{"id":969910,"date":"2024-12-27T05:21:14","date_gmt":"2024-12-26T21:21:14","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/969910.html"},"modified":"2024-12-27T05:21:16","modified_gmt":"2024-12-26T21:21:16","slug":"python%e8%af%ad%e8%a8%80%e5%a6%82%e4%bd%95%e8%af%bb%e5%8f%96%e5%9b%be%e7%89%87","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/969910.html","title":{"rendered":"python\u8bed\u8a00\u5982\u4f55\u8bfb\u53d6\u56fe\u7247"},"content":{"rendered":"

\"python\u8bed\u8a00\u5982\u4f55\u8bfb\u53d6\u56fe\u7247\"<\/p>\n

\u5f00\u5934\u6bb5\u843d\uff1a
Python\u8bed\u8a00\u8bfb\u53d6\u56fe\u7247\u7684\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528PIL\u5e93\u3001\u5229\u7528OpenCV\u5e93\u3001\u5e94\u7528matplotlib\u5e93<\/strong>\u3002\u8fd9\u4e9b\u65b9\u6cd5\u5404\u6709\u4f18\u52a3\uff0c\u5176\u4e2d\u4f7f\u7528PIL\u5e93\u662f\u6700\u5e38\u89c1\u548c\u7b80\u4fbf\u7684\u65b9\u5f0f<\/strong>\u3002PIL\uff08Python Imaging Library\uff09\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u5e93\uff0c\u652f\u6301\u6253\u5f00\u3001\u64cd\u4f5c\u548c\u4fdd\u5b58\u8bb8\u591a\u4e0d\u540c\u683c\u5f0f\u7684\u56fe\u50cf\u6587\u4ef6\u3002\u4f7f\u7528PIL\u8bfb\u53d6\u56fe\u7247\u65f6\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u5904\u7406\u56fe\u50cf\u7684\u5404\u79cd\u64cd\u4f5c\uff0c\u5982\u88c1\u526a\u3001\u65cb\u8f6c\u3001\u8c03\u6574\u5927\u5c0f\u7b49\u3002\u4e3a\u4e86\u8bfb\u53d6\u56fe\u7247\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5PIL\u5e93\u7684\u73b0\u4ee3\u5316\u7248\u672cPillow\uff0c\u7136\u540e\u4f7f\u7528Image.open()<\/code>\u51fd\u6570\u8f7b\u677e\u52a0\u8f7d\u56fe\u50cf\u3002\u6b64\u5916\uff0cOpenCV\u5219\u63d0\u4f9b\u4e86\u66f4\u5f3a\u5927\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u529f\u80fd\uff0c\u53ef\u4ee5\u8bfb\u53d6\u548c\u5904\u7406\u56fe\u7247\u53ca\u89c6\u9891\u6d41\uff0c\u800cmatplotlib\u5e93\u5219\u9002\u5408\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\u548c\u7b80\u5355\u56fe\u50cf\u663e\u793a\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528PIL\u5e93\u8bfb\u53d6\u56fe\u7247<\/p>\n<\/p>\n

PIL\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u56fe\u50cf\u5904\u7406\u5e93\u4e4b\u4e00\u3002\u867d\u7136PIL\u672c\u8eab\u5df2\u7ecf\u505c\u6b62\u66f4\u65b0\uff0c\u4f46\u5176\u5206\u652f\u7248\u672cPillow\u7ee7\u7eed\u5f97\u5230\u4e86\u79ef\u6781\u7684\u7ef4\u62a4\u548c\u53d1\u5c55\u3002Pillow\u517c\u5bb9PIL\uff0c\u5e76\u589e\u52a0\u4e86\u8bb8\u591a\u65b0\u529f\u80fd\u548c\u6539\u8fdb\uff0c\u662f\u5904\u7406\u56fe\u7247\u7684\u9996\u9009\u5de5\u5177\u3002<\/p>\n<\/p>\n

    \n
  1. \u5b89\u88c5Pillow\u5e93<\/li>\n<\/ol>\n

    \u8981\u4f7f\u7528PIL\u529f\u80fd\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5Pillow\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528pip\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

    pip install Pillow<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    1. \u8bfb\u53d6\u56fe\u7247<\/li>\n<\/ol>\n
      \u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7PIL\u5e93\u4e2d\u7684Image\u6a21\u5757\u8f7b\u677e\u8bfb\u53d6\u56fe\u7247\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\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
      \u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n
      image.show()<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u901a\u8fc7Image.open()<\/code>\u65b9\u6cd5\u52a0\u8f7d\u56fe\u50cf\u6587\u4ef6\uff0c\u5e76\u4f7f\u7528show()<\/code>\u65b9\u6cd5\u663e\u793a\u56fe\u50cf\u3002<\/p>\n<\/p>\n
