{"id":1045615,"date":"2024-12-31T13:25:11","date_gmt":"2024-12-31T05:25:11","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1045615.html"},"modified":"2024-12-31T13:25:14","modified_gmt":"2024-12-31T05:25:14","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86%e7%9f%a9%e9%98%b5%e8%be%93%e5%87%ba%e4%b8%ba%e5%9b%be%e5%83%8f","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1045615.html","title":{"rendered":"python\u5982\u4f55\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/e243ccdf-ae41-49aa-b25a-60e46b102bd6.webp?x-oss-process=image\/auto-orient,1\/format,webp\" alt=\"python\u5982\u4f55\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf\" \/><\/p>\n<p><p> <strong>Python\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf\u7684\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Pillow\u5e93\u3001\u4f7f\u7528OpenCV\u5e93\u3002<\/strong>\u8fd9\u4e09\u79cd\u65b9\u6cd5\u90fd\u53ef\u4ee5\u5c06\u77e9\u9635\u6570\u636e\u8f6c\u6362\u5e76\u4fdd\u5b58\u4e3a\u56fe\u50cf\u6587\u4ef6\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e09\u79cd\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528Matplotlib\u5e93<\/h3>\n<\/p>\n<p><p>Matplotlib\u662f\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684\u7ed8\u56fe\u5e93\uff0c\u9002\u7528\u4e8e\u5404\u79cd\u56fe\u5f62\u7684\u7ed8\u5236\uff0c\u5305\u62ec\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf\u3002\u4f7f\u7528Matplotlib\u5e93\u53ef\u4ee5\u975e\u5e38\u65b9\u4fbf\u5730\u5c06\u77e9\u9635\u6570\u636e\u8f6c\u6362\u4e3a\u56fe\u50cf\u3002<\/p>\n<\/p>\n<p><h4>1.1 \u5b89\u88c5Matplotlib\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\u9700\u8981\u786e\u4fdd\u5b89\u88c5\u4e86Matplotlib\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install matplotlib<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>1.2 \u4f7f\u7528Matplotlib\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6f14\u793a\u5982\u4f55\u4f7f\u7528Matplotlib\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf\u5e76\u4fdd\u5b58\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u77e9\u9635<\/strong><\/h2>\n<p>matrix = np.random.rand(10, 10)<\/p>\n<h2><strong>\u4f7f\u7528imshow\u51fd\u6570\u5c06\u77e9\u9635\u7ed8\u5236\u4e3a\u56fe\u50cf<\/strong><\/h2>\n<p>plt.imshow(matrix, cmap=&#39;viridis&#39;)<\/p>\n<h2><strong>\u6dfb\u52a0\u989c\u8272\u6761<\/strong><\/h2>\n<p>plt.colorbar()<\/p>\n<h2><strong>\u4fdd\u5b58\u56fe\u50cf\u5230\u6587\u4ef6<\/strong><\/h2>\n<p>plt.savefig(&#39;matrix_image.png&#39;)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li><strong>\u521b\u5efa\u77e9\u9635<\/strong>\uff1a\u9996\u5148\u521b\u5efa\u4e00\u4e2a\u968f\u673a\u77e9\u9635\u4f5c\u4e3a\u793a\u4f8b\u6570\u636e\u3002<\/li>\n<li><strong>\u7ed8\u5236\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>plt.imshow()<\/code>\u51fd\u6570\u5c06\u77e9\u9635\u6570\u636e\u7ed8\u5236\u4e3a\u56fe\u50cf\uff0c\u5e76\u8bbe\u7f6e\u989c\u8272\u6620\u5c04\u4e3a<code>viridis<\/code>\u3002<\/li>\n<li><strong>\u6dfb\u52a0\u989c\u8272\u6761<\/strong>\uff1a\u4f7f\u7528<code>plt.colorbar()<\/code>\u51fd\u6570\u6dfb\u52a0\u989c\u8272\u6761\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u7406\u89e3\u77e9\u9635\u6570\u636e\u7684\u503c\u3002<\/li>\n<li><strong>\u4fdd\u5b58\