{"id":1021176,"date":"2024-12-27T13:19:56","date_gmt":"2024-12-27T05:19:56","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1021176.html"},"modified":"2024-12-27T13:19:59","modified_gmt":"2024-12-27T05:19:59","slug":"python%e4%b8%ad%e5%a6%82%e4%bd%95%e5%90%88%e5%b9%b6%e5%9b%be%e5%83%8f","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1021176.html","title":{"rendered":"python\u4e2d\u5982\u4f55\u5408\u5e76\u56fe\u50cf"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25163447\/97dc12ed-dfde-4f32-9539-2fda9facae67.webp\" alt=\"python\u4e2d\u5982\u4f55\u5408\u5e76\u56fe\u50cf\" \/><\/p>\n<p><p> \u5728Python\u4e2d\u5408\u5e76\u56fe\u50cf\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6765\u5b9e\u73b0\uff0c<strong>\u5e38\u89c1\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528Pillow\u5e93\u3001OpenCV\u5e93\u3001NumPy\u5e93<\/strong>\u3002\u8fd9\u4e9b\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\uff0c\u80fd\u6ee1\u8db3\u5927\u591a\u6570\u7684\u56fe\u50cf\u5408\u5e76\u9700\u6c42\u3002\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f\u4f7f\u7528Pillow\u5e93\uff0c\u56e0\u4e3a\u5b83\u7b80\u5355\u6613\u7528\uff0c\u540c\u65f6\u4e5f\u80fd\u5f88\u597d\u5730\u5904\u7406\u56fe\u50cf\u5408\u5e76\u7684\u4efb\u52a1\u3002<\/p>\n<\/p>\n<p><p><strong>\u4f7f\u7528Pillow\u5e93\u5408\u5e76\u56fe\u50cf<\/strong>\uff1aPillow\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u5b83\u652f\u6301\u591a\u79cd\u56fe\u50cf\u683c\u5f0f\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u56fe\u50cf\u5408\u5e76\u64cd\u4f5c\u3002\u5408\u5e76\u56fe\u50cf\u65f6\uff0c\u53ef\u4ee5\u5c06\u591a\u5f20\u56fe\u50cf\u6309\u7167\u6c34\u5e73\u65b9\u5411\u6216\u5782\u76f4\u65b9\u5411\u62fc\u63a5\u5728\u4e00\u8d77\u3002\u4e0b\u9762\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u4f7f\u7528Pillow\u5e93\u6765\u5408\u5e76\u56fe\u50cf\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001PILLOW\u5e93\u7684\u57fa\u672c\u4ecb\u7ecd<\/h3>\n<\/p>\n<p><p>Pillow\u662fPython Imaging Library\uff08PIL\uff09\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u5b83\u4e3aPython\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7b80\u6d01\u7684\u56fe\u50cf\u5904\u7406\u80fd\u529b\u3002Pillow\u53ef\u4ee5\u5904\u7406\u591a\u79cd\u56fe\u50cf\u6587\u4ef6\u683c\u5f0f\uff0c\u5982JPEG\u3001PNG\u3001BMP\u7b49\uff0c\u652f\u6301\u56fe\u50cf\u7684\u6253\u5f00\u3001\u4fdd\u5b58\u3001\u8f6c\u6362\u3001\u5904\u7406\u53ca\u5408\u5e76\u7b49\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><h4>1. \u5b89\u88c5Pillow\u5e93<\/h4>\n<\/p>\n<p><p>\u5728Python\u73af\u5883\u4e2d\u5b89\u88c5Pillow\u5e93\u975e\u5e38\u7b80\u5355\uff0c\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\u5c31\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Pillow\u5e93\uff0c\u5e76\u4f7f\u7528\u5176\u529f\u80fd\u3002<\/p>\n<\/p>\n<p><h4>2. Pillow\u5e93\u7684\u57fa\u672c\u529f\u80fd<\/h4>\n<\/p>\n<p><p>Pillow\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\uff0c\u5305\u62ec\u56fe\u50cf\u7684\u6253\u5f00\u3001\u663e\u793a\u3001\u4fdd\u5b58\u3001\u683c\u5f0f\u8f6c\u6362\u3001\u5927\u5c0f\u8c03\u6574\u3001\u65cb\u8f6c\u3001\u88c1\u526a\u3001\u6ee4\u955c\u5e94\u7528\u7b49\u3002\u5bf9\u4e8e\u56fe\u50cf\u5408\u5e76\uff0cPillow\u63d0\u4f9b\u4e86\u4e00\u79cd\u7b80\u5355\u7684\u65b9\u5f0f\