{"id":1054706,"date":"2024-12-31T14:44:33","date_gmt":"2024-12-31T06:44:33","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1054706.html"},"modified":"2024-12-31T14:44:35","modified_gmt":"2024-12-31T06:44:35","slug":"python%e5%a6%82%e4%bd%95%e4%bf%ae%e6%94%b9%e5%9b%be%e5%83%8f%e5%83%8f%e7%b4%a0%e5%b9%b6%e4%bf%9d%e5%ad%98","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1054706.html","title":{"rendered":"python\u5982\u4f55\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58"},"content":{"rendered":"

\"python\u5982\u4f55\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\"<\/p>\n

Python\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u7684\u65b9\u6cd5<\/strong><\/p>\n<\/p>\n

\u5728Python\u4e2d\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u7684\u65b9\u6cd5\u6709\u5f88\u591a\uff0c\u5176\u4e2d\u4e00\u4e9b\u5e38\u7528\u7684\u5e93\u6709Pillow\u3001OpenCV\u7b49\u3002\u4f7f\u7528Pillow\u5e93\u3001\u4f7f\u7528OpenCV\u5e93\u3001\u6539\u53d8\u56fe\u50cf\u7684\u50cf\u7d20\u503c\u3001\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/strong>\u3002\u5176\u4e2d\uff0c\u4f7f\u7528Pillow\u5e93\u662f\u6700\u4e3a\u7b80\u5355\u4e14\u76f4\u89c2\u7684\u4e00\u79cd\u65b9\u6cd5\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pillow\u5e93\u6765\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pillow\u5e93<\/p>\n<\/p>\n

Pillow\u662fPython\u4e2d\u7684\u4e00\u4e2a\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u4f7f\u7528Pillow\u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u8bfb\u53d6\u3001\u4fee\u6539\u548c\u4fdd\u5b58\u56fe\u50cf\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Pillow\u5e93\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n

    \n
  1. \u5b89\u88c5Pillow\u5e93<\/li>\n
  2. \u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6<\/li>\n
  3. \u4fee\u6539\u56fe\u50cf\u50cf\u7d20<\/li>\n
  4. \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/li>\n<\/ol>\n

    1\u3001\u5b89\u88c5Pillow\u5e93<\/h3>\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\u88c5Pillow\u5e93\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\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6<\/h3>\n<\/p>\n
    \u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u4f7f\u7528Pillow\u5e93\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\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
    \u6253\u5370\u56fe\u50cf\u7684\u5c3a\u5bf8<\/strong><\/h2>\n
    print(image.size)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528Image.open()<\/code>\u51fd\u6570\u6253\u5f00\u56fe\u50cf\u6587\u4ef6\uff0c\u5e76\u5c06\u5176\u5b58\u50a8\u5728\u53d8\u91cfimage<\/code>\u4e2d\u3002image.size<\/code>\u5c5e\u6027\u8fd4\u56de\u56fe\u50cf\u7684\u5c3a\u5bf8\uff08\u5bbd\u5ea6\u548c\u9ad8\u5ea6\uff09\u3002<\/p>\n<\/p>\n
    3\u3001\u4fee\u6539\u56fe\u50cf\u50cf\u7d20<\/h3>\n<\/p>\n
    \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pillow\u5e93\u4fee\u6539\u56fe\u50cf\u7684\u50cf\u7d20\u3002\u4ee5\u4e0b\u662f\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
    # \u83b7\u53d6\u56fe\u50cf\u7684\u50cf\u7d20\u6570\u636e<\/p>\n
    pixels = image.load()<\/p>\n
    \u4fee\u6539\u56fe\u50cf\u7684\u50cf\u7d20<\/strong><\/h2>\n
    for i in range(image.width):<\/p>\n
        for j in range(image.height):<\/p>\n
            # \u83b7\u53d6\u5f53\u524d\u50cf\u7d20\u7684\u989c\u8272\u503c<\/p>\n
            r, g, b = pixels[i, j]<\/p>\n
            # \u4fee\u6539\u50cf\u7d20\u7684\u989c\u8272\u503c<\/p>\n
