{"id":974121,"date":"2024-12-27T06:02:36","date_gmt":"2024-12-26T22:02:36","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/974121.html"},"modified":"2024-12-27T06:02:38","modified_gmt":"2024-12-26T22:02:38","slug":"python%e5%92%8cyolo%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/974121.html","title":{"rendered":"python\u548cyolo\u5982\u4f55\u4f7f\u7528"},"content":{"rendered":"

\"python\u548cyolo\u5982\u4f55\u4f7f\u7528\"<\/p>\n

Python\u548cYOLO\u7684\u7ed3\u5408\u4f7f\u7528\u65b9\u6cd5\u4e3b\u8981\u5305\u62ec\uff1a\u5b89\u88c5\u5fc5\u8981\u7684\u5e93\u3001\u914d\u7f6eYOLO\u73af\u5883\u3001\u52a0\u8f7d\u9884\u8bad\u7ec3\u6a21\u578b\u3001\u5904\u7406\u8f93\u5165\u6570\u636e\u3001\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u3001\u53ef\u89c6\u5316\u68c0\u6d4b\u7ed3\u679c\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5Python\u73af\u5883\u548cYOLO\u76f8\u5173\u5e93\uff0c\u7136\u540e\u914d\u7f6eYOLO\u7684\u6a21\u578b\u6587\u4ef6\u548c\u6743\u91cd\u6587\u4ef6\u3002\u5176\u6b21\uff0c\u5229\u7528OpenCV\u6216PyTorch\u7b49\u5e93\u52a0\u8f7dYOLO\u6a21\u578b\uff0c\u5e76\u5bf9\u8f93\u5165\u6570\u636e\u8fdb\u884c\u9884\u5904\u7406\u3002\u63a5\u4e0b\u6765\uff0c\u4f7f\u7528YOLO\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\uff0c\u6700\u540e\u53ef\u89c6\u5316\u68c0\u6d4b\u7ed3\u679c\u4ee5\u9a8c\u8bc1\u6548\u679c\u3002<\/strong>\u5176\u4e2d\uff0c\u5b89\u88c5\u548c\u914d\u7f6e\u73af\u5883\u662f\u5173\u952e\u7684\u4e00\u6b65\uff0c\u56e0\u4e3a\u8fd9\u51b3\u5b9a\u4e86\u540e\u7eed\u6b65\u9aa4\u80fd\u5426\u987a\u5229\u8fdb\u884c\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8\u6bcf\u4e00\u4e2a\u6b65\u9aa4\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u5fc5\u8981\u7684\u5e93<\/h3>\n<\/p>\n

\u5728\u4f7f\u7528YOLO\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5Python\u73af\u5883\u53ca\u76f8\u5173\u7684\u5e93\u3002\u8fd9\u4e9b\u5e93\u5305\u62ecOpenCV\u3001NumPy\u3001\u4ee5\u53caYOLO\u7684\u5b9e\u73b0\u5e93\u5982darknet\u6216PyTorch\u3002\u901a\u8fc7\u8fd9\u4e9b\u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u8c03\u7528YOLO\u6a21\u578b\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u3002<\/p>\n<\/p>\n

    \n
  1. \n

    Python\u548c\u5e93\u7684\u5b89\u88c5<\/strong>\uff1a\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u7684\u8ba1\u7b97\u673a\u4e0a\u5df2\u7ecf\u5b89\u88c5\u4e86Python\u3002\u53ef\u4ee5\u901a\u8fc7Python\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u5e76\u5b89\u88c5\u6700\u65b0\u7248\u672c\u7684Python\u3002\u6b64\u5916\uff0c\u8fd8\u9700\u8981\u5b89\u88c5pip\u5de5\u5177\u4ee5\u4fbf\u4e8e\u5b89\u88c5\u5176\u4ed6\u5e93\u3002\u63a5\u7740\u4f7f\u7528pip\u547d\u4ee4\u5b89\u88c5OpenCV\u3001NumPy\u7b49\u5fc5\u8981\u7684\u5e93\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5OpenCV\uff1apip install opencv-python<\/code>\u3002<\/p>\n<\/p>\n<\/li>\n

