{"id":68783,"date":"2026-01-30T18:09:17","date_gmt":"2026-01-30T10:09:17","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/68783.html"},"modified":"2026-01-30T18:09:17","modified_gmt":"2026-01-30T10:09:17","slug":"opencv%e5%ae%9e%e6%97%b6%e6%91%84%e5%83%8f%e5%a4%b4%e5%a4%84%e7%90%86%ef%bc%9a%e6%9b%9d%e5%85%89%e8%b0%83%e8%8a%82%e3%80%81%e9%99%8d%e5%99%aa%e4%b8%8e%e4%ba%8c%e5%80%bc%e5%8c%96%e5%ae%9e%e6%88%98","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/68783.html","title":{"rendered":"OpenCV\u5b9e\u65f6\u6444\u50cf\u5934\u5904\u7406\uff1a\u66dd\u5149\u8c03\u8282\u3001\u964d\u566a\u4e0e\u4e8c\u503c\u5316\u5b9e\u6218"},"content":{"rendered":"

\u524d\u8a00<\/h2>\n

\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u5b66\u4e60\u8fc7\u7a0b\u4e2d，\u5b9e\u65f6\u6444\u50cf\u5934\u89c6\u9891\u6d41\u5904\u7406\u662f\u6700\u57fa\u7840\u4e5f\u6700\u6838\u5fc3\u7684\u5e94\u7528\u573a\u666f\u4e4b\u4e00\u3002\u672c\u6587\u57fa\u4e8eOpenCV-Python\u5b9e\u73b0\u4e86\u4e00\u4e2a\u5b8c\u6574\u7684\u6444\u50cf\u5934\u5b9e\u65f6\u5904\u7406demo，\u6db5\u76d6\u66dd\u5149\u53c2\u6570\u52a8\u6001\u8c03\u8282\u3001\u53cc\u8fb9\u6ee4\u6ce2\u964d\u566a\u3001\u7070\u5ea6\u8f6c\u6362\u4e0e\u4e8c\u503c\u5316\u7b49\u6838\u5fc3\u529f\u80fd，\u9002\u5408OpenCV\u5165\u95e8\u5b66\u4e60\u8005\u7406\u89e3\u89c6\u9891\u6d41\u5904\u7406\u7684\u57fa\u672c\u6d41\u7a0b\u548c\u5173\u952eAPI\u7528\u6cd5，\u4e5f\u662f\u535a\u4e3b\u51c6\u5907\u7535\u8d5b\u65f6\u8ba4\u4e3a\u975e\u5e38\u597d\u7528\u7684\u56fe\u50cf\u5904\u7406\u65b9\u6cd5\u3002<\/p>\n

\u76ee\u5f55<\/p>\n

\u524d\u8a00<\/p>\n

\u4e00\u3001\u529f\u80fd\u6574\u4f53\u8bf4\u660e<\/p>\n

\u4e8c\u3001\u73af\u5883\u51c6\u5907<\/p>\n

\u4e09\u3001\u4ee3\u7801\u9010\u884c\u89e3\u6790<\/p>\n

3.1 \u57fa\u7840\u521d\u59cb\u5316：\u6444\u50cf\u5934\u8c03\u7528\u4e0e\u7a97\u53e3\u521b\u5efa<\/p>\n

3.2 \u66dd\u5149\u53c2\u6570\u52a8\u6001\u8c03\u8282：\u6ed1\u52a8\u6761\u7ed1\u5b9a<\/p>\n

3.3 \u964d\u566a\u53c2\u6570\u52a8\u6001\u8c03\u8282：\u53cc\u8fb9\u6ee4\u6ce2\u6ed1\u52a8\u6761<\/p>\n

3.4 \u89c6\u9891\u6d41\u5faa\u73af\u5904\u7406：\u6838\u5fc3\u903b\u8f91<\/p>\n

3.5 \u8d44\u6e90\u91ca\u653e：\u5f02\u5e38\u5904\u7406\u4e0e\u6536\u5c3e<\/p>\n

\u56db\u3001\u8fd0\u884c\u6548\u679c\u4e0e\u5e38\u89c1\u95ee\u9898<\/p>\n

4.1 \u8fd0\u884c\u6548\u679c<\/p>\n

4.2 \u5e38\u89c1\u95ee\u9898\u89e3\u51b3<\/p>\n

\u4e94\u3001\u6269\u5c55\u4e0e\u4f18\u5316\u65b9\u5411<\/p>\n

\u516d\u3001\u603b\u7ed3<\/p>\n

\u9644：\u5b8c\u6574\u4ee3\u7801<\/p>\n

\u8865\u5145\u8bf4\u660e<\/p>\n

\n

\u8bba\u6587\u6295\u7a3f： \u7b2c\u4e8c\u5c4a\u8ba1\u7b97\u673a\u89c6\u89c9\u7814\u7a76\u8fdb\u5c55\u4e0e\u5e94\u7528\u56fd\u9645\u5b66\u672f\u4f1a\u8bae (ACVRA 2026) \u5927\u4f1a\u5b98\u7f51：https:\/\/ais.cn\/u\/2YrM7j \u5927\u4f1a\u65f6\u95f4：2026\u5e742\u67086-8\u65e5 \u5927\u4f1a\u5730\u70b9：\u4e2d\u56fd-\u6b66\u6c49<\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

