{"id":1097033,"date":"2025-01-08T15:07:45","date_gmt":"2025-01-08T07:07:45","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1097033.html"},"modified":"2025-01-08T15:07:46","modified_gmt":"2025-01-08T07:07:46","slug":"cv%e5%a6%82%e4%bd%95%e6%98%be%e7%a4%ba%e4%b8%a4%e5%bc%a0%e5%9b%be%e7%89%87python-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1097033.html","title":{"rendered":"cv\u5982\u4f55\u663e\u793a\u4e24\u5f20\u56fe\u7247python"},"content":{"rendered":"

\"cv\u5982\u4f55\u663e\u793a\u4e24\u5f20\u56fe\u7247python\"<\/p>\n

\u5728Python\u4e2d\u4f7f\u7528OpenCV\u663e\u793a\u4e24\u5f20\u56fe\u7247<\/strong><\/p>\n<\/p>\n

\u5728Python\u4e2d\u4f7f\u7528OpenCV\u663e\u793a\u4e24\u5f20\u56fe\u7247\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u6cd5\u5b9e\u73b0\uff1acv2.imshow\u51fd\u6570\u3001plt.imshow\u51fd\u6570\u3001\u5c06\u4e24\u5f20\u56fe\u7247\u62fc\u63a5\u5728\u4e00\u8d77<\/strong>\u3002\u73b0\u5728\u6211\u4eec\u5c06\u8be6\u7ec6\u63cf\u8ff0\u5176\u4e2d\u4e00\u79cd\u65b9\u6cd5\u2014\u2014\u4f7f\u7528cv2.imshow<\/code>\u51fd\u6570\u6765\u663e\u793a\u4e24\u5f20\u56fe\u7247\u3002<\/p>\n<\/p>\n

\u4f7f\u7528OpenCV\u7684cv2.imshow<\/code>\u51fd\u6570\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u663e\u793a\u56fe\u50cf\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5OpenCV\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n<\/p>\n

pip install opencv-python<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u6b65\u9aa4\u5b9e\u73b0\u663e\u793a\u4e24\u5f20\u56fe\u7247\uff1a<\/p>\n<\/p>\n
\u4e00\u3001\u8bfb\u53d6\u4e0e\u663e\u793a\u56fe\u7247<\/strong><\/p>\n<\/p>\n
import cv2<\/p>\n
\u8bfb\u53d6\u7b2c\u4e00\u5f20\u56fe\u7247<\/strong><\/h2>\n
image1 = cv2.imread('path_to_first_image.jpg')<\/p>\n
\u8bfb\u53d6\u7b2c\u4e8c\u5f20\u56fe\u7247<\/strong><\/h2>\n
image2 = cv2.imread('path_to_second_image.jpg')<\/p>\n
\u663e\u793a\u7b2c\u4e00\u5f20\u56fe\u7247<\/strong><\/h2>\n
cv2.imshow('Image 1', image1)<\/p>\n
\u663e\u793a\u7b2c\u4e8c\u5f20\u56fe\u7247<\/strong><\/h2>\n
cv2.imshow('Image 2', image2)<\/p>\n
\u7b49\u5f85\u7528\u6237\u6309\u952e\u6309\u4e0b<\/strong><\/h2>\n
cv2.wAI<\/a>tKey(0)<\/p>\n
\u9500\u6bc1\u6240\u6709\u7a97\u53e3<\/strong><\/h2>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528cv2.imread<\/code>\u51fd\u6570\u8bfb\u53d6\u4e24\u5f20\u56fe\u7247\uff0c\u5e76\u5206\u522b\u4f7f\u7528cv2.imshow<\/code>\u51fd\u6570\u663e\u793a\u8fd9\u4e24\u5f20\u56fe\u7247\u3002\u6700\u540e\uff0c\u6211\u4eec\u4f7f\u7528cv2.waitKey(0)<\/code>\u7b49\u5f85\u7528\u6237\u6309\u952e\u6309\u4e0b\uff0c\u7136\u540e\u4f7f\u7528cv2.destroyAllWindows<\/code>\u9500\u6bc1\u6240\u6709\u7a97\u53e3\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u5e76\u6392\u663e\u793a\u4e24\u5f20\u56fe\u7247<\/strong><\/p>\n<\/p>\n
