{"id":1106731,"date":"2025-01-08T16:42:59","date_gmt":"2025-01-08T08:42:59","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1106731.html"},"modified":"2025-01-08T16:43:01","modified_gmt":"2025-01-08T08:43:01","slug":"python%e5%a6%82%e4%bd%95%e8%af%bb%e5%8f%96%e5%9b%be%e7%89%87%e5%b1%95%e7%a4%ba%e5%9b%be%e7%89%87%e5%a4%a7%e5%b0%8f","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1106731.html","title":{"rendered":"python\u5982\u4f55\u8bfb\u53d6\u56fe\u7247\u5c55\u793a\u56fe\u7247\u5927\u5c0f"},"content":{"rendered":"

\"python\u5982\u4f55\u8bfb\u53d6\u56fe\u7247\u5c55\u793a\u56fe\u7247\u5927\u5c0f\"<\/p>\n

\u5728Python\u4e2d\uff0c\u8bfb\u53d6\u56fe\u7247\u5e76\u5c55\u793a\u56fe\u7247\u5927\u5c0f\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u5b9e\u73b0\u3002\u5e38\u7528\u7684\u5e93\u5305\u62ecPillow\u3001OpenCV\u548cMatplotlib<\/strong>\u3002\u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5e93\u6765\u8bfb\u53d6\u548c\u663e\u793a\u56fe\u7247\u4ee5\u53ca\u5c55\u793a\u56fe\u7247\u7684\u5927\u5c0f\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pillow\u5e93\u8bfb\u53d6\u548c\u5c55\u793a\u56fe\u7247\u5927\u5c0f<\/p>\n<\/p>\n

Pillow\uff08PIL\u7684\u4e00\u4e2a\u53cb\u597d\u5206\u652f\uff09\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u5e93\u3002\u5b83\u652f\u6301\u4f17\u591a\u56fe\u50cf\u683c\u5f0f\uff0c\u4e14\u6613\u4e8e\u4f7f\u7528\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528Pillow\u5e93\u8bfb\u53d6\u56fe\u7247\u5e76\u5c55\u793a\u56fe\u7247\u5927\u5c0f\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n

from PIL import Image<\/p>\n
\u8bfb\u53d6\u56fe\u7247<\/strong><\/h2>\n
image = Image.open("example.jpg")<\/p>\n
\u5c55\u793a\u56fe\u7247\u5927\u5c0f<\/strong><\/h2>\n
width, height = image.size<\/p>\n
print(f"\u56fe\u7247\u5bbd\u5ea6\uff1a{width}px, \u56fe\u7247\u9ad8\u5ea6\uff1a{height}px")<\/p>\n
\u5c55\u793a\u56fe\u7247<\/strong><\/h2>\n
image.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8be6\u7ec6\u63cf\u8ff0<\/strong>\uff1a\u9996\u5148\uff0c\u4f60\u9700\u8981\u5bfc\u5165Pillow\u5e93\u4e2d\u7684Image\u6a21\u5757\u3002\u7136\u540e\uff0c\u4f7f\u7528Image.open()<\/code>\u65b9\u6cd5\u6253\u5f00\u56fe\u7247\u6587\u4ef6\u3002\u83b7\u53d6\u56fe\u7247\u7684\u5927\u5c0f\u53ef\u4ee5\u901a\u8fc7image.size<\/code>\u5c5e\u6027\uff0c\u8be5\u5c5e\u6027\u8fd4\u56de\u4e00\u4e2a\u5305\u542b\u5bbd\u5ea6\u548c\u9ad8\u5ea6\u7684\u5143\u7ec4\u3002\u6700\u540e\uff0c\u4f7f\u7528image.show()<\/code>\u65b9\u6cd5\u6765\u5c55\u793a\u56fe\u7247\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528OpenCV\u5e93\u8bfb\u53d6\u548c\u5c55\u793a\u56fe\u7247\u5927\u5c0f<\/p>\n<\/p>\n
OpenCV\uff08Open Source Computer Vision Library\uff09\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u673a\u5668\u5b66\u4e60<\/a>\u8f6f\u4ef6\u5e93\u3002\u5b83\u5305\u542b\u4e86\u6570\u5343\u79cd\u4f18\u5316\u7b97\u6cd5\uff0c\u53ef\u7528\u4e8e\u56fe\u50cf\u548c\u89c6\u9891\u7684\u5904\u7406\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528OpenCV\u5e93\u8bfb\u53d6\u56fe\u7247\u5e76\u5c55\u793a\u56fe\u7247\u5927\u5c0f\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
