{"id":958106,"date":"2024-12-27T03:15:24","date_gmt":"2024-12-26T19:15:24","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/958106.html"},"modified":"2024-12-27T03:15:27","modified_gmt":"2024-12-26T19:15:27","slug":"python%e5%a6%82%e4%bd%95%e8%af%bb%e5%8f%96%e5%9b%be%e7%89%87pix","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/958106.html","title":{"rendered":"python\u5982\u4f55\u8bfb\u53d6\u56fe\u7247pix"},"content":{"rendered":"

\"python\u5982\u4f55\u8bfb\u53d6\u56fe\u7247pix\"<\/p>\n

Python\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20\u7684\u65b9\u6cd5\u4e3b\u8981\u6709\u4ee5\u4e0b\u51e0\u79cd\uff1a\u4f7f\u7528PIL\u5e93\u3001OpenCV\u5e93\u3001scikit-image\u5e93\u3002<\/strong>\u5176\u4e2d\uff0cPIL\u5e93\u63d0\u4f9b\u4e86\u7b80\u5355\u6613\u7528\u7684\u63a5\u53e3\u6765\u5904\u7406\u56fe\u50cf\u6570\u636e\uff0cOpenCV\u5e93\u529f\u80fd\u5f3a\u5927\uff0c\u9002\u7528\u4e8e\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u56fe\u50cf\u5904\u7406\uff0cscikit-image\u5e93\u5219\u662f\u57fa\u4e8enumpy\u7684\u56fe\u50cf\u5904\u7406\u5de5\u5177\uff0c\u9002\u5408\u79d1\u5b66\u8ba1\u7b97\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e09\u79cd\u65b9\u6cd5\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528PIL\u5e93\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20<\/p>\n<\/p>\n

PIL\uff08Python Imaging Library\uff09\u662fPython\u4e2d\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684\u56fe\u50cf\u5904\u7406\u5e93\u3002\u867d\u7136PIL\u5df2\u7ecf\u4e0d\u518d\u66f4\u65b0\uff0c\u4f46\u5176\u6d3e\u751f\u7248\u672cPillow\u4ecd\u7136\u6d3b\u8dc3\u7ef4\u62a4\u5e76\u65b0\u589e\u4e86\u8bb8\u591a\u529f\u80fd\uff0c\u56e0\u6b64\u6211\u4eec\u901a\u5e38\u4f7f\u7528Pillow\u6765\u5904\u7406\u56fe\u50cf\u3002<\/p>\n<\/p>\n

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

    \u5728\u5f00\u59cb\u4e4b\u524d\uff0c\u8bf7\u786e\u4fdd\u5df2\u5b89\u88c5Pillow\u5e93\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

    pip install pillow<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    1. \u4f7f\u7528Pillow\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20<\/li>\n<\/ol>\n
      Pillow\u63d0\u4f9b\u4e86\u7b80\u5355\u7684\u63a5\u53e3\u6765\u8bfb\u53d6\u548c\u64cd\u4f5c\u56fe\u50cf\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528Pillow\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
      from PIL import Image<\/p>\n
      \u6253\u5f00\u56fe\u7247<\/strong><\/h2>\n
      image = Image.open('path_to_image.jpg')<\/p>\n
      \u83b7\u53d6\u56fe\u7247\u7684\u5bbd\u548c\u9ad8<\/strong><\/h2>\n
      width, height = image.size<\/p>\n
      \u8bfb\u53d6\u50cf\u7d20<\/strong><\/h2>\n
      pixels = list(image.getdata())<\/p>\n
      \u8f93\u51fa\u56fe\u7247\u7684\u524d10\u4e2a\u50cf\u7d20<\/strong><\/h2>\n
