{"id":1089264,"date":"2025-01-08T13:52:02","date_gmt":"2025-01-08T05:52:02","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1089264.html"},"modified":"2025-01-08T13:52:04","modified_gmt":"2025-01-08T05:52:04","slug":"python%e4%b8%ad%e5%a6%82%e4%bd%95%e5%be%97%e5%88%b0%e5%9b%be%e5%83%8f%e7%9a%84%e5%ae%bd%e9%ab%98-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1089264.html","title":{"rendered":"python\u4e2d\u5982\u4f55\u5f97\u5230\u56fe\u50cf\u7684\u5bbd\u9ad8"},"content":{"rendered":"

\"python\u4e2d\u5982\u4f55\u5f97\u5230\u56fe\u50cf\u7684\u5bbd\u9ad8\"<\/p>\n

\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\uff0c\u5305\u62ecPillow\u3001OpenCV\u548cmatplotlib\u7b49\u3002\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528Pillow\u5e93\u7684Image.size<\/code>\u5c5e\u6027\u3001OpenCV\u5e93\u7684shape<\/code>\u5c5e\u6027\u3001\u4ee5\u53camatplotlib\u5e93\u7684imshow<\/code>\u51fd\u6570\u3002<\/strong> \u5176\u4e2d\uff0cPillow\u5e93<\/strong>\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u53ef\u4ee5\u8bfb\u53d6\u548c\u5904\u7406\u591a\u79cd\u683c\u5f0f\u7684\u56fe\u50cf\u6587\u4ef6\uff1bOpenCV<\/strong>\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u53ef\u4ee5\u8fdb\u884c\u56fe\u50cf\u548c\u89c6\u9891\u5904\u7406\uff1bmatplotlib<\/strong>\u4e3b\u8981\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\uff0c\u4f46\u4e5f\u53ef\u4ee5\u8bfb\u53d6\u56fe\u50cf\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u51e0\u79cd\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pillow\u5e93\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8<\/h3>\n<\/p>\n

Pillow\uff08PIL\u7684\u5347\u7ea7\u7248\uff09\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u56fe\u50cf\u5904\u7406\u5e93\u4e4b\u4e00\uff0c\u5b83\u53ef\u4ee5\u5904\u7406\u5404\u79cd\u56fe\u50cf\u683c\u5f0f\uff0c\u5e76\u63d0\u4f9b\u4e86\u8bb8\u591a\u65b9\u4fbf\u7684\u56fe\u50cf\u64cd\u4f5c\u529f\u80fd\u3002\u4f7f\u7528Pillow\u5e93\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u8981\u51e0\u4e2a\u6b65\u9aa4\u3002<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5Pillow\u5e93<\/h4>\n<\/p>\n

\u5728\u5f00\u59cb\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5148\u5b89\u88c5Pillow\u5e93\u3002\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pillow<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528Pillow\u5e93\u8bfb\u53d6\u56fe\u50cf\u5e76\u83b7\u53d6\u5bbd\u9ad8<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528Pillow\u5e93\u8bfb\u53d6\u56fe\u50cf\u5e76\u83b7\u53d6\u5bbd\u9ad8\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
from PIL import Image<\/p>\n
\u6253\u5f00\u56fe\u50cf\u6587\u4ef6<\/strong><\/h2>\n
image = Image.open("example.jpg")<\/p>\n
\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8<\/strong><\/h2>\n
width, height = image.size<\/p>\n
print("\u56fe\u50cf\u5bbd\u5ea6:", width)<\/p>\n
print("\u56fe\u50cf\u9ad8\u5ea6:", height)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u6bb5\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u4f7f\u7528Image.open<\/code>\u65b9\u6cd5\u6253\u5f00\u56fe\u50cf\u6587\u4ef6\uff0c\u7136\u540e\u4f7f\u7528image.size<\/code>\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\u3002image.size<\/code>\u8fd4\u56de\u4e00\u4e2a\u5305\u542b\u5bbd\u5ea6\u548c\u9ad8\u5ea6\u7684\u5143\u7ec4\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528OpenCV\u5e93\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8<\/h3>\n<\/p>\n