  2. \n

    YOLO\u5b9e\u73b0\u5e93\u7684\u5b89\u88c5<\/strong>\uff1aYOLO\u6709\u591a\u79cd\u5b9e\u73b0\u65b9\u5f0f\uff0c\u5305\u62ecdarknet\u3001PyTorch\u3001Keras\u7b49\u3002\u9009\u62e9\u5408\u9002\u7684\u5e93\u8fdb\u884c\u5b89\u88c5\u3002\u4f8b\u5982\uff0c\u82e5\u4f7f\u7528PyTorch\u7248\u672c\u7684YOLO\uff0c\u53ef\u4ee5\u901a\u8fc7GitHub\u4e0a\u76f8\u5173\u9879\u76ee\u7684\u6307\u5bfc\u6587\u6863\u8fdb\u884c\u5b89\u88c5\u548c\u914d\u7f6e\u3002\u901a\u5e38\u9700\u8981\u514b\u9686\u9879\u76ee\u4ed3\u5e93\u5e76\u5b89\u88c5\u5176\u4f9d\u8d56\u9879\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

    \u4e8c\u3001\u914d\u7f6eYOLO\u73af\u5883<\/h3>\n<\/p>\n

    \u5728\u5b89\u88c5\u5b8c\u5fc5\u8981\u7684\u5e93\u540e\uff0c\u63a5\u4e0b\u6765\u9700\u8981\u914d\u7f6eYOLO\u6a21\u578b\u7684\u73af\u5883\u3002\u8fd9\u5305\u62ec\u4e0b\u8f7d\u6a21\u578b\u7684\u914d\u7f6e\u6587\u4ef6\u548c\u9884\u8bad\u7ec3\u7684\u6743\u91cd\u6587\u4ef6\u3002<\/p>\n<\/p>\n

      \n
    1. \n

      \u4e0b\u8f7d\u914d\u7f6e\u6587\u4ef6\u548c\u6743\u91cd\u6587\u4ef6<\/strong>\uff1aYOLO\u7684\u914d\u7f6e\u6587\u4ef6\u901a\u5e38\u4ee5.cfg\u4e3a\u540e\u7f00\uff0c\u6743\u91cd\u6587\u4ef6\u4ee5.weights\u4e3a\u540e\u7f00\u3002\u53ef\u4ee5\u4eceYOLO\u7684\u5b98\u65b9GitHub\u9875\u9762\u4e0b\u8f7d\u8fd9\u4e9b\u6587\u4ef6\u3002\u4f8b\u5982\uff0cYOLOv3\u7684\u914d\u7f6e\u6587\u4ef6\u662fyolov3.cfg<\/code>\uff0c\u6743\u91cd\u6587\u4ef6\u662fyolov3.weights<\/code>\u3002<\/p>\n<\/p>\n<\/li>\n

    2. \n

      \u914d\u7f6e\u6587\u4ef6\u8def\u5f84<\/strong>\uff1a\u5c06\u4e0b\u8f7d\u7684\u914d\u7f6e\u6587\u4ef6\u548c\u6743\u91cd\u6587\u4ef6\u653e\u7f6e\u5728\u9879\u76ee\u76ee\u5f55\u4e2d\uff0c\u5e76\u786e\u8ba4\u8def\u5f84\u6b63\u786e\u3002\u5728\u7a0b\u5e8f\u4e2d\u9700\u8981\u6307\u5b9a\u8fd9\u4e9b\u6587\u4ef6\u7684\u8def\u5f84\uff0c\u4ee5\u4fbf\u4e8e\u52a0\u8f7dYOLO\u6a21\u578b\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

      \u4e09\u3001\u52a0\u8f7d\u9884\u8bad\u7ec3\u6a21\u578b<\/h3>\n<\/p>\n

      \u5728\u5b8c\u6210\u914d\u7f6e\u540e\uff0c\u63a5\u4e0b\u6765\u5c31\u662f\u52a0\u8f7dYOLO\u7684\u9884\u8bad\u7ec3\u6a21\u578b\u3002\u8fd9\u4e00\u6b65\u901a\u5e38\u4f7f\u7528OpenCV\u6216PyTorch\u7b49\u5e93\u6765\u5b8c\u6210\u3002<\/p>\n<\/p>\n

        \n
      1. \n

        \u4f7f\u7528OpenCV\u52a0\u8f7dYOLO<\/strong>\uff1a\u5982\u679c\u4f7f\u7528OpenCV\uff0c\u53ef\u4ee5\u901a\u8fc7cv2.dnn.readNetFromDarknet<\/code>\u51fd\u6570\u6765\u52a0\u8f7dYOLO\u6a21\u578b\u3002\u9700\u8981\u63d0\u4f9b\u914d\u7f6e\u6587\u4ef6\u8def\u5f84\u548c\u6743\u91cd\u6587\u4ef6\u8def\u5f84\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n

