{"id":1013336,"date":"2024-12-27T11:47:05","date_gmt":"2024-12-27T03:47:05","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1013336.html"},"modified":"2024-12-27T11:47:07","modified_gmt":"2024-12-27T03:47:07","slug":"python%e4%b8%ad%e8%89%b2%e5%bd%a9%e5%a6%82%e4%bd%95%e4%b8%8a%e8%89%b2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1013336.html","title":{"rendered":"python\u4e2d\u8272\u5f69\u5982\u4f55\u4e0a\u8272"},"content":{"rendered":"

\"python\u4e2d\u8272\u5f69\u5982\u4f55\u4e0a\u8272\"<\/p>\n

\u5728Python\u4e2d\uff0c\u8272\u5f69\u4e0a\u8272\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u6765\u5b9e\u73b0\uff0c\u5982\u4f7f\u7528matplotlib\u5e93\u3001PIL\u5e93\u3001OpenCV\u5e93\u3001turtle\u5e93\u7b49\u3002\u4f7f\u7528matplotlib\u5e93\u7ed8\u5236\u56fe\u5f62\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u53c2\u6570\u8bbe\u7f6e\u989c\u8272\u3001\u4f7f\u7528PIL\u5e93\u5904\u7406\u56fe\u50cf\u65f6\u53ef\u4ee5\u901a\u8fc7\u50cf\u7d20\u64cd\u4f5c\u6539\u53d8\u989c\u8272\u3001OpenCV\u5219\u53ef\u4ee5\u7528\u4e8e\u590d\u6742\u7684\u56fe\u50cf\u5904\u7406\u548c\u989c\u8272\u53d8\u6362\u3002<\/strong>\u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8\u8fd9\u4e9b\u65b9\u6cd5\u4e2d\u7684\u4e00\u79cd\uff1a\u4f7f\u7528matplotlib\u5e93\u6765\u8bbe\u7f6e\u548c\u6539\u53d8\u56fe\u5f62\u7684\u989c\u8272\u3002<\/p>\n<\/p>\n

\u4f7f\u7528matplotlib\u5e93\u8fdb\u884c\u56fe\u5f62\u7ed8\u5236\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bb8\u591a\u53c2\u6570\u6765\u63a7\u5236\u989c\u8272\uff0c\u5982color<\/code>\u3001cmap<\/code>\u7b49\u3002color<\/code>\u53c2\u6570\u53ef\u4ee5\u76f4\u63a5\u8bbe\u7f6e\u5177\u4f53\u7684\u989c\u8272\u503c\uff0c\u5982\u7ea2\u8272\u3001\u7eff\u8272\u3001\u84dd\u8272\u7b49\uff0c\u652f\u6301\u989c\u8272\u540d\u79f0\u3001\u5341\u516d\u8fdb\u5236\u989c\u8272\u4ee3\u7801\u4ee5\u53caRGB\u5143\u7ec4\u7b49\u591a\u79cd\u683c\u5f0f\u3002cmap<\/code>\u53c2\u6570\u5219\u7528\u4e8e\u8bbe\u7f6e\u989c\u8272\u6620\u5c04\uff0c\u7279\u522b\u9002\u7528\u4e8e\u6e10\u53d8\u8272\u6216\u663e\u793a\u6570\u636e\u5206\u5e03\u7684\u70ed\u56fe\u7b49\u3002<\/p>\n<\/p>\n

\u4e00\u3001MATPLOTLIB\u5e93\u7684\u57fa\u672c\u8272\u5f69\u8bbe\u7f6e<\/p>\n<\/p>\n

\u5728\u4f7f\u7528matplotlib\u7ed8\u5236\u56fe\u5f62\u65f6\uff0c\u6700\u5e38\u7528\u7684\u5c31\u662fcolor<\/code>\u53c2\u6570\u3002\u901a\u8fc7\u8fd9\u4e2a\u53c2\u6570\uff0c\u6211\u4eec\u53ef\u4ee5\u4e3a\u5404\u79cd\u56fe\u5f62\u5143\u7d20\u6307\u5b9a\u989c\u8272\u3002matplotlib\u652f\u6301\u591a\u79cd\u989c\u8272\u8868\u793a\u65b9\u5f0f\uff0c\u5305\u62ec\uff1a<\/p>\n<\/p>\n