\u4e00\u3001\u529f\u80fd\u6574\u4f53\u8bf4\u660e<\/h3>\n

\u672c\u4ee3\u7801\u5b9e\u73b0\u7684\u6838\u5fc3\u529f\u80fd：<\/p>\n

  • \n

    \u8c03\u7528\u7535\u8111\u672c\u5730\u6444\u50cf\u5934，\u5b9e\u65f6\u8bfb\u53d6\u89c6\u9891\u6d41\u5e76\u663e\u793a\u539f\u59cb\u753b\u9762；<\/p>\n<\/li>\n

  • \n

    \u901a\u8fc7\u6ed1\u52a8\u6761\u52a8\u6001\u8c03\u8282\u6444\u50cf\u5934\u66dd\u5149\u53c2\u6570，\u5b9e\u65f6\u9884\u89c8\u66dd\u5149\u8c03\u6574\u6548\u679c；<\/p>\n<\/li>\n

  • \n

    \u5bf9\u539f\u59cb\u753b\u9762\u8fdb\u884c\u53cc\u8fb9\u6ee4\u6ce2\u964d\u566a\u5904\u7406，\u5355\u72ec\u7a97\u53e3\u663e\u793a\u964d\u566a\u540e\u6548\u679c；<\/p>\n<\/li>\n

  • \n

    \u5c06\u964d\u566a\u540e\u7684\u56fe\u50cf\u8f6c\u4e3a\u7070\u5ea6\u56fe，\u5e76\u901a\u8fc7\u9608\u503c\u5904\u7406\u751f\u6210\u4e8c\u503c\u56fe\u50cf，\u5355\u72ec\u7a97\u53e3\u5c55\u793a；<\/p>\n<\/li>\n

  • \n

    \u652f\u6301\u6309\u952e\u9000\u51fa，\u81ea\u52a8\u91ca\u653e\u6444\u50cf\u5934\u8d44\u6e90\u5e76\u5173\u95ed\u6240\u6709\u7a97\u53e3\u3002<\/p>\n<\/li>\n

    \u4e8c\u3001\u73af\u5883\u51c6\u5907<\/h3>\n

    \u5728\u8fd0\u884c\u4ee3\u7801\u524d，\u9700\u786e\u4fdd\u73af\u5883\u5df2\u5b89\u88c5\u5bf9\u5e94\u4f9d\u8d56：<\/p>\n

    # \u5b89\u88c5OpenCV-Python
    \npip install opencv-python
    \n# \u9a8c\u8bc1\u5b89\u88c5（\u53ef\u9009）
    \npython -c "import cv2; print(cv2.__version__)" <\/p>\n

    \u6ce8\u610f：\u4e0d\u540c\u64cd\u4f5c\u7cfb\u7edf（Windows\/macOS\/Linux）\u7684\u6444\u50cf\u5934\u8c03\u7528\u903b\u8f91\u4e00\u81f4，\u4f46\u90e8\u5206\u8bbe\u5907\u53ef\u80fd\u9700\u8981\u8c03\u6574\u6444\u50cf\u5934ID（\u901a\u5e380\u4e3a\u5185\u7f6e\u6444\u50cf\u5934，1\u4e3a\u5916\u63a5\u6444\u50cf\u5934）\u3002<\/p>\n

    \u4e09\u3001\u4ee3\u7801\u9010\u884c\u89e3\u6790<\/h3>\n

    3.1 \u57fa\u7840\u521d\u59cb\u5316：\u6444\u50cf\u5934\u8c03\u7528\u4e0e\u7a97\u53e3\u521b\u5efa<\/h4>\n

    import cv2<\/p>\n

    def main():
    \n # \u6444\u50cf\u5934\u8bbe\u5907\u7f16\u53f7，\u901a\u5e380\u4e3a\u5185\u7f6e\u6444\u50cf\u5934，1\u4e3a\u5916\u63a5
    \n camera_id = 0
    \n # \u521b\u5efaVideoCapture\u5bf9\u8c61，\u7ed1\u5b9a\u6444\u50cf\u5934
    \n cap = cv2.VideoCapture(camera_id)<\/p>\n

    # \u68c0\u67e5\u6444\u50cf\u5934\u662f\u5426\u6210\u529f\u6253\u5f00
    \n if not cap.isOpened():
    \n print("Error: Could not open camera.")
    \n return<\/p>\n

    # \u521b\u5efa\u663e\u793a\u7a97\u53e3（WINDOW_NORMAL\u652f\u6301\u7a97\u53e3\u5927\u5c0f\u8c03\u6574）
    \n cv2.namedWindow('Camera Feed', cv2.WINDOW_NORMAL) # \u539f\u59cb\u753b\u9762\u7a97\u53e3
    \n cv2.namedWindow('Denoised', cv2.WINDOW_NORMAL) # \u964d\u566a\u540e\u7a97\u53e3
    \n cv2.namedWindow('Binary', cv2.WINDOW_NORMAL) # \u4e8c\u503c\u5316\u7a97\u53e3 <\/p>\n