import cv2<\/p>\n
\u8bfb\u53d6\u56fe\u7247<\/strong><\/h2>\n
image = cv2.imread("example.jpg")<\/p>\n
\u5c55\u793a\u56fe\u7247\u5927\u5c0f<\/strong><\/h2>\n
height, width, channels = image.shape<\/p>\n
print(f"\u56fe\u7247\u5bbd\u5ea6\uff1a{width}px, \u56fe\u7247\u9ad8\u5ea6\uff1a{height}px")<\/p>\n
\u5c55\u793a\u56fe\u7247<\/strong><\/h2>\n
cv2.imshow("Image", image)<\/p>\n
cv2.wAI<\/a>tKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8be6\u7ec6\u63cf\u8ff0<\/strong>\uff1a\u9996\u5148\uff0c\u5bfc\u5165OpenCV\u5e93\u3002\u7136\u540e\uff0c\u4f7f\u7528cv2.imread()<\/code>\u65b9\u6cd5\u8bfb\u53d6\u56fe\u7247\u6587\u4ef6\u3002\u83b7\u53d6\u56fe\u7247\u7684\u5927\u5c0f\u53ef\u4ee5\u901a\u8fc7image.shape<\/code>\u5c5e\u6027\uff0c\u8be5\u5c5e\u6027\u8fd4\u56de\u4e00\u4e2a\u5305\u542b\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u548c\u989c\u8272\u901a\u9053\u6570\u7684\u5143\u7ec4\u3002\u4f7f\u7528cv2.imshow()<\/code>\u65b9\u6cd5\u5c55\u793a\u56fe\u7247\uff0c\u4f7f\u7528cv2.waitKey(0)<\/code>\u65b9\u6cd5\u7b49\u5f85\u7528\u6237\u6309\u952e\u5173\u95ed\u7a97\u53e3\uff0c\u6700\u540e\u4f7f\u7528cv2.destroyAllWindows()<\/code>\u65b9\u6cd5\u9500\u6bc1\u6240\u6709\u521b\u5efa\u7684\u7a97\u53e3\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Matplotlib\u5e93\u8bfb\u53d6\u548c\u5c55\u793a\u56fe\u7247\u5927\u5c0f<\/p>\n<\/p>\n
Matplotlib\u662f\u4e00\u4e2a\u7ed8\u56fe\u5e93\uff0c\u7279\u522b\u9002\u5408\u7528\u6765\u5c55\u793a\u56fe\u50cf\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528Matplotlib\u5e93\u8bfb\u53d6\u56fe\u7247\u5e76\u5c55\u793a\u56fe\u7247\u5927\u5c0f\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import matplotlib.image as mpimg<\/p>\n
\u8bfb\u53d6\u56fe\u7247<\/strong><\/h2>\n
image = mpimg.imread("example.jpg")<\/p>\n
\u5c55\u793a\u56fe\u7247\u5927\u5c0f<\/strong><\/h2>\n
height, width, channels = image.shape<\/p>\n
print(f"\u56fe\u7247\u5bbd\u5ea6\uff1a{width}px, \u56fe\u7247\u9ad8\u5ea6\uff1a{height}px")<\/p>\n
\u5c55\u793a\u56fe\u7247<\/strong><\/h2>\n
plt.imshow(image)<\/p>\n
plt.axis('off')  # \u4e0d\u663e\u793a\u5750\u6807\u8f74<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8be6\u7ec6\u63cf\u8ff0<\/strong>\uff1a\u9996\u5148\uff0c\u5bfc\u5165Matplotlib\u5e93\u4e2d\u7684pyplot<\/code>\u6a21\u5757\u548cimage<\/code>\u6a21\u5757\u3002\u4f7f\u7528mpimg.imread()<\/code>\u65b9\u6cd5\u8bfb\u53d6\u56fe\u7247\u6587\u4ef6\u3002\u83b7\u53d6\u56fe\u7247\u7684\u5927\u5c0f\u53ef\u4ee5\u901a\u8fc7image.shape<\/code>\u5c5e\u6027\uff0c\u8be5\u5c5e\u6027\u8fd4\u56de\u4e00\u4e2a\u5305\u542b\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u548c\u989c\u8272\u901a\u9053\u6570\u7684\u5143\u7ec4\u3002\u4f7f\u7528plt.imshow()<\/code>\u65b9\u6cd5\u5c55\u793a\u56fe\u7247\uff0c\u5e76\u4f7f\u7528plt.axis('off')<\/code>\u65b9\u6cd5\u9690\u85cf\u5750\u6807\u8f74\uff0c\u6700\u540e\u4f7f\u7528plt.show()<\/code>\u65b9\u6cd5\u663e\u793a\u56fe\u7247\u3002<\/p>\n<\/p>\n