      print(pixels[:10])<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u4f7f\u7528Image.open()<\/code>\u65b9\u6cd5\u6253\u5f00\u4e00\u5f20\u56fe\u7247\u3002\u7136\u540e\u901a\u8fc7image.size<\/code>\u83b7\u53d6\u56fe\u7247\u7684\u5bbd\u5ea6\u548c\u9ad8\u5ea6\u3002\u63a5\u7740\u4f7f\u7528image.getdata()<\/code>\u65b9\u6cd5\u83b7\u53d6\u56fe\u7247\u7684\u50cf\u7d20\u6570\u636e\uff0c\u5e76\u5c06\u5176\u8f6c\u6362\u4e3a\u5217\u8868\u5f62\u5f0f\u3002\u8fd9\u6837\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bbf\u95ee\u548c\u5904\u7406\u6bcf\u4e2a\u50cf\u7d20\u3002<\/p>\n<\/p>\n
      \u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong>Pillow\u901a\u8fc7getdata()<\/code>\u65b9\u6cd5\u5c06\u56fe\u50cf\u50cf\u7d20\u4ee5\u6241\u5e73\u5217\u8868\u5f62\u5f0f\u8fd4\u56de\uff0c\u6bcf\u4e2a\u5143\u7d20\u4ee3\u8868\u4e00\u4e2a\u50cf\u7d20\u503c\u3002\u5bf9\u4e8eRGB\u56fe\u50cf\uff0c\u6bcf\u4e2a\u50cf\u7d20\u7531\u4e09\u4e2a\u503c\uff08R, G, B\uff09\u7ec4\u6210\uff0c\u5bf9\u4e8e\u7070\u5ea6\u56fe\u50cf\uff0c\u6bcf\u4e2a\u50cf\u7d20\u53ea\u6709\u4e00\u4e2a\u503c\u3002\u53ef\u4ee5\u5229\u7528\u8fd9\u4e9b\u50cf\u7d20\u503c\u8fdb\u884c\u56fe\u50cf\u5206\u6790\u3001\u4fee\u6539\u7b49\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
      \u4e8c\u3001\u4f7f\u7528OpenCV\u5e93\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20<\/p>\n<\/p>\n
      OpenCV\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u548c\u89c6\u9891\u5904\u7406\u529f\u80fd\uff0c\u5728\u5de5\u4e1a\u754c\u548c\u5b66\u672f\u754c\u5e7f\u6cdb\u5e94\u7528\u3002<\/p>\n<\/p>\n
        \n
      1. \u5b89\u88c5OpenCV<\/li>\n<\/ol>\n
        \u9996\u5148\u9700\u8981\u5b89\u88c5OpenCV\u5e93\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
        pip install opencv-python<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        1. \u4f7f\u7528OpenCV\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20<\/li>\n<\/ol>\n
          \u4ee5\u4e0b\u662f\u4f7f\u7528OpenCV\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
          import cv2<\/p>\n
          \u8bfb\u53d6\u56fe\u7247<\/strong><\/h2>\n
          image = cv2.imread('path_to_image.jpg')<\/p>\n
          \u83b7\u53d6\u56fe\u7247\u7684\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u548c\u901a\u9053\u6570<\/strong><\/h2>\n
          height, width, channels = image.shape<\/p>\n
          \u8bfb\u53d6\u50cf\u7d20<\/strong><\/h2>\n
          \u8bbf\u95ee\u50cf\u7d20\u503c\uff0cimage[y, x] \u5f62\u5f0f\u8868\u793a<\/strong><\/h2>\n
          pixel_value = image[0, 0]  # \u83b7\u53d6(0,0)\u4f4d\u7f6e\u7684\u50cf\u7d20\u503c<\/p>\n
          \u8f93\u51fa\u56fe\u7247\u7684\u524d10\u4e2a\u50cf\u7d20<\/strong><\/h2>\n
          print([image[y, x] for y in range(min(10, height)) for x in range(min(10, width))])<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528cv2.imread()<\/code>\u65b9\u6cd5\u8bfb\u53d6\u56fe\u7247\u3002OpenCV\u5c06\u56fe\u7247\u6570\u636e\u5b58\u50a8\u4e3anumpy\u6570\u7ec4\uff0cimage.shape<\/code>\u8fd4\u56de\u56fe\u7247\u7684\u7ef4\u5ea6\u4fe1\u606f\uff0c\u5305\u62ec\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u548c\u901a\u9053\u6570\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7image[y, x]<\/code>\u7684\u65b9\u5f0f\u76f4\u63a5\u8bbf\u95ee\u548c\u4fee\u6539\u6bcf\u4e2a\u50cf\u7d20\u7684\u503c\u3002<\/p>\n<\/p>\n