OpenCV\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u5e7f\u6cdb\u7528\u4e8e\u56fe\u50cf\u548c\u89c6\u9891\u5904\u7406\u3002\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u51fd\u6570\u5e93\uff0c\u6db5\u76d6\u4e86\u4ece\u57fa\u672c\u56fe\u50cf\u5904\u7406\u5230\u9ad8\u7ea7\u8ba1\u7b97\u673a\u89c6\u89c9\u7684\u5404\u4e2a\u65b9\u9762\u3002\u4f7f\u7528OpenCV\u5e93\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\u4e5f\u975e\u5e38\u7b80\u5355\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5OpenCV\u5e93<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5OpenCV\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install opencv-python<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528OpenCV\u5e93\u8bfb\u53d6\u56fe\u50cf\u5e76\u83b7\u53d6\u5bbd\u9ad8<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528OpenCV\u5e93\u8bfb\u53d6\u56fe\u50cf\u5e76\u83b7\u53d6\u5bbd\u9ad8\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6<\/strong><\/h2>\n
image = cv2.imread("example.jpg")<\/p>\n
\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8<\/strong><\/h2>\n
height, width, channels = image.shape<\/p>\n
print("\u56fe\u50cf\u5bbd\u5ea6:", width)<\/p>\n
print("\u56fe\u50cf\u9ad8\u5ea6:", height)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u6bb5\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528cv2.imread<\/code>\u65b9\u6cd5\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\uff0c\u7136\u540e\u4f7f\u7528image.shape<\/code>\u83b7\u53d6\u56fe\u50cf\u7684\u5f62\u72b6\u3002image.shape<\/code>\u8fd4\u56de\u4e00\u4e2a\u5305\u542b\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u548c\u901a\u9053\u6570\u7684\u5143\u7ec4\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528matplotlib\u5e93\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8<\/h3>\n<\/p>\n
matplotlib\u662f\u4e00\u4e2a\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\u7684\u5e93\uff0c\u901a\u5e38\u7528\u4e8e\u7ed8\u5236\u56fe\u8868\u548c\u56fe\u50cf\u3002\u867d\u7136matplotlib\u4e3b\u8981\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\uff0c\u4f46\u5b83\u4e5f\u53ef\u4ee5\u8bfb\u53d6\u56fe\u50cf\u5e76\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5matplotlib\u5e93<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5matplotlib\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install matplotlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528matplotlib\u5e93\u8bfb\u53d6\u56fe\u50cf\u5e76\u83b7\u53d6\u5bbd\u9ad8<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528matplotlib\u5e93\u8bfb\u53d6\u56fe\u50cf\u5e76\u83b7\u53d6\u5bbd\u9ad8\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import matplotlib.image as mpimg<\/p>\n
\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6<\/strong><\/h2>\n
image = mpimg.imread("example.jpg")<\/p>\n
\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8<\/strong><\/h2>\n
height, width = image.shape[:2]<\/p>\n
print("\u56fe\u50cf\u5bbd\u5ea6:", width)<\/p>\n
print("\u56fe\u50cf\u9ad8\u5ea6:", height)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u6bb5\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528mpimg.imread<\/code>\u65b9\u6cd5\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\uff0c\u7136\u540e\u901a\u8fc7image.shape<\/code>\u83b7\u53d6\u56fe\u50cf\u7684\u5f62\u72b6\u3002\u7531\u4e8e\u56fe\u50cf\u6570\u636e\u901a\u5e38\u662f\u4e09\u7ef4\u6570\u7ec4\uff08\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u3001\u901a\u9053\u6570\uff09\uff0c\u6240\u4ee5\u6211\u4eec\u4f7f\u7528image.shape[:2]<\/code>\u6765\u83b7\u53d6\u9ad8\u5ea6\u548c\u5bbd\u5ea6\u3002<\/p>\n<\/p>\n
