{"id":4781,"date":"2022-07-20T22:51:32","date_gmt":"2022-07-20T14:51:32","guid":{"rendered":"http:\/\/139.9.1.231\/?p=4781"},"modified":"2022-09-17T20:59:39","modified_gmt":"2022-09-17T12:59:39","slug":"yolov6","status":"publish","type":"post","link":"http:\/\/139.9.1.231\/index.php\/2022\/07\/20\/yolov6\/","title":{"rendered":"yolov6  \u53c8\u5feb\u53c8\u51c6\u7684\u76ee\u6807\u68c0\u6d4b\u6846\u67b6"},"content":{"rendered":"\n<p>\u591a\u5e74\u6765\uff0c<code>YOLO<\/code>&nbsp;\u7cfb\u5217\u4e00\u76f4\u662f\u9ad8\u6548\u76ee\u6807\u68c0\u6d4b\u7684\u884c\u4e1a\u6807\u51c6\u3002<code>YOLO<\/code>&nbsp;\u793e\u533a\u84ec\u52c3\u53d1\u5c55\uff0c\u4e30\u5bcc\u4e86\u5176\u5728\u4f17\u591a\u786c\u4ef6\u5e73\u53f0\u548c\u4e30\u5bcc\u573a\u666f\u4e2d\u7684\u4f7f\u7528\u3002\u5728\u8fd9\u4efd\u6280\u672f\u62a5\u544a\u529b\u6c42\u5c06\u5176\u6781\u9650\u63a8\u5411\u65b0\u7684\u9ad8\u5ea6\uff0c\u4ee5\u575a\u5b9a\u4e0d\u79fb\u7684\u884c\u4e1a\u5e94\u7528\u5fc3\u6001\u5411\u524d\u8fc8\u8fdb\u3002<\/p>\n\n\n\n<p>\u8003\u8651\u5230\u771f\u5b9e\u73af\u5883\u4e2d\u5bf9\u901f\u5ea6\u548c\u51c6\u786e\u6027\u7684\u4e0d\u540c\u8981\u6c42\uff0c\u4f5c\u8005\u5e7f\u6cdb\u7814\u7a76\u4e86\u6765\u81ea\u5de5\u4e1a\u754c\u6216\u5b66\u672f\u754c\u7684\u6700\u65b0\u76ee\u6807\u68c0\u6d4b\u8fdb\u5c55\u3002\u5177\u4f53\u6765\u8bf4\uff0c\u4ece\u6700\u8fd1\u7684\u7f51\u7edc\u8bbe\u8ba1\u3001\u8bad\u7ec3\u7b56\u7565\u3001\u6d4b\u8bd5\u6280\u672f\u3001\u91cf\u5316\u548c\u4f18\u5316\u65b9\u6cd5\u4e2d\u5927\u91cf\u5438\u6536\u4e86\u4e00\u4e9b\u60f3\u6cd5\u3002\u6700\u91cd\u8981\u7684\u662f\uff0c\u6574\u5408\u601d\u60f3\u548c\u5b9e\u8df5\uff0c\u6784\u5efa\u4e86\u4e00\u5957\u4e0d\u540c\u89c4\u6a21\u7684\u90e8\u7f72\u7f51\u7edc\uff0c\u4ee5\u9002\u5e94\u591a\u6837\u5316\u7684\u7528\u4f8b\u3002<\/p>\n\n\n\n<p>\u5728&nbsp;<code>YOLO<\/code>&nbsp;\u4f5c\u8005\u7684\u6177\u6168\u8bb8\u53ef\u4e0b\uff0c\u4f5c\u8005\u5c06\u5176\u547d\u540d\u4e3a&nbsp;<code>YOLOv6<\/code>\u3002\u4f5c\u8005\u4e5f\u70ed\u70c8\u6b22\u8fce\u7528\u6237\u548c\u8d21\u732e\u8005\u8fdb\u4e00\u6b65\u589e\u5f3a\u3002<code>YOLOv6-N<\/code>&nbsp;\u5728&nbsp;<code>NVIDIA Tesla T4 GPU<\/code>&nbsp;\u4e0a\u4ee5 1234 FPS \u7684\u541e\u5410\u91cf\u5728&nbsp;<code>COCO<\/code>&nbsp;\u6570\u636e\u96c6\u4e0a\u8fbe\u5230 35.9% \u7684 