            pixels[i, j] = (r \/\/ 2, g \/\/ 2, b \/\/ 2)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528image.load()<\/code>\u51fd\u6570\u83b7\u53d6\u56fe\u50cf\u7684\u50cf\u7d20\u6570\u636e\uff0c\u5e76\u5c06\u5176\u5b58\u50a8\u5728\u53d8\u91cfpixels<\/code>\u4e2d\u3002\u7136\u540e\uff0c\u6211\u4eec\u4f7f\u7528\u5d4c\u5957\u7684for<\/code>\u5faa\u73af\u904d\u5386\u56fe\u50cf\u7684\u6bcf\u4e00\u4e2a\u50cf\u7d20\uff0c\u5e76\u4fee\u6539\u6bcf\u4e2a\u50cf\u7d20\u7684\u989c\u8272\u503c\u3002<\/p>\n<\/p>\n
    4\u3001\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/h3>\n<\/p>\n
    \u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pillow\u5e93\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf\u3002\u4ee5\u4e0b\u662f\u4fdd\u5b58\u56fe\u50cf\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
    # \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/p>\n
    image.save('modified_example.jpg')<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528image.save()<\/code>\u51fd\u6570\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf\uff0c\u5e76\u5c06\u5176\u5b58\u50a8\u5728\u6587\u4ef6modified_example.jpg<\/code>\u4e2d\u3002<\/p>\n<\/p>\n
    \u4e8c\u3001\u4f7f\u7528OpenCV\u5e93<\/p>\n<\/p>\n
    OpenCV\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u4f7f\u7528OpenCV\u5e93\uff0c\u6211\u4eec\u4e5f\u53ef\u4ee5\u8f7b\u677e\u5730\u8bfb\u53d6\u3001\u4fee\u6539\u548c\u4fdd\u5b58\u56fe\u50cf\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528OpenCV\u5e93\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
      \n
    1. \u5b89\u88c5OpenCV\u5e93<\/li>\n
    2. \u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6<\/li>\n
    3. \u4fee\u6539\u56fe\u50cf\u50cf\u7d20<\/li>\n
    4. \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/li>\n<\/ol>\n
      1\u3001\u5b89\u88c5OpenCV\u5e93<\/h3>\n<\/p>\n
      \u5728\u5f00\u59cb\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5148\u5b89\u88c5OpenCV\u5e93\u3002\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5OpenCV\u5e93\uff0c\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\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6<\/h3>\n<\/p>\n
      \u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u4f7f\u7528OpenCV\u5e93\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\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
      \u6253\u5370\u56fe\u50cf\u7684\u5c3a\u5bf8<\/strong><\/h2>\n
      print(image.shape)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528cv2.imread()<\/code>\u51fd\u6570\u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6\uff0c\u5e76\u5c06\u5176\u5b58\u50a8\u5728\u53d8\u91cfimage<\/code>\u4e2d\u3002image.shape<\/code>\u5c5e\u6027\u8fd4\u56de\u56fe\u50cf\u7684\u5c3a\u5bf8\uff08\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u548c\u901a\u9053\u6570\uff09\u3002<\/p>\n<\/p>\n
      3\u3001\u4fee\u6539\u56fe\u50cf\u50cf\u7d20<\/h3>\n<\/p>\n
      \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528OpenCV\u5e93\u4fee\u6539\u56fe\u50cf\u7684\u50cf\u7d20\u3002\u4ee5\u4e0b\u662f\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
      # \u4fee\u6539\u56fe\u50cf\u7684\u50cf\u7d20<\/p>\n
      for i in range(image.shape[1]):<\/p>\n
          for j in range(image.shape[0]):<\/p>\n
              # \u83b7\u53d6\u5f53\u524d\u50cf\u7d20\u7684\u989c\u8272\u503c<\/p>\n
              b, g, r = image[j, i]<\/p>\n
              # \u4fee\u6539\u50cf\u7d20\u7684\u989c\u8272\u503c<\/p>\n
              image[j, i] = [b \/\/ 2, g \/\/ 2, r \/\/ 2]<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528\u5d4c\u5957\u7684for<\/code>\u5faa\u73af\u904d\u5386\u56fe\u50cf\u7684\u6bcf\u4e00\u4e2a\u50cf\u7d20\uff0c\u5e76\u4fee\u6539\u6bcf\u4e2a\u50cf\u7d20\u7684\u989c\u8272\u503c\u3002<\/p>\n<\/p>\n
