{"id":189528,"date":"2024-05-09T17:41:38","date_gmt":"2024-05-09T09:41:38","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/189528.html"},"modified":"2024-05-09T17:41:44","modified_gmt":"2024-05-09T09:41:44","slug":"%e6%b7%b1%e5%ba%a6%e5%ad%a6%e4%b9%a0%e5%9c%a8%e5%b7%a5%e4%b8%9a%e6%9c%ba%e5%99%a8%e8%a7%86%e8%a7%89%e6%a3%80%e6%b5%8b%e4%b8%8a%e6%9c%89%e6%b2%a1%e6%9c%89%e5%93%aa%e4%b8%aa%e8%bd%af%e4%bb%b6%e6%af%94","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/189528.html","title":{"rendered":"\u6df1\u5ea6\u5b66\u4e60\u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u4e0a\u6709\u6ca1\u6709\u54ea\u4e2a\u8f6f\u4ef6\u6bd4\u8f83\u597d\u7684"},"content":{"rendered":"

\"\u6df1\u5ea6\u5b66\u4e60\u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u4e0a\u6709\u6ca1\u6709\u54ea\u4e2a\u8f6f\u4ef6\u6bd4\u8f83\u597d\u7684\"<\/p>\n

\u6df1\u5ea6\u5b66\u4e60\u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u9886\u57df\u6b63\u5c55\u73b0\u51fa\u524d\u6240\u672a\u6709\u7684\u5b9e\u529b\uff0c\u8fd9\u5f97\u76ca\u4e8e\u5176\u5728\u5f71\u50cf\u5206\u6790\u3001\u6a21\u5f0f\u8bc6\u522b\u7b49\u65b9\u9762\u7684\u5353\u8d8a\u80fd\u529b\u3002\u5bf9\u4e8e\u5bfb\u627e\u6027\u80fd\u4f18\u5f02\u7684\u8f6f\u4ef6\u800c\u8a00\uff0cTensorFlow\u3001PyTorch\u3001OpenCV\u3001MATLAB<\/strong>\u7b49\u5747\u4ee5\u5176\u72ec\u7279\u4f18\u52bf\u8131\u9896\u800c\u51fa\u3002\u8fd9\u4e9b\u8f6f\u4ef6\u5728\u7b97\u6cd5\u5b9e\u73b0\u3001\u6a21\u578b\u8bad\u7ec3\u3001\u56fe\u50cf\u5904\u7406\u7b49\u65b9\u9762\u5404\u6709\u6240\u957f\uff0c\u662f\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u9886\u57df\u4e0d\u53ef\u6216\u7f3a\u7684\u5de5\u5177\u3002TensorFlow<\/strong>\uff0c\u4f5c\u4e3a\u4e00\u4e2a\u7531Google\u5f00\u53d1\u7684\u5f00\u6e90\u673a\u5668\u5b66\u4e60<\/a>\u6846\u67b6\uff0c\u56e0\u5176\u5f3a\u5927\u7684\u7075\u6d3b\u6027\u548c\u5e7f\u6cdb\u7684\u793e\u533a\u652f\u6301\uff0c\u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u5e94\u7528\u4e2d\u5c24\u4e3a\u7a81\u51fa\u3002<\/p>\n<\/p>\n

\u4e00\u3001TENSORFLOW\u5728\u5de5\u4e1a\u89c6\u89c9\u4e2d\u7684\u5e94\u7528<\/h3>\n<\/p>\n

TensorFlow\u5728\u5de5\u4e1a\u89c6\u89c9\u68c0\u6d4b\u4e2d\u7684\u5f3a\u9879\u5305\u62ec\u4f46\u4e0d\u9650\u4e8e\u5176\u5bf9\u590d\u6742\u6570\u636e\u64cd\u4f5c\u7684\u9ad8\u6548\u5904\u7406\u3001\u4ee5\u53ca\u53ef\u6269\u5c55\u7684\u67b6\u6784\u8bbe\u8ba1\uff0c\u4f7f\u5f97\u5de5\u7a0b\u5e08\u80fd\u591f\u8f7b\u677e\u90e8\u7f72\u5b66\u4e60\u6a21\u578b\u81f3\u5404\u79cd\u5e73\u53f0\uff0c\u5305\u542b\u79fb\u52a8\u8bbe\u5907\u548c\u5d4c\u5165\u5f0f\u8bbe\u5907\u3002\u5176\u81ea\u52a8\u5fae\u5206\u6280\u672f\u4e5f\u5927\u5927\u7b80\u5316\u4e86\u6a21\u578b\u7684\u8bbe\u8ba1\u548c\u6d4b\u8bd5\u8fc7\u7a0b\uff0c\u8ba9\u7814\u53d1\u4eba\u5458\u53ef\u4ee5\u66f4\u4e13\u6ce8\u4e8e\u7b97\u6cd5\u7684\u6539\u8fdb\u548c\u4f18\u5316\u3002<\/p>\n<\/p>\n