AP\u3002<code>YOLOv6-S<\/code>&nbsp;\u4ee5 495 FPS \u7684\u901f\u5ea6\u8fbe\u5230 43.5% \u7684 AP\uff0c\u4f18\u4e8e\u540c\u89c4\u6a21\u7684\u5176\u4ed6\u4e3b\u6d41\u68c0\u6d4b\u5668\uff08<code>YOLOv5-S<\/code>\u3001<code>YOLOX-S<\/code>&nbsp;\u548c&nbsp;<code>PPYOLOE-S<\/code>\uff09\u3002<\/p>\n\n\n\n<p><code>YOLOv6-S<\/code>&nbsp;\u91cf\u5316\u7248\u672c\u751a\u81f3\u5e26\u6765\u4e86 869 FPS \u7684\u6700\u65b0 43.3% AP\u3002\u6b64\u5916\uff0c\u4e0e\u5177\u6709\u76f8\u4f3c\u63a8\u7406\u901f\u5ea6\u7684\u5176\u4ed6\u68c0\u6d4b\u5668\u76f8\u6bd4\uff0c<code>YOLOv6-M\/L<\/code>&nbsp;\u8fd8\u5b9e\u73b0\u4e86\u66f4\u597d\u7684\u51c6\u786e\u5ea6\u6027\u80fd\uff08\u5373 49.5%\/52.3%\uff09\u3002<\/p>\n\n\n\n<p>         \u8fd1\u65e5\uff0c\u7f8e\u56e2\u89c6\u89c9\u667a\u80fd\u90e8\u7814\u53d1\u4e86\u4e00\u6b3e\u81f4\u529b\u4e8e\u5de5\u4e1a\u5e94\u7528\u7684\u76ee\u6807\u68c0\u6d4b\u6846\u67b6 YOLOv6\uff0c\u80fd\u591f\u540c\u65f6\u4e13\u6ce8\u4e8e\u68c0\u6d4b\u7684\u7cbe\u5ea6\u548c\u63a8\u7406\u6548\u7387\u3002\u5728\u7814\u53d1\u8fc7\u7a0b\u4e2d\uff0c\u89c6\u89c9\u667a\u80fd\u90e8\u4e0d\u65ad\u8fdb\u884c\u4e86\u63a2\u7d22\u548c\u4f18\u5316\uff0c\u540c\u65f6\u5438\u53d6\u501f\u9274\u4e86\u5b66\u672f\u754c\u548c\u5de5\u4e1a\u754c\u7684\u4e00\u4e9b\u524d\u6cbf\u8fdb\u5c55\u548c\u79d1\u7814\u6210\u679c\u3002\u5728\u76ee\u6807\u68c0\u6d4b\u6743\u5a01\u6570\u636e\u96c6 COCO \u4e0a\u7684\u5b9e\u9a8c\u7ed3\u679c\u663e\u793a\uff0cYOLOv6 \u5728\u68c0\u6d4b\u7cbe\u5ea6\u548c\u901f\u5ea6\u65b9\u9762\u5747\u8d85\u8d8a\u5176\u4ed6\u540c\u4f53\u91cf\u7684\u7b97\u6cd5\uff0c\u540c\u65f6\u652f\u6301\u591a\u79cd\u4e0d\u540c\u5e73\u53f0\u7684\u90e8\u7f72\uff0c\u6781\u5927\u7b80\u5316\u5de5\u7a0b\u90e8\u7f72\u65f6\u7684\u9002\u914d\u5de5\u4f5c\u3002\u7279\u6b64\u5f00\u6e90\uff0c\u5e0c\u671b\u80fd\u5e2e\u52a9\u5230\u66f4\u591a\u7684\u540c\u5b66\u3002<\/p>\n\n\n\n<p>YOLOv6 \u662f\u7f8e\u56e2\u89c6\u89c9\u667a\u80fd\u90e8\u7814\u53d1\u7684\u4e00\u6b3e\u76ee\u6807\u68c0\u6d4b\u6846\u67b6\uff0c\u81f4\u529b\u4e8e\u5de5\u4e1a\u5e94\u7528\u3002\u672c\u6846\u67b6\u540c\u65f6\u4e13\u6ce8\u4e8e\u68c0\u6d4b\u7684\u7cbe\u5ea6\u548c\u63a8\u7406\u6548\u7387\uff0c\u5728\u5de5\u4e1a\u754c\u5e38\u7528\u7684\u5c3a\u5bf8\u6a21\u578b\u4e2d\uff1aYOLOv6-nano \u5728 COCO \u4e0a\u7cbe\u5ea6\u53ef\u8fbe 35.0% AP\uff0c\u5728 T4 \u4e0a\u63a8\u7406\u901f\u5ea6\u53ef\u8fbe 1242 FPS\uff1bYOLOv6-s \u5728 COCO \u4e0a\u7cbe\u5ea6\u53ef\u8fbe 43.1% AP\uff0c\u5728 T4 \u4e0a\u63a8\u7406\u901f\u5ea6\u53ef\u8fbe 520 FPS\u3002\u5728\u90e8\u7f72\u65b9\u9762\uff0cYOLOv6 \u652f\u6301 GPU\uff08TensorRT\uff09\u3001CPU\uff08OPENVINO\uff09\u3001ARM\uff08MNN\u3001TNN\u3001NCNN\uff09\u7b49\u4e0d\u540c\u5e73\u53f0\u7684\u90e8\u7f72\uff0c\u6781\u5927\u5730\u7b80\u5316\u5de5\u7a0b\u90e8\u7f72\u65f6\u7684\u9002\u914d\u5de5\u4f5c\u3002<\/p>\n\n\n\n<p>\u76ee\u524d\uff0c\u9879\u76ee\u5df2\u5f00\u6e90\u81f3Github\uff0c\u4f20\u9001\u95e8\uff1a<a href=\"https:\/\/github.com\/meituan\/YOLOv6\">YOLOv6<\/a>\u3002\u6b22\u8fce\u6709\u9700\u8981\u7684\u5c0f\u4f19\u4f34\u4eecStar\u6536\u85cf\uff0c\u968f\u65f6\u53d6\u7528\u3002<\/p>\n\n\n\n<h3 id=\"\u7cbe\u5ea6\u4e0e\u901f\u5ea6\u8fdc\u8d85-yolov5-\u548c-yolox-\u7684\u65b0\u6846\u67b6\">\u7cbe\u5ea6\u4e0e\u901f\u5ea6\u8fdc\u8d85 YOLOv5 \u548c YOLOX \u7684\u65b0\u6846\u67b6<\/h3>\n\n\n\n<p>\u76ee\u6807\u68c0\u6d4b\u4f5c\u4e3a\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\u7684\u4e00\u9879\u57fa\u7840\u6027\u6280\u672f\uff0c\u5728\u5de5\u4e1a\u754c\u5f97\u5230\u4e86\u5e7f\u6cdb\u7684\u5e94\u7528\uff0c\u5176\u4e2d YOLO \u7cfb\u5217\u7b97\u6cd5\u56e0\u5176\u8f83\u597d\u7684\u7efc\u5408\u6027\u80fd\uff0c\u9010\u6e10\u6210\u4e3a\u5927\u591a\u6570\u5de5\u4e1a\u5e94\u7528\u65f6\u7684\u9996\u9009\u6846\u67b6\u3002\u81f3\u4eca\uff0c\u4e1a\u754c\u5df2\u884d\u751f\u51fa\u8bb8\u591a YOLO \u68c0\u6d4b\u6846\u67b6\uff0c\u5176\u4e2d\u4ee5 YOLOv5<sup>[1]<\/sup>\u3001YOLOX<sup>[2]<\/sup>&nbsp;\u548c PP-YOLOE<sup>[3]<\/sup>&nbsp;\u6700\u5177\u4ee3\u8868\u6027\uff0c\u4f46\u5728\u5b9e\u9645\u4f7f\u7528\u4e2d\uff0c\u6211\u4eec\u53d1\u73b0\u4e0a\u8ff0\u6846\u67b6\u5728\u901f\u5ea6\u548c\u7cbe\u5ea6\u65b9\u9762\u4ecd\u6709\u5f88\u5927\u7684\u63d0\u5347\u7684\u7a7a\u95f4\u3002\u57fa\u4e8e\u6b64\uff0c\u6211\u4eec\u901a\u8fc7\u7814\u7a76\u5e76\u501f\u9274\u4e86\u4e1a\u754c\u5df2\u6709\u7684\u5148\u8fdb\u6280\u672f\uff0c\u5f00\u53d1\u4e86\u4e00\u5957\u65b0\u7684\u76ee\u6807\u68c0\u6d4b\u6846\u67b6\u2014\u2014YOLOv6\u3002\u8be5\u6846\u67b6\u652f\u6301\u6a21\u578b\u8bad\u7ec3\u3001\u63a8\u7406\u53ca\u591a\u5e73\u53f0\u90e8\u7f72\u7b49\u5168\u94fe\u6761\u7684\u5de5\u4e1a\u5e94\u7528\u9700\u6c42\uff0c\u5e76\u5728\u7f51\u7edc\u7ed3\u6784\u3001\u8bad\u7ec3\u7b56\u7565\u7b49\u7b97\u6cd5\u5c42\u9762\u8fdb\u884c\u4e86\u591a\u9879\u6539\u8fdb\u548c\u4f18\u5316\uff0c\u5728 