    \n
  1. \n

    \u989c\u8272\u540d\u79f0<\/strong>\uff1a\u5982'red'\u3001'blue'\u3001'green'\u7b49\u3002matplotlib\u4e2d\u9884\u5b9a\u4e49\u4e86\u8bb8\u591a\u57fa\u672c\u989c\u8272\u7684\u540d\u79f0\uff0c\u4f7f\u7528\u8d77\u6765\u975e\u5e38\u65b9\u4fbf\u3002<\/p>\n<\/p>\n<\/li>\n

  2. \n

    \u5341\u516d\u8fdb\u5236\u989c\u8272\u4ee3\u7801<\/strong>\uff1a\u5982'#FF0000'\u8868\u793a\u7ea2\u8272\uff0c'#00FF00'\u8868\u793a\u7eff\u8272\uff0c'#0000FF'\u8868\u793a\u84dd\u8272\u3002\u8fd9\u79cd\u65b9\u5f0f\u5141\u8bb8\u6211\u4eec\u8bbe\u7f6e\u66f4\u52a0\u7cbe\u7ec6\u7684\u989c\u8272\u3002<\/p>\n<\/p>\n<\/li>\n

  3. \n

    RGB\u6216RGBA\u5143\u7ec4<\/strong>\uff1a\u5982(1, 0, 0)\u8868\u793a\u7ea2\u8272\uff0c(0, 1, 0)\u8868\u793a\u7eff\u8272\uff0c(0, 0, 1)\u8868\u793a\u84dd\u8272\u3002RGBA\u6a21\u5f0f\u4e2dA\u8868\u793a\u900f\u660e\u5ea6\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

    \u4f8b\u5982\uff0c\u5728\u7ed8\u5236\u4e00\u6761\u7ea2\u8272\u7684\u76f4\u7ebf\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n