      \n
    • \n

      cv2.VideoCapture(camera_id)：\u521b\u5efa\u89c6\u9891\u6355\u83b7\u5bf9\u8c61，\u53c2\u6570\u4e3a\u6444\u50cf\u5934\u8bbe\u5907ID，\u82e5\u8c03\u7528\u5931\u8d25\u9700\u68c0\u67e5\u6444\u50cf\u5934\u662f\u5426\u88ab\u5360\u7528\u6216ID\u662f\u5426\u6b63\u786e；<\/p>\n<\/li>\n

    • \n

      cap.isOpened()：\u6821\u9a8c\u6444\u50cf\u5934\u662f\u5426\u6210\u529f\u6253\u5f00，\u662f\u907f\u514d\u7a0b\u5e8f\u5d29\u6e83\u7684\u5173\u952e\u5224\u65ad；<\/p>\n<\/li>\n

    • \n

      cv2.namedWindow()：\u521b\u5efa\u663e\u793a\u7a97\u53e3，cv2.WINDOW_NORMAL\u53c2\u6570\u5141\u8bb8\u624b\u52a8\u8c03\u6574\u7a97\u53e3\u5927\u5c0f（\u9ed8\u8ba4WINDOW_AUTOSIZE\u4e3a\u56fa\u5b9a\u5927\u5c0f）\u3002<\/p>\n<\/li>\n<\/ul>\n

      3.2 \u66dd\u5149\u53c2\u6570\u52a8\u6001\u8c03\u8282：\u6ed1\u52a8\u6761\u7ed1\u5b9a<\/h4>\n

      # \u521d\u59cb\u66dd\u5149\u503c（\u4e0d\u540c\u6444\u50cf\u5934\u53d6\u503c\u8303\u56f4\u4e0d\u540c，\u9700\u81ea\u884c\u6d4b\u8bd5）
      \n initial_exposure_value = -6
      \n cap.set(cv2.CAP_PROP_EXPOSURE, initial_exposure_value)<\/p>\n

      # \u5b9a\u4e49\u66dd\u5149\u8c03\u6574\u56de\u8c03\u51fd\u6570
      \n def on_exposure_change(value):
      \n # \u6ed1\u52a8\u6761\u53d6\u503c\u8303\u56f4\u662f0-20，\u8f6c\u6362\u4e3a\u5b9e\u9645\u66dd\u5149\u503c（-10 ~ 10）
      \n cap.set(cv2.CAP_PROP_EXPOSURE, value – 10)<\/p>\n

      # \u521b\u5efa\u66dd\u5149\u8c03\u8282\u6ed1\u52a8\u6761：\u53c2\u6570（\u6ed1\u52a8\u6761\u540d，\u7ed1\u5b9a\u7a97\u53e3，\u521d\u59cb\u503c，\u6700\u5927\u503c，\u56de\u8c03\u51fd\u6570）
      \n cv2.createTrackbar('Exposure', 'Camera Feed', 10, 20, on_exposure_change)
      \n # \u8bbe\u7f6e\u6ed1\u52a8\u6761\u521d\u59cb\u4f4d\u7f6e（\u5bf9\u5e94\u521d\u59cb\u66dd\u5149\u503c）
      \n cv2.setTrackbarPos('Exposure', 'Camera Feed', initial_exposure_value + 10) <\/p>\n

      \u6838\u5fc3\u77e5\u8bc6\u70b9：<\/p>\n

        \n
      • \n

        cv2.CAP_PROP_EXPOSURE：\u6444\u50cf\u5934\u66dd\u5149\u5c5e\u6027\u5e38\u91cf，\u4e0d\u540c\u8bbe\u5907\u7684\u66dd\u5149\u503c\u8303\u56f4\u4e0d\u540c（\u901a\u5e38\u4e3a\u8d1f\u6570，\u503c\u8d8a\u5c0f\u66dd\u5149\u8d8a\u4f4e）；<\/p>\n<\/li>\n

      • \n

        cv2.createTrackbar()：\u521b\u5efa\u6ed1\u52a8\u6761，\u9700\u7ed1\u5b9a\u5230\u6307\u5b9a\u7a97\u53e3，\u6ed1\u52a8\u65f6\u89e6\u53d1\u56de\u8c03\u51fd\u6570；<\/p>\n<\/li>\n

      • \n

        \u56de\u8c03\u51fd\u6570on_exposure_change：\u6ed1\u52a8\u6761\u7684\u53d6\u503c\u4f1a\u4f5c\u4e3a\u53c2\u6570\u4f20\u5165，\u6b64\u5904\u901a\u8fc7value – 10\u5c06\u6ed1\u52a8\u6761\u76840-20\u8303\u56f4\u8f6c\u6362\u4e3a\u5b9e\u9645\u66dd\u5149\u503c\u7684-10~10\u8303\u56f4，\u9002\u914d\u6444\u50cf\u5934\u66dd\u5149\u53c2\u6570\u3002<\/p>\n<\/li>\n<\/ul>\n

        3.3 \u964d\u566a\u53c2\u6570\u52a8\u6001\u8c03\u8282：\u53cc\u8fb9\u6ee4\u6ce2\u6ed1\u52a8\u6761<\/h4>\n

