\u660e\u5177\u4f53\u5b9e\u73b0\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528NumPy\u5e93<\/h3>\n<\/p>\n<p><p>NumPy\u662fPython\u4e2d\u5904\u7406\u6570\u7ec4\u548c\u77e9\u9635\u8fd0\u7b97\u7684\u57fa\u7840\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5de5\u5177\u6765\u521b\u5efa\u548c\u64cd\u4f5c\u591a\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><h4>1.1 \u4f7f\u7528 np.newaxis<\/h4>\n<\/p>\n<p><p><code>np.newaxis<\/code>\u662fNumPy\u4e2d\u6dfb\u52a0\u65b0\u8f74\u7684\u5e38\u7528\u65b9\u6cd5\u3002\u5b83\u53ef\u4ee5\u5728\u73b0\u6709\u6570\u7ec4\u7684\u7279\u5b9a\u4f4d\u7f6e\u63d2\u5165\u4e00\u4e2a\u65b0\u8f74\uff0c\u4ece\u800c\u5c06\u4e8c\u7ef4\u77e9\u9635\u6269\u5c55\u4e3a\u4e09\u7ef4\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u9635<\/strong><\/h2>\n<p>matrix_2d = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u4f7f\u7528 np.newaxis \u5c06\u4e8c\u7ef4\u77e9\u9635\u8f6c\u6362\u4e3a\u4e09\u7ef4<\/strong><\/h2>\n<p>matrix_3d = matrix_2d[:, :, np.newaxis]<\/p>\n<p>print(matrix_3d)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u901a\u8fc7\u5728\u7d22\u5f15\u4f4d\u7f6e\u63d2\u5165<code>np.newaxis<\/code>\uff0c\u6211\u4eec\u628a\u4e8c\u7ef4\u77e9\u9635\u6269\u5c55\u6210\u4e86\u4e09\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><h4>1.2 \u4f7f\u7528 np.expand_dims<\/h4>\n<\/p>\n<p><p><code>np.expand_dims<\/code>\u51fd\u6570\u53ef\u4ee5\u663e\u5f0f\u5730\u5728\u6307\u5b9a\u4f4d\u7f6e\u6dfb\u52a0\u4e00\u4e2a\u65b0\u7684\u8f74\uff0c\u6548\u679c\u4e0e<code>np.newaxis<\/code>\u7c7b\u4f3c\uff0c\u4f46\u8bed\u6cd5\u4e0a\u66f4\u52a0\u76f4\u89c2\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u9635<\/strong><\/h2>\n<p>matrix_2d = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u4f7f\u7528 np.expand_dims \u5c06\u4e8c\u7ef4\u77e9\u9635\u8f6c\u6362\u4e3a\u4e09\u7ef4<\/strong><\/h2>\n<p>matrix_3d = np.expand_dims(matrix_2d, axis=2)<\/p>\n<p>print(matrix_3d)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u91cc<code>axis=2<\/code>\u8868\u793a\u5728\u7b2c\u4e09\u4e2a\u8f74\uff08\u4ece0\u5f00\u59cb\u8ba1\u6570\uff09\u7684\u4f4d\u7f6e\u63d2\u5165\u65b0\u8f74\uff0c\u8f6c\u6362\u540e\u7684\u4e09\u7ef4\u6570\u7ec4\u5f62\u72b6\u4e3a <code>(2, 3, 1)<\/code>\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528\u5e7f\u64ad\u673a\u5236<\/h3>\n<\/p>\n<p><p>\u5e7f\u64ad\u662fNumPy\u4e2d\u5904\u7406\u4e0d\u540c\u5f62\u72b6\u6570\u7ec4\u8fd0\u7b97\u7684\u5f3a\u5927\u673a\u5236\u3002\u901a\u8fc7\u5e7f\u64ad\uff0c\u53ef\u4ee5\u5c06\u8f83\u4f4e\u7ef4\u5ea6\u7684\u6570\u7ec4\u4e0e\u8f83\u9ad8\u7ef4\u5ea6\u7684\u6570\u7ec4\u8fdb\u884c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><h4>2.1 \u4f7f\u7528\u5e7f\u64ad\u673a\u5236\u5c06\u4e8c\u7ef4\u77e9\u9635\u6269\u5c55\u4e3a\u4e09\u7ef4<\/h4>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u9635<\/strong><\/h2>\n<p>matrix_2d = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u4f7f\u7528\u5e7f\u64ad\u673a\u5236\u5c06\u4e8c\u7ef4\u77e9\u9635\u6269\u5c55\u4e3a\u4e09\u7ef4<\/strong><\/h2>\n<p>matrix_3d = matrix_2d[:, :, np.newaxis] + np.zeros((2, 3, 2))<\/p>\n<p>print(matrix_3d)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u901a\u8fc7\u5c06\u4e8c\u7ef4\u77e9\u9635\u4e0e\u4e00\u4e2a\u5f62\u72b6\u4e3a <code>(2, 3, 2)<\/code> \u7684\u96f6\u77e9\u9635\u76f8\u52a0\uff0c\u5229\u7528\u5e7f\u64ad\u673a\u5236\u5c06\u4e8c\u7ef4\u77e9\u9635\u6269\u5c55\u6210\u4e09\u7ef4\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u76f4\u63a5\u5d4c\u5957\u5217\u8868<\/h3>\n<\/p>\n<p><p>\u5982\u679c\u4e0d\u4f7f\u7528NumPy\u5e93\uff0c\u4e5f\u53ef\u4ee5\u901a\u8fc7\u76f4\u63a5\u5d4c\u5957\u5217\u8868\u7684\u65b9\u5f0f\u6765\u521b\u5efa\u4e09\u7ef4\u6570\u7ec4\u3002\u8fd9\u79cd\u65b9\u6cd5\u5728\u5904\u7406\u7b80\u5355\u60c5\u51b5\u65f6\u4e5f\u975e\u5e38\u6709\u6548\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u9635<\/p>\n<p>matrix_2d = [[1, 2, 3], [4, 5, 6]]<\/p>\n<h2><strong>\u5c06\u4e8c\u7ef4\u77e9\u9635\u5d4c\u5957\u6210\u4e09\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>matrix_3d = [matrix_2d]<\/p>\n<p>print(matrix_3d)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u76f4\u63a5\u5c06\u4e8c\u7ef4\u77e9\u9635\u5d4c\u5957\u5728\u4e00\u4e2a\u5217\u8868\u4e2d\uff0c\u4ece\u800c\u751f\u6210\u4e86\u4e00\u4e2a\u4e09\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u4f7f\u7528NumPy\u7684 reshape \u51fd\u6570<\/h3>\n<\/p>\n<p><p><code>reshape<\/code>\u51fd\u6570\u53ef\u4ee5\u91cd\u65b0\u8c03\u6574\u6570\u7ec4\u7684\u5f62\u72b6\u3002\u901a\u8fc7\u9002\u5f53\u5730\u8c03\u6574\u5f62\u72b6\u53c2\u6570\uff0c\u53ef\u4ee5\u5b9e\u73b0\u4ece\u4e8c\u7ef4\u5230\u4e09\u7ef4\u7684\u8f6c\u6362\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u9635<\/strong><\/h2>\n<p>matrix_2d = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u4f7f\u7528 reshape \u51fd\u6570\u5c06\u4e8c\u7ef4\u77e9\u9635\u8f6c\u6362\u4e3a\u4e09\u7ef4<\/strong><\/h2>\n<p>matrix_3d = matrix_2d.reshape((2, 3, 1))<\/p>\n<p>print(matrix_3d)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4f7f\u7528<code>reshape<\/code>\u51fd\u6570\u65f6\u9700\u8981\u786e\u4fdd\u65b0\u5f62\u72b6\u7684\u5143\u7d20\u603b\u6570\u4e0e\u539f\u6570\u7ec4\u4e00\u81f4\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u5b9e\u9645\u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n<p><p>\u5c06\u4e8c\u7ef4\u77e9\u9635\u8d4b\u503c\u5230\u4e09\u7ef4\u6570\u7ec4\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u975e\u5e38\u5e7f\u6cdb\uff0c\u5c24\u5176\u5728\u56fe\u50cf\u5904\u7406\u3001\u6570\u636e\u5206\u6790\u548c<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u9886\u57df\u3002\u4f8b\u5982\uff0c\u5904\u7406\u7070\u5ea6\u56fe\u50cf\u65f6\uff0c\u901a\u5e38\u9700\u8981\u5c06\u4e8c\u7ef4\u56fe\u50cf\u6570\u636e\u6269\u5c55\u5230\u4e09\u7ef4\uff0c\u4ee5\u4fbf\u4e0eRGB\u56fe\u50cf\u7684\u4e09\u7ef4\u7ed3\u6784\u4fdd\u6301\u4e00\u81f4\u3002<\/p>\n<\/p>\n<p><h4>5.1 \u56fe\u50cf\u5904\u7406\u4e2d\u7684\u5e94\u7528<\/h4>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u6a21\u62df\u4e00\u4e2a\u7070\u5ea6\u56fe\u50cf\u6570\u636e<\/strong><\/h2>\n<p>gray_image = np.array([[100, 150, 200], [50, 100, 150]])<\/p>\n<h2><strong>\u5c06\u7070\u5ea6\u56fe\u50cf\u6269\u5c55\u4e3a\u4e09\u7ef4<\/strong><\/h2>\n<p>rgb_image = np.expand_dims(gray_image, axis=2)<\/p>\n<h2><strong>\u5c06\u6269\u5c55\u540e\u7684\u56fe\u50cf\u590d\u5236\u5230\u4e09\u4e2a\u901a\u9053<\/strong><\/h2>\n<p>rgb_image = np.concatenate([rgb_image, rgb_image, rgb_image], axis=2)<\/p>\n<p>print(rgb_image)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u901a\u8fc7\u6269\u5c55\u548c\u590d\u5236\u7070\u5ea6\u56fe\u50cf\u7684\u901a\u9053\uff0c\u6211\u4eec\u5c06\u5176\u8f6c\u6362\u6210\u4e86RGB\u56fe\u50cf\u7684\u683c\u5f0f\u3002<\/p>\n<\/p>\n<p><h4>5.2 \u6570\u636e\u5206\u6790\u4e2d\u7684\u5e94\u7528<\/h4>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u6a21\u62df\u4e00\u4e2a\u4e8c\u7ef4\u6570\u636e\u96c6<\/strong><\/h2>\n<p>data_2d = np.array([[1.1, 2.2, 3.3], [4.4, 5.5, 6.6]])<\/p>\n<h2><strong>\u6269\u5c55\u4e8c\u7ef4\u6570\u636e\u96c6\u5230\u4e09\u7ef4<\/strong><\/h2>\n<p>data_3d = np.expand_dims(data_2d, axis=0)<\/p>\n<p>print(data_3d)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u901a\u8fc7\u5c06\u4e8c\u7ef4\u6570\u636e\u96c6\u6269\u5c55\u4e3a\u4e09\u7ef4\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6279\u91cf\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n<p><h3>\u603b\u7ed3<\/h3>\n<\/p>\n<p><p><strong>\u901a\u8fc7\u4f7f\u7528NumPy\u5e93\u3001\u5e7f\u64ad\u673a\u5236\u3001\u76f4\u63a5\u5d4c\u5957\u5217\u8868\u548creshape\u51fd\u6570\u7b49\u65b9\u6cd5<\/strong>\uff0c\u53ef\u4ee5\u5c06\u4e8c\u7ef4\u77e9\u9635\u8d4b\u503c\u5230\u4e09\u7ef4\u6570\u7ec4\u4e2d\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u7279\u5b9a\u7684\u5e94\u7528\u573a\u666f\u548c\u4f18\u52bf\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5927\u5927\u63d0\u9ad8\u4ee3\u7801\u7684\u6548\u7387\u548c\u53ef\u8bfb\u6027\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5c06\u4e8c\u7ef4\u77e9\u9635\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u8f7b\u677e\u5730\u5c06\u4e8c\u7ef4\u77e9\u9635\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u3002\u9996\u5148\uff0c\u786e\u4fdd\u60a8\u5df2\u7ecf\u5b89\u88c5\u4e86NumPy\u5e93\u3002\u7136\u540e\uff0c\u4f7f\u7528<code>numpy.reshape()<\/code>\u51fd\u6570\u5c06\u4e8c\u7ef4\u77e9\u9635\u91cd\u5851\u4e3a\u4e09\u7ef4\u6570\u7ec4\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u91cd\u5851\u540e\u7684\u6570\u7ec4\u7684\u603b\u5143\u7d20\u6570\u91cf\u5fc5\u987b\u4e0e\u539f\u59cb\u6570\u7ec4\u76f8\u540c\u3002<\/p>\n<p><strong>\u5728\u8d4b\u503c\u8fc7\u7a0b\u4e2d\uff0c\u5982\u4f55\u786e\u4fdd\u6570\u636e\u7684\u5b8c\u6574\u6027\uff1f<\/strong><br \/>\u5728\u8f6c\u6362\u4e8c\u7ef4\u77e9\u9635\u4e3a\u4e09\u7ef4\u6570\u7ec4\u65f6\uff0c\u786e\u4fdd\u539f\u59cb\u6570\u636e\u7684\u5b8c\u6574\u6027\u81f3\u5173\u91cd\u8981\u3002\u60a8\u53ef\u4ee5\u901a\u8fc7\u68c0\u67e5\u539f\u59cb\u77e9\u9635\u7684\u5f62\u72b6\u548c\u91cd\u5851\u540e\u7684\u5f62\u72b6\u662f\u5426\u5339\u914d\u6765\u9a8c\u8bc1\u6570\u636e\u7684\u5b8c\u6574\u6027\u3002\u540c\u65f6\uff0c\u4f7f\u7528<code>.shape<\/code>\u5c5e\u6027\u53ef\u4ee5\u5e2e\u52a9\u60a8\u786e\u8ba4\u8f6c\u6362\u540e\u7684\u6570\u7ec4\u7684\u7ef4\u5ea6\u662f\u5426\u7b26\u5408\u9884\u671f\u3002<\/p>\n<p><strong>\u6709\u6ca1\u6709\u793a\u4f8b\u4ee3\u7801\u53ef\u4ee5\u53c2\u8003\uff1f<\/strong><br \/>\u5f53\u7136\uff01\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a  <\/p>\n<pre><code class=\"language-python\">import numpy as np\n\n# \u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u9635\nmatrix_2d = np.array([[1, 2], [3, 4]])\n\n# \u5c06\u4e8c\u7ef4\u77e9\u9635\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\nmatrix_3d = matrix_2d.reshape((2, 1, 2))  # \u8fd9\u91cc\u7684\u53c2\u6570\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8c03\u6574\nprint(matrix_3d)\n<\/code><\/pre>\n<p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u60a8\u53ef\u4ee5\u770b\u5230\u5982\u4f55\u5c06\u4e00\u4e2a2&#215;2\u7684\u4e8c\u7ef4\u77e9\u9635\u91cd\u5851\u4e3a\u4e00\u4e2a2x1x2\u7684\u4e09\u7ef4\u6570\u7ec4\u3002\u6839\u636e\u5b9e\u9645\u9700\u6c42\uff0c\u60a8\u53ef\u4ee5\u8c03\u6574<code>reshape<\/code>\u4e2d\u7684\u53c2\u6570\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u8981\u5c06\u4e8c\u7ef4\u77e9\u9635\u8d4b\u503c\u7ed9\u4e09\u7ef4Python\u6570\u7ec4\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u3001\u901a\u8fc7\u6269\u5c55\u7ef4\u5ea6\u3001\u5e7f\u64ad\u6216\u76f4\u63a5\u5d4c\u5957\u7b49\u65b9\u6cd5\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684 [&hellip;]","protected":false},"author":3,"featured_media":1145165,"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\/1145155"}],"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=1145155"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1145155\/revisions"}],"predecessor-version":[{"id":1145167,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1145155\/revisions\/1145167"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1145165"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1145155"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1145155"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1145155"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}