    import matplotlib.pyplot as plt<\/p>\n
    plt.plot([0, 1], [0, 1], color='red')  # \u4f7f\u7528\u989c\u8272\u540d\u79f0<\/p>\n
    plt.plot([0, 1], [1, 2], color='#00FF00')  # \u4f7f\u7528\u5341\u516d\u8fdb\u5236\u989c\u8272\u4ee3\u7801<\/p>\n
    plt.plot([0, 1], [2, 3], color=(0, 0, 1))  # \u4f7f\u7528RGB\u5143\u7ec4<\/p>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u8fd9\u79cd\u7075\u6d3b\u7684\u989c\u8272\u8bbe\u7f6e\u65b9\u5f0f\u4f7f\u5f97matplotlib\u5728\u5904\u7406\u56fe\u5f62\u7ed8\u5236\u65f6\u975e\u5e38\u5f3a\u5927\u4e14\u6613\u4e8e\u4f7f\u7528\u3002<\/p>\n<\/p>\n
    \u4e8c\u3001MATPLOTLIB\u4e2d\u7684COLORMAP<\/p>\n<\/p>\n
    \u9664\u4e86\u76f4\u63a5\u8bbe\u7f6e\u989c\u8272\u4e4b\u5916\uff0cmatplotlib\u8fd8\u63d0\u4f9b\u4e86\u989c\u8272\u6620\u5c04\uff08colormap\uff09\u7684\u529f\u80fd\uff0c\u8fd9\u5bf9\u4e8e\u53ef\u89c6\u5316\u6570\u636e\u5206\u5e03\u975e\u5e38\u6709\u7528\u3002\u989c\u8272\u6620\u5c04\u662f\u6307\u5c06\u6570\u503c\u6570\u636e\u6620\u5c04\u4e3a\u989c\u8272\u7684\u4e00\u79cd\u65b9\u5f0f\uff0c\u901a\u8fc7\u989c\u8272\u53d8\u5316\u6765\u53cd\u6620\u6570\u636e\u7684\u53d8\u5316\u3002<\/p>\n<\/p>\n
      \n
    1. \u4f7f\u7528colormap<\/strong>\uff1a\u5728\u7ed8\u5236\u56fe\u5f62\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7cmap<\/code>\u53c2\u6570\u6307\u5b9a\u989c\u8272\u6620\u5c04\u3002\u4f8b\u5982\uff0c\u5728\u7ed8\u5236\u6563\u70b9\u56fe\u65f6\uff0c\u53ef\u4ee5\u6839\u636e\u6570\u636e\u7684\u503c\u6765\u8bbe\u7f6e\u70b9\u7684\u989c\u8272\u3002<\/li>\n<\/ol>\n
      import numpy as np<\/p>\n
      import matplotlib.pyplot as plt<\/p>\n
      x = np.random.rand(100)<\/p>\n
      y = np.random.rand(100)<\/p>\n
      colors = np.random.rand(100)<\/p>\n
      plt.scatter(x, y, c=colors, cmap='viridis')<\/p>\n
      plt.colorbar()  # \u6dfb\u52a0\u989c\u8272\u6761<\/p>\n
      plt.show()<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u5728\u4e0a\u9762\u7684\u4f8b\u5b50\u4e2d\uff0ccmap='viridis'<\/code>\u6307\u5b9a\u4e86\u989c\u8272\u6620\u5c04\u4e3a'viridis'\uff0c\u8fd9\u662fmatplotlib\u4e2d\u4e00\u4e2a\u975e\u5e38\u53d7\u6b22\u8fce\u7684\u6e10\u53d8\u8272\u65b9\u6848\u3002<\/p>\n<\/p>\n
        \n
      1. \u81ea\u5b9a\u4e49colormap<\/strong>\uff1a\u5982\u679c\u9884\u5b9a\u4e49\u7684\u989c\u8272\u6620\u5c04\u4e0d\u80fd\u6ee1\u8db3\u9700\u6c42\uff0c\u8fd8\u53ef\u4ee5\u81ea\u5b9a\u4e49\u989c\u8272\u6620\u5c04\u3002\u901a\u8fc7LinearSegmentedColormap<\/code>\u7c7b\uff0c\u53ef\u4ee5\u521b\u5efa\u81ea\u5b9a\u4e49\u989c\u8272\u6620\u5c04\u3002<\/li>\n<\/ol>\n
        from matplotlib.colors import LinearSegmentedColormap<\/p>\n
        cmap = LinearSegmentedColormap.from_list('my_cmap', ['blue', 'white', 'red'])<\/p>\n
        plt.scatter(x, y, c=colors, cmap=cmap)<\/p>\n
        plt.colorbar()<\/p>\n
        plt.show()<\/p>\n
        <\/code><\/pre>\n<\/p>\n
        \u81ea\u5b9a\u4e49\u989c\u8272\u6620\u5c04\u63d0\u4f9b\u4e86\u66f4\u591a\u7684\u7075\u6d3b\u6027\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u7684\u9700\u6c42\u8c03\u6574\u989c\u8272\u7684\u6e10\u53d8\u3002<\/p>\n<\/p>\n
        \u4e09\u3001PIL\u5e93\u4e2d\u7684\u8272\u5f69\u64cd\u4f5c<\/p>\n<\/p>\n