        # \u5b9a\u4e49\u964d\u566a\u53c2\u6570\u56de\u8c03\u51fd\u6570
        \n def on_denoise_change(value):
        \n nonlocal denoise_value # \u58f0\u660e\u4f7f\u7528\u5916\u90e8\u7684denoise_value\u53d8\u91cf
        \n denoise_value = value<\/p>\n

        # \u521d\u59cb\u964d\u566a\u53c2\u6570
        \n denoise_value = 10
        \n # \u521b\u5efa\u964d\u566a\u8c03\u8282\u6ed1\u52a8\u6761
        \n cv2.createTrackbar('Denoise', 'Denoised', 10, 100, on_denoise_change)
        \n cv2.setTrackbarPos('Denoise', 'Denoised', denoise_value) <\/p>\n

          \n
        • \n

          nonlocal\u5173\u952e\u5b57：\u7528\u4e8e\u5728\u5d4c\u5957\u51fd\u6570\u4e2d\u4fee\u6539\u5916\u90e8\u51fd\u6570\u7684\u53d8\u91cf（\u82e5\u7528global\u5219\u662f\u4fee\u6539\u5168\u5c40\u53d8\u91cf）；<\/p>\n<\/li>\n

        • \n

          \u6ed1\u52a8\u6761\u6700\u5927\u503c\u8bbe\u4e3a100：\u53cc\u8fb9\u6ee4\u6ce2\u7684\u6838\u5927\u5c0f\u53c2\u6570\u4e0d\u5b9c\u8fc7\u5927，\u5426\u5219\u4f1a\u5bfc\u81f4\u753b\u9762\u6a21\u7cca\u8fc7\u5ea6\u4e14\u5904\u7406\u901f\u5ea6\u53d8\u6162\u3002<\/p>\n<\/li>\n<\/ul>\n

          3.4 \u89c6\u9891\u6d41\u5faa\u73af\u5904\u7406：\u6838\u5fc3\u903b\u8f91<\/h4>\n

          try:
          \n while True:
          \n # \u8bfb\u53d6\u4e00\u5e27\u56fe\u50cf：ret\u4e3a\u662f\u5426\u8bfb\u53d6\u6210\u529f，frame\u4e3a\u5e27\u6570\u636e（BGR\u683c\u5f0f）
          \n ret, frame = cap.read()
          \n if not ret:
          \n print("Failed to grab frame")
          \n break<\/p>\n

          # \u663e\u793a\u539f\u59cb\u753b\u9762
          \n cv2.imshow('Camera Feed', frame)<\/p>\n

          # \u53cc\u8fb9\u6ee4\u6ce2\u964d\u566a：\u53c2\u6570（\u56fe\u50cf，\u6838\u5927\u5c0f，\u989c\u8272\u7a7a\u95f4\u6807\u51c6\u5dee，\u50cf\u7d20\u7a7a\u95f4\u6807\u51c6\u5dee）
          \n denoised = cv2.bilateralFilter(frame, denoise_value, 75, 75)
          \n # \u663e\u793a\u964d\u566a\u540e\u753b\u9762
          \n cv2.imshow('Denoised', denoised)<\/p>\n

          # \u7070\u5ea6\u8f6c\u6362：BGR（OpenCV\u9ed8\u8ba4）\u8f6cGRAY
          \n gray = cv2.cvtColor(denoised, cv2.COLOR_BGR2GRAY)<\/p>\n

          # \u4e8c\u503c\u5316\u5904\u7406：\u53c2\u6570（\u7070\u5ea6\u56fe，\u9608\u503c，\u6700\u5927\u503c，\u4e8c\u503c\u5316\u65b9\u5f0f）
          \n _, binary = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
          \n # \u663e\u793a\u4e8c\u503c\u5316\u753b\u9762
          \n cv2.imshow('Binary', binary)<\/p>\n

          # \u6309\u952e\u68c0\u6d4b：\u6bcf1ms\u68c0\u6d4b\u4e00\u6b21，\u6309\u4e0bq\u952e\u9000\u51fa
          \n key = cv2.waitKey(1) & 0xFF
          \n if key == ord('q'):
          \n break <\/p>\n

          \u6838\u5fc3API\u89e3\u6790：<\/p>\n

        • \n

          cap.read()：\u9010\u5e27\u8bfb\u53d6\u89c6\u9891\u6d41，\u8fd4\u56de\u503cret\u4e3a\u5e03\u5c14\u578b（\u662f\u5426\u8bfb\u53d6\u6210\u529f），frame\u4e3a\u5f53\u524d\u5e27\u7684\u56fe\u50cf\u6570\u636e（OpenCV\u9ed8\u8ba4BGR\u989c\u8272\u7a7a\u95f4）；<\/p>\n<\/li>\n

        • \n

          cv2.bilateralFilter()：\u53cc\u8fb9\u6ee4\u6ce2，\u76f8\u6bd4\u5747\u503c\u6ee4\u6ce2\u3001\u9ad8\u65af\u6ee4\u6ce2，\u80fd\u5728\u964d\u566a\u7684\u540c\u65f6\u4fdd\u7559\u56fe\u50cf\u8fb9\u7f18\u7ec6\u8282，\u53c2\u6570\u8bf4\u660e：<\/p>\n