      4\u3001\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/h3>\n<\/p>\n
      \u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528OpenCV\u5e93\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf\u3002\u4ee5\u4e0b\u662f\u4fdd\u5b58\u56fe\u50cf\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
      # \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/p>\n
      cv2.imwrite('modified_example.jpg', image)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528cv2.imwrite()<\/code>\u51fd\u6570\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf\uff0c\u5e76\u5c06\u5176\u5b58\u50a8\u5728\u6587\u4ef6modified_example.jpg<\/code>\u4e2d\u3002<\/p>\n<\/p>\n
      \u4e09\u3001\u6539\u53d8\u56fe\u50cf\u7684\u50cf\u7d20\u503c<\/p>\n<\/p>\n
      \u5728\u56fe\u50cf\u5904\u7406\u4e2d\uff0c\u6539\u53d8\u56fe\u50cf\u7684\u50cf\u7d20\u503c\u662f\u4e00\u4e2a\u5e38\u89c1\u7684\u64cd\u4f5c\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u6539\u53d8\u56fe\u50cf\u7684\u50cf\u7d20\u503c\uff0c\u4f8b\u5982\u8c03\u6574\u4eae\u5ea6\u3001\u5bf9\u6bd4\u5ea6\u3001\u989c\u8272\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u6539\u53d8\u56fe\u50cf\u50cf\u7d20\u503c\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
      1\u3001\u8c03\u6574\u4eae\u5ea6<\/h3>\n<\/p>\n
      \u8c03\u6574\u56fe\u50cf\u7684\u4eae\u5ea6\u662f\u6539\u53d8\u56fe\u50cf\u50cf\u7d20\u503c\u7684\u4e00\u79cd\u5e38\u89c1\u65b9\u6cd5\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u589e\u52a0\u6216\u51cf\u5c11\u50cf\u7d20\u7684\u989c\u8272\u503c\u6765\u8c03\u6574\u56fe\u50cf\u7684\u4eae\u5ea6\u3002\u4ee5\u4e0b\u662f\u8c03\u6574\u56fe\u50cf\u4eae\u5ea6\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\u50cf\u7d20\u6570\u636e<\/strong><\/h2>\n
      pixels = image.load()<\/p>\n
      \u8c03\u6574\u56fe\u50cf\u4eae\u5ea6<\/strong><\/h2>\n
      for i in range(image.width):<\/p>\n
          for j in range(image.height):<\/p>\n
              # \u83b7\u53d6\u5f53\u524d\u50cf\u7d20\u7684\u989c\u8272\u503c<\/p>\n
              r, g, b = pixels[i, j]<\/p>\n
              # \u589e\u52a0\u4eae\u5ea6<\/p>\n
              pixels[i, j] = (min(r + 50, 255), min(g + 50, 255), min(b + 50, 255))<\/p>\n
      \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n
      image.save('bright_example.jpg')<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7\u589e\u52a0\u50cf\u7d20\u7684\u989c\u8272\u503c\u6765\u8c03\u6574\u56fe\u50cf\u7684\u4eae\u5ea6\uff0c\u5e76\u4f7f\u7528min()<\/code>\u51fd\u6570\u786e\u4fdd\u989c\u8272\u503c\u4e0d\u8d85\u8fc7255\u3002<\/p>\n<\/p>\n
      2\u3001\u8c03\u6574\u5bf9\u6bd4\u5ea6<\/h3>\n<\/p>\n
      \u8c03\u6574\u56fe\u50cf\u7684\u5bf9\u6bd4\u5ea6\u662f\u6539\u53d8\u56fe\u50cf\u50cf\u7d20\u503c\u7684\u53e6\u4e00\u79cd\u5e38\u89c1\u65b9\u6cd5\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574\u50cf\u7d20\u989c\u8272\u503c\u7684\u8303\u56f4\u6765\u5b9e\u73b0\u5bf9\u6bd4\u5ea6\u7684\u8c03\u6574\u3002\u4ee5\u4e0b\u662f\u8c03\u6574\u56fe\u50cf\u5bf9\u6bd4\u5ea6\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
      from PIL import Image, ImageEnhance<\/p>\n
      \u6253\u5f00\u56fe\u50cf\u6587\u4ef6<\/strong><\/h2>\n
      image = Image.open('example.jpg')<\/p>\n
      \u521b\u5efa\u56fe\u50cf\u589e\u5f3a\u5bf9\u8c61<\/strong><\/h2>\n
      enhancer = ImageEnhance.Contrast(image)<\/p>\n
      \u8c03\u6574\u5bf9\u6bd4\u5ea6<\/strong><\/h2>\n
      enhanced_image = enhancer.enhance(1.5)<\/p>\n