COCO \u6570\u636e\u96c6\u4e0a\uff0cYOLOv6 \u5728\u7cbe\u5ea6\u548c\u901f\u5ea6\u65b9\u9762\u5747\u8d85\u8d8a\u5176\u4ed6\u540c\u4f53\u91cf\u7b97\u6cd5\uff0c\u76f8\u5173\u7ed3\u679c\u5982\u4e0b\u56fe 1 \u6240\u793a\uff1a<\/p>\n\n\n\n<figure class=\"wp-block-image is-resized\"><img loading=\"lazy\" src=\"https:\/\/p0.meituan.net\/travelcube\/6e04535a78a8e341615ceab2dd474b18144058.png\" alt=\"\u56fe1-1 YOLOv6 \u5404\u5c3a\u5bf8\u6a21\u578b\u4e0e\u5176\u4ed6\u6a21\u578b\u6027\u80fd\u5bf9\u6bd4\" width=\"690\" height=\"498\"\/><figcaption>\u56fe1-1 YOLOv6 \u5404\u5c3a\u5bf8\u6a21\u578b\u4e0e\u5176\u4ed6\u6a21\u578b\u6027\u80fd\u5bf9\u6bd4<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p0.meituan.net\/travelcube\/ae8d801a76f96eee5ddfd40d13901b0d141917.png\" alt=\"\u56fe1-2 YOLOv6 \u4e0e\u5176\u4ed6\u6a21\u578b\u5728\u4e0d\u540c\u5206\u8fa8\u7387\u4e0b\u6027\u80fd\u5bf9\u6bd4\"\/><figcaption>\u56fe1-2 YOLOv6 \u4e0e\u5176\u4ed6\u6a21\u578b\u5728\u4e0d\u540c\u5206\u8fa8\u7387\u4e0b\u6027\u80fd\u5bf9\u6bd4<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"1024\" height=\"390\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/09\/image-180-1024x390.png\" alt=\"\" class=\"wp-image-7876\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/09\/image-180-1024x390.png 1024w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/09\/image-180-300x114.png 300w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/09\/image-180-768x292.png 768w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/09\/image-180.png 1090w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>\u56fe 1-1 \u5c55\u793a\u4e86\u4e0d\u540c\u5c3a\u5bf8\u7f51\u7edc\u4e0b\u5404\u68c0\u6d4b\u7b97\u6cd5\u7684\u6027\u80fd\u5bf9\u6bd4\uff0c\u66f2\u7ebf\u4e0a\u7684\u70b9\u5206\u522b\u8868\u793a\u8be5\u68c0\u6d4b\u7b97\u6cd5\u5728\u4e0d\u540c\u5c3a\u5bf8\u7f51\u7edc\u4e0b\uff08s\/tiny\/nano\uff09\u7684\u6a21\u578b\u6027\u80fd\uff0c\u4ece\u56fe\u4e2d\u53ef\u4ee5\u770b\u5230\uff0cYOLOv6 \u5728\u7cbe\u5ea6\u548c\u901f\u5ea6\u65b9\u9762\u5747\u8d85\u8d8a\u5176\u4ed6 YOLO \u7cfb\u5217\u540c\u4f53\u91cf\u7b97\u6cd5\u3002<\/p>\n\n\n\n<p>\u56fe 1-2 \u5c55\u793a\u4e86\u8f93\u5165\u5206\u8fa8\u7387\u53d8\u5316\u65f6\u5404\u68c0\u6d4b\u7f51\u7edc\u6a21\u578b\u7684\u6027\u80fd\u5bf9\u6bd4\uff0c\u66f2\u7ebf\u4e0a\u7684\u70b9\u4ece\u5de6\u5f80\u53f3\u5206\u522b\u8868\u793a\u56fe\u50cf\u5206\u8fa8\u7387\u4f9d\u6b21\u589e\u5927\u65f6\uff08384\/448\/512\/576\/640\uff09\u8be5\u6a21\u578b\u7684\u6027\u80fd\uff0c\u4ece\u56fe\u4e2d\u53ef\u4ee5\u770b\u5230\uff0cYOLOv6 \u5728\u4e0d\u540c\u5206\u8fa8\u7387\u4e0b\uff0c\u4ecd\u7136\u4fdd\u6301\u8f83\u5927\u7684\u6027\u80fd\u4f18\u52bf\u3002<\/p>\n\n\n\n<h2 id=\"2-yolov6\u5173\u952e\u6280\u672f\u4ecb\u7ecd\">2. YOLOv6\u5173\u952e\u6280\u672f\u4ecb\u7ecd<\/h2>\n\n\n\n<p>YOLOv6 \u4e3b\u8981\u5728 BackBone\u3001Neck\u3001Head \u4ee5\u53ca\u8bad\u7ec3\u7b56\u7565\u7b49\u65b9\u9762\u8fdb\u884c\u4e86\u8bf8\u591a\u7684\u6539\u8fdb\uff1a<\/p>\n\n\n\n<ul><li>\u8bbe\u8ba1\u4e86\u66f4\u9ad8\u6548\u7684 Backbone \u548c Neck \uff1a\u53d7\u5230\u786c\u4ef6\u611f\u77e5\u795e\u7ecf\u7f51\u7edc\u8bbe\u8ba1\u601d\u60f3\u7684\u542f\u53d1\uff0c\u57fa\u4e8e RepVGG style<sup>[4]<\/sup>\u00a0\u8bbe\u8ba1\u4e86\u53ef\u91cd\u53c2\u6570\u5316\u3001\u66f4\u9ad8\u6548\u7684\u9aa8\u5e72\u7f51\u7edc EfficientRep Backbone \u548c Rep-PAN Neck\u3002<\/li><li>\u4f18\u5316\u8bbe\u8ba1\u4e86\u66f4\u7b80\u6d01\u6709\u6548\u7684 Efficient Decoupled Head\uff0c\u5728\u7ef4\u6301\u7cbe\u5ea6\u7684\u540c\u65f6\uff0c\u8fdb\u4e00\u6b65\u964d\u4f4e\u4e86\u4e00\u822c\u89e3\u8026\u5934\u5e26\u6765\u7684\u989d\u5916\u5ef6\u65f6\u5f00\u9500\u3002<\/li><li>\u5728\u8bad\u7ec3\u7b56\u7565\u4e0a\uff0c\u6211\u4eec\u91c7\u7528Anchor-free \u65e0\u951a\u8303\u5f0f\uff0c\u540c\u65f6\u8f85\u4ee5 SimOTA<sup>[2]<\/sup>\u00a0\u6807\u7b7e\u5206\u914d\u7b56\u7565\u4ee5\u53ca SIoU<sup>[9]<\/sup>\u00a0\u8fb9\u754c\u6846\u56de\u5f52\u635f\u5931\u6765\u8fdb\u4e00\u6b65\u63d0\u9ad8\u68c0\u6d4b\u7cbe\u5ea6\u3002<\/li><\/ul>\n\n\n\n<p>\u5c06&nbsp;<code>YOLOv6<\/code>&nbsp;\u7684\u4e3b\u8981\u65b9\u9762\u603b\u7ed3\u5982\u4e0b\uff1a<\/p>\n\n\n\n<ul><li>\u9488\u5bf9\u4e0d\u540c\u573a\u666f\u4e2d\u7684\u5de5\u4e1a\u5e94\u7528\u91cd\u65b0\u8bbe\u8ba1\u4e86\u4e00\u7cfb\u5217\u4e0d\u540c\u89c4\u6a21\u7684\u7f51\u7edc\u3002\u4e0d\u540c\u89c4\u6a21\u7684\u67b6\u6784\u5404\u4e0d\u76f8\u540c\uff0c\u4ee5\u5b9e\u73b0\u6700\u4f73\u7684\u901f\u5ea6\u548c\u51c6\u786e