        • \n

          \u7b2c1\u4e2a\u53c2\u6570：\u8f93\u5165\u56fe\u50cf；<\/p>\n<\/li>\n

        • \n

          \u7b2c2\u4e2a\u53c2\u6570：\u6ee4\u6ce2\u6838\u5927\u5c0f（\u9700\u4e3a\u5947\u6570，\u503c\u8d8a\u5927\u964d\u566a\u6548\u679c\u8d8a\u5f3a，\u4f46\u5904\u7406\u901f\u5ea6\u8d8a\u6162）；<\/p>\n<\/li>\n

        • \n

          \u7b2c3\u4e2a\u53c2\u6570：\u989c\u8272\u7a7a\u95f4\u6807\u51c6\u5dee（\u503c\u8d8a\u5927，\u5141\u8bb8\u66f4\u591a\u989c\u8272\u5dee\u5f02\u7684\u50cf\u7d20\u53c2\u4e0e\u6ee4\u6ce2）；<\/p>\n<\/li>\n

        • \n

          \u7b2c4\u4e2a\u53c2\u6570：\u50cf\u7d20\u7a7a\u95f4\u6807\u51c6\u5dee（\u503c\u8d8a\u5927，\u6ee4\u6ce2\u8303\u56f4\u8d8a\u5927）；<\/p>\n<\/li>\n<\/li>\n

        • \n

          cv2.cvtColor()：\u989c\u8272\u7a7a\u95f4\u8f6c\u6362，COLOR_BGR2GRAY\u5c06BGR\u5f69\u8272\u56fe\u8f6c\u4e3a\u7070\u5ea6\u56fe；<\/p>\n<\/li>\n

        • \n

          cv2.threshold()：\u56fa\u5b9a\u9608\u503c\u4e8c\u503c\u5316，127\u4e3a\u9608\u503c，255\u4e3a\u6700\u5927\u503c，THRESH_BINARY\u8868\u793a：<\/p>\n

        • \n

          \u50cf\u7d20\u503c > 127 \u2192 255（\u767d\u8272）；<\/p>\n<\/li>\n

        • \n

          \u50cf\u7d20\u503c \u2264 127 \u2192 0（\u9ed1\u8272）；<\/p>\n<\/li>\n<\/li>\n

        • \n

          cv2.waitKey(1)：\u6309\u952e\u68c0\u6d4b，\u53c2\u6570\u4e3a\u7b49\u5f85\u65f6\u95f4（ms），\u8fd4\u56de\u6309\u952e\u7684ASCII\u7801，& 0xFF\u7528\u4e8e\u517c\u5bb9\u4e0d\u540c\u5e73\u53f0\u7684\u6309\u952e\u503c\u3002<\/p>\n<\/li>\n

          3.5 \u8d44\u6e90\u91ca\u653e：\u5f02\u5e38\u5904\u7406\u4e0e\u6536\u5c3e<\/h4>\n

          finally:
          \n # \u91ca\u653e\u6444\u50cf\u5934\u8d44\u6e90
          \n cap.release()
          \n # \u5173\u95ed\u6240\u6709\u521b\u5efa\u7684\u7a97\u53e3
          \n cv2.destroyAllWindows()<\/p>\n

          if __name__ == "__main__":
          \n main() <\/p>\n

            \n
          • \n

            finally\u4ee3\u7801\u5757：\u65e0\u8bba\u5faa\u73af\u6b63\u5e38\u9000\u51fa\u8fd8\u662f\u5f02\u5e38\u4e2d\u65ad，\u90fd\u4f1a\u6267\u884c\u8d44\u6e90\u91ca\u653e，\u907f\u514d\u6444\u50cf\u5934\u88ab\u5360\u7528；<\/p>\n<\/li>\n

          • \n

            cap.release()：\u91ca\u653eVideoCapture\u5bf9\u8c61，\u5fc5\u987b\u8c03\u7528，\u5426\u5219\u540e\u7eed\u65e0\u6cd5\u518d\u6b21\u8c03\u7528\u6444\u50cf\u5934；<\/p>\n<\/li>\n

          • \n

            cv2.destroyAllWindows()：\u5173\u95ed\u6240\u6709OpenCV\u521b\u5efa\u7684\u7a97\u53e3，\u6e05\u7406\u5185\u5b58\u3002<\/p>\n<\/li>\n<\/ul>\n

            \u56db\u3001\u8fd0\u884c\u6548\u679c\u4e0e\u5e38\u89c1\u95ee\u9898<\/h3>\n

            4.1 \u8fd0\u884c\u6548\u679c<\/h4>\n

            \u542f\u52a8\u7a0b\u5e8f\u540e，\u4f1a\u5f39\u51fa3\u4e2a\u7a97\u53e3：<\/p>\n

              \n
            • \n

              Camera Feed：\u539f\u59cb\u6444\u50cf\u5934\u753b\u9762，\u5e26\u6709\u66dd\u5149\u8c03\u8282\u6ed1\u52a8\u6761；<\/p>\n<\/li>\n

            • \n

              Denoised：\u964d\u566a\u540e\u7684\u753b\u9762，\u5e26\u6709\u964d\u566a\u53c2\u6570\u6ed1\u52a8\u6761；<\/p>\n<\/li>\n

            • \n

              Binary：\u4e8c\u503c\u5316\u540e\u7684\u9ed1\u767d\u753b\u9762\u3002<\/p>\n<\/li>\n<\/ul>\n

