{"id":702,"date":"2026-01-29T13:57:44","date_gmt":"2026-01-29T05:57:44","guid":{"rendered":"https:\/\/www.starverse-ai.com\/guide\/?p=702"},"modified":"2026-01-29T14:02:05","modified_gmt":"2026-01-29T06:02:05","slug":"yolov5%e8%ae%ad%e7%bb%83%e6%a8%a1%e5%9e%8b%e7%9a%84%e6%ad%a5%e9%aa%a4","status":"publish","type":"post","link":"https:\/\/www.starverse-ai.com\/guide\/archives\/702","title":{"rendered":"yolov5\u8bad\u7ec3\u6a21\u578b\u7684\u6b65\u9aa4"},"content":{"rendered":"\n

\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\uff0cYOLO(You Only Look Once)\u7cfb\u5217\u4ee5\u9ad8\u6548\u7684\u5b9e\u65f6\u76ee\u6807\u68c0\u6d4b\u80fd\u529b\u95fb\u540d\uff0c\u800c YOLOv5 \u4f5c\u4e3a\u8be5\u7cfb\u5217\u4e2d\u6027\u80fd\u7a33\u5b9a\u3001\u6613\u4e8e\u90e8\u7f72\u7684\u7248\u672c\uff0c\u88ab\u5e7f\u6cdb\u5e94\u7528\u4e8e\u7269\u4f53\u68c0\u6d4b\u3001\u5b89\u9632\u76d1\u63a7\u3001\u5de5\u4e1a\u68c0\u6d4b\u3001\u65e0\u4eba\u9a7e\u9a76\u7b49\u573a\u666f\u3002 YOLOv5 \u6a21\u578b\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\uff0c\u4ece\u73af\u5883\u51c6\u5907\u3001\u6570\u636e\u96c6\u6784\u5efa\u3001\u6a21\u578b\u9009\u62e9\u3001\u8bad\u7ec3\u914d\u7f6e\u5230\u540e\u671f\u4f18\u5316\u548c\u90e8\u7f72\uff0c\u529b\u6c42\u5168\u9762\u800c\u5b9e\u7528\u3002<\/p>\n\n\n\n

\u4e00\u3001\u73af\u5883\u642d\u5efa\u4e0e\u4f9d\u8d56\u914d\u7f6e<\/p>\n\n\n\n

\u8bad\u7ec3 YOLOv5 \u6a21\u578b\u7684\u9996\u8981\u4efb\u52a1\u662f\u73af\u5883\u642d\u5efa\u3002YOLOv5 \u662f\u57fa\u4e8e PyTorch \u5f00\u53d1\u7684\uff0c\u56e0\u6b64 GPU \u73af\u5883\u5c24\u4e3a\u91cd\u8981\u3002\u6211\u7684\u8bad\u7ec3\u73af\u5883\u4e3a Ubuntu 22.04 \u7cfb\u7edf\uff0c\u914d\u5907 NVIDIA RTX 4090 \u663e\u5361\uff0cCUDA \u7248\u672c\u4e3a 12.1.\u663e\u5b58 24GB\u3002\u5bf9\u4e8e\u663e\u5b58\u6709\u9650\u7684\u7528\u6237\uff0c\u8bad\u7ec3\u5927\u6a21\u578b\u53ef\u4ee5\u8003\u8651\u964d\u4f4e batch size \u6216\u4f7f\u7528\u5c0f\u89c4\u6a21\u7f51\u7edc\u3002<\/p>\n\n\n\n