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>plt.savefig()<\/code>\u51fd\u6570\u5c06\u56fe\u50cf\u4fdd\u5b58\u4e3a\u6587\u4ef6\u3002<\/li>\n<li><strong>\u663e\u793a\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>plt.show()<\/code>\u51fd\u6570\u663e\u793a\u56fe\u50cf\u3002<\/li>\n<\/ul>\n<p><h3>\u4e8c\u3001\u4f7f\u7528Pillow\u5e93<\/h3>\n<\/p>\n<p><p>Pillow\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u53ef\u4ee5\u5904\u7406\u5404\u79cd\u56fe\u50cf\u64cd\u4f5c\u3002\u4f7f\u7528Pillow\u5e93\u4e5f\u53ef\u4ee5\u5c06\u77e9\u9635\u6570\u636e\u8f6c\u6362\u4e3a\u56fe\u50cf\u3002<\/p>\n<\/p>\n<p><h4>2.1 \u5b89\u88c5Pillow\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\u9700\u8981\u786e\u4fdd\u5b89\u88c5\u4e86Pillow\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\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><h4>2.2 \u4f7f\u7528Pillow\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6f14\u793a\u5982\u4f55\u4f7f\u7528Pillow\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf\u5e76\u4fdd\u5b58\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from PIL import Image<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u77e9\u9635<\/strong><\/h2>\n<p>matrix = np.random.rand(10, 10) * 255<\/p>\n<p>matrix = matrix.astype(np.uint8)<\/p>\n<h2><strong>\u5c06\u77e9\u9635\u8f6c\u6362\u4e3a\u56fe\u50cf<\/strong><\/h2>\n<p>image = Image.fromarray(matrix)<\/p>\n<h2><strong>\u4fdd\u5b58\u56fe\u50cf\u5230\u6587\u4ef6<\/strong><\/h2>\n<p>image.save(&#39;matrix_image.png&#39;)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n<p>image.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li><strong>\u521b\u5efa\u77e9\u9635<\/strong>\uff1a\u9996\u5148\u521b\u5efa\u4e00\u4e2a\u968f\u673a\u77e9\u9635\u4f5c\u4e3a\u793a\u4f8b\u6570\u636e\uff0c\u5e76\u5c06\u5176\u503c\u7f29\u653e\u52300\u5230255\u4e4b\u95f4\uff0c\u540c\u65f6\u8f6c\u6362\u4e3a\u65e0\u7b26\u53f78\u4f4d\u6574\u6570\u7c7b\u578b\u3002<\/li>\n<li><strong>\u8f6c\u6362\u4e3a\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>Image.fromarray()<\/code>\u51fd\u6570\u5c06\u77e9\u9635\u6570\u636e\u8f6c\u6362\u4e3a\u56fe\u50cf\u5bf9\u8c61\u3002<\/li>\n<li><strong>\u4fdd\u5b58\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>image.save()<\/code>\u51fd\u6570\u5c06\u56fe\u50cf\u4fdd\u5b58\u4e3a\u6587\u4ef6\u3002<\/li>\n<li><strong>\u663e\u793a\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>image.show()<\/code>\u51fd\u6570\u663e\u793a\u56fe\u50cf\u3002<\/li>\n<\/ul>\n<p><h3>\u4e09\u3001\u4f7f\u7528OpenCV\u5e93<\/h3>\n<\/p>\n<p><p>OpenCV\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u4f7f\u7528OpenCV\u5e93\u4e5f\u53ef\u4ee5\u5c06\u77e9\u9635\u6570\u636e\u8f6c\u6362\u4e3a\u56fe\u50cf\u3002<\/p>\n<\/p>\n<p><h4>3.1 \u5b89\u88c5OpenCV\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\u9700\u8981\u786e\u4fdd\u5b89\u88c5\u4e86OpenCV\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install opencv-python<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3.2 \u4f7f\u7528OpenCV\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6f14\u793a\u5982\u4f55\u4f7f\u7528OpenCV\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf\u5e76\u4fdd\u5b58\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import