      \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n
      enhanced_image.save('contrast_example.jpg')<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528ImageEnhance.Contrast()<\/code>\u51fd\u6570\u521b\u5efa\u56fe\u50cf\u589e\u5f3a\u5bf9\u8c61\uff0c\u5e76\u4f7f\u7528enhancer.enhance()<\/code>\u51fd\u6570\u8c03\u6574\u56fe\u50cf\u7684\u5bf9\u6bd4\u5ea6\u3002<\/p>\n<\/p>\n
      3\u3001\u8c03\u6574\u989c\u8272<\/h3>\n<\/p>\n
      \u8c03\u6574\u56fe\u50cf\u7684\u989c\u8272\u662f\u6539\u53d8\u56fe\u50cf\u50cf\u7d20\u503c\u7684\u53e6\u4e00\u79cd\u65b9\u6cd5\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u6539\u53d8\u50cf\u7d20\u7684\u989c\u8272\u503c\u6765\u5b9e\u73b0\u989c\u8272\u7684\u8c03\u6574\u3002\u4ee5\u4e0b\u662f\u8c03\u6574\u56fe\u50cf\u989c\u8272\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
      from PIL import Image, ImageEnhance<\/p>\n
      \u6253\u5f00\u56fe\u50cf\u6587\u4ef6<\/strong><\/h2>\n
      image = Image.open('example.jpg')<\/p>\n
      \u521b\u5efa\u56fe\u50cf\u589e\u5f3a\u5bf9\u8c61<\/strong><\/h2>\n
      enhancer = ImageEnhance.Color(image)<\/p>\n
      \u8c03\u6574\u989c\u8272<\/strong><\/h2>\n
      enhanced_image = enhancer.enhance(1.5)<\/p>\n
      \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n
      enhanced_image.save('color_example.jpg')<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528ImageEnhance.Color()<\/code>\u51fd\u6570\u521b\u5efa\u56fe\u50cf\u589e\u5f3a\u5bf9\u8c61\uff0c\u5e76\u4f7f\u7528enhancer.enhance()<\/code>\u51fd\u6570\u8c03\u6574\u56fe\u50cf\u7684\u989c\u8272\u3002<\/p>\n<\/p>\n
      \u56db\u3001\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/p>\n<\/p>\n
      \u5728\u5b8c\u6210\u56fe\u50cf\u50cf\u7d20\u503c\u7684\u4fee\u6539\u540e\uff0c\u6211\u4eec\u9700\u8981\u5c06\u4fee\u6539\u540e\u7684\u56fe\u50cf\u4fdd\u5b58\u5230\u6587\u4ef6\u4e2d\u3002Pillow\u548cOpenCV\u5e93\u90fd\u63d0\u4f9b\u4e86\u4fdd\u5b58\u56fe\u50cf\u7684\u65b9\u6cd5\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Pillow\u5e93\u548cOpenCV\u5e93\u4fdd\u5b58\u56fe\u50cf\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
      1\u3001\u4f7f\u7528Pillow\u5e93\u4fdd\u5b58\u56fe\u50cf<\/h3>\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
      \u4fee\u6539\u56fe\u50cf\u7684\u50cf\u7d20<\/strong><\/h2>\n
      ...<\/strong><\/h2>\n
      \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n
      image.save('modified_example.jpg')<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      2\u3001\u4f7f\u7528OpenCV\u5e93\u4fdd\u5b58\u56fe\u50cf<\/h3>\n<\/p>\n
      import cv2<\/p>\n
      \u8bfb\u53d6\u56fe\u50cf\u6587\u4ef6<\/strong><\/h2>\n
      image = cv2.imread('example.jpg')<\/p>\n
      \u4fee\u6539\u56fe\u50cf\u7684\u50cf\u7d20<\/strong><\/h2>\n
      ...<\/strong><\/h2>\n
      \u4fdd\u5b58\u4fee\u6539\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n
      cv2.imwrite('modified_example.jpg', image)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u603b\u7ed3<\/p>\n<\/p>\n
      \u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u4eec\u4ecb\u7ecd\u4e86\u5982\u4f55\u4f7f\u7528Python\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u3002\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u4f7f\u7528Pillow\u5e93\u548cOpenCV\u5e93\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u7684\u65b9\u6cd5\uff0c\u5e76\u63d0\u4f9b\u4e86\u4e00\u4e9b\u5e38\u89c1\u7684\u6539\u53d8\u56fe\u50cf\u50cf\u7d20\u503c\u7684\u65b9\u6cd5\uff0c\u5982\u8c03\u6574\u4eae\u5ea6\u3001\u5bf9\u6bd4\u5ea6\u548c\u989c\u8272\u3002\