        PIL\uff08Python Imaging Library\uff09\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u5e93\uff0c\u652f\u6301\u591a\u79cd\u56fe\u50cf\u683c\u5f0f\uff0c\u53ef\u4ee5\u7528\u6765\u5904\u7406\u56fe\u50cf\u7684\u989c\u8272\u3002PIL\u7684\u4e00\u4e2a\u5e38\u7528\u6a21\u5757\u662fImage<\/code>\uff0c\u901a\u8fc7\u8fd9\u4e2a\u6a21\u5757\u53ef\u4ee5\u5bf9\u56fe\u50cf\u8fdb\u884c\u5404\u79cd\u64cd\u4f5c\uff0c\u5305\u62ec\u989c\u8272\u53d8\u6362\u3002<\/p>\n<\/p>\n
          \n
        1. \u52a0\u8f7d\u548c\u663e\u793a\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528PIL\u52a0\u8f7d\u56fe\u50cf\u975e\u5e38\u7b80\u5355\uff0c\u53ef\u4ee5\u901a\u8fc7Image.open()<\/code>\u51fd\u6570\u6765\u5b9e\u73b0\u3002<\/li>\n<\/ol>\n
          from PIL import Image<\/p>\n
          image = Image.open('example.jpg')<\/p>\n
          image.show()<\/p>\n
          <\/code><\/pre>\n<\/p>\n
            \n
          1. \u56fe\u50cf\u989c\u8272\u8f6c\u6362<\/strong>\uff1aPIL\u652f\u6301\u591a\u79cd\u989c\u8272\u6a21\u5f0f\uff0c\u53ef\u4ee5\u4f7f\u7528convert()<\/code>\u51fd\u6570\u8fdb\u884c\u8f6c\u6362\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf\u3002<\/li>\n<\/ol>\n
            gray_image = image.convert('L')<\/p>\n
            gray_image.show()<\/p>\n
            <\/code><\/pre>\n<\/p>\n
              \n
            1. \u56fe\u50cf\u989c\u8272\u589e\u5f3a<\/strong>\uff1aPIL\u63d0\u4f9b\u4e86ImageEnhance<\/code>\u6a21\u5757\uff0c\u53ef\u4ee5\u7528\u6765\u589e\u5f3a\u56fe\u50cf\u7684\u5bf9\u6bd4\u5ea6\u3001\u4eae\u5ea6\u3001\u989c\u8272\u7b49\u3002<\/li>\n<\/ol>\n
              from PIL import ImageEnhance<\/p>\n
              enhancer = ImageEnhance.Color(image)<\/p>\n
              enhanced_image = enhancer.enhance(2.0)  # \u589e\u5f3a\u989c\u8272\u9971\u548c\u5ea6<\/p>\n
              enhanced_image.show()<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u56db\u3001OPENCV\u5e93\u4e2d\u7684\u8272\u5f69\u5904\u7406<\/p>\n<\/p>\n
              OpenCV\u662f\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93\uff0c\u652f\u6301\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u529f\u80fd\u3002\u4e0ePIL\u76f8\u6bd4\uff0cOpenCV\u66f4\u52a0\u4e13\u6ce8\u4e8e\u9ad8\u7ea7\u56fe\u50cf\u5904\u7406\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\u3002<\/p>\n<\/p>\n
                \n
              1. \u52a0\u8f7d\u548c\u663e\u793a\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528OpenCV\u52a0\u8f7d\u56fe\u50cf\uff0c\u53ef\u4ee5\u4f7f\u7528cv2.imread()<\/code>\u51fd\u6570\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0cOpenCV\u9ed8\u8ba4\u4f7f\u7528BGR\u989c\u8272\u987a\u5e8f\uff0c\u800c\u4e0d\u662f\u5e38\u89c1\u7684RGB\u3002<\/li>\n<\/ol>\n
                import cv2<\/p>\n
                image = cv2.imread('example.jpg')<\/p>\n
                cv2.imshow('Image', image)<\/p>\n
                cv2.wAI<\/a>tKey(0)<\/p>\n
                cv2.destroyAllWindows()<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                  \n
                1. \u989c\u8272\u7a7a\u95f4\u8f6c\u6362<\/strong>\uff1aOpenCV\u652f\u6301\u591a\u79cd\u989c\u8272\u7a7a\u95f4\uff0c\u53ef\u4ee5\u4f7f\u7528cv2.cvtColor()<\/code>\u51fd\u6570\u8fdb\u884c\u8f6c\u6362\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u5c06BGR\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf\u3002<\/li>\n<\/ol>\n