cv2<\/p>\n<p>import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u77e9\u9635<\/strong><\/h2>\n<p>matrix = np.random.rand(10, 10) * 255<\/p>\n<p>matrix = matrix.astype(np.uint8)<\/p>\n<h2><strong>\u5c06\u77e9\u9635\u8f6c\u6362\u4e3a\u56fe\u50cf<\/strong><\/h2>\n<p>image = cv2.applyColorMap(matrix, cv2.COLORMAP_JET)<\/p>\n<h2><strong>\u4fdd\u5b58\u56fe\u50cf\u5230\u6587\u4ef6<\/strong><\/h2>\n<p>cv2.imwrite(&#39;matrix_image.png&#39;, image)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imshow(&#39;Matrix 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<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li><strong>\u521b\u5efa\u77e9\u9635<\/strong>\uff1a\u9996\u5148\u521b\u5efa\u4e00\u4e2a\u968f\u673a\u77e9\u9635\u4f5c\u4e3a\u793a\u4f8b\u6570\u636e\uff0c\u5e76\u5c06\u5176\u503c\u7f29\u653e\u52300\u5230255\u4e4b\u95f4\uff0c\u540c\u65f6\u8f6c\u6362\u4e3a\u65e0\u7b26\u53f78\u4f4d\u6574\u6570\u7c7b\u578b\u3002<\/li>\n<li><strong>\u8f6c\u6362\u4e3a\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>cv2.applyColorMap()<\/code>\u51fd\u6570\u5c06\u77e9\u9635\u6570\u636e\u8f6c\u6362\u4e3a\u5f69\u8272\u56fe\u50cf\uff0c\u5e76\u5e94\u7528\u989c\u8272\u6620\u5c04\u3002<\/li>\n<li><strong>\u4fdd\u5b58\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>cv2.imwrite()<\/code>\u51fd\u6570\u5c06\u56fe\u50cf\u4fdd\u5b58\u4e3a\u6587\u4ef6\u3002<\/li>\n<li><strong>\u663e\u793a\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528<code>cv2.imshow()<\/code>\u51fd\u6570\u663e\u793a\u56fe\u50cf\uff0c\u5e76\u4f7f\u7528<code>cv2.waitKey()<\/code>\u51fd\u6570\u7b49\u5f85\u952e\u76d8\u8f93\u5165\u4ee5\u5173\u95ed\u7a97\u53e3\u3002<\/li>\n<\/ul>\n<p><h3>\u56db\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u4ee5\u4e0a\u4ecb\u7ecd\u4e86\u4e09\u79cd\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf\u7684\u65b9\u6cd5\uff0c\u5206\u522b\u662f\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Pillow\u5e93\u548c\u4f7f\u7528OpenCV\u5e93\u3002<strong>Matplotlib\u9002\u7528\u4e8e\u5404\u79cd\u56fe\u5f62\u7684\u7ed8\u5236\uff0cPillow\u9002\u7528\u4e8e\u56fe\u50cf\u5904\u7406\uff0cOpenCV\u9002\u7528\u4e8e\u8ba1\u7b97\u673a\u89c6\u89c9\u3002<\/strong>\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u9ad8\u6548\u5730\u5c06\u77e9\u9635\u6570\u636e\u8f6c\u6362\u4e3a\u56fe\u50cf\u5e76\u4fdd\u5b58\u3002\u65e0\u8bba\u662f\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3001\u56fe\u50cf\u5904\u7406\u8fd8\u662f\u8ba1\u7b97\u673a\u89c6\u89c9\u5e94\u7528\uff0c\u8fd9\u4e9b\u65b9\u6cd5\u90fd\u80fd\u6ee1\u8db3\u4e0d\u540c\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u5c06\u77e9\u9635\u8f6c\u6362\u4e3a\u56fe\u50cf\uff1f<\/strong><\/p>\n<p>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u4e2a\u5e93\u5c06\u77e9\u9635\u8f6c\u6362\u4e3a\u56fe\u50cf\u3002\u5176\u4e2d\uff0c\u6700\u5e38\u7528\u7684\u5e93\u5305\u62ecNumPy\u548cMatplotlib\u3002\u9996\u5148\uff0c\u901a\u8fc7NumPy\u521b\u5efa\u4e00\u4e2a\u77e9\u9635\uff0c\u7136\u540e\u4f7f\u7528Matplotlib\u7684<code>imshow()<\/code>\u51fd\u6570\u5c06\u8be5\u77e9\u9635\u53ef\u89c6\u5316\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\nimport matplotlib.pyplot as plt\n\n# \u521b\u5efa\u4e00\u4e2a\u968f\u673a\u77e9\u9635\nmatrix = np.random.rand(10, 