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528PILLOW\u5e93\u5408\u5e76\u56fe\u50cf<\/h3>\n<\/p>\n<p><p>\u4f7f\u7528Pillow\u5e93\u5408\u5e76\u56fe\u50cf\u4e3b\u8981\u6d89\u53ca\u5230\u51e0\u4e2a\u6b65\u9aa4\uff1a\u52a0\u8f7d\u56fe\u50cf\u3001\u521b\u5efa\u65b0\u56fe\u50cf\u3001\u5408\u5e76\u56fe\u50cf\u3001\u4fdd\u5b58\u5408\u5e76\u540e\u7684\u56fe\u50cf\u3002<\/p>\n<\/p>\n<p><h4>1. \u52a0\u8f7d\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u9700\u8981\u4f7f\u7528Pillow\u5e93\u7684<code>Image<\/code>\u6a21\u5757\u6765\u52a0\u8f7d\u8981\u5408\u5e76\u7684\u56fe\u50cf\u6587\u4ef6\u3002\u53ef\u4ee5\u4f7f\u7528<code>Image.open()<\/code>\u65b9\u6cd5\u6765\u6253\u5f00\u56fe\u50cf\u6587\u4ef6\uff0c\u5e76\u8fd4\u56de\u4e00\u4e2a\u56fe\u50cf\u5bf9\u8c61\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from PIL import Image<\/p>\n<h2><strong>\u6253\u5f00\u56fe\u50cf\u6587\u4ef6<\/strong><\/h2>\n<p>image1 = Image.open(&#39;path\/to\/image1.jpg&#39;)<\/p>\n<p>image2 = Image.open(&#39;path\/to\/image2.jpg&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u521b\u5efa\u65b0\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u9700\u8981\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u56fe\u50cf\u5bf9\u8c61\u6765\u5b58\u653e\u5408\u5e76\u540e\u7684\u56fe\u50cf\u3002\u53ef\u4ee5\u6839\u636e\u9700\u8981\u5408\u5e76\u7684\u65b9\u5411\uff08\u6c34\u5e73\u6216\u5782\u76f4\uff09\uff0c\u8ba1\u7b97\u65b0\u56fe\u50cf\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6<\/p>\n<p>width1, height1 = image1.size<\/p>\n<p>width2, height2 = image2.size<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u56fe\u50cf\u5bf9\u8c61\uff0c\u5bbd\u5ea6\u4e3a\u4e24\u5f20\u56fe\u50cf\u7684\u5bbd\u5ea6\u4e4b\u548c\uff0c\u9ad8\u5ea6\u4e3a\u4e24\u5f20\u56fe\u50cf\u7684\u6700\u5927\u9ad8\u5ea6<\/strong><\/h2>\n<p>new_image = Image.new(&#39;RGB&#39;, (width1 + width2, max(height1, height2)))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3. \u5408\u5e76\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528<code>paste()<\/code>\u65b9\u6cd5\u5c06\u56fe\u50cf\u7c98\u8d34\u5230\u65b0\u521b\u5efa\u7684\u56fe\u50cf\u5bf9\u8c61\u4e0a\u3002\u6839\u636e\u5408\u5e76\u65b9\u5411\uff0c\u5c06\u56fe\u50cf\u7c98\u8d34\u5230\u76f8\u5e94\u7684\u4f4d\u7f6e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5728\u65b0\u56fe\u50cf\u4e0a\u7c98\u8d34\u7b2c\u4e00\u5f20\u56fe\u50cf<\/p>\n<p>new_image.paste(image1, (0, 0))<\/p>\n<h2><strong>\u5728\u65b0\u56fe\u50cf\u4e0a\u7c98\u8d34\u7b2c\u4e8c\u5f20\u56fe\u50cf\uff0c\u4f4d\u7f6e\u4e3a\u7b2c\u4e00\u5f20\u56fe\u50cf\u7684\u53f3\u8fb9<\/strong><\/h2>\n<p>new_image.paste(image2, (width1, 0))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4. \u4fdd\u5b58\u5408\u5e76\u540e\u7684\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>\u6700\u540e\uff0c\u4f7f\u7528<code>save()<\/code>\u65b9\u6cd5\u4fdd\u5b58\u5408\u5e76\u540e\u7684\u56fe\u50cf\u5230\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u4fdd\u5b58\u5408\u5e76\u540e\u7684\u56fe\u50cf<\/p>\n<p>new_image.save(&#39;path\/to\/merged_image.jpg&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528OPENCV\u5e93\u5408\u5e76\u56fe\u50cf<\/h3>\n<\/p>\n<p><p>OpenCV\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\u3002\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