        net = cv2.dnn.readNetFromDarknet('yolov3.cfg', 'yolov3.weights')<\/p>\n
        <\/code><\/pre>\n<\/p>\n<\/li>\n
      2. \n
        \u4f7f\u7528PyTorch\u52a0\u8f7dYOLO<\/strong>\uff1a\u5982\u679c\u4f7f\u7528PyTorch\u5b9e\u73b0\u7684YOLO\u6a21\u578b\uff0c\u53ef\u4ee5\u901a\u8fc7\u76f8\u5173\u5e93\u63d0\u4f9b\u7684\u63a5\u53e3\u52a0\u8f7d\u6a21\u578b\u3002\u4f8b\u5982\uff0c\u901a\u8fc7torch.load<\/code>\u51fd\u6570\u52a0\u8f7d\u6a21\u578b\u6743\u91cd\uff0c\u5e76\u4f7f\u7528\u6a21\u578b\u7c7b\u8fdb\u884c\u5b9e\u4f8b\u5316\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
        \u56db\u3001\u5904\u7406\u8f93\u5165\u6570\u636e<\/h3>\n<\/p>\n
        \u5728\u52a0\u8f7d\u6a21\u578b\u540e\uff0c\u63a5\u4e0b\u6765\u9700\u8981\u5bf9\u8f93\u5165\u6570\u636e\u8fdb\u884c\u5904\u7406\uff0c\u4ee5\u4fbf\u4e8eYOLO\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u3002\u901a\u5e38\uff0c\u6211\u4eec\u9700\u8981\u5bf9\u56fe\u50cf\u8fdb\u884c\u9884\u5904\u7406\uff0c\u5305\u62ec\u8c03\u6574\u5c3a\u5bf8\u3001\u5f52\u4e00\u5316\u7b49\u3002<\/p>\n<\/p>\n
          \n
        1. \n
          \u56fe\u50cf\u9884\u5904\u7406<\/strong>\uff1a\u5c06\u8f93\u5165\u56fe\u50cf\u8c03\u6574\u4e3aYOLO\u6a21\u578b\u6240\u9700\u7684\u5c3a\u5bf8\uff08\u4f8b\u5982416×416\uff09\uff0c\u5e76\u8fdb\u884c\u5f52\u4e00\u5316\u5904\u7406\u3002\u53ef\u4ee5\u4f7f\u7528OpenCV\u7684cv2.resize<\/code>\u51fd\u6570\u8c03\u6574\u5c3a\u5bf8\uff0c\u5e76\u5c06\u50cf\u7d20\u503c\u7f29\u653e\u52300\u52301\u4e4b\u95f4\u3002<\/p>\n<\/p>\n<\/li>\n
        2. \n
          \u751f\u6210\u8f93\u5165\u5f20\u91cf<\/strong>\uff1a\u5c06\u9884\u5904\u7406\u540e\u7684\u56fe\u50cf\u8f6c\u6362\u4e3a\u6a21\u578b\u6240\u9700\u7684\u8f93\u5165\u683c\u5f0f\u3002\u4f8b\u5982\uff0c\u5bf9\u4e8ePyTorch\u5b9e\u73b0\uff0c\u9700\u8981\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u5f20\u91cf\u683c\u5f0f\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
          \u4e94\u3001\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b<\/h3>\n<\/p>\n
          \u5728\u5b8c\u6210\u8f93\u5165\u6570\u636e\u7684\u5904\u7406\u540e\uff0c\u53ef\u4ee5\u8c03\u7528YOLO\u6a21\u578b\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u3002\u8fd9\u4e00\u6b65\u6d89\u53ca\u5230\u6a21\u578b\u7684\u524d\u5411\u4f20\u64ad\uff0c\u83b7\u53d6\u68c0\u6d4b\u7ed3\u679c\u3002<\/p>\n<\/p>\n
            \n
          1. \n
            \u6a21\u578b\u524d\u5411\u4f20\u64ad<\/strong>\uff1a\u5c06\u5904\u7406\u540e\u7684\u56fe\u50cf\u8f93\u5165\u5230YOLO\u6a21\u578b\u4e2d\uff0c\u901a\u8fc7\u524d\u5411\u4f20\u64ad\u83b7\u53d6\u68c0\u6d4b\u7ed3\u679c\u3002\u5bf9\u4e8eOpenCV\u5b9e\u73b0\uff0c\u53ef\u4ee5\u4f7f\u7528net.forward<\/code>\u51fd\u6570\u83b7\u53d6\u68c0\u6d4b\u7ed3\u679c\u3002<\/p>\n<\/p>\n<\/li>\n
          2. \n