\u5982\u679c\u6211\u4eec\u5e0c\u671b\u5c06\u4e24\u5f20\u56fe\u7247\u5e76\u6392\u663e\u793a\uff0c\u53ef\u4ee5\u4f7f\u7528numpy<\/code>\u5e93\u5c06\u4e24\u5f20\u56fe\u7247\u62fc\u63a5\u5728\u4e00\u8d77\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5numpy<\/code>\u5e93\uff1a<\/p>\n<\/p>\n
pip install numpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5b9e\u73b0\u56fe\u7247\u7684\u5e76\u6392\u663e\u793a\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
import numpy as np<\/p>\n
\u8bfb\u53d6\u7b2c\u4e00\u5f20\u56fe\u7247<\/strong><\/h2>\n
image1 = cv2.imread('path_to_first_image.jpg')<\/p>\n
\u8bfb\u53d6\u7b2c\u4e8c\u5f20\u56fe\u7247<\/strong><\/h2>\n
image2 = cv2.imread('path_to_second_image.jpg')<\/p>\n
\u8c03\u6574\u4e24\u5f20\u56fe\u7247\u7684\u5927\u5c0f\uff0c\u4f7f\u5b83\u4eec\u5177\u6709\u76f8\u540c\u7684\u9ad8\u5ea6<\/strong><\/h2>\n
height1, width1 = image1.shape[:3]<\/p>\n
height2, width2 = image2.shape[:3]<\/p>\n
\u8ba1\u7b97\u65b0\u7684\u5bbd\u5ea6<\/strong><\/h2>\n
new_width1 = int(width1 * (height2 \/ height1))<\/p>\n
new_width2 = int(width2 * (height2 \/ height2))<\/p>\n
\u8c03\u6574\u56fe\u7247\u5927\u5c0f<\/strong><\/h2>\n
image1_resized = cv2.resize(image1, (new_width1, height2))<\/p>\n
image2_resized = cv2.resize(image2, (new_width2, height2))<\/p>\n
\u5c06\u4e24\u5f20\u56fe\u7247\u62fc\u63a5\u5728\u4e00\u8d77<\/strong><\/h2>\n
combined_image = np.hstack((image1_resized, image2_resized))<\/p>\n
\u663e\u793a\u62fc\u63a5\u540e\u7684\u56fe\u7247<\/strong><\/h2>\n
cv2.imshow('Combined Image', combined_image)<\/p>\n
\u7b49\u5f85\u7528\u6237\u6309\u952e\u6309\u4e0b<\/strong><\/h2>\n
cv2.waitKey(0)<\/p>\n
\u9500\u6bc1\u6240\u6709\u7a97\u53e3<\/strong><\/h2>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u8bfb\u53d6\u4e24\u5f20\u56fe\u7247\uff0c\u5e76\u8c03\u6574\u5b83\u4eec\u7684\u5927\u5c0f\u4f7f\u5b83\u4eec\u5177\u6709\u76f8\u540c\u7684\u9ad8\u5ea6\u3002\u7136\u540e\uff0c\u6211\u4eec\u4f7f\u7528numpy<\/code>\u5e93\u7684hstack<\/code>\u51fd\u6570\u5c06\u4e24\u5f20\u56fe\u7247\u6c34\u5e73\u62fc\u63a5\u5728\u4e00\u8d77\u3002\u6700\u540e\uff0c\u6211\u4eec\u4f7f\u7528cv2.imshow<\/code>\u51fd\u6570\u663e\u793a\u62fc\u63a5\u540e\u7684\u56fe\u7247\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Matplotlib\u663e\u793a\u4e24\u5f20\u56fe\u7247<\/strong><\/p>\n<\/p>\n
\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528Matplotlib<\/code>\u5e93\u6765\u663e\u793a\u4e24\u5f20\u56fe\u7247\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5Matplotlib<\/code>\u5e93\uff1a<\/p>\n<\/p>\n
pip install matplotlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5b9e\u73b0\u56fe\u7247\u7684\u663e\u793a\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u8bfb\u53d6\u7b2c\u4e00\u5f20\u56fe\u7247<\/strong><\/h2>\n