\u6027\u6743\u8861\uff0c\u5176\u4e2d\u5c0f\u578b\u6a21\u578b\u5177\u6709\u7b80\u5355\u7684\u5355\u8def\u5f84\u4e3b\u5e72\uff0c\u5927\u578b\u6a21\u578b\u5efa\u7acb\u5728\u9ad8\u6548\u7684\u591a\u5206\u652f\u5757\u4e0a\u3002<\/li><li>\u4e3a&nbsp;<code>YOLOv6<\/code>&nbsp;\u6ce8\u5165\u4e86\u4e00\u79cd<code>self-distillation<\/code>\u7b56\u7565\uff0c\u5728\u5206\u7c7b\u4efb\u52a1\u548c\u56de\u5f52\u4efb\u52a1\u4e0a\u90fd\u6267\u884c\u3002\u540c\u65f6\uff0c\u52a8\u6001\u8c03\u6574\u6765\u81ea\u6559\u5e08\u548c\u6807\u7b7e\u7684\u77e5\u8bc6\uff0c\u4ee5\u5e2e\u52a9\u5b66\u751f\u6a21\u578b\u5728\u6240\u6709\u8bad\u7ec3\u9636\u6bb5\u66f4\u6709\u6548\u5730\u5b66\u4e60\u77e5\u8bc6\u3002<\/li><li>\u5e7f\u6cdb\u9a8c\u8bc1\u6807\u7b7e\u5206\u914d\u3001\u635f\u5931\u51fd\u6570\u548c\u6570\u636e\u589e\u5f3a\u6280\u672f\u7684\u5148\u8fdb\u68c0\u6d4b\u6280\u672f\uff0c\u5e76\u6709\u9009\u62e9\u5730\u91c7\u7528\u5b83\u4eec\u4ee5\u8fdb\u4e00\u6b65\u63d0\u9ad8\u6027\u80fd\u3002<\/li><li>\u5728&nbsp;<code>RepOptimizer<\/code>&nbsp;\u548c\u901a\u9053\u84b8\u998f\u7684\u5e2e\u52a9\u4e0b\u6539\u8fdb\u4e86\u68c0\u6d4b\u7684\u91cf\u5316\u65b9\u6848\uff0c\u8fd9\u5e26\u6765\u4e86\u5177\u6709 43.3% \u7684 COCO AP \u548c 869 FPS \u7684\u541e\u5410\u91cf\u7684\u5feb\u901f\u51c6\u786e\u7684\u68c0\u6d4b\u5668\uff0c\u6279\u91cf\u5927\u5c0f\u4e3a 32\u3002<\/li><\/ul>\n\n\n\n<h3 id=\"2-1-hardware-friendly-\u7684\u9aa8\u5e72\u7f51\u7edc\u8bbe\u8ba1\">2.1 Hardware-friendly \u7684\u9aa8\u5e72\u7f51\u7edc\u8bbe\u8ba1<\/h3>\n\n\n\n<p>YOLOv5\/YOLOX \u4f7f\u7528\u7684 Backbone \u548c Neck \u90fd\u57fa\u4e8e CSPNet<sup>[5]<\/sup>&nbsp;\u642d\u5efa\uff0c\u91c7\u7528\u4e86\u591a\u5206\u652f\u7684\u65b9\u5f0f\u548c\u6b8b\u5dee\u7ed3\u6784\u3002\u5bf9\u4e8e GPU \u7b49\u786c\u4ef6\u6765\u8bf4\uff0c\u8fd9\u79cd\u7ed3\u6784\u4f1a\u4e00\u5b9a\u7a0b\u5ea6\u4e0a\u589e\u52a0\u5ef6\u65f6\uff0c\u540c\u65f6\u51cf\u5c0f\u5185\u5b58\u5e26\u5bbd\u5229\u7528\u7387\u3002\u4e0b\u56fe 2 \u4e3a\u8ba1\u7b97\u673a\u4f53\u7cfb\u7ed3\u6784\u9886\u57df\u4e2d\u7684 Roofline Model<sup>[8]<\/sup>&nbsp;\u4ecb\u7ecd\u56fe\uff0c\u663e\u793a\u4e86\u786c\u4ef6\u4e2d\u8ba1\u7b97\u80fd\u529b\u548c\u5185\u5b58\u5e26\u5bbd\u4e4b\u95f4\u7684\u5173\u8054\u5173\u7cfb\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p0.meituan.net\/travelcube\/340c70143e36a3c6dfb1ee333cabe3f083168.png\" alt=\"\u56fe2 