{"id":205231,"date":"2025-05-29T11:53:07","date_gmt":"2025-05-29T03:53:07","guid":{"rendered":"https:\/\/server.hk\/cnblog\/205231\/"},"modified":"2025-05-29T11:53:07","modified_gmt":"2025-05-29T03:53:07","slug":"%e5%a6%82%e4%bd%95%e7%94%a8-pillow-%e7%9b%b4%e6%8e%a5%e6%98%be%e7%a4%ba-matplotlib-%e7%94%9f%e6%88%90%e7%9a%84%e5%9b%be%e7%89%87%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/server.hk\/cnblog\/205231\/","title":{"rendered":"\u5982\u4f55\u7528 Pillow \u76f4\u63a5\u663e\u793a Matplotlib \u751f\u6210\u7684\u56fe\u7247\uff1f"},"content":{"rendered":"

<\/b> <\/p>\n

\u5982\u4f55\u7528 Pillow \u76f4\u63a5\u663e\u793a Matplotlib \u751f\u6210\u7684\u56fe\u7247\uff1f<\/h1>\n

\u5728\u6587\u7ae0\u5b9e\u6218\u5f00\u53d1\u7684\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u7ecf\u5e38\u4f1a\u9047\u5230\u4e00\u4e9b\u8fd9\u6837\u90a3\u6837\u7684\u95ee\u9898\uff0c\u7136\u540e\u8981\u5361\u597d\u534a\u5929\uff0c\u7b49\u95ee\u9898\u89e3\u51b3\u4e86\u624d\u53d1\u73b0\u539f\u6765\u4e00\u4e9b\u7ec6\u8282\u77e5\u8bc6\u70b9\u8fd8\u662f\u6ca1\u6709\u638c\u63e1\u597d\u3002\u4eca\u5929\u5c31\u6574\u7406\u5206\u4eab\u300a\u5982\u4f55\u7528 Pillow \u76f4\u63a5\u663e\u793a Matplotlib \u751f\u6210\u7684\u56fe\u7247\uff1f\u300b\uff0c\u804a\u804a\uff0c\u5e0c\u671b\u53ef\u4ee5\u5e2e\u52a9\u5230\u6b63\u5728\u52aa\u529b\u8d5a\u94b1\u7684\u4f60\u3002<\/p>\n

<\/p>\n

\u5728 python pillow \u4e2d\u76f4\u63a5\u663e\u793a matplotlib \u751f\u6210\u7684\u56fe\u7247<\/strong><\/p>\n

\u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u4ecb\u7ecd\u5982\u4f55\u5728 pillow \u5e93\u4e2d\u76f4\u63a5\u663e\u793a matplotlib \u751f\u6210\u7684\u56fe\u7247\uff0c\u800c\u65e0\u9700\u521b\u5efa\u4e2d\u95f4\u6587\u4ef6\u3002<\/p>\n

\u901a\u5e38\uff0c\u5728\u4f7f\u7528 pillow \u663e\u793a matplotlib \u751f\u6210\u7684\u56fe\u7247\u65f6\uff0c\u6211\u4eec\u9700\u8981\u5148\u4fdd\u5b58\u56fe\u7247\u5230\u6587\u4ef6\u4e2d\uff0c\u7136\u540e\u518d\u4f7f\u7528 pillow \u6253\u5f00\u3002\u8fd9\u79cd\u65b9\u5f0f\u5bf9\u4e8e\u9700\u8981\u4fdd\u5b58\u56fe\u7247\u5230\u78c1\u76d8\u7684\u60c5\u51b5\u662f\u5408\u9002\u7684\uff0c\u4f46\u5f53\u6211\u4eec\u53ea\u60f3\u5728\u5185\u5b58\u4e2d\u663e\u793a\u56fe\u7247\u65f6\uff0c\u5c31\u4f1a\u9020\u6210\u4e0d\u5fc5\u8981\u7684\u5f00\u9500\u3002<\/p>\n