\u5728\u8f6f\u4ef6\u4f9d\u8d56\u65b9\u9762\uff0c\u6211\u4f7f\u7528 Python 3.10 \u5e76\u521b\u5efa\u4e86\u72ec\u7acb\u865a\u62df\u73af\u5883\u3002\u865a\u62df\u73af\u5883\u80fd\u591f\u9694\u79bb\u4f9d\u8d56\uff0c\u907f\u514d\u4e0e\u7cfb\u7edf\u4e2d\u5176\u4ed6\u9879\u76ee\u51b2\u7a81\u3002\u63a5\u7740\uff0c\u5b89\u88c5 PyTorch \u548c torchvision\uff0c\u5e76\u786e\u4fdd\u5176\u652f\u6301 CUDA GPU \u52a0\u901f\uff0c\u8fd9\u662f YOLOv5 \u80fd\u591f\u9ad8\u901f\u8bad\u7ec3\u548c\u63a8\u7406\u7684\u5173\u952e\u3002\u968f\u540e\uff0c\u6211\u5b89\u88c5\u4e86 YOLOv5 \u5b98\u65b9\u4ee3\u7801\u5e93\u7684\u4f9d\u8d56\uff0c\u5305\u62ec numpy\u3001pandas\u3001opencv-python\u3001matplotlib\u3001PyYAML \u7b49\uff0c\u8fd9\u4e9b\u5e93\u8d1f\u8d23\u6570\u636e\u52a0\u8f7d\u3001\u56fe\u50cf\u5904\u7406\u3001\u53ef\u89c6\u5316\u548c\u914d\u7f6e\u7ba1\u7406\u3002<\/p>\n\n\n\n

\u6b64\u5916\uff0c\u4e3a\u4fdd\u8bc1\u8bad\u7ec3\u6548\u7387\uff0c\u6211\u8fd8\u5b89\u88c5\u4e86\u90e8\u5206\u52a0\u901f\u5de5\u5177\uff0c\u5982 Apex \u6216 PyTorch \u5b98\u65b9\u7684 AMP(Automatic Mixed Precision)\u652f\u6301\u6df7\u5408\u7cbe\u5ea6\u8bad\u7ec3\uff0c\u8fd9\u80fd\u591f\u663e\u8457\u51cf\u5c11\u663e\u5b58\u5360\u7528\uff0c\u540c\u65f6\u63d0\u5347\u8bad\u7ec3\u901f\u5ea6\u3002<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

\u4e8c\u3001\u6570\u636e\u96c6\u51c6\u5907<\/p>\n\n\n\n

\u9ad8\u8d28\u91cf\u6570\u636e\u96c6\u662f YOLOv5 \u6a21\u578b\u8bad\u7ec3\u6210\u529f\u7684\u5173\u952e\u3002\u6570\u636e\u96c6\u51c6\u5907\u5305\u62ec\u56fe\u50cf\u6536\u96c6\u3001\u6807\u6ce8\u548c\u683c\u5f0f\u5316\u3002\u8bad\u7ec3\u76ee\u6807\u901a\u5e38\u6d89\u53ca\u5355\u7c7b\u6216\u591a\u7c7b\u7269\u4f53\u68c0\u6d4b\uff0c\u56e0\u6b64\u6807\u6ce8\u7cbe\u5ea6\u76f4\u63a5\u5f71\u54cd\u6a21\u578b\u6027\u80fd\u3002\u6211\u4f7f\u7528\u4e86\u5e38\u7528\u6807\u6ce8\u5de5\u5177\u5bf9\u56fe\u50cf\u8fdb\u884c\u77e9\u5f62\u6846\u6807\u6ce8\uff0c\u8bb0\u5f55\u6bcf\u4e2a\u76ee\u6807\u7684\u7c7b\u522b\u548c\u8fb9\u754c\u6846\u5750\u6807\u3002<\/p>\n\n\n\n

\u661f\u5b87\u667a\u7b97\u5b98\u7f51AI\u5e94\u7528\u4e00\u952e\u90e8\u7f72\u514d\u8d39\u8bd5\u7528\uff01<\/strong><\/p>\n\n\n

\n
\"GPU\u7b97\u529b\u670d\u52a1\u5668\u514d\u8d39\u8bd5\u7528\"<\/a><\/figure>\n<\/div>\n\n\n