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u5b9e\u73b0\u56fe\u50cf\u7684\u50cf\u7d20\u4fee\u6539\u548c\u4fdd\u5b58\u3002\u65e0\u8bba\u662f\u5bf9\u56fe\u50cf\u8fdb\u884c\u7b80\u5355\u7684\u50cf\u7d20\u4fee\u6539\uff0c\u8fd8\u662f\u8fdb\u884c\u590d\u6742\u7684\u56fe\u50cf\u5904\u7406\uff0cPillow\u548cOpenCV\u5e93\u90fd\u662f\u975e\u5e38\u6709\u7528\u7684\u5de5\u5177\u3002\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u80fd\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\uff0c\u5e76\u4e3a\u4f60\u7684\u56fe\u50cf\u5904\u7406\u5de5\u4f5c\u63d0\u4f9b\u4e00\u4e9b\u53c2\u8003\u3002<\/p>\n<\/p>\n
      \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
       \u5982\u4f55\u4f7f\u7528Python\u8bfb\u53d6\u56fe\u50cf\u5e76\u8bbf\u95ee\u5176\u50cf\u7d20\u6570\u636e\uff1f<\/strong>
      \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pillow\u5e93\u6765\u8bfb\u53d6\u56fe\u50cf\u3002\u9996\u5148\uff0c\u5b89\u88c5Pillow\u5e93\uff0c\u7136\u540e\u4f7f\u7528Image.open()<\/code>\u65b9\u6cd5\u6253\u5f00\u56fe\u50cf\u6587\u4ef6\u3002\u8bfb\u53d6\u56fe\u50cf\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7load()<\/code>\u65b9\u6cd5\u8bbf\u95ee\u50cf\u7d20\u6570\u636e\u3002\u6bcf\u4e2a\u50cf\u7d20\u53ef\u4ee5\u901a\u8fc7\u5176\u5750\u6807\uff08x, y\uff09\u8fdb\u884c\u8bbf\u95ee\uff0c\u4f8b\u5982pixel_data[x, y]<\/code>\u3002<\/p>\n
      \u6211\u53ef\u4ee5\u4f7f\u7528\u54ea\u4e9b\u5e93\u6765\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\uff1f<\/strong>
      Pillow\u662f\u6700\u5e38\u7528\u7684\u5e93\u4e4b\u4e00\uff0c\u63d0\u4f9b\u4e86\u7b80\u5355\u6613\u7528\u7684\u63a5\u53e3\u6765\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u3002\u6b64\u5916\uff0cNumPy\u4e5f\u53ef\u4ee5\u7528\u6765\u5904\u7406\u56fe\u50cf\u6570\u636e\uff0c\u7279\u522b\u662f\u5f53\u9700\u8981\u8fdb\u884c\u590d\u6742\u7684\u6570\u5b66\u8fd0\u7b97\u65f6\u3002OpenCV\u4e5f\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u5e93\uff0c\u9002\u5408\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\u3002<\/p>\n
      \u5982\u4f55\u5c06\u4fee\u6539\u540e\u7684\u56fe\u50cf\u4fdd\u5b58\u4e3a\u65b0\u6587\u4ef6\uff1f<\/strong>
      \u5728\u4f7f\u7528Pillow\u5e93\u4fee\u6539\u56fe\u50cf\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528save()<\/code>\u65b9\u6cd5\u5c06\u56fe\u50cf\u4fdd\u5b58\u4e3a\u65b0\u6587\u4ef6\u3002\u53ef\u4ee5\u6307\u5b9a\u6587\u4ef6\u540d\u548c\u683c\u5f0f\uff0c\u4f8b\u5982image.save("new_image.png")<\/code>\u3002\u786e\u4fdd\u5728\u4fdd\u5b58\u65f6\u9009\u62e9\u5408\u9002\u7684\u6587\u4ef6\u683c\u5f0f\uff0c\u4ee5\u4fdd\u6301\u56fe\u50cf\u8d28\u91cf\u548c\u900f\u660e\u5ea6\u7b49\u7279\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u7684\u65b9\u6cd5 \u5728Python\u4e2d\u4fee\u6539\u56fe\u50cf\u50cf\u7d20\u5e76\u4fdd\u5b58\u7684\u65b9\u6cd5\u6709\u5f88\u591a\uff0c\u5176\u4e2d\u4e00\u4e9b\u5e38\u7528\u7684\u5e93\u6709Pil […]","protected":false},"author":3,"featured_media":1054709,"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\/1054706"}],"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=1054706"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1054706\/revisions"}],"predecessor-version":[{"id":1054712,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1054706\/revisions\/1054712"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1054709"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1054706"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1054706"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1054706"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}