              \u62d6\u52a8\u6ed1\u52a8\u6761\u53ef\u5b9e\u65f6\u8c03\u6574\u66dd\u5149\u548c\u964d\u566a\u6548\u679c，\u6309\u4e0bq\u952e\u9000\u51fa\u7a0b\u5e8f\u3002<\/p>\n

              \"\"\"\"\"\"<\/p>\n

              4.2 \u5e38\u89c1\u95ee\u9898\u89e3\u51b3<\/h4>\n
            • \n

              \u6444\u50cf\u5934\u65e0\u6cd5\u6253\u5f00：<\/p>\n

            • \n

              \u68c0\u67e5\u6444\u50cf\u5934\u662f\u5426\u88ab\u5176\u4ed6\u7a0b\u5e8f\u5360\u7528（\u5982\u5fae\u4fe1\u3001Zoom）；<\/p>\n<\/li>\n

            • \n

              \u8c03\u6574camera_id\u4e3a1\u62162，\u5c1d\u8bd5\u5916\u63a5\u6444\u50cf\u5934；<\/p>\n<\/li>\n

            • \n

              Linux\/macOS\u9700\u8d4b\u4e88\u6444\u50cf\u5934\u6743\u9650：sudo chmod 777 \/dev\/video0\u3002<\/p>\n<\/li>\n<\/li>\n

            • \n

              \u66dd\u5149\u8c03\u8282\u65e0\u6548\u679c：<\/p>\n

            • \n

              \u90e8\u5206\u7b14\u8bb0\u672c\u6444\u50cf\u5934\u4e0d\u652f\u6301\u624b\u52a8\u8c03\u8282\u66dd\u5149，\u9700\u66f4\u6362\u6444\u50cf\u5934；<\/p>\n<\/li>\n

            • \n

              \u8c03\u6574\u6ed1\u52a8\u6761\u7684\u53d6\u503c\u8303\u56f4（\u5982\u5c0620\u6539\u4e3a30），\u9002\u914d\u4e0d\u540c\u6444\u50cf\u5934\u7684\u66dd\u5149\u53c2\u6570\u8303\u56f4\u3002<\/p>\n<\/li>\n<\/li>\n

            • \n

              \u753b\u9762\u5361\u987f：<\/p>\n

            • \n

              \u964d\u4f4e\u53cc\u8fb9\u6ee4\u6ce2\u7684\u6838\u5927\u5c0f（\u51cf\u5c0fdenoise_value\u7684\u6700\u5927\u503c）；<\/p>\n<\/li>\n

            • \n

              \u5173\u95ed\u5176\u4ed6\u5360\u7528CPU\/GPU\u7684\u7a0b\u5e8f，\u51cf\u5c11\u8d44\u6e90\u6d88\u8017\u3002<\/p>\n<\/li>\n<\/li>\n

              \u4e94\u3001\u6269\u5c55\u4e0e\u4f18\u5316\u65b9\u5411<\/h3>\n
            • \n

              \u81ea\u9002\u5e94\u9608\u503c\u4e8c\u503c\u5316：\u66ff\u6362\u56fa\u5b9a\u9608\u503c\u4e3acv2.adaptiveThreshold()，\u9002\u914d\u4e0d\u540c\u5149\u7167\u73af\u5883；<\/p>\n<\/li>\n

            • \n

              \u5e27\u7387\u663e\u793a：\u6dfb\u52a0\u5e27\u7387\u8ba1\u7b97\u903b\u8f91，\u5728\u753b\u9762\u4e0a\u663e\u793a\u5b9e\u65f6FPS；<\/p>\n<\/li>\n

            • \n

              \u56fe\u50cf\u4fdd\u5b58：\u6dfb\u52a0\u6309\u952e\u89e6\u53d1\u529f\u80fd，\u4fdd\u5b58\u5f53\u524d\u5e27\u7684\u539f\u59cb\/\u964d\u566a\/\u4e8c\u503c\u5316\u56fe\u50cf；<\/p>\n<\/li>\n

            • \n

              \u8272\u5f69\u7a7a\u95f4\u5207\u6362：\u589e\u52a0HSV\u3001YCrCb\u7b49\u8272\u5f69\u7a7a\u95f4\u7684\u8f6c\u6362\u548c\u663e\u793a；<\/p>\n<\/li>\n

            • \n

              \u5b9e\u65f6\u8fb9\u7f18\u68c0\u6d4b：\u5728\u4e8c\u503c\u5316\u57fa\u7840\u4e0a\u6dfb\u52a0Canny\u8fb9\u7f18\u68c0\u6d4b，\u589e\u5f3a\u7279\u5f81\u63d0\u53d6\u80fd\u529b\u3002<\/p>\n<\/li>\n

              \u516d\u3001\u603b\u7ed3<\/h3>\n

              \u672c\u6587\u901a\u8fc7\u4e00\u4e2a\u5b8c\u6574\u7684OpenCV\u6444\u50cf\u5934\u5904\u7406demo，\u8bb2\u89e3\u4e86\u89c6\u9891\u6d41\u8bfb\u53d6\u3001\u53c2\u6570\u52a8\u6001\u8c03\u8282\u3001\u56fe\u50cf\u6ee4\u6ce2\u3001\u989c\u8272\u7a7a\u95f4\u8f6c\u6362\u548c\u4e8c\u503c\u5316\u7b49\u6838\u5fc3\u77e5\u8bc6\u70b9\u3002\u5173\u952e\u8981\u70b9：<\/p>\n