          \u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong>OpenCV\u9ed8\u8ba4\u4ee5BGR\uff08\u84dd\u3001\u7eff\u3001\u7ea2\uff09\u987a\u5e8f\u8bfb\u53d6\u56fe\u50cf\u50cf\u7d20\uff0c\u800c\u4e0d\u662f\u901a\u5e38\u7684RGB\u987a\u5e8f\u3002\u9700\u8981\u6ce8\u610f\u5728\u5904\u7406\u56fe\u50cf\u65f6\uff0c\u6839\u636e\u9700\u8981\u8fdb\u884c\u901a\u9053\u987a\u5e8f\u8f6c\u6362\u3002\u6b64\u5916\uff0cOpenCV\u5229\u7528numpy\u6570\u7ec4\u8fdb\u884c\u50cf\u7d20\u64cd\u4f5c\uff0c\u6548\u7387\u8f83\u9ad8\uff0c\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u56fe\u50cf\u6570\u636e\u3002<\/p>\n<\/p>\n
          \u4e09\u3001\u4f7f\u7528scikit-image\u5e93\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20<\/p>\n<\/p>\n
          scikit-image\u662f\u4e00\u4e2a\u57fa\u4e8enumpy\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u7528\u4e8e\u56fe\u50cf\u5206\u6790\u548c\u5904\u7406\u7684\u5de5\u5177\u51fd\u6570\uff0c\u9002\u5408\u79d1\u5b66\u8ba1\u7b97\u548c\u5b9e\u9a8c\u7814\u7a76\u3002<\/p>\n<\/p>\n
            \n
          1. \u5b89\u88c5scikit-image<\/li>\n<\/ol>\n
            \u9996\u5148\u5b89\u88c5scikit-image\u5e93\uff1a<\/p>\n<\/p>\n
            pip install scikit-image<\/p>\n
            <\/code><\/pre>\n<\/p>\n
              \n
            1. \u4f7f\u7528scikit-image\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20<\/li>\n<\/ol>\n
              \u4ee5\u4e0b\u662f\u4f7f\u7528scikit-image\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
              from skimage import io<\/p>\n
              import numpy as np<\/p>\n
              \u8bfb\u53d6\u56fe\u7247<\/strong><\/h2>\n
              image = io.imread('path_to_image.jpg')<\/p>\n
              \u83b7\u53d6\u56fe\u7247\u7684\u9ad8\u5ea6\u548c\u5bbd\u5ea6<\/strong><\/h2>\n
              height, width = image.shape[:2]<\/p>\n
              \u8bfb\u53d6\u50cf\u7d20<\/strong><\/h2>\n
              \u8bbf\u95ee\u50cf\u7d20\u503c\uff0cimage[y, x] \u5f62\u5f0f\u8868\u793a<\/strong><\/h2>\n
              pixel_value = image[0, 0]  # \u83b7\u53d6(0,0)\u4f4d\u7f6e\u7684\u50cf\u7d20\u503c<\/p>\n
              \u8f93\u51fa\u56fe\u7247\u7684\u524d10\u4e2a\u50cf\u7d20<\/strong><\/h2>\n
              print([image[y, x] for y in range(min(10, height)) for x in range(min(10, width))])<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528io.imread()<\/code>\u51fd\u6570\u8bfb\u53d6\u56fe\u7247\u3002scikit-image\u4f7f\u7528numpy\u6570\u7ec4\u5b58\u50a8\u56fe\u50cf\u6570\u636e\uff0c\u652f\u6301\u76f4\u63a5\u8bbf\u95ee\u548c\u64cd\u4f5c\u56fe\u50cf\u50cf\u7d20\u3002image.shape<\/code>\u8fd4\u56de\u56fe\u7247\u7684\u7ef4\u5ea6\u4fe1\u606f\uff0c\u53ef\u4ee5\u901a\u8fc7image[y, x]<\/code>\u65b9\u5f0f\u8bbf\u95ee\u50cf\u7d20\u3002<\/p>\n<\/p>\n