u548c\u89c6\u9891\u5904\u7406\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u4e8e\u5b9e\u65f6\u7684\u56fe\u50cf\u5408\u5e76\u3002<\/p>\n<\/p>\n<p><h4>1. \u5b89\u88c5OpenCV\u5e93<\/h4>\n<\/p>\n<p><p>\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u5b89\u88c5OpenCV\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><h4>2. \u4f7f\u7528OpenCV\u5408\u5e76\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>OpenCV\u63d0\u4f9b\u4e86<code>cv2.hconcat()<\/code>\u548c<code>cv2.vconcat()<\/code>\u65b9\u6cd5\uff0c\u5206\u522b\u7528\u4e8e\u6c34\u5e73\u5408\u5e76\u548c\u5782\u76f4\u5408\u5e76\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>image1 = cv2.imread(&#39;path\/to\/image1.jpg&#39;)<\/p>\n<p>image2 = cv2.imread(&#39;path\/to\/image2.jpg&#39;)<\/p>\n<h2><strong>\u6c34\u5e73\u5408\u5e76\u56fe\u50cf<\/strong><\/h2>\n<p>merged_image_horizontal = cv2.hconcat([image1, image2])<\/p>\n<h2><strong>\u5782\u76f4\u5408\u5e76\u56fe\u50cf<\/strong><\/h2>\n<p>merged_image_vertical = cv2.vconcat([image1, image2])<\/p>\n<h2><strong>\u4fdd\u5b58\u5408\u5e76\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imwrite(&#39;path\/to\/merged_image_horizontal.jpg&#39;, merged_image_horizontal)<\/p>\n<p>cv2.imwrite(&#39;path\/to\/merged_image_vertical.jpg&#39;, merged_image_vertical)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u4f7f\u7528NUMPY\u5e93\u5408\u5e76\u56fe\u50cf<\/h3>\n<\/p>\n<p><p>NumPy\u662f\u4e00\u4e2a\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\u3002\u53ef\u4ee5\u4f7f\u7528NumPy\u6765\u5bf9\u56fe\u50cf\u8fdb\u884c\u5408\u5e76\uff0c\u5c24\u5176\u662f\u5728\u9700\u8981\u5bf9\u56fe\u50cf\u8fdb\u884c\u590d\u6742\u7684\u6570\u5b66\u64cd\u4f5c\u65f6\u3002<\/p>\n<\/p>\n<p><h4>1. \u5b89\u88c5NumPy\u5e93<\/h4>\n<\/p>\n<p><p>\u540c\u6837\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u5b89\u88c5NumPy\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u4f7f\u7528NumPy\u5408\u5e76\u56fe\u50cf<\/h4>\n<\/p>\n<p><p>\u5728\u4f7f\u7528NumPy\u5408\u5e76\u56fe\u50cf\u65f6\uff0c\u9996\u5148\u9700\u8981\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3aNumPy\u6570\u7ec4\uff0c\u7136\u540e\u4f7f\u7528<code>numpy.concatenate()<\/code>\u65b9\u6cd5\u8fdb\u884c\u5408\u5e76\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<\/strong><\/h2>\n<p>image1 = cv2.imread(&#39;path\/to\/image1.jpg&#39;)<\/p>\n<p>image2 = cv2.imread(&#39;path\/to\/image2.jpg&#39;)<\/p>\n<h2><strong>\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3aNumPy\u6570\u7ec4<\/strong><\/h2>\n<p>array1 = np.array(image1)<\/p>\n<p>array2 = np.array(image2)<\/p>\n<h2><strong>\u6c34\u5e73\u5408\u5e76\u56fe\u50cf<\/strong><\/h2>\n<p>merged_array_horizontal = np.concatenate((array1, array2), axis=1)<\/p>\n<h2><strong>\u5782\u76f4\u5408\u5e76\u56fe\u50cf<\/strong><\/h2>\n<p>merged_array_vertical = np.concatenate((array1, array2), axis=0)<\/p>\n<h2><strong>\u4fdd\u5b58\u5408\u5e76\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n<p>cv2.imwrite(&#39;path\/to\/merged_image_horizontal_numpy.jpg&#39;, merged_array_horizontal)<\/p>\n<p>cv2.imwrite(&#39;path\/to\/merged_image_vertical_numpy.jpg&#39;, merged_array_vertical)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u5408\u5e76\u56fe\u50cf\u7684\u5b9e\u9645\u5e94\u7528<\/h3>\n<\/p>\n<p><p>\u56fe\u50cf\u5408\u5e76\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u6709\u5f88\u591a\u573a\u666f\uff0c\u6bd4\u5982\u521b\u5efa\u62fc\u63a5\u56fe\u3001\u5bf9\u6bd4\u56fe\u3001\u56fe\u50cf\u62fc\u63a5\u7b49\u3002\u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u8fd9\u4e9b\u529f\u80fd\u3002<\/p>\n<\/p>\n<p><h4>1. \u521b\u5efa\u62fc\u63a5\u56fe<\/h4>\n<\/p>\n<p><p>\u5728\u7535\u5546\u7f51\u7ad9\u4e0a\uff0c\u7ecf\u5e38\u9700\u8981\u5c06\u591a\u4e2a\u4ea7\u54c1\u56fe\u7247\u62fc\u63a5\u5728\u4e00\u8d77\uff0c\u5f62\u6210\u4e00\u5f20\u62fc\u63a5\u56fe\u3002\u53ef\u4ee5\u4f7f\u7528Pillow\u6216OpenCV\u5e93\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><h4>2. \u751f\u6210\u5bf9\u6bd4\u56fe<\/h4>\n<\/p>\n<p><p>\u5728\u56fe\u50cf\u5904\u7406\u6216\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u7ed3\u679c\u5c55\u793a\u4e2d\uff0c\u7ecf\u5e38\u9700\u8981\u5c06\u539f\u59cb\u56fe\u50cf\u548c\u5904\u7406\u540e\u56fe\u50cf\u8fdb\u884c\u5bf9\u6bd4\u3002\u53ef\u4ee5\u901a\u8fc7\u5408\u5e76\u4e24\u5f20\u56fe\u50cf\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><h4>3. \u56fe\u50cf\u62fc\u63a5<\/h4>\n<\/p>\n<p><p>\u5728\u5168\u666f\u56fe\u7684\u5236\u4f5c\u4e2d\uff0c\u9700\u8981\u5c06\u591a\u5f20\u56fe\u50cf\u62fc\u63a5\u5728\u4e00\u8d77\uff0c\u5f62\u6210\u4e00\u5f20\u5b8c\u6574\u7684\u5168\u666f\u56fe\u3002\u53ef\u4ee5\u4f7f\u7528OpenCV\u5e93\u7684\u56fe\u50cf\u62fc\u63a5\u529f\u80fd\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><h3>\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u5728Python\u4e2d\u5408\u5e76\u56fe\u50cf\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4f9b\u9009\u62e9\uff0c<strong>Pillow\u5e93\u3001OpenCV\u5e93\u548cNumPy\u5e93\u90fd\u662f\u5f3a\u5927\u7684\u5de5\u5177<\/strong>\uff0c\u5b83\u4eec\u5404\u81ea\u6709\u4e0d\u540c\u7684\u4f18\u7f3a\u70b9\u548c\u9002\u7528\u573a\u666f\u3002\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u548c\u5de5\u5177\uff0c\u53ef\u4ee5\u9ad8\u6548\u5730\u5b8c\u6210\u56fe\u50cf\u5408\u5e76\u4efb\u52a1\u3002\u901a\u8fc7\u638c\u63e1\u8fd9\u4e9b\u6280\u672f\uff0c\u80fd\u591f\u6ee1\u8db3\u5927\u591a\u6570\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\u5728Python\u4e2d\u5408\u5e76\u591a\u5f20\u56fe\u50cf\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528PIL\uff08Pillow\uff09\u5e93\u6765\u5408\u5e76\u591a\u5f20\u56fe\u50cf\u3002\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Pillow\u5e93\uff0c\u53ef\u4ee5\u901a\u8fc7\u547d\u4ee4<code>pip install Pillow<\/code>\u8fdb\u884c\u5b89\u88c5\u3002\u5408\u5e76\u56fe\u50cf\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u6253\u5f00\u56fe\u50cf\u6587\u4ef6\uff0c\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u7a7a\u767d\u56fe\u50cf\uff0c\u63a5\u7740\u5c06\u5404\u4e2a\u56fe\u50cf\u7c98\u8d34\u5230\u7a7a\u767d\u56fe\u50cf\u4e0a\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<pre><code class=\"language-python\">from PIL import Image\n\n# \u6253\u5f00\u56fe\u50cf\nimage1 = Image.open(&#39;image1.jpg&#39;)\nimage2 = Image.open(&#39;image2.jpg&#39;)\n\n# \u521b\u5efa\u4e00\u4e2a\u65b0\u56fe\u50cf\uff0c\u5927\u5c0f\u4e3a\u4e24\u4e2a\u56fe\u50cf\u7684\u5bbd\u5ea6\u4e4b\u548c\u548c\u6700\u5927\u9ad8\u5ea6\nnew_image = Image.new(&#39;RGB&#39;, (image1.width + image2.width, max(image1.height, image2.height)))\n\n# \u7c98\u8d34\u56fe\u50cf\nnew_image.paste(image1, (0, 0))\nnew_image.paste(image2, (image1.width, 0))\n\n# \u4fdd\u5b58\u5408\u5e76\u540e\u7684\u56fe\u50cf\nnew_image.save(&#39;merged_image.jpg&#39;)\n<\/code><\/pre>\n<p><strong>\u5408\u5e76\u56fe\u50cf\u65f6\uff0c\u5982\u4f55\u5904\u7406\u4e0d\u540c\u5927\u5c0f\u7684\u56fe\u50cf\uff1f<\/strong><br \/>\u5904\u7406\u4e0d\u540c\u5927\u5c0f\u7684\u56fe\u50cf\u65f6\uff0c\u53ef\u4ee5\u9009\u62e9\u7f29\u653e\u3001\u88c1\u526a\u6216\u4fdd\u6301\u539f\u59cb\u6bd4\u4f8b\u3002\u4f7f\u7528PIL\u5e93\uff0c\u60a8\u53ef\u4ee5\u8c03\u7528<code>resize()<\/code>\u65b9\u6cd5\u8c03\u6574\u56fe\u50cf\u5927\u5c0f\uff0c\u6216\u8005\u4f7f\u7528<code>crop()<\/code>\u65b9\u6cd5\u88c1\u526a\u56fe\u50cf\u3002\u4f8b\u5982\uff0c\u5982\u679c\u9700\u8981\u5c06\u5c0f\u56fe\u50cf\u653e\u5927\u5230\u4e0e\u5927\u56fe\u50cf\u76f8\u540c\u7684\u9ad8\u5ea6\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<pre><code class=\"language-python\">base_height = image1.height\nimage2 = image2.resize((int((base_height \/ image2.height) * image2.width), base_height))\n<\/code><\/pre>\n<p><strong>\u6709\u6ca1\u6709\u5176\u4ed6\u5e93\u53ef\u4ee5\u7528\u6765\u5408\u5e76\u56fe\u50cf\uff1f<\/strong><br \/>\u9664\u4e86PIL\uff08Pillow\uff09\u4e4b\u5916\uff0cOpenCV\u4e5f\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u53ef\u4ee5\u7528\u6765\u5408\u5e76\u56fe\u50cf\u3002OpenCV\u63d0\u4f9b\u4e86<code>cv2.hconcat()<\/code>\u548c<code>cv2.vconcat()<\/code>\u65b9\u6cd5\uff0c\u5206\u522b\u7528\u4e8e\u6c34\u5e73\u548c\u5782\u76f4\u5408\u5e76\u56fe\u50cf\u3002\u4f7f\u7528OpenCV\u5408\u5e76\u56fe\u50cf\u7684\u4f8b\u5b50\u5982\u4e0b\uff1a<\/p>\n<pre><code class=\"language-python\">import cv2\n\n# \u8bfb\u53d6\u56fe\u50cf\nimage1 = cv2.imread(&#39;image1.jpg&#39;)\nimage2 = cv2.imread(&#39;image2.jpg&#39;)\n\n# \u6c34\u5e73\u5408\u5e76\u56fe\u50cf\nmerged_image = cv2.hconcat([image1, image2])\n\n# \u4fdd\u5b58\u5408\u5e76\u540e\u7684\u56fe\u50cf\ncv2.imwrite(&#39;merged_image.jpg&#39;, merged_image)\n<\/code><\/pre>\n<p>\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u7528\u6237\u53ef\u4ee5\u7075\u6d3b\u5730\u9009\u62e9\u5408\u9002\u7684\u5e93\u548c\u6280\u672f\u6765\u5408\u5e76\u56fe\u50cf\uff0c\u6839\u636e\u4e0d\u540c\u7684\u9700\u6c42\u5904\u7406\u56fe\u50cf\u5408\u5e76\u7684\u5404\u79cd\u60c5\u51b5\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u5408\u5e76\u56fe\u50cf\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6765\u5b9e\u73b0\uff0c\u5e38\u89c1\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528Pillow\u5e93\u3001OpenCV\u5e93\u3001NumPy\u5e93 [&hellip;]","protected":false},"author":3,"featured_media":1021185,"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\/1021176"}],"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=1021176"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1021176\/revisions"}],"predecessor-version":[{"id":1021187,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1021176\/revisions\/1021187"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1021185"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1021176"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1021176"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1021176"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}