\u56db\u3001\u603b\u7ed3<\/p>\n<\/p>\n
\u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u4f7f\u7528\u4e09\u79cd\u4e0d\u540c\u7684Python\u5e93\uff08Pillow\u3001OpenCV\u548cMatplotlib\uff09\u6765\u8bfb\u53d6\u56fe\u7247\u3001\u5c55\u793a\u56fe\u7247\u5927\u5c0f\u5e76\u663e\u793a\u56fe\u7247\u3002\u6bcf\u4e2a\u5e93\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\uff1a<\/p>\n<\/p>\n
    \n
  • Pillow<\/strong>\uff1a\u7b80\u5355\u6613\u7528\uff0c\u9002\u5408\u5904\u7406\u56fe\u50cf\u6587\u4ef6\u7684\u57fa\u672c\u64cd\u4f5c\u3002<\/li>\n
  • OpenCV<\/strong>\uff1a\u529f\u80fd\u5f3a\u5927\uff0c\u9002\u5408\u590d\u6742\u7684\u56fe\u50cf\u5904\u7406\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\u3002<\/li>\n
  • Matplotlib<\/strong>\uff1a\u7ed8\u56fe\u5e93\uff0c\u9002\u5408\u6570\u636e\u53ef\u89c6\u5316\u548c\u5c55\u793a\u56fe\u50cf\u6570\u636e\u3002<\/li>\n<\/ul>\n
    \u65e0\u8bba\u4f60\u9009\u62e9\u54ea\u79cd\u5e93\uff0c\u90fd\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u8bfb\u53d6\u56fe\u7247\u3001\u5c55\u793a\u56fe\u7247\u5927\u5c0f\u5e76\u663e\u793a\u56fe\u7247\u7684\u9700\u6c42\u3002\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\uff0c\u8ba9\u4f60\u5728Python\u56fe\u50cf\u5904\u7406\u7684\u9053\u8def\u4e0a\u66f4\u52a0\u987a\u7545\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u4f7f\u7528Python\u8bfb\u53d6\u56fe\u7247\u5e76\u83b7\u53d6\u5176\u5c3a\u5bf8\uff1f<\/strong>
    \u8981\u4f7f\u7528Python\u8bfb\u53d6\u56fe\u7247\u5e76\u83b7\u53d6\u5176\u5c3a\u5bf8\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528PIL\u5e93\uff08Pillow\uff09\u3002\u9996\u5148\uff0c\u786e\u4fdd\u5b89\u88c5\u4e86Pillow\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u547d\u4ee4 pip install Pillow<\/code> \u5b89\u88c5\u3002\u63a5\u4e0b\u6765\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u8bfb\u53d6\u56fe\u7247\u5e76\u663e\u793a\u5176\u5c3a\u5bf8\uff1a<\/p>\n
    from PIL import Image\n\n# \u8bfb\u53d6\u56fe\u7247\nimage = Image.open('path_to_your_image.jpg')\n# \u83b7\u53d6\u56fe\u7247\u5c3a\u5bf8\nwidth, height = image.size\nprint(f"\u56fe\u7247\u5bbd\u5ea6: {width}, \u56fe\u7247\u9ad8\u5ea6: {height}")\n<\/code><\/pre>\n
    \u8fd9\u6bb5\u4ee3\u7801\u5c06\u6253\u5f00\u6307\u5b9a\u8def\u5f84\u7684\u56fe\u7247\uff0c\u5e76\u8f93\u51fa\u5176\u5bbd\u5ea6\u548c\u9ad8\u5ea6\u3002<\/p>\n
    \u5728Python\u4e2d\uff0c\u8bfb\u53d6\u4e0d\u540c\u683c\u5f0f\u7684\u56fe\u7247\u662f\u5426\u6709\u5dee\u5f02\uff1f<\/strong>
    \u4f7f\u7528Pillow\u5e93\u65f6\uff0c\u8bfb\u53d6\u4e0d\u540c\u683c\u5f0f\u7684\u56fe\u7247\uff08\u5982JPEG\u3001PNG\u3001BMP\u7b49\uff09\u57fa\u672c\u4e0a\u6ca1\u6709\u5dee\u5f02\u3002Pillow\u4f1a\u81ea\u52a8\u8bc6\u522b\u6587\u4ef6\u683c\u5f0f\u5e76\u8fdb\u884c\u76f8\u5e94\u5904\u7406\u3002\u53ea\u9700\u786e\u4fdd\u6587\u4ef6\u8def\u5f84\u6b63\u786e\uff0c\u4f7f\u7528 Image.open()<\/code> \u65b9\u6cd5\u5c31\u80fd\u987a\u5229\u8bfb\u53d6\u5404\u7c7b\u56fe\u7247\u3002<\/p>\n