10)\n\n# \u4f7f\u7528imshow()\u51fd\u6570\u663e\u793a\u77e9\u9635\nplt.imshow(matrix, cmap=&#39;gray&#39;)\nplt.colorbar()  # \u6dfb\u52a0\u989c\u8272\u6761\nplt.show()\n<\/code><\/pre>\n<p>\u8fd9\u4e2a\u4ee3\u7801\u7247\u6bb5\u5c06\u751f\u6210\u4e00\u4e2a10&#215;10\u7684\u968f\u673a\u77e9\u9635\uff0c\u5e76\u5c06\u5176\u4ee5\u7070\u5ea6\u56fe\u7684\u5f62\u5f0f\u5c55\u793a\u3002<\/p>\n<p><strong>\u5728Python\u4e2d\u5982\u4f55\u8c03\u6574\u8f93\u51fa\u56fe\u50cf\u7684\u989c\u8272\u6620\u5c04\uff1f<\/strong><\/p>\n<p>\u5728\u751f\u6210\u56fe\u50cf\u65f6\uff0c\u989c\u8272\u6620\u5c04\u662f\u4e00\u4e2a\u91cd\u8981\u7684\u53c2\u6570\uff0c\u5b83\u53ef\u4ee5\u5f71\u54cd\u56fe\u50cf\u7684\u89c6\u89c9\u6548\u679c\u3002\u4f7f\u7528Matplotlib\u7684<code>cmap<\/code>\u53c2\u6570\u53ef\u4ee5\u8f7b\u677e\u8c03\u6574\u989c\u8272\u6620\u5c04\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528<code>cmap=&#39;hot&#39;<\/code>\u3001<code>cmap=&#39;viridis&#39;<\/code>\u7b49\u4e0d\u540c\u7684\u9009\u9879\u6765\u6539\u53d8\u56fe\u50cf\u7684\u989c\u8272\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<pre><code class=\"language-python\">plt.imshow(matrix, cmap=&#39;viridis&#39;)  # \u4f7f\u7528viridis\u989c\u8272\u6620\u5c04\nplt.colorbar()\nplt.show()\n<\/code><\/pre>\n<p>\u4e0d\u540c\u7684\u989c\u8272\u6620\u5c04\u9002\u7528\u4e8e\u4e0d\u540c\u7c7b\u578b\u7684\u6570\u636e\uff0c\u9009\u62e9\u5408\u9002\u7684\u989c\u8272\u6620\u5c04\u53ef\u4ee5\u66f4\u597d\u5730\u5c55\u793a\u6570\u636e\u7684\u7279\u5f81\u3002<\/p>\n<p><strong>\u5982\u4f55\u4fdd\u5b58\u751f\u6210\u7684\u56fe\u50cf\u5230\u6587\u4ef6\uff1f<\/strong><\/p>\n<p>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684<code>savefig()<\/code>\u51fd\u6570\u5c06\u751f\u6210\u7684\u56fe\u50cf\u4fdd\u5b58\u4e3a\u6587\u4ef6\u3002\u53ef\u4ee5\u9009\u62e9\u591a\u79cd\u6587\u4ef6\u683c\u5f0f\uff0c\u5982PNG\u3001JPEG\u7b49\u3002\u5728\u663e\u793a\u56fe\u50cf\u4e4b\u524d\u8c03\u7528<code>savefig()<\/code>\u51fd\u6570\u5373\u53ef\u3002\u4f8b\u5982\uff1a<\/p>\n<pre><code class=\"language-python\">plt.imshow(matrix, cmap=&#39;gray&#39;)\nplt.colorbar()\nplt.savefig(&#39;matrix_image.png&#39;)  # \u4fdd\u5b58\u4e3aPNG\u683c\u5f0f\nplt.show()\n<\/code><\/pre>\n<p>\u8fd9\u79cd\u65b9\u5f0f\u5141\u8bb8\u7528\u6237\u5c06\u751f\u6210\u7684\u56fe\u50cf\u4fdd\u5b58\u4ee5\u4fbf\u4e8e\u540e\u7eed\u4f7f\u7528\u6216\u5206\u4eab\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5c06\u77e9\u9635\u8f93\u51fa\u4e3a\u56fe\u50cf\u7684\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Pillow\u5e93\u3001\u4f7f\u7528OpenCV\u5e93\u3002\u8fd9\u4e09 [&hellip;]","protected":false},"author":3,"featured_media":1045629,"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\/1045615"}],"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=1045615"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1045615\/revisions"}],"predecessor-version":[{"id":1045632,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1045615\/revisions\/1045632"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1045629"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1045615"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1045615"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1045615"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}