\u6b64\u5916\uff0cTensorFlow\u63d0\u4f9b\u7684TensorBoard\u53ef\u89c6\u5316\u5de5\u5177\uff0c\u8ba9\u8bad\u7ec3\u8fc7\u7a0b\u548c\u6a21\u578b\u7ed3\u6784\u7684\u7406\u89e3\u66f4\u4e3a\u76f4\u89c2\u3002\u8fd9\u5bf9\u4e8e\u8c03\u8bd5\u590d\u6742\u7684\u7f51\u7edc\u7ed3\u6784\u548c\u5927\u89c4\u6a21\u6570\u636e\u96c6\u800c\u8a00\uff0c\u662f\u975e\u5e38\u6709\u76ca\u7684\u8f85\u52a9\u5de5\u5177\u3002\u501f\u52a9\u4e8e\u8fd9\u79cd\u53ef\u89c6\u5316\uff0c\u5de5\u7a0b\u5e08\u53ef\u4ee5\u5feb\u901f\u8bc6\u522b\u5e76\u89e3\u51b3\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u7684\u95ee\u9898\uff0c\u6709\u6548\u5730\u63d0\u9ad8\u6a21\u578b\u7684\u51c6\u786e\u7387\u548c\u6027\u80fd\u3002<\/p>\n<\/p>\n

\u4e8c\u3001PYTORCH\u4e0eTensorFlow\u7684\u5bf9\u6bd4<\/h3>\n<\/p>\n

PyTorch\uff0c\u4e00\u6b3e\u540c\u6837\u6df1\u53d7\u5de5\u4e1a\u89c6\u89c9\u68c0\u6d4b\u5f00\u53d1\u8005\u9752\u7750\u7684\u5f00\u6e90\u673a\u5668\u5b66\u4e60\u5e93\uff0c\u5b83\u4ee5\u5176\u52a8\u6001\u8ba1\u7b97\u56fe\u548c\u4f18\u79c0\u7684GPU\u52a0\u901f\u652f\u6301\u95fb\u540d\u3002\u4e0eTensorFlow\u76f8\u6bd4\uff0cPyTorch\u63d0\u4f9b\u4e86\u66f4\u4e3a\u76f4\u89c2\u7684\u7f16\u7801\u4f53\u9a8c\uff0c\u7279\u522b\u662f\u5728\u8fdb\u884c\u539f\u578b\u8bbe\u8ba1\u548c\u5b9e\u9a8c\u6027\u9879\u76ee\u65f6\uff0c\u5176\u52a8\u6001\u56fe\u7684\u7279\u6027\u8ba9\u8c03\u8bd5\u548c\u8fed\u4ee3\u53d8\u5f97\u66f4\u52a0\u7b80\u4fbf\u3002<\/p>\n<\/p>\n

\u540c\u65f6\uff0cPyTorch\u4e5f\u5728\u793e\u533a\u652f\u6301\u548c\u5b66\u672f\u7814\u7a76\u4e0a\u5360\u636e\u4e00\u5e2d\u4e4b\u5730\u3002\u5f88\u591a\u6700\u65b0\u7684\u673a\u5668\u5b66\u4e60\u8bba\u6587\u548c\u9879\u76ee\u9009\u62e9\u4e86PyTorch\u4f5c\u4e3a\u5b9e\u73b0\u57fa\u7840\uff0c\u8fd9\u4e5f\u4e3a\u5de5\u4e1a\u754c\u5e26\u6765\u4e86\u6e90\u6e90\u4e0d\u65ad\u7684\u521b\u65b0\u601d\u8def\u548c\u89e3\u51b3\u65b9\u6848\u3002\u7136\u800c\uff0cTensorFlow\u51ed\u501f\u5176\u5728\u751f\u4ea7\u90e8\u7f72\u4e0a\u7684\u6210\u719f\u548c\u5e7f\u6cdb\u7684\u6a21\u578b\u751f\u6001\uff0c\u4f9d\u7136\u662f\u8bb8\u591a\u4f01\u4e1a\u9996\u9009\u7684\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u3002<\/p>\n<\/p>\n

\u4e09\u3001OPENCV\u5728\u56fe\u50cf\u5904\u7406\u7684\u91cd\u8981\u6027<\/h3>\n<\/p>\n