YOLOv5 \u8981\u6c42\u7684\u6570\u636e\u683c\u5f0f\u4e3a\u6bcf\u5f20\u56fe\u50cf\u5bf9\u5e94\u4e00\u4e2a\u6587\u672c\u6587\u4ef6\uff0c\u6587\u672c\u6587\u4ef6\u4e2d\u6bcf\u884c\u5305\u542b\u76ee\u6807\u7c7b\u522b\u7f16\u53f7\u3001\u8fb9\u754c\u6846\u4e2d\u5fc3\u70b9\u5750\u6807\u548c\u5bbd\u9ad8\uff0c\u5e76\u5f52\u4e00\u5316\u5230 0~1 \u8303\u56f4\u5185\u3002\u8fd9\u79cd\u683c\u5f0f\u7b80\u6d01\u4e14\u65b9\u4fbf\u52a0\u8f7d\u3002\u5728\u6807\u6ce8\u5b8c\u6210\u540e\uff0c\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u5212\u5206\uff0c\u4e00\u822c\u5206\u4e3a\u8bad\u7ec3\u96c6\u3001\u9a8c\u8bc1\u96c6\u548c\u6d4b\u8bd5\u96c6\uff0c\u6bd4\u4f8b\u5927\u7ea6\u4e3a 8:1:1.\u8bad\u7ec3\u96c6\u7528\u4e8e\u6a21\u578b\u53c2\u6570\u66f4\u65b0\uff0c\u9a8c\u8bc1\u96c6\u7528\u4e8e\u8c03\u53c2\u548c\u9632\u6b62\u8fc7\u62df\u5408\uff0c\u6d4b\u8bd5\u96c6\u5219\u7528\u4e8e\u6700\u7ec8\u6027\u80fd\u8bc4\u4f30\u3002<\/p>\n\n\n\n

\u5728\u6570\u636e\u9884\u5904\u7406\u65b9\u9762\uff0c\u6211\u5bf9\u56fe\u50cf\u8fdb\u884c\u4e86\u5c3a\u5bf8\u7edf\u4e00\u548c\u589e\u5f3a\u3002\u56fe\u50cf\u7edf\u4e00\u5c3a\u5bf8\u6709\u52a9\u4e8e batch \u52a0\u8f7d\u548c\u6a21\u578b\u6536\u655b\uff0c\u800c\u589e\u5f3a\u64cd\u4f5c\u5219\u63d0\u9ad8\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002\u5e38\u7528\u589e\u5f3a\u5305\u62ec\u65cb\u8f6c\u3001\u7f29\u653e\u3001\u88c1\u526a\u3001\u8272\u5f69\u6296\u52a8\u3001\u6c34\u5e73\u7ffb\u8f6c\u7b49\u3002\u901a\u8fc7\u591a\u6837\u5316\u7684\u6570\u636e\u8f93\u5165\uff0c\u6a21\u578b\u80fd\u591f\u66f4\u597d\u5730\u9002\u5e94\u4e0d\u540c\u62cd\u6444\u89d2\u5ea6\u3001\u5149\u7167\u6761\u4ef6\u548c\u7269\u4f53\u5c3a\u5ea6\u3002<\/p>\n\n\n\n

\u4e09\u3001\u6a21\u578b\u9009\u62e9\u4e0e\u914d\u7f6e<\/p>\n\n\n\n

YOLOv5 \u63d0\u4f9b\u4e86\u4ece\u5c0f\u578b\u5230\u5927\u578b\u7684\u4e0d\u540c\u7f51\u7edc\u7ed3\u6784\uff0c\u5982 YOLOv5s\u3001YOLOv5m\u3001YOLOv5l \u548c YOLOv5x\u3002\u5c0f\u578b\u7f51\u7edc\u901f\u5ea6\u5feb\u3001\u663e\u5b58\u5360\u7528\u4f4e\uff0c\u9002\u5408\u5feb\u901f\u8fed\u4ee3\u6216\u8d44\u6e90\u6709\u9650\u7684\u73af\u5883;\u5927\u578b\u7f51\u7edc\u53c2\u6570\u591a\u3001\u7cbe\u5ea6\u9ad8\uff0c\u9002\u5408\u7cbe\u5ea6\u4f18\u5148\u7684\u4efb\u52a1\u3002\u6211\u7684\u8bad\u7ec3\u76ee\u6807\u662f\u4e2d\u7b49\u7cbe\u5ea6\u548c\u5b9e\u65f6\u6027\u5e73\u8861\uff0c\u56e0\u6b64\u9009\u62e9\u4e86 YOLOv5m \u6a21\u578b\u3002<\/p>\n\n\n\n