      \u4e8c\u3001\u4f7f\u7528OpenCV\u5e93\u8bfb\u53d6\u56fe\u7247<\/p>\n<\/p>\n
      OpenCV\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u529f\u80fd\u5f3a\u5927\uff0c\u9002\u7528\u4e8e\u56fe\u50cf\u548c\u89c6\u9891\u5904\u7406\u3002\u5b83\u652f\u6301\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00\uff0c\u5305\u62ecPython\u3002<\/p>\n<\/p>\n
        \n
      1. \u5b89\u88c5OpenCV\u5e93<\/li>\n<\/ol>\n
        \u8981\u5728Python\u4e2d\u4f7f\u7528OpenCV\uff0c\u9700\u8981\u5b89\u88c5opencv-python\u5305\uff1a<\/p>\n<\/p>\n
        pip install opencv-python<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        1. \u8bfb\u53d6\u56fe\u7247<\/li>\n<\/ol>\n
          \u4f7f\u7528OpenCV\u8bfb\u53d6\u56fe\u7247\u53ef\u4ee5\u901a\u8fc7cv2\u6a21\u5757\u5b9e\u73b0\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
          import cv2<\/p>\n
          \u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
          image = cv2.imread('example.jpg')<\/p>\n
          \u663e\u793a\u56fe\u50cf<\/strong><\/h2>\n
          cv2.imshow('Image', image)<\/p>\n
          \u7b49\u5f85\u6309\u952e\u8f93\u5165\u4ee5\u5173\u95ed\u7a97\u53e3<\/strong><\/h2>\n
          cv2.wAI<\/a>tKey(0)<\/p>\n
          cv2.destroyAllWindows()<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u4f7f\u7528cv2.imread()<\/code>\u65b9\u6cd5\u52a0\u8f7d\u56fe\u50cf\uff0c\u5e76\u901a\u8fc7cv2.imshow()<\/code>\u65b9\u6cd5\u663e\u793a\u56fe\u50cf\u3002\u6ce8\u610f\u9700\u8981\u4f7f\u7528cv2.waitKey(0)<\/code>\u6765\u6682\u505c\u7a97\u53e3\uff0c\u4ee5\u4fbf\u53ef\u4ee5\u67e5\u770b\u56fe\u50cf\u3002<\/p>\n<\/p>\n
          \u4e09\u3001\u4f7f\u7528matplotlib\u5e93\u8bfb\u53d6\u56fe\u7247<\/p>\n<\/p>\n
          matplotlib\u662f\u4e00\u4e2a\u5e7f\u6cdb\u4f7f\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u4e5f\u53ef\u4ee5\u7528\u4e8e\u7b80\u5355\u7684\u56fe\u50cf\u663e\u793a\u548c\u5904\u7406\u3002<\/p>\n<\/p>\n
            \n
          1. \u5b89\u88c5matplotlib\u5e93<\/li>\n<\/ol>\n
            \u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u5b89\u88c5matplotlib\u5e93\uff1a<\/p>\n<\/p>\n
            pip install matplotlib<\/p>\n
            <\/code><\/pre>\n<\/p>\n
              \n
            1. \u8bfb\u53d6\u56fe\u7247<\/li>\n<\/ol>\n
              \u4f7f\u7528matplotlib\u5e93\u53ef\u4ee5\u901a\u8fc7pyplot\u6a21\u5757\u6765\u8bfb\u53d6\u548c\u663e\u793a\u56fe\u7247\uff1a<\/p>\n<\/p>\n
              import matplotlib.pyplot as plt<\/p>\n
              import matplotlib.image as mpimg<\/p>\n
              \u8bfb\u53d6\u56fe\u50cf<\/strong><\/h2>\n
              image = mpimg.imread('example.jpg')<\/p>\n
              \u663e\u793a\u56fe\u50cf<\/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
              \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u4f7f\u7528mpimg.imread()<\/code>\u65b9\u6cd5\u52a0\u8f7d\u56fe\u50cf\uff0c\u5e76\u901a\u8fc7plt.imshow()<\/code>\u65b9\u6cd5\u663e\u793a\u56fe\u50cf\u3002plt.axis('off')<\/code>\u7528\u4e8e\u9690\u85cf\u5750\u6807\u8f74\uff0c\u4f7f\u663e\u793a\u7684\u56fe\u50cf\u66f4\u52a0\u6e05\u6670\u3002<\/p>\n<\/p>\n
              \u56db\u3001\u6bd4\u8f83\u4e0d\u540c\u65b9\u6cd5\u7684\u4f18\u52a3<\/p>\n<\/p>\n
              \u5404\u4e2a\u5e93\u5728\u8bfb\u53d6\u56fe\u7247\u65b9\u9762\u5404\u6709\u4f18\u52a3\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53d6\u51b3\u4e8e\u5177\u4f53\u7684\u9700\u6c42\u548c\u573a\u666f\u3002<\/p>\n<\/p>\n