OpenCV\u662f\u4e00\u4e2a\u5305\u542b\u4e86\u4f17\u591a\u8ba1\u7b97\u673a\u89c6\u89c9\u7b97\u6cd5\u7684\u5f00\u6e90\u5e93\uff0c\u5b83\u5728\u56fe\u50cf\u5904\u7406\u3001\u89c6\u9891\u5206\u6790\u3001\u5bf9\u8c61\u548c\u9762\u90e8\u8bc6\u522b\u7b49\u9886\u57df\u6709\u7740\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u4e2d\uff0cOpenCV\u4e0d\u4ec5\u53ef\u4ee5\u7528\u4f5c\u56fe\u50cf\u9884\u5904\u7406\u548c\u7279\u5f81\u63d0\u53d6\u7684\u5de5\u5177\uff0c\u8fd8\u80fd\u4e0e\u6df1\u5ea6\u5b66\u4e60\u5e93\u5982TensorFlow\u548cPyTorch\u7ed3\u5408\u4f7f\u7528\uff0c\u5b9e\u73b0\u66f4\u590d\u6742\u7684\u56fe\u50cf\u8bc6\u522b\u548c\u5206\u7c7b\u4efb\u52a1\u3002<\/p>\n<\/p>\n

OpenCV\u4e2d\u7684\u7b97\u6cd5\u9ad8\u5ea6\u4f18\u5316\uff0c\u80fd\u591f\u5728\u4e0d\u540c\u7684\u8bbe\u5907\u548c\u5e73\u53f0\u4e0a\u9ad8\u6548\u8fd0\u884c\uff0c\u8fd9\u5bf9\u4e8e\u5b9e\u65f6\u673a\u5668\u89c6\u89c9\u7cfb\u7edf\u6765\u8bf4\u81f3\u5173\u91cd\u8981\u3002\u5176\u63d0\u4f9b\u7684\u529f\u80fd\u6db5\u76d6\u4e86\u4ece\u56fe\u50cf\u91c7\u96c6\u3001\u5904\u7406\u5230\u590d\u6742\u7684\u56fe\u50cf\u5206\u6790\u7b49\u51e0\u4e4e\u6240\u6709\u7684\u89c6\u89c9\u5904\u7406\u9636\u6bb5\uff0c\u4f7f\u5176\u6210\u4e3a\u5de5\u4e1a\u5e94\u7528\u4e2d\u4e0d\u53ef\u6216\u7f3a\u7684\u4e00\u5458\u3002<\/p>\n<\/p>\n

\u56db\u3001MATLAB\u5728\u673a\u5668\u89c6\u89c9\u4e2d\u7684\u5e94\u7528<\/h3>\n<\/p>\n

MATLAB\uff0c\u4e00\u4e2a\u5e7f\u6cdb\u4f7f\u7528\u4e8e\u7b97\u6cd5\u5f00\u53d1\u3001\u6570\u636e\u53ef\u89c6\u5316\u548c\u6570\u503c\u5206\u6790\u7684\u9ad8\u7ea7\u6280\u672f\u8ba1\u7b97\u8bed\u8a00\u548c\u4ea4\u4e92\u5f0f\u73af\u5883\u3002\u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u9886\u57df\u4e2d\uff0cMATLAB\u63d0\u4f9b\u4e86\u4e00\u4e2aImage Processing Toolbox\uff0c\u5176\u4e2d\u5305\u542b\u4e86\u4e30\u5bcc\u7684\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\u529f\u80fd\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u5f00\u53d1\u590d\u6742\u7684\u56fe\u50cf\u5904\u7406\u548c\u5bf9\u8c61\u8bc6\u522b\u7b97\u6cd5\u3002<\/p>\n<\/p>\n

\u5c3d\u7ba1MATLAB\u4e0d\u662f\u4e00\u4e2a\u4e13\u95e8\u7684\u673a\u5668\u5b66\u4e60\u6216\u6df1\u5ea6\u5b66\u4e60\u5de5\u5177\uff0c\u4f46\u5176\u5f3a\u5927\u7684\u77e9\u9635\u64cd\u4f5c\u80fd\u529b\u548c\u5185\u7f6e\u7684\u6570\u5b66\u51fd\u6570\u5e93\uff0c\u4f7f\u5f97\u5728\u6d89\u53ca\u6570\u503c\u5bc6\u96c6\u578b\u7684\u7b97\u6cd5\u5f00\u53d1\u65f6\u6781\u4e3a\u65b9\u4fbf\u3002\u6b64\u5916\uff0cMATLAB\u7684Simulink\u73af\u5883\u8fd8\u652f\u6301\u6a21\u578b\u548c\u7b97\u6cd5\u7684\u4eff\u771f\uff0c\u8fd9\u5bf9\u4e8e\u9a8c\u8bc1\u590d\u6742\u7684\u89c6\u89c9\u68c0\u6d4b\u7cfb\u7edf\u975e\u5e38\u6709\u5e2e\u52a9\u3002<\/p>\n<\/p>\n