            • \n

              OpenCV\u5904\u7406\u6444\u50cf\u5934\u89c6\u9891\u6d41\u7684\u6838\u5fc3\u6d41\u7a0b\u662f\u300c\u6253\u5f00\u6444\u50cf\u5934\u2192\u9010\u5e27\u8bfb\u53d6\u2192\u5904\u7406\u2192\u663e\u793a\u2192\u91ca\u653e\u8d44\u6e90\u300d；<\/p>\n<\/li>\n

            • \n

              \u6ed1\u52a8\u6761\u7ed3\u5408\u56de\u8c03\u51fd\u6570\u53ef\u5b9e\u73b0\u53c2\u6570\u52a8\u6001\u8c03\u8282，\u63d0\u5347\u4ea4\u4e92\u6027；<\/p>\n<\/li>\n

            • \n

              \u53cc\u8fb9\u6ee4\u6ce2\u662f\u517c\u987e\u964d\u566a\u548c\u8fb9\u7f18\u4fdd\u7559\u7684\u4f18\u8d28\u6ee4\u6ce2\u7b97\u6cd5，\u9002\u5408\u5b9e\u65f6\u89c6\u9891\u5904\u7406；<\/p>\n<\/li>\n

            • \n

              \u4e8c\u503c\u5316\u662f\u56fe\u50cf\u5206\u5272\u548c\u7279\u5f81\u63d0\u53d6\u7684\u57fa\u7840，\u9700\u6839\u636e\u573a\u666f\u9009\u62e9\u56fa\u5b9a\u9608\u503c\u6216\u81ea\u9002\u5e94\u9608\u503c\u3002<\/p>\n<\/li>\n

              \u901a\u8fc7\u672c\u6848\u4f8b\u7684\u5b66\u4e60，\u53ef\u638c\u63e1OpenCV\u5b9e\u65f6\u89c6\u9891\u5904\u7406\u7684\u57fa\u672c\u6846\u67b6，\u4e3a\u540e\u7eed\u7684\u4eba\u8138\u68c0\u6d4b\u3001\u7269\u4f53\u8ddf\u8e2a\u7b49\u9ad8\u7ea7\u5e94\u7528\u6253\u4e0b\u57fa\u7840\u3002<\/p>\n

              \u9644：\u5b8c\u6574\u4ee3\u7801<\/h3>\n

              import cv2<\/p>\n

              def main():
              \n # \u6444\u50cf\u5934\u8bbe\u5907\u7f16\u53f7，\u901a\u5e38\u662f0\u62161
              \n camera_id = 0
              \n # \u521b\u5efaVideoCapture\u5bf9\u8c61
              \n cap = cv2.VideoCapture(camera_id)<\/p>\n

              # \u68c0\u67e5\u662f\u5426\u6210\u529f\u6253\u5f00\u6444\u50cf\u5934
              \n if not cap.isOpened():
              \n print("Error: Could not open camera.")
              \n return<\/p>\n

              # \u521b\u5efa\u4e00\u4e2a\u7a97\u53e3\u6765\u663e\u793a\u89c6\u9891\u6d41
              \n cv2.namedWindow('Camera Feed', cv2.WINDOW_NORMAL)
              \n cv2.namedWindow('Denoised', cv2.WINDOW_NORMAL)
              \n cv2.namedWindow('Binary', cv2.WINDOW_NORMAL)<\/p>\n

              # \u521d\u59cb\u66dd\u5149\u503c
              \n initial_exposure_value = -6
              \n cap.set(cv2.CAP_PROP_EXPOSURE, initial_exposure_value)<\/p>\n

              # \u521b\u5efa\u4e00\u4e2a\u6ed1\u52a8\u6761
              \n def on_exposure_change(value):
              \n # \u66f4\u65b0\u66dd\u5149\u503c
              \n cap.set(cv2.CAP_PROP_EXPOSURE, value – 10)<\/p>\n

              # \u521b\u5efa\u6ed1\u52a8\u6761，\u521d\u59cb\u4f4d\u7f6e\u8bbe\u4e3a\u4e2d\u95f4\u503c
              \n cv2.createTrackbar('Exposure', 'Camera Feed', 10, 20, on_exposure_change)
              \n cv2.setTrackbarPos('Exposure', 'Camera Feed', initial_exposure_value + 10)<\/p>\n

              # \u521b\u5efa\u4e00\u4e2a\u6ed1\u52a8\u6761\u6765\u8c03\u6574\u53cc\u8fb9\u6ee4\u6ce2\u7684\u53c2\u6570
              \n def on_denoise_change(value):
              \n nonlocal denoise_value
              \n denoise_value = value<\/p>\n

              denoise_value = 10
              \n cv2.createTrackbar('Denoise', 'Denoised', 10, 100, on_denoise_change)
              \n cv2.setTrackbarPos('Denoise', 'Denoised', denoise_value)<\/p>\n

              try:
              \n while True:
              \n # \u8bfb\u53d6\u4e00\u5e27\u56fe\u50cf
              \n ret, frame = cap.read()
              \n if not ret:
              \n print("Failed to grab frame")
              \n break<\/p>\n