                  gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)<\/p>\n
                  cv2.imshow('Gray Image', gray_image)<\/p>\n
                  cv2.waitKey(0)<\/p>\n
                  cv2.destroyAllWindows()<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                    \n
                  1. \u989c\u8272\u6ee4\u6ce2<\/strong>\uff1aOpenCV\u652f\u6301\u591a\u79cd\u989c\u8272\u6ee4\u6ce2\u6280\u672f\uff0c\u53ef\u4ee5\u7528\u6765\u63d0\u53d6\u7279\u5b9a\u989c\u8272\u8303\u56f4\u7684\u50cf\u7d20\u3002\u901a\u8fc7cv2.inRange()<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u5b9e\u73b0\u7b80\u5355\u7684\u989c\u8272\u8fc7\u6ee4\u3002<\/li>\n<\/ol>\n
                    lower_blue = np.array([100, 150, 0])<\/p>\n
                    upper_blue = np.array([140, 255, 255])<\/p>\n
                    hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)<\/p>\n
                    mask = cv2.inRange(hsv_image, lower_blue, upper_blue)<\/p>\n
                    result = cv2.bitwise_and(image, image, mask=mask)<\/p>\n
                    cv2.imshow('Blue Filtered Image', result)<\/p>\n
                    cv2.waitKey(0)<\/p>\n
                    cv2.destroyAllWindows()<\/p>\n
                    <\/code><\/pre>\n<\/p>\n
                    \u4e94\u3001TURTLE\u5e93\u7684\u7b80\u5355\u7ed8\u56fe<\/p>\n<\/p>\n
                    \u5bf9\u4e8e\u7b80\u5355\u7684\u56fe\u5f62\u7ed8\u5236\u548c\u989c\u8272\u586b\u5145\uff0cPython\u7684turtle\u5e93\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\u3002\u5b83\u9002\u7528\u4e8e\u6559\u5b66\u548c\u7b80\u5355\u56fe\u5f62\u7684\u5feb\u901f\u5b9e\u73b0\u3002<\/p>\n<\/p>\n
                      \n
                    1. \u57fa\u672c\u7ed8\u56fe\u548c\u989c\u8272\u8bbe\u7f6e<\/strong>\uff1a\u4f7f\u7528turtle\u5e93\u7ed8\u56fe\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7pencolor()<\/code>\u548cfillcolor()<\/code>\u51fd\u6570\u6765\u8bbe\u7f6e\u753b\u7b14\u548c\u586b\u5145\u989c\u8272\u3002<\/li>\n<\/ol>\n
                      import turtle<\/p>\n
                      t = turtle.Turtle()<\/p>\n
                      t.pencolor("blue")<\/p>\n
                      t.fillcolor("red")<\/p>\n
                      t.begin_fill()<\/p>\n
                      for _ in range(4):<\/p>\n
                          t.forward(100)<\/p>\n
                          t.right(90)<\/p>\n
                      t.end_fill()<\/p>\n
                      turtle.done()<\/p>\n
                      <\/code><\/pre>\n<\/p>\n
                        \n
                      1. \u989c\u8272\u6a21\u5f0f\u548c\u81ea\u5b9a\u4e49\u989c\u8272<\/strong>\uff1aturtle\u5e93\u652f\u6301\u591a\u79cd\u989c\u8272\u6a21\u5f0f\uff0c\u5305\u62ecRGB\u6a21\u5f0f\u3002\u53ef\u4ee5\u901a\u8fc7colormode()<\/code>\u51fd\u6570\u6765\u8bbe\u7f6e\u989c\u8272\u6a21\u5f0f\u3002<\/li>\n<\/ol>\n
                        turtle.colormode(255)<\/p>\n
                        t.pencolor(0, 128, 0)  # \u4f7f\u7528RGB\u6a21\u5f0f\u8bbe\u7f6e\u989c\u8272<\/p>\n
                        t.forward(100)<\/p>\n
                        turtle.done()<\/p>\n
                        <\/code><\/pre>\n<\/p>\n
                        \u516d\u3001\u603b\u7ed3<\/p>\n<\/p>\n
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