\u5728\u914d\u7f6e\u6a21\u578b\u65f6\uff0c\u9700\u8981\u7f16\u8f91 YAML \u914d\u7f6e\u6587\u4ef6\uff0c\u5305\u62ec\u7c7b\u522b\u6570\u91cf\u3001\u7c7b\u522b\u540d\u79f0\u3001\u6a21\u578b\u5c42\u7ed3\u6784\u4ee5\u53ca\u8d85\u53c2\u6570\u3002YOLOv5 \u7684\u8d85\u53c2\u6570\u5305\u62ec\u5b66\u4e60\u7387\u3001\u52a8\u91cf\u3001\u6743\u91cd\u8870\u51cf\u3001batch size\u3001epoch \u6570\u7b49\u3002\u8fd9\u4e9b\u8d85\u53c2\u6570\u76f4\u63a5\u5f71\u54cd\u6a21\u578b\u6536\u655b\u901f\u5ea6\u548c\u68c0\u6d4b\u7cbe\u5ea6\u3002\u6211\u7684\u7ecf\u9a8c\u662f\uff0c\u521d\u59cb\u8bad\u7ec3\u53ef\u4f7f\u7528\u9ed8\u8ba4\u8d85\u53c2\u6570\uff0c\u4f46\u5728\u6570\u636e\u91cf\u8f83\u5927\u6216\u7c7b\u522b\u4e0d\u5747\u8861\u65f6\uff0c\u9002\u5f53\u8c03\u6574\u5b66\u4e60\u7387\u548c batch size \u80fd\u83b7\u5f97\u66f4\u597d\u6548\u679c\u3002<\/p>\n\n\n\n

\u56db\u3001\u8bad\u7ec3\u6d41\u7a0b<\/p>\n\n\n\n

\u5b8c\u6210\u73af\u5883\u3001\u6570\u636e\u548c\u6a21\u578b\u914d\u7f6e\u540e\uff0c\u5c31\u53ef\u4ee5\u5f00\u59cb\u8bad\u7ec3 YOLOv5 \u6a21\u578b\u3002\u8bad\u7ec3\u6d41\u7a0b\u901a\u5e38\u5305\u62ec\u4ee5\u4e0b\u51e0\u4e2a\u6b65\u9aa4\uff1a<\/p>\n\n\n\n

\u6a21\u578b\u521d\u59cb\u5316<\/p>\n\n\n\n

\u52a0\u8f7d\u9884\u8bad\u7ec3\u6743\u91cd\u53ef\u4ee5\u663e\u8457\u52a0\u901f\u6536\u655b\u3002YOLOv5 \u63d0\u4f9b COCO \u6570\u636e\u96c6\u9884\u8bad\u7ec3\u6743\u91cd\uff0c\u6211\u5728\u8bad\u7ec3\u81ea\u5b9a\u4e49\u6570\u636e\u96c6\u65f6\u9009\u62e9\u57fa\u4e8e COCO \u6743\u91cd\u5fae\u8c03\uff0c\u4ece\u800c\u5229\u7528\u5176\u901a\u7528\u7279\u5f81\u63d0\u53d6\u80fd\u529b\u3002<\/p>\n\n\n\n