image1 = cv2.imread('path_to_first_image.jpg')<\/p>\n
\u5c06\u56fe\u7247\u4eceBGR\u8f6c\u6362\u4e3aRGB<\/strong><\/h2>\n
image1_rgb = cv2.cvtColor(image1, cv2.COLOR_BGR2RGB)<\/p>\n
\u8bfb\u53d6\u7b2c\u4e8c\u5f20\u56fe\u7247<\/strong><\/h2>\n
image2 = cv2.imread('path_to_second_image.jpg')<\/p>\n
\u5c06\u56fe\u7247\u4eceBGR\u8f6c\u6362\u4e3aRGB<\/strong><\/h2>\n
image2_rgb = cv2.cvtColor(image2, cv2.COLOR_BGR2RGB)<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u56fe\u5f62\u7a97\u53e3<\/strong><\/h2>\n
plt.figure(figsize=(10, 5))<\/p>\n
\u5728\u7b2c\u4e00\u4e2a\u5b50\u56fe\u4e2d\u663e\u793a\u7b2c\u4e00\u5f20\u56fe\u7247<\/strong><\/h2>\n
plt.subplot(1, 2, 1)<\/p>\n
plt.imshow(image1_rgb)<\/p>\n
plt.title('Image 1')<\/p>\n
plt.axis('off')<\/p>\n
\u5728\u7b2c\u4e8c\u4e2a\u5b50\u56fe\u4e2d\u663e\u793a\u7b2c\u4e8c\u5f20\u56fe\u7247<\/strong><\/h2>\n
plt.subplot(1, 2, 2)<\/p>\n
plt.imshow(image2_rgb)<\/p>\n
plt.title('Image 2')<\/p>\n
plt.axis('off')<\/p>\n
\u663e\u793a\u56fe\u5f62\u7a97\u53e3<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u8bfb\u53d6\u4e24\u5f20\u56fe\u7247\uff0c\u5e76\u5c06\u5b83\u4eec\u4eceBGR\u989c\u8272\u7a7a\u95f4\u8f6c\u6362\u4e3aRGB\u989c\u8272\u7a7a\u95f4\u3002\u7136\u540e\uff0c\u6211\u4eec\u4f7f\u7528Matplotlib<\/code>\u5e93\u521b\u5efa\u4e00\u4e2a\u56fe\u5f62\u7a97\u53e3\uff0c\u5e76\u5728\u4e24\u4e2a\u5b50\u56fe\u4e2d\u5206\u522b\u663e\u793a\u4e24\u5f20\u56fe\u7247\u3002\u6700\u540e\uff0c\u6211\u4eec\u4f7f\u7528plt.show<\/code>\u51fd\u6570\u663e\u793a\u56fe\u5f62\u7a97\u53e3\u3002<\/p>\n<\/p>\n
\u56db\u3001\u603b\u7ed3<\/strong><\/p>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u4e09\u79cd\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u4f7f\u7528OpenCV\u663e\u793a\u4e24\u5f20\u56fe\u7247\uff1a\u76f4\u63a5\u4f7f\u7528cv2.imshow\u51fd\u6570\u3001\u5c06\u4e24\u5f20\u56fe\u7247\u62fc\u63a5\u5728\u4e00\u8d77\u3001\u4f7f\u7528Matplotlib\u5e93\u8fdb\u884c\u663e\u793a<\/strong>\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u4f18\u70b9\u548c\u9002\u7528\u573a\u666f\uff0c\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u3002\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u80fd\u591f\u5e2e\u52a9\u5927\u5bb6\u66f4\u597d\u5730\u7406\u89e3\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528OpenCV\u663e\u793a\u4e24\u5f20\u56fe\u7247\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528OpenCV\u663e\u793a\u4e24\u5f20\u56fe\u7247\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u4f7f\u7528OpenCV\u5e93\u53ef\u4ee5\u975e\u5e38\u65b9\u4fbf\u5730\u540c\u65f6\u663e\u793a\u591a\u5f20\u56fe\u7247\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u7a97\u53e3\u5e76\u4f7f\u7528cv2.imshow()<\/code>\u51fd\u6570\u6765\u5b9e\u73b0\u3002\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u5b89\u88c5OpenCV\u5e93\uff0c\u7136\u540e\u8bfb\u53d6\u4e24\u5f20\u56fe\u7247\uff0c\u6700\u540e\u5c06\u5b83\u4eec\u5e76\u6392\u663e\u793a\u6216\u8005\u5728\u4e0d\u540c\u7a97\u53e3\u4e2d\u663e\u793a\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528numpy<\/code>\u6765\u62fc\u63a5\u4e24\u5f20\u56fe\u7247\u540e\u518d\u663e\u793a\u3002<\/p>\n