\u56db\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5728Python\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\uff0c\u5305\u62ecPillow\u3001OpenCV\u548cmatplotlib\u7b49\u3002\u8fd9\u4e9b\u5e93\u5404\u6709\u4f18\u7f3a\u70b9\uff0c\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\u3002Pillow\u5e93\u7b80\u5355\u6613\u7528\uff0c\u9002\u5408\u5904\u7406\u5404\u79cd\u683c\u5f0f\u7684\u56fe\u50cf\uff1bOpenCV\u5e93\u529f\u80fd\u5f3a\u5927\uff0c\u9002\u5408\u8fdb\u884c\u590d\u6742\u7684\u56fe\u50cf\u548c\u89c6\u9891\u5904\u7406\uff1bmatplotlib\u5e93\u4e3b\u8981\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\uff0c\u4f46\u4e5f\u53ef\u4ee5\u8bfb\u53d6\u56fe\u50cf\u3002<\/p>\n<\/p>\n
\u603b\u7684\u6765\u8bf4\uff0cPillow\u5e93<\/strong>\u9002\u5408\u5904\u7406\u7b80\u5355\u7684\u56fe\u50cf\u64cd\u4f5c\uff0cOpenCV\u5e93<\/strong>\u9002\u5408\u8fdb\u884c\u590d\u6742\u7684\u56fe\u50cf\u548c\u89c6\u9891\u5904\u7406\uff0cmatplotlib\u5e93<\/strong>\u9002\u5408\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u548c\u7b80\u5355\u7684\u56fe\u50cf\u5904\u7406\u3002\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\uff0c\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u5b8c\u6210\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\u7684\u5bbd\u9ad8\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\u5e76\u83b7\u53d6\u5176\u5bbd\u9ad8\u3002\u5e38\u89c1\u7684\u5e93\u5305\u62ecPIL\uff08Pillow\uff09\u3001OpenCV\u548cmatplotlib\u3002\u4f7f\u7528Pillow\u5e93\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u5f0f\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\uff1a<\/p>\n
from PIL import Image\n\nimage = Image.open('path_to_image.jpg')\nwidth, height = image.size\nprint(f'\u5bbd\u5ea6: {width}, \u9ad8\u5ea6: {height}')\n<\/code><\/pre>\n
\u4f7f\u7528OpenCV\u83b7\u53d6\u56fe\u50cf\u5bbd\u9ad8\u7684\u65b9\u6cd5\u662f\u4ec0\u4e48\uff1f<\/strong>
OpenCV\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u9002\u7528\u4e8e\u56fe\u50cf\u5904\u7406\u3002\u8981\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n
import cv2\n\nimage = cv2.imread('path_to_image.jpg')\nheight, width, _ = image.shape\nprint(f'\u5bbd\u5ea6: {width}, \u9ad8\u5ea6: {height}')\n<\/code><\/pre>\n
\u5728matplotlib\u4e2d\u5982\u4f55\u663e\u793a\u56fe\u50cf\u5e76\u83b7\u53d6\u5176\u5c3a\u5bf8\uff1f<\/strong>
matplotlib\u4e3b\u8981\u7528\u4e8e\u7ed8\u56fe\uff0c\u4f46\u4e5f\u53ef\u4ee5\u7528\u4e8e\u663e\u793a\u56fe\u50cf\u3002\u60a8\u53ef\u4ee5\u5728\u663e\u793a\u56fe\u50cf\u7684\u540c\u65f6\u83b7\u53d6\u5176\u5bbd\u9ad8\uff0c\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
import matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\n\nimage = mpimg.imread('path_to_image.jpg')\nheight, width, _ = image.shape\nplt.imshow(image)\nplt.show()\nprint(f'\u5bbd\u5ea6: {width}, \u9ad8\u5ea6: {height}')\n<\/code><\/pre>\n
\u8fd9\u4e9b\u65b9\u6cd5\u4f7f\u60a8\u80fd\u591f\u8f7b\u677e\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\uff0c\u9002\u7528\u4e8e\u5404\u79cd\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u83b7\u53d6\u56fe\u50cf\u7684\u5bbd\u9ad8\uff0c\u5305\u62ecPillow\u3001OpenCV\u548cmatplotlib\u7b49\u3002\u4e3b\u8981 […]","protected":false},"author":3,"featured_media":1089271,"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\/1089264"}],"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=1089264"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1089264\/revisions"}],"predecessor-version":[{"id":1089272,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1089264\/revisions\/1089272"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1089271"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1089264"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1089264"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1089264"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}