              \u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong>scikit-image\u63d0\u4f9b\u4e86\u8bb8\u591a\u9ad8\u7ea7\u56fe\u50cf\u5904\u7406\u5de5\u5177\uff0c\u6bd4\u5982\u5f62\u6001\u5b66\u53d8\u6362\u3001\u6ee4\u6ce2\u3001\u8fb9\u7f18\u68c0\u6d4b\u7b49\u3002\u9002\u7528\u4e8e\u9700\u8981\u4f7f\u7528\u5927\u91cf\u79d1\u5b66\u8ba1\u7b97\u7684\u5e94\u7528\u573a\u666f\u3002\u5728\u8bfb\u53d6\u548c\u64cd\u4f5c\u50cf\u7d20\u65f6\uff0cscikit-image\u7684\u63a5\u53e3\u4e0enumpy\u9ad8\u5ea6\u517c\u5bb9\uff0c\u6613\u4e8e\u4f7f\u7528\u3002<\/p>\n<\/p>\n
              \u56db\u3001\u603b\u7ed3\u4e0e\u5e94\u7528\u573a\u666f<\/p>\n<\/p>\n
              \u901a\u8fc7\u4ee5\u4e0a\u4e09\u79cd\u65b9\u6cd5\uff0cPython\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bfb\u53d6\u548c\u5904\u7406\u56fe\u7247\u50cf\u7d20\u3002\u6bcf\u79cd\u65b9\u6cd5\u5404\u6709\u7279\u70b9\uff1a<\/p>\n<\/p>\n
                \n
              • Pillow<\/strong>\uff1a\u7b80\u5355\u6613\u7528\uff0c\u9002\u5408\u5904\u7406\u57fa\u672c\u56fe\u50cf\u64cd\u4f5c\uff0c\u5982\u56fe\u50cf\u683c\u5f0f\u8f6c\u6362\u3001\u7f29\u653e\u3001\u88c1\u526a\u7b49\u3002\u9002\u5408\u521d\u5b66\u8005\u548c\u9700\u8981\u5feb\u901f\u5b9e\u73b0\u56fe\u50cf\u5904\u7406\u529f\u80fd\u7684\u573a\u666f\u3002<\/li>\n
              • OpenCV<\/strong>\uff1a\u529f\u80fd\u5f3a\u5927\uff0c\u652f\u6301\u591a\u79cd\u56fe\u50cf\u548c\u89c6\u9891\u5904\u7406\u7b97\u6cd5\uff0c\u9002\u5408\u8ba1\u7b97\u673a\u89c6\u89c9\u5e94\u7528\u3002\u9002\u5408\u9700\u8981\u590d\u6742\u56fe\u50cf\u5904\u7406\u548c\u5b9e\u65f6\u89c6\u9891\u5206\u6790\u7684\u573a\u666f\u3002<\/li>\n
              • scikit-image<\/strong>\uff1a\u57fa\u4e8enumpy\uff0c\u63d0\u4f9b\u4e30\u5bcc\u7684\u79d1\u5b66\u8ba1\u7b97\u5de5\u5177\uff0c\u9002\u5408\u56fe\u50cf\u5206\u6790\u548c\u7814\u7a76\u3002\u9002\u5408\u9700\u8981\u8fdb\u884c\u56fe\u50cf\u5206\u6790\u3001\u79d1\u5b66\u5b9e\u9a8c\u548c\u6570\u636e\u5904\u7406\u7684\u573a\u666f\u3002<\/li>\n<\/ul>\n
                \u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u5e93\u3002\u4f8b\u5982\uff0c\u5728\u5f00\u53d1\u4e00\u4e2a\u7b80\u5355\u7684\u56fe\u50cf\u67e5\u770b\u5668\u65f6\uff0cPillow\u53ef\u80fd\u662f\u4e0d\u9519\u7684\u9009\u62e9\uff1b\u5728\u5b9e\u73b0\u4e00\u4e2a\u5b9e\u65f6\u4eba\u8138\u8bc6\u522b\u7cfb\u7edf\u65f6\uff0cOpenCV\u66f4\u4e3a\u5408\u9002\uff1b\u800c\u5728\u8fdb\u884c\u56fe\u50cf\u7279\u5f81\u5206\u6790\u548c\u79d1\u5b66\u7814\u7a76\u65f6\uff0cscikit-image\u53ef\u80fd\u66f4\u80fd\u6ee1\u8db3\u8981\u6c42\u3002<\/p>\n<\/p>\n
                \u901a\u8fc7\u638c\u63e1\u8fd9\u4e9b\u5de5\u5177\u5e93\u7684\u4f7f\u7528\u65b9\u6cd5\uff0c\u4f60\u53ef\u4ee5\u5728Python\u4e2d\u7075\u6d3b\u5730\u5904\u7406\u56fe\u50cf\u6570\u636e\uff0c\u5b9e\u73b0\u591a\u79cd\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\u5e94\u7528\u3002\u65e0\u8bba\u662f\u57fa\u672c\u7684\u56fe\u50cf\u64cd\u4f5c\uff0c\u8fd8\u662f\u590d\u6742\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\uff0c\u8fd9\u4e9b\u5e93\u90fd\u80fd\u4e3a\u4f60\u63d0\u4f9b\u5f3a\u6709\u529b\u7684\u652f\u6301\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\uff0c\u5305\u62ecpix\u683c\u5f0f\uff1f<\/strong>