              # \u663e\u793a\u539f\u59cb\u56fe\u50cf
              \n cv2.imshow('Camera Feed', frame)<\/p>\n

              # \u5e94\u7528\u53cc\u8fb9\u6ee4\u6ce2\u8fdb\u884c\u964d\u566a（\u6838\u5927\u5c0f\u9700\u4e3a\u5947\u6570，\u907f\u514d\u62a5\u9519）
              \n denoise_ksize = denoise_value if denoise_value % 2 == 1 else denoise_value + 1
              \n denoise_ksize = max(1, denoise_ksize) # \u786e\u4fdd\u6838\u5927\u5c0f\u81f3\u5c11\u4e3a1
              \n denoised = cv2.bilateralFilter(frame, denoise_ksize, 75, 75)<\/p>\n

              # \u663e\u793a\u964d\u566a\u540e\u7684\u56fe\u50cf
              \n cv2.imshow('Denoised', denoised)<\/p>\n

              # \u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf
              \n gray = cv2.cvtColor(denoised, cv2.COLOR_BGR2GRAY)<\/p>\n

              # \u5e94\u7528\u9608\u503c\u5904\u7406，\u5f97\u5230\u4e8c\u503c\u56fe\u50cf
              \n _, binary = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)<\/p>\n

              # \u663e\u793a\u4e8c\u503c\u56fe\u50cf
              \n cv2.imshow('Binary', binary)<\/p>\n

              # \u83b7\u53d6\u6309\u952e\u8f93\u5165
              \n key = cv2.waitKey(1) & 0xFF<\/p>\n

              # \u6309\u4e0b 'q' \u952e\u9000\u51fa\u5faa\u73af
              \n if key == ord('q'):
              \n break<\/p>\n

              finally:
              \n # \u5728\u6700\u540e\u91ca\u653e\u8d44\u6e90\u548c\u5173\u95ed\u7a97\u53e3
              \n cap.release()
              \n cv2.destroyAllWindows()<\/p>\n

              if __name__ == "__main__":
              \n main() <\/p>\n

              \u8865\u5145\u8bf4\u660e<\/h4>\n

              \u4f18\u5316\u540e\u7684\u4ee3\u7801\u4fee\u590d\u4e86\u53cc\u8fb9\u6ee4\u6ce2\u6838\u5927\u5c0f\u4e3a\u5076\u6570\u65f6\u7684\u62a5\u9519\u95ee\u9898，\u589e\u52a0\u4e86\u53c2\u6570\u5408\u6cd5\u6027\u6821\u9a8c，\u63d0\u5347\u4e86\u7a0b\u5e8f\u7684\u5065\u58ee\u6027\u3002\u5728CSDN\u53d1\u5e03\u65f6，\u53ef\u642d\u914d\u8fd0\u884c\u6548\u679c\u622a\u56fe（\u59823\u4e2a\u7a97\u53e3\u7684\u5b9e\u9645\u663e\u793a\u6548\u679c），\u5e76\u5728\u8bc4\u8bba\u533a\u4e0e\u8bfb\u8005\u4e92\u52a8\u89e3\u7b54\u95ee\u9898\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

              \u524d\u8a00
              \n\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u5b66\u4e60\u8fc7\u7a0b\u4e2d，\u5b9e\u65f6\u6444\u50cf\u5934\u89c6\u9891\u6d41\u5904\u7406\u662f\u6700\u57fa\u7840\u4e5f\u6700\u6838\u5fc3\u7684\u5e94\u7528\u573a\u666f\u4e4b\u4e00\u3002\u672c\u6587\u57fa\u4e8eOpenCV-Python\u5b9e\u73b0\u4e86\u4e00\u4e2a\u5b8c\u6574\u7684\u6444\u50cf\u5934\u5b9e\u65f6\u5904\u7406demo，\u6db5\u76d6\u66dd\u5149\u53c2\u6570\u52a8\u6001\u8c03\u8282\u3001\u53cc\u8fb9\u6ee4\u6ce2\u964d\u566a\u3001\u7070\u5ea6\u8f6c\u6362\u4e0e\u4e8c\u503c\u5316\u7b49\u6838\u5fc3\u529f\u80fd，\u9002\u5408OpenCV\u5165\u95e8\u5b66\u4e60\u8005\u7406\u89e3\u89c6\u9891\u6d41\u5904\u7406\u7684\u57fa\u672c\u6d41\u7a0b\u548c\u5173\u952eAPI\u7528\u6cd5，\u4e5f\u662f\u535a\u4e3b\u51c6\u5907\u7535\u8d5b\u65f6\u8ba4\u4e3a\u975e\u5e38\u597d\u7528\u7684\u56fe\u50cf\u5904\u7406\u65b9\u6cd5\u3002
              \n\u76ee\u5f55
              \n\u524d\u8a00
              \n\u4e00\u3001\u529f\u80fd\u6574\u4f53\u8bf4\u660e
              \n\u4e8c\u3001\u73af\u5883\u51c6\u5907
              \n\u4e09\u3001\u4ee3\u7801\u9010\u884c\u89e3\u6790
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