                \n
              1. PIL\/Pillow\u5e93<\/strong><\/li>\n<\/ol>\n
                PIL\u5e93\u4ee5\u5176\u7b80\u5355\u6613\u7528\u800c\u8457\u79f0\uff0c\u9002\u5408\u5feb\u901f\u5904\u7406\u56fe\u50cf\u7684\u57fa\u672c\u64cd\u4f5c\uff0c\u5982\u88c1\u526a\u3001\u65cb\u8f6c\u3001\u8c03\u6574\u5927\u5c0f\u7b49\u3002\u7531\u4e8e\u5176\u4e30\u5bcc\u7684\u56fe\u50cf\u683c\u5f0f\u652f\u6301\u548c\u4fbf\u6377\u7684API\uff0cPillow\u6210\u4e3a\u4e86\u8bb8\u591aPython\u5f00\u53d1\u8005\u7684\u9996\u9009\u3002<\/p>\n<\/p>\n
                  \n
                1. OpenCV\u5e93<\/strong><\/li>\n<\/ol>\n
                  OpenCV\u5e93\u529f\u80fd\u5f3a\u5927\uff0c\u5c24\u5176\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\u8868\u73b0\u51fa\u8272\u3002\u9664\u4e86\u57fa\u672c\u7684\u56fe\u50cf\u8bfb\u53d6\u548c\u663e\u793a\uff0cOpenCV\u8fd8\u652f\u6301\u9ad8\u7ea7\u7684\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\uff0c\u5982\u8fb9\u7f18\u68c0\u6d4b\u3001\u7279\u5f81\u63d0\u53d6\u3001\u76ee\u6807\u8ddf\u8e2a\u7b49\u3002\u867d\u7136OpenCV\u7684API\u76f8\u5bf9\u590d\u6742\uff0c\u4f46\u5176\u5f3a\u5927\u7684\u529f\u80fd\u8db3\u4ee5\u5f25\u8865\u8fd9\u4e00\u7f3a\u70b9\u3002<\/p>\n<\/p>\n
                    \n
                  1. matplotlib\u5e93<\/strong><\/li>\n<\/ol>\n
                    matplotlib\u5e93\u4e3b\u8981\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\uff0c\u9002\u5408\u9700\u8981\u5c06\u56fe\u50cf\u4e0e\u5176\u4ed6\u6570\u636e\u56fe\u8868\u7ed3\u5408\u4f7f\u7528\u7684\u573a\u666f\u3002\u5176\u7b80\u5355\u7684\u56fe\u50cf\u663e\u793a\u529f\u80fd\u53ef\u4ee5\u6ee1\u8db3\u57fa\u672c\u9700\u6c42\uff0c\u4f46\u4e0d\u9002\u5408\u590d\u6742\u7684\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u3002<\/p>\n<\/p>\n
                    \u4e94\u3001\u603b\u7ed3\u4e0e\u5efa\u8bae<\/p>\n<\/p>\n
                    Python\u8bed\u8a00\u63d0\u4f9b\u4e86\u591a\u79cd\u8bfb\u53d6\u56fe\u7247\u7684\u65b9\u6cd5\uff0c\u5404\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u9002\u7528\u7684\u573a\u666f\u548c\u4f18\u70b9\u3002\u5728\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u65f6\uff0c\u5e94\u6839\u636e\u5b9e\u9645\u9700\u6c42\u548c\u9879\u76ee\u7279\u6027\u8fdb\u884c\u6743\u8861\u3002\u5982\u679c\u9700\u8981\u8fdb\u884c\u7b80\u5355\u7684\u56fe\u50cf\u64cd\u4f5c\uff0cPIL\u5e93\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\uff1b\u5982\u679c\u9700\u8981\u8fdb\u884c\u9ad8\u7ea7\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\uff0cOpenCV\u5c06\u63d0\u4f9b\u5f3a\u5927\u7684\u652f\u6301\uff1b\u800c\u5728\u6570\u636e\u53ef\u89c6\u5316\u60c5\u5883\u4e0b\uff0cmatplotlib\u5219\u66f4\u4e3a\u9002\u7528\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u53ef\u4ee5\u6839\u636e\u9700\u6c42\u7ed3\u5408\u4f7f\u7528\u591a\u4e2a\u5e93\uff0c\u5145\u5206\u53d1\u6325\u5b83\u4eec\u7684\u4f18\u52bf\uff0c\u5b9e\u73b0\u9ad8\u6548\u7684\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n
                    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                     \u5982\u4f55\u4f7f\u7528Python\u8bfb\u53d6\u4e0d\u540c\u683c\u5f0f\u7684\u56fe\u7247\uff1f<\/strong>