                Python\u53ef\u4ee5\u901a\u8fc7\u591a\u4e2a\u5e93\u6765\u8bfb\u53d6\u56fe\u7247\u6587\u4ef6\uff0c\u5305\u62ecPIL\uff08Pillow\uff09\u3001OpenCV\u7b49\u3002\u5bf9\u4e8epix\u683c\u5f0f\u7684\u56fe\u7247\uff0c\u901a\u5e38\u9700\u8981\u4f7f\u7528Pillow\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528Image.open()<\/code>\u65b9\u6cd5\u6765\u8bfb\u53d6\u56fe\u7247\uff0c\u5e76\u901a\u8fc7show()<\/code>\u65b9\u6cd5\u5c55\u793a\u56fe\u7247\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
                from PIL import Image\n\n# \u8bfb\u53d6pix\u683c\u5f0f\u7684\u56fe\u7247\nimg = Image.open('path_to_image.pix')\nimg.show()\n<\/code><\/pre>\n
                \u786e\u4fdd\u5b89\u88c5\u4e86Pillow\u5e93\uff0c\u53ef\u4ee5\u901a\u8fc7pip install Pillow<\/code>\u547d\u4ee4\u6765\u5b89\u88c5\u3002<\/p>\n
                \u5728\u8bfb\u53d6pix\u683c\u5f0f\u7684\u56fe\u7247\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u54ea\u4e9b\u5e38\u89c1\u95ee\u9898\uff1f<\/strong>
                \u8bfb\u53d6pix\u683c\u5f0f\u7684\u56fe\u7247\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u6587\u4ef6\u8def\u5f84\u9519\u8bef\u3001\u6587\u4ef6\u683c\u5f0f\u4e0d\u652f\u6301\u6216\u5e93\u672a\u5b89\u88c5\u7b49\u95ee\u9898\u3002\u786e\u4fdd\u6587\u4ef6\u8def\u5f84\u6b63\u786e\uff0c\u5e76\u4e14\u4f7f\u7528\u7684\u5e93\u652f\u6301\u8be5\u683c\u5f0f\u3002\u6b64\u5916\uff0c\u68c0\u67e5\u6587\u4ef6\u662f\u5426\u635f\u574f\u4e5f\u662f\u89e3\u51b3\u95ee\u9898\u7684\u4e00\u4e2a\u5173\u952e\u6b65\u9aa4\u3002<\/p>\n
                \u6709\u54ea\u4e9b\u5176\u4ed6Python\u5e93\u53ef\u4ee5\u7528\u6765\u5904\u7406\u56fe\u7247\u6587\u4ef6\uff1f<\/strong>
                \u9664\u4e86Pillow\uff0cPython\u8fd8\u63d0\u4f9b\u4e86\u5176\u4ed6\u591a\u4e2a\u5e93\u7528\u4e8e\u5904\u7406\u56fe\u7247\u6587\u4ef6\u3002\u4f8b\u5982\uff0cOpenCV\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u9002\u5408\u8fdb\u884c\u590d\u6742\u7684\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\uff1bMatplotlib\u4e0d\u4ec5\u53ef\u4ee5\u8bfb\u53d6\u548c\u663e\u793a\u56fe\u7247\uff0c\u8fd8\u53ef\u4ee5\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002\u4f7f\u7528\u8fd9\u4e9b\u5e93\u53ef\u4ee5\u6839\u636e\u9700\u6c42\u9009\u62e9\u6700\u5408\u9002\u7684\u5de5\u5177\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8bfb\u53d6\u56fe\u7247\u50cf\u7d20\u7684\u65b9\u6cd5\u4e3b\u8981\u6709\u4ee5\u4e0b\u51e0\u79cd\uff1a\u4f7f\u7528PIL\u5e93\u3001OpenCV\u5e93\u3001scikit-image\u5e93\u3002\u5176\u4e2d\uff0c […]","protected":false},"author":3,"featured_media":958109,"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\/958106"}],"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=958106"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/958106\/revisions"}],"predecessor-version":[{"id":958110,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/958106\/revisions\/958110"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/958109"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=958106"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=958106"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=958106"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}