\u5728\u663e\u793a\u7684\u56fe\u7247\u4e2d\u6dfb\u52a0\u6587\u5b57\u8bf4\u660e\u7684\u6700\u4f73\u65b9\u5f0f\u662f\u4ec0\u4e48\uff1f<\/strong>
\u4e3a\u4e86\u8ba9\u89c2\u4f17\u66f4\u597d\u5730\u7406\u89e3\u4f60\u7684\u56fe\u7247\uff0c\u53ef\u4ee5\u4f7f\u7528OpenCV\u4e2d\u7684cv2.putText()<\/code>\u51fd\u6570\u5728\u56fe\u7247\u4e0a\u6dfb\u52a0\u6587\u5b57\u8bf4\u660e\u3002\u8fd9\u53ef\u4ee5\u5e2e\u52a9\u4f60\u63d0\u4f9b\u989d\u5916\u7684\u4fe1\u606f\u6216\u6807\u6ce8\u3002\u4f60\u53ef\u4ee5\u8bbe\u7f6e\u5b57\u4f53\u3001\u5927\u5c0f\u3001\u989c\u8272\u548c\u4f4d\u7f6e\uff0c\u4f7f\u5f97\u6587\u5b57\u6e05\u6670\u53ef\u89c1\uff0c\u589e\u5f3a\u4fe1\u606f\u4f20\u8fbe\u7684\u6548\u679c\u3002<\/p>\n
\u5982\u4f55\u5728Python\u4e2d\u8c03\u6574\u56fe\u7247\u7684\u5927\u5c0f\u4ee5\u9002\u5e94\u663e\u793a\u7a97\u53e3\uff1f<\/strong>
\u5728\u663e\u793a\u56fe\u7247\u4e4b\u524d\uff0c\u6709\u65f6\u9700\u8981\u8c03\u6574\u5b83\u4eec\u7684\u5927\u5c0f\u4ee5\u786e\u4fdd\u5b83\u4eec\u9002\u5408\u663e\u793a\u7a97\u53e3\u3002\u53ef\u4ee5\u4f7f\u7528cv2.resize()<\/code>\u51fd\u6570\u8fdb\u884c\u8c03\u6574\u3002\u4f60\u53ef\u4ee5\u6307\u5b9a\u65b0\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6\uff0c\u6216\u8005\u4f7f\u7528\u6bd4\u4f8b\u56e0\u5b50\u6765\u6309\u6bd4\u4f8b\u7f29\u653e\u56fe\u7247\u3002\u8fd9\u6837\uff0c\u7528\u6237\u53ef\u4ee5\u66f4\u597d\u5730\u67e5\u770b\u56fe\u7247\uff0c\u800c\u4e0d\u4f1a\u56e0\u4e3a\u5c3a\u5bf8\u8fc7\u5927\u6216\u8fc7\u5c0f\u800c\u5f71\u54cd\u4f53\u9a8c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u4f7f\u7528OpenCV\u663e\u793a\u4e24\u5f20\u56fe\u7247 \u5728Python\u4e2d\u4f7f\u7528OpenCV\u663e\u793a\u4e24\u5f20\u56fe\u7247\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9 […]","protected":false},"author":3,"featured_media":1097035,"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\/1097033"}],"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=1097033"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1097033\/revisions"}],"predecessor-version":[{"id":1097037,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1097033\/revisions\/1097037"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1097035"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1097033"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1097033"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1097033"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}