\u4e3a\u4e86\u907f\u514d\u521b\u5efa\u4e2d\u95f4\u6587\u4ef6\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 io.bytesio \u7c7b\u6765\u521b\u5efa\u4e00\u4e2a\u7c7b\u4f3c\u4e8e\u6587\u4ef6\u7684\u5bf9\u8c61\uff0c\u8be5\u5bf9\u8c61\u53ef\u4ee5\u5b58\u50a8\u56fe\u7247\u6570\u636e\u3002\u8fd9\u79cd\u65b9\u6cd5\u88ab\u79f0\u4e3a\u201c\u9e2d\u5b50\u7c7b\u578b\u201d\uff0c\u56e0\u4e3a\u5b83\u5141\u8bb8\u6211\u4eec\u4f7f\u7528 pillow \u6253\u5f00 bytesio \u5bf9\u8c61\uff0c\u5373\u4f7f\u5b83\u4e0d\u662f\u771f\u6b63\u7684\u6587\u4ef6\u3002<\/p>\n

\u5177\u4f53\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n

    \n
  1. \u4f7f\u7528 matplotlib \u751f\u6210\u56fe\u7247\u5e76\u5c06\u5176\u4fdd\u5b58\u5230 bytesio \u5bf9\u8c61\u4e2d\uff1a<\/li>\n<\/ol>\n
    import io\nimport matplotlib.pyplot as plt\nfrom pil import image\n\n# \u751f\u6210\u56fe\u7247\nplt.plot([1, 2, 3, 4])\n\n# \u4fdd\u5b58\u56fe\u7247\u5230 bytesio \u5bf9\u8c61\noutput = io.bytesio()\nplt.savefig(output, format=\"png\")<\/pre>\n
      \n
    1. \u4f7f\u7528 pillow \u6253\u5f00 bytesio \u5bf9\u8c61\u4e2d\u7684\u56fe\u7247\u5e76\u663e\u793a\uff1a<\/li>\n<\/ol>\n
      # \u4ece BytesIO \u5bf9\u8c61\u4e2d\u8bfb\u53d6\u56fe\u7247\u6570\u636e\npil_image = Image.open(output)\n\n# \u663e\u793a\u56fe\u7247\npil_image.show()<\/pre>\n
      \u901a\u8fc7\u8fd9\u79cd\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u5728\u4e0d\u521b\u5efa\u4e2d\u95f4\u6587\u4ef6\u7684\u60c5\u51b5\u4e0b\u76f4\u63a5\u5728 pillow \u4e2d\u663e\u793a matplotlib \u751f\u6210\u7684\u56fe\u7247\u3002\u5b83\u5bf9\u4e8e\u9700\u8981\u5feb\u901f\u663e\u793a\u56fe\u7247\u6216\u5728\u5185\u5b58\u4e2d\u5904\u7406\u56fe\u7247\u7684\u5e94\u7528\u7a0b\u5e8f\u5f88\u6709\u7528\u3002<\/p>\n
      \u4ee5\u4e0a\u5c31\u662f\u672c\u6587\u7684\u5168\u90e8\u5185\u5bb9\u4e86\uff0c\u662f\u5426\u6709\u987a\u5229\u5e2e\u52a9\u4f60\u89e3\u51b3\u95ee\u9898\uff1f\u82e5\u662f\u80fd\u7ed9\u4f60\u5e26\u6765\u5b66\u4e60\u4e0a\u7684\u5e2e\u52a9\uff0c\u8bf7\u5927\u5bb6\u591a\u591a\u652f\u6301\uff01\u66f4\u591a\u5173\u4e8e\u6587\u7ae0\u7684\u76f8\u5173\u77e5\u8bc6\uff0c\u4e5f\u53ef\u5173\u6ce8\u516c\u4f17\u53f7\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
      \u5982\u4f55\u7528 Pillow \u76f4\u63a5\u663e\u793a ...<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4925],"tags":[],"class_list":["post-205231","post","type-post","status-publish","format-standard","hentry","category-4925"],"_links":{"self":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/205231","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/comments?post=205231"}],"version-history":[{"count":0,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/205231\/revisions"}],"wp:attachment":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/media?parent=205231"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/categories?post=205231"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/tags?post=205231"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}