\u6570\u636e\u52a0\u8f7d<\/p>\n\n\n\n

YOLOv5 \u4f7f\u7528 Dataloader \u8bfb\u53d6\u56fe\u50cf\u548c\u6807\u7b7e\uff0c\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u5f20\u91cf\u5e76\u5f52\u4e00\u5316\uff0c\u540c\u65f6\u8fdb\u884c\u6570\u636e\u589e\u5f3a\u3002\u5728\u591a GPU \u73af\u5883\u4e0b\uff0cDataloader \u4f1a\u81ea\u52a8\u8fdb\u884c\u6279\u91cf\u5206\u914d\u3002<\/p>\n\n\n\n

\u524d\u5411\u4f20\u64ad\u4e0e\u635f\u5931\u8ba1\u7b97<\/p>\n\n\n\n

\u6bcf\u4e2a batch \u6570\u636e\u7ecf\u8fc7\u6a21\u578b\u524d\u5411\u4f20\u64ad\u751f\u6210\u9884\u6d4b\uff0c\u968f\u540e\u8ba1\u7b97\u635f\u5931\u3002YOLOv5 \u635f\u5931\u51fd\u6570\u7531\u76ee\u6807\u6846\u5b9a\u4f4d\u635f\u5931\u3001\u7c7b\u522b\u635f\u5931\u548c\u7f6e\u4fe1\u5ea6\u635f\u5931\u7ec4\u6210\u3002\u901a\u8fc7\u7efc\u5408\u635f\u5931\u53cd\u5411\u4f20\u64ad\uff0c\u66f4\u65b0\u6a21\u578b\u53c2\u6570\u3002<\/p>\n\n\n\n

\u68af\u5ea6\u4f18\u5316<\/p>\n\n\n\n

\u4f7f\u7528\u4f18\u5316\u5668(\u901a\u5e38\u4e3a Adam \u6216 SGD)\u6839\u636e\u68af\u5ea6\u8c03\u6574\u53c2\u6570\u3002\u6df7\u5408\u7cbe\u5ea6\u8bad\u7ec3\u548c\u68af\u5ea6\u7d2f\u79ef\u5728\u8fd9\u91cc\u80fd\u591f\u63d0\u9ad8\u8bad\u7ec3\u6548\u7387\u5e76\u964d\u4f4e\u663e\u5b58\u6d88\u8017\u3002<\/p>\n\n\n\n

\u9a8c\u8bc1\u4e0e\u76d1\u63a7<\/p>\n\n\n\n

\u6bcf\u8f6e\u8bad\u7ec3\u540e\uff0c\u4f7f\u7528\u9a8c\u8bc1\u96c6\u8bc4\u4f30\u6a21\u578b\u6027\u80fd\u3002YOLOv5 \u63d0\u4f9b mAP\u3001Precision\u3001Recall \u7b49\u6307\u6807\uff0c\u5e2e\u52a9\u5224\u65ad\u6a21\u578b\u662f\u5426\u8fc7\u62df\u5408\u6216\u6b20\u62df\u5408\u3002\u6211\u5728\u8bad\u7ec3\u4e2d\u4f7f\u7528 TensorBoard \u8bb0\u5f55\u635f\u5931\u66f2\u7ebf\u548c\u6307\u6807\u53d8\u5316\uff0c\u4ee5\u4fbf\u968f\u65f6\u8c03\u6574\u8d85\u53c2\u6570\u3002<\/p>\n\n\n\n

\u6a21\u578b\u4fdd\u5b58<\/p>\n\n\n\n

YOLOv5 \u4f1a\u5728\u6bcf\u8f6e\u6216\u6bcf\u9694\u56fa\u5b9a\u6b65\u4fdd\u5b58 checkpoint\uff0c\u786e\u4fdd\u8bad\u7ec3\u4e2d\u65ad\u65f6\u53ef\u4ee5\u7eed\u8bad\u3002\u6700\u7ec8\u8bad\u7ec3\u5b8c\u6210\u540e\uff0c\u9009\u62e9\u9a8c\u8bc1\u96c6\u8868\u73b0\u6700\u4f73\u7684\u6743\u91cd\u7528\u4e8e\u63a8\u7406\u548c\u90e8\u7f72\u3002<\/p>\n\n\n\n

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