                    Python\u652f\u6301\u591a\u79cd\u56fe\u7247\u683c\u5f0f\uff0c\u5982JPEG\u3001PNG\u3001BMP\u7b49\u3002\u8981\u8bfb\u53d6\u8fd9\u4e9b\u683c\u5f0f\u7684\u56fe\u7247\uff0c\u53ef\u4ee5\u4f7f\u7528PIL\uff08Pillow\uff09\u5e93\u3002\u9996\u5148\uff0c\u786e\u4fdd\u5b89\u88c5\u4e86Pillow\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528pip install Pillow<\/code>\u547d\u4ee4\u3002\u7136\u540e\uff0c\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u8bfb\u53d6\u56fe\u7247\uff1a  <\/p>\n
                    from PIL import Image\n\n# \u6253\u5f00\u56fe\u7247\u6587\u4ef6\nimage = Image.open('your_image_file.jpg')\nimage.show()  # \u663e\u793a\u56fe\u7247\n<\/code><\/pre>\n
                    \u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5904\u7406\u591a\u79cd\u683c\u5f0f\uff0c\u4e14\u6613\u4e8e\u4f7f\u7528\u3002<\/p>\n
                    \u5728Python\u4e2d\u5982\u4f55\u5904\u7406\u8bfb\u53d6\u5230\u7684\u56fe\u7247\u6570\u636e\uff1f<\/strong>
                    \u8bfb\u53d6\u56fe\u7247\u540e\uff0c\u60a8\u53ef\u80fd\u60f3\u5bf9\u5176\u8fdb\u884c\u5904\u7406\u3002Pillow\u5e93\u63d0\u4f9b\u4e86\u591a\u79cd\u64cd\u4f5c\uff0c\u5982\u88c1\u526a\u3001\u65cb\u8f6c\u3001\u8c03\u6574\u5927\u5c0f\u7b49\u3002\u4f8b\u5982\uff0c\u88c1\u526a\u56fe\u7247\u53ef\u4ee5\u4f7f\u7528crop<\/code>\u65b9\u6cd5\uff1a  <\/p>\n
                    # \u88c1\u526a\u56fe\u7247\ncropped_image = image.crop((left, upper, right, lower))\ncropped_image.show()\n<\/code><\/pre>\n
                    \u8fd9\u6837\u53ef\u4ee5\u65b9\u4fbf\u5730\u5bf9\u56fe\u7247\u8fdb\u884c\u5404\u79cd\u64cd\u4f5c\uff0c\u6ee1\u8db3\u4e0d\u540c\u9700\u6c42\u3002<\/p>\n
                    \u5982\u4f55\u5728Python\u4e2d\u6279\u91cf\u8bfb\u53d6\u591a\u5f20\u56fe\u7247\uff1f<\/strong>
                    \u5f53\u9700\u8981\u8bfb\u53d6\u591a\u5f20\u56fe\u7247\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528os<\/code>\u5e93\u904d\u5386\u6307\u5b9a\u6587\u4ef6\u5939\u4e2d\u7684\u6240\u6709\u56fe\u7247\u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff1a  <\/p>\n
                    import os\nfrom PIL import Image\n\n# \u6307\u5b9a\u56fe\u7247\u6587\u4ef6\u5939\u8def\u5f84\nfolder_path = 'your_image_folder'\n\n# \u904d\u5386\u6587\u4ef6\u5939\u4e2d\u7684\u6240\u6709\u6587\u4ef6\nfor filename in os.listdir(folder_path):\n    if filename.endswith('.jpg') or filename.endswith('.png'):\n        image_path = os.path.join(folder_path, filename)\n        image = Image.open(image_path)\n        image.show()  # \u663e\u793a\u6bcf\u4e00\u5f20\u56fe\u7247\n<\/code><\/pre>\n
                    \u8fd9\u79cd\u65b9\u6cd5\u9002\u5408\u4e8e\u9700\u8981\u5904\u7406\u5927\u91cf\u56fe\u7247\u7684\u573a\u666f\uff0c\u4f7f\u5f97\u64cd\u4f5c\u66f4\u52a0\u9ad8\u6548\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5f00\u5934\u6bb5\u843d\uff1aPython\u8bed\u8a00\u8bfb\u53d6\u56fe\u7247\u7684\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528PIL\u5e93\u3001\u5229\u7528OpenCV\u5e93\u3001\u5e94\u7528matplotlib\u5e93\u3002 […]","protected":false},"author":3,"featured_media":969915,"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\/969910"}],"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=969910"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/969910\/revisions"}],"predecessor-version":[{"id":969916,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/969910\/revisions\/969916"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/969915"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=969910"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=969910"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=969910"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}