    \u5982\u4f55\u5728Python\u4e2d\u5c55\u793a\u8bfb\u53d6\u7684\u56fe\u7247\uff1f<\/strong>
    \u9664\u4e86\u83b7\u53d6\u56fe\u7247\u7684\u5c3a\u5bf8\uff0c\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528Pillow\u5e93\u76f4\u63a5\u5c55\u793a\u56fe\u7247\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5728Python\u4e2d\u5c55\u793a\u8bfb\u53d6\u7684\u56fe\u7247\uff1a<\/p>\n
    image.show()\n<\/code><\/pre>\n
    \u8fd9\u6761\u547d\u4ee4\u4f1a\u5728\u9ed8\u8ba4\u7684\u56fe\u7247\u67e5\u770b\u5668\u4e2d\u6253\u5f00\u8be5\u56fe\u7247\uff0c\u60a8\u53ef\u4ee5\u76f4\u89c2\u5730\u67e5\u770b\u56fe\u7247\u5185\u5bb9\u3002<\/p>\n
    \u5982\u4f55\u5904\u7406\u5927\u5c3a\u5bf8\u56fe\u7247\uff0c\u9632\u6b62\u5185\u5b58\u6ea2\u51fa\uff1f<\/strong>
    \u8bfb\u53d6\u5927\u5c3a\u5bf8\u56fe\u7247\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u5185\u5b58\u4e0d\u8db3\u7684\u95ee\u9898\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u5f0f\u51cf\u5c0f\u5185\u5b58\u5360\u7528\uff1a<\/p>\n
      \n
    1. \u4f7f\u7528 Image.open()<\/code> \u6253\u5f00\u56fe\u7247\u65f6\uff0c\u4e0d\u7acb\u5373\u52a0\u8f7d\u6574\u4e2a\u56fe\u50cf\uff0c\u53ef\u4ee5\u901a\u8fc7 image.thumbnail()<\/code> \u65b9\u6cd5\u751f\u6210\u7f29\u7565\u56fe\u6765\u5360\u7528\u66f4\u5c11\u7684\u5185\u5b58\u3002<\/li>\n
    2. \u4f7f\u7528 image.convert()<\/code> \u65b9\u6cd5\u5c06\u56fe\u7247\u8f6c\u6362\u4e3a\u4e0d\u540c\u7684\u6a21\u5f0f\uff08\u5982 'L' \u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\uff09\uff0c\u4ece\u800c\u51cf\u5c0f\u5185\u5b58\u4f7f\u7528\u3002<\/li>\n
    3. \u8003\u8651\u5206\u5757\u8bfb\u53d6\u56fe\u7247\uff0c\u5c24\u5176\u662f\u5904\u7406\u9ad8\u6e05\u56fe\u50cf\u65f6\uff0c\u53ef\u4ee5\u6709\u6548\u964d\u4f4e\u5185\u5b58\u8d1f\u62c5\u3002<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u8bfb\u53d6\u56fe\u7247\u5e76\u5c55\u793a\u56fe\u7247\u5927\u5c0f\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u5b9e\u73b0\u3002\u5e38\u7528\u7684\u5e93\u5305\u62ecPillow\u3001OpenCV\u548cMa […]","protected":false},"author":3,"featured_media":1106736,"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\/1106731"}],"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=1106731"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1106731\/revisions"}],"predecessor-version":[{"id":1106738,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1106731\/revisions\/1106738"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1106736"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1106731"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1106731"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1106731"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}