            \u89e3\u6790\u68c0\u6d4b\u7ed3\u679c<\/strong>\uff1aYOLO\u6a21\u578b\u7684\u8f93\u51fa\u901a\u5e38\u5305\u62ec\u68c0\u6d4b\u6846\u7684\u4f4d\u7f6e\u3001\u7c7b\u522b\u548c\u7f6e\u4fe1\u5ea6\u3002\u9700\u8981\u5bf9\u8fd9\u4e9b\u7ed3\u679c\u8fdb\u884c\u89e3\u6790\uff0c\u7b5b\u9009\u51fa\u7f6e\u4fe1\u5ea6\u8f83\u9ad8\u7684\u68c0\u6d4b\u7ed3\u679c\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
            \u516d\u3001\u53ef\u89c6\u5316\u68c0\u6d4b\u7ed3\u679c<\/h3>\n<\/p>\n
            \u6700\u540e\uff0c\u5bf9\u68c0\u6d4b\u7ed3\u679c\u8fdb\u884c\u53ef\u89c6\u5316\u5c55\u793a\uff0c\u4ee5\u9a8c\u8bc1\u6a21\u578b\u7684\u68c0\u6d4b\u6548\u679c\u3002\u8fd9\u4e00\u6b65\u901a\u5e38\u4f7f\u7528OpenCV\u8fdb\u884c\u56fe\u50cf\u7ed8\u5236\u3002<\/p>\n<\/p>\n
              \n
            1. \n
              \u7ed8\u5236\u68c0\u6d4b\u6846<\/strong>\uff1a\u5728\u539f\u59cb\u56fe\u50cf\u4e0a\u7ed8\u5236\u68c0\u6d4b\u6846\uff0c\u6807\u8bb0\u51fa\u68c0\u6d4b\u5230\u7684\u76ee\u6807\u7269\u4f53\u3002\u53ef\u4ee5\u4f7f\u7528OpenCV\u7684cv2.rectangle<\/code>\u51fd\u6570\u7ed8\u5236\u77e9\u5f62\u6846\u3002<\/p>\n<\/p>\n<\/li>\n
            2. \n
              \u663e\u793a\u68c0\u6d4b\u7ed3\u679c<\/strong>\uff1a\u5c06\u7ed8\u5236\u597d\u68c0\u6d4b\u6846\u7684\u56fe\u50cf\u8fdb\u884c\u5c55\u793a\uff0c\u53ef\u4ee5\u4f7f\u7528OpenCV\u7684cv2.imshow<\/code>\u51fd\u6570\u663e\u793a\u56fe\u50cf\u3002\u786e\u4fdd\u5728\u663e\u793a\u540e\u8c03\u7528cv2.wAI<\/a>tKey<\/code>\u51fd\u6570\u4ee5\u4fdd\u6301\u7a97\u53e3\u6253\u5f00\u72b6\u6001\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
              \u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u73af\u5883\u4e2d\u6210\u529f\u4f7f\u7528YOLO\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u3002\u6bcf\u4e00\u4e2a\u6b65\u9aa4\u90fd\u81f3\u5173\u91cd\u8981\uff0c\u786e\u4fdd\u6bcf\u4e00\u6b65\u90fd\u6267\u884c\u6b63\u786e\uff0c\u624d\u80fd\u83b7\u5f97\u7406\u60f3\u7684\u68c0\u6d4b\u6548\u679c\u3002<\/p>\n<\/p>\n
              \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
               \u5982\u4f55\u5728Python\u4e2d\u5b89\u88c5YOLO\u5e76\u5f00\u59cb\u4f7f\u7528\uff1f<\/strong>
              \u8981\u5728Python\u4e2d\u4f7f\u7528YOLO\uff0c\u60a8\u9700\u8981\u5148\u5b89\u88c5\u76f8\u5173\u7684\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0c\u5982TensorFlow\u6216PyTorch\u3002\u63a5\u7740\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528YOLO\u7684\u5b9e\u73b0\u5e93\uff0c\u4f8b\u5982darknet<\/code>\u6216yolov5<\/code>\u3002\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u52a0\u8f7d\u9884\u8bad\u7ec3\u7684\u6a21\u578b\u6765\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u3002\u8be6\u7ec6\u6b65\u9aa4\u5305\u62ec\u4e0b\u8f7dYOLO\u6743\u91cd\u6587\u4ef6\u3001\u8bbe\u7f6e\u914d\u7f6e\u6587\u4ef6\uff0c\u5e76\u7528Python\u7f16\u5199\u4ee3\u7801\u6765\u52a0\u8f7d\u6a21\u578b\u5e76\u5904\u7406\u56fe\u50cf\u6216\u89c6\u9891\u3002<\/p>\n
              YOLO\u4e0e\u5176\u4ed6\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\u76f8\u6bd4\u6709\u4ec0\u4e48\u4f18\u52bf\uff1f<\/strong>
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