\u7efc\u4e0a\u6240\u8ff0\uff0c\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u9886\u57df\u4e2d\u7684\u8f6f\u4ef6\u9009\u62e9\u5e94\u57fa\u4e8e\u9879\u76ee\u7684\u5177\u4f53\u9700\u6c42\u3002TensorFlow\u3001PyTorch\u3001OpenCV\u548cMATLAB\u90fd\u662f\u5404\u6709\u7279\u8272\u4e14\u529f\u80fd\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u5b83\u4eec\u53ef\u4ee5\u6839\u636e\u4e0d\u540c\u7684\u5e94\u7528\u573a\u666f\u548c\u5f00\u53d1\u9700\u6c42\u88ab\u7075\u6d3b\u5730\u8fd0\u7528\u4e8e\u5404\u7c7b\u673a\u5668\u89c6\u89c9\u9879\u76ee\u4e2d\u3002<\/p>\n<\/p>\n

\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n

1. \u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u4e0a\uff0c\u6709\u54ea\u4e9b\u6df1\u5ea6\u5b66\u4e60\u8f6f\u4ef6\u503c\u5f97\u63a8\u8350\uff1f<\/strong><\/p>\n

\u5bf9\u4e8e\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\uff0c\u6709\u8bb8\u591a\u6df1\u5ea6\u5b66\u4e60\u8f6f\u4ef6\u53ef\u4f9b\u9009\u62e9\u3002\u5176\u4e2d\u4e00\u6b3e\u503c\u5f97\u63a8\u8350\u7684\u8f6f\u4ef6\u662fTensorFlow\uff0c\u5b83\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0c\u5177\u6709\u5f3a\u5927\u7684\u529f\u80fd\u548c\u4e30\u5bcc\u7684\u8d44\u6e90\u652f\u6301\u3002TensorFlow\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684API\u548c\u5de5\u5177\uff0c\u4f7f\u5f97\u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u4e2d\u5b9e\u73b0\u5404\u79cd\u7b97\u6cd5\u548c\u6a21\u578b\u53d8\u5f97\u66f4\u52a0\u4fbf\u6377\u3002\u6b64\u5916\uff0c\u8fd8\u6709\u5176\u4ed6\u6d41\u884c\u7684\u6df1\u5ea6\u5b66\u4e60\u8f6f\u4ef6\u5982PyTorch\u3001Caffe\u7b49\uff0c\u5b83\u4eec\u4e5f\u90fd\u5177\u6709\u76f8\u5e94\u7684\u4f18\u70b9\u548c\u9002\u7528\u573a\u666f\uff0c\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u8fdb\u884c\u9009\u62e9\u3002<\/p>\n

2. \u6709\u4ec0\u4e48\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u8f6f\u4ef6\u53ef\u4ee5\u4e0e\u6df1\u5ea6\u5b66\u4e60\u7ed3\u5408\u4f7f\u7528\uff1f<\/strong><\/p>\n

\u5728\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u4e2d\uff0c\u7ed3\u5408\u6df1\u5ea6\u5b66\u4e60\u8f6f\u4ef6\u53ef\u4ee5\u53d6\u5f97\u66f4\u597d\u7684\u6548\u679c\u3002\u9664\u4e86\u4e0a\u8ff0\u63d0\u5230\u7684TensorFlow\u3001PyTorch\u3001Caffe\u7b49\u6df1\u5ea6\u5b66\u4e60\u8f6f\u4ef6\uff0c\u8fd8\u6709\u4e00\u4e9b\u4e13\u95e8\u7528\u4e8e\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u7684\u8f6f\u4ef6\u53ef\u4ee5\u4e0e\u6df1\u5ea6\u5b66\u4e60\u7ed3\u5408\u4f7f\u7528\u3002\u4f8b\u5982\uff0cCognex VisionPro\u8f6f\u4ef6\u5177\u6709\u5f3a\u5927\u7684\u56fe\u50cf\u5904\u7406\u548c\u5206\u6790\u80fd\u529b\uff0c\u53ef\u4ee5\u4e0e\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7ed3\u5408\uff0c\u5b9e\u73b0\u66f4\u51c6\u786e\u7684\u76ee\u6807\u68c0\u6d4b\u548c\u8bc6\u522b\u3002MVTec HALCON\u4e5f\u662f\u4e00\u6b3e\u5e38\u7528\u7684\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u8f6f\u4ef6\uff0c\u652f\u6301\u4e0e\u5404\u79cd\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u7684\u96c6\u6210\uff0c\u53ef\u4ee5\u6709\u6548\u63d0\u5347\u68c0\u6d4b\u6548\u679c\u3002<\/p>\n

3. \u5982\u4f55\u9009\u62e9\u9002\u5408\u5de5\u4e1a\u673a\u5668\u89c6\u89c9\u68c0\u6d4b\u7684\u6df1\u5ea6\u5b66\u4e60\u8f6f\u4ef6\uff1f<\/strong><\/p>\n

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