Roofline Model \u4ecb\u7ecd\u56fe\"\/><figcaption>\u56fe2 Roofline Model \u4ecb\u7ecd\u56fe<\/figcaption><\/figure>\n\n\n\n<p>     \u4e8e\u662f\uff0c\u6211\u4eec\u57fa\u4e8e\u786c\u4ef6\u611f\u77e5\u795e\u7ecf\u7f51\u7edc\u8bbe\u8ba1\u7684\u601d\u60f3\uff0c\u5bf9 Backbone \u548c Neck \u8fdb\u884c\u4e86\u91cd\u65b0\u8bbe\u8ba1\u548c\u4f18\u5316\u3002\u8be5\u601d\u60f3\u57fa\u4e8e\u786c\u4ef6\u7684\u7279\u6027\u3001\u63a8\u7406\u6846\u67b6\/\u7f16\u8bd1\u6846\u67b6\u7684\u7279\u70b9\uff0c\u4ee5\u786c\u4ef6\u548c\u7f16\u8bd1\u53cb\u597d\u7684\u7ed3\u6784\u4f5c\u4e3a\u8bbe\u8ba1\u539f\u5219\uff0c\u5728\u7f51\u7edc\u6784\u5efa\u65f6\uff0c\u7efc\u5408\u8003\u8651\u786c\u4ef6\u8ba1\u7b97\u80fd\u529b\u3001\u5185\u5b58\u5e26\u5bbd\u3001\u7f16\u8bd1\u4f18\u5316\u7279\u6027\u3001\u7f51\u7edc\u8868\u5f81\u80fd\u529b\u7b49\uff0c\u8fdb\u800c\u83b7\u5f97\u53c8\u5feb\u53c8\u597d\u7684\u7f51\u7edc\u7ed3\u6784\u3002\u5bf9\u4e0a\u8ff0\u91cd\u65b0\u8bbe\u8ba1\u7684\u4e24\u4e2a\u68c0\u6d4b\u90e8\u4ef6\uff0c\u6211\u4eec\u5728 YOLOv6 \u4e2d\u5206\u522b\u79f0\u4e3a<strong> EfficientRep Backbone <\/strong>\u548c <strong>Rep-PAN Neck<\/strong>\uff0c\u5176\u4e3b\u8981\u8d21\u732e\u70b9\u5728\u4e8e\uff1a<\/p>\n\n\n\n<ol><li>\u5f15\u5165\u4e86 RepVGG<sup>[4]<\/sup>&nbsp;style \u7ed3\u6784\u3002<\/li><li>\u57fa\u4e8e\u786c\u4ef6\u611f\u77e5\u601d\u60f3\u91cd\u65b0\u8bbe\u8ba1\u4e86 Backbone \u548c Neck\u3002<\/li><\/ol>\n\n\n\n<p>RepVGG<sup>[4]<\/sup>&nbsp;Style \u7ed3\u6784\u662f\u4e00\u79cd\u5728\u8bad\u7ec3\u65f6\u5177\u6709\u591a\u5206\u652f\u62d3\u6251\uff0c\u800c\u5728\u5b9e\u9645\u90e8\u7f72\u65f6\u53ef\u4ee5\u7b49\u6548\u878d\u5408\u4e3a\u5355\u4e2a 3&#215;3 \u5377\u79ef\u7684\u4e00\u79cd\u53ef\u91cd\u53c2\u6570\u5316\u7684\u7ed3\u6784\uff08\u878d\u5408\u8fc7\u7a0b\u5982\u4e0b\u56fe 3 \u6240\u793a\uff09\u3002\u901a\u8fc7\u878d\u5408\u6210\u7684 3&#215;3 \u5377\u79ef\u7ed3\u6784\uff0c\u53ef\u4ee5\u6709\u6548\u5229\u7528\u8ba1\u7b97\u5bc6\u96c6\u578b\u786c\u4ef6\u8ba1\u7b97\u80fd\u529b\uff08\u6bd4\u5982 GPU\uff09\uff0c\u540c\u65f6\u4e5f\u53ef\u83b7\u5f97 GPU\/CPU \u4e0a\u5df2\u7ecf\u9ad8\u5ea6\u4f18\u5316\u7684 NVIDIA cuDNN \u548c Intel MKL \u7f16\u8bd1\u6846\u67b6\u7684\u5e2e\u52a9\u3002<\/p>\n\n\n\n<p>\u5b9e\u9a8c\u8868\u660e\uff0c\u901a\u8fc7\u4e0a\u8ff0\u7b56\u7565\uff0cYOLOv6 \u51cf\u5c11\u4e86\u5728\u786c\u4ef6\u4e0a\u7684\u5ef6\u65f6\uff0c\u5e76\u663e\u7740\u63d0\u5347\u4e86\u7b97\u6cd5\u7684\u7cbe\u5ea6\uff0c\u8ba9\u68c0\u6d4b\u7f51\u7edc\u66f4\u5feb\u66f4\u5f3a\u3002\u4ee5 nano \u5c3a\u5bf8\u6a21\u578b\u4e3a\u4f8b\uff0c\u5bf9\u6bd4 YOLOv5-nano \u91c7\u7528\u7684\u7f51\u7edc\u7ed3\u6784\uff0c\u672c\u65b9\u6cd5\u5728\u901f\u5ea6\u4e0a\u63d0\u5347\u4e8621%\uff0c\u540c\u65f6\u7cbe\u5ea6\u63d0\u5347 3.6% AP\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p0.meituan.net\/travelcube\/9f7878c7872787f9b8706b28e5e7c611237315.png\" alt=\"\u56fe3 Rep\u7b97\u5b50\u7684\u878d\u5408\u8fc7\u7a0b[4]\"\/><figcaption>\u56fe3 Rep\u7b97\u5b50\u7684\u878d\u5408\u8fc7\u7a0b[4]<\/figcaption><\/figure>\n\n\n\n<p><strong>EfficientRep Backbone<\/strong>\uff1a\u5728 Backbone \u8bbe\u8ba1\u65b9\u9762\uff0c\u6211\u4eec\u57fa\u4e8e\u4ee5\u4e0a Rep \u7b97\u5b50\u8bbe\u8ba1\u4e86\u4e00\u4e2a\u9ad8\u6548\u7684Backbone\u3002\u76f8\u6bd4\u4e8e YOLOv5 \u91c7\u7528\u7684 CSP-Backbone\uff0c\u8be5 Backbone \u80fd\u591f\u9ad8\u6548\u5229\u7528\u786c\u4ef6\uff08\u5982 GPU\uff09\u7b97\u529b\u7684\u540c\u65f6\uff0c\u8fd8\u5177\u6709\u8f83\u5f3a\u7684\u8868\u5f81\u80fd\u529b\u3002<\/p>\n\n\n\n<p>\u4e0b\u56fe 4 \u4e3a EfficientRep Backbone \u5177\u4f53\u8bbe\u8ba1\u7ed3\u6784\u56fe\uff0c\u5c06 Backbone \u4e2d stride=2 \u7684\u666e\u901a Conv \u5c42\u66ff\u6362\u6210\u4e86 stride=2 \u7684 RepConv\u5c42\u3002\u540c\u65f6\uff0c\u5c06\u539f\u59cb\u7684 CSP-Block \u90fd\u91cd\u65b0\u8bbe\u8ba1\u4e3a RepBlock\uff0c\u5176\u4e2d RepBlock \u7684\u7b2c\u4e00\u4e2a RepConv \u4f1a\u505a channel \u7ef4\u5ea6\u7684\u53d8\u6362\u548c\u5bf9\u9f50\u3002\u53e6\u5916\uff0c\u6211\u4eec\u8fd8\u5c06\u539f\u59cb\u7684 SPPF \u4f18\u5316\u8bbe\u8ba1\u4e3a\u66f4\u52a0\u9ad8\u6548\u7684 SimSPPF\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p0.meituan.net\/travelcube\/8ec8337d37c2545b8fcf355625854802145939.png\" alt=\"\u56fe4 EfficientRep Backbone \u7ed3\u6784\u56fe\"\/><figcaption>\u56fe4 EfficientRep Backbone \u7ed3\u6784\u56fe<\/figcaption><\/figure>\n\n\n\n<p><strong>Rep-PAN<\/strong>\uff1a\u5728 Neck \u8bbe\u8ba1\u65b9\u9762\uff0c\u4e3a\u4e86\u8ba9\u5176\u5728\u786c\u4ef6\u4e0a\u63a8\u7406\u66f4\u52a0\u9ad8\u6548\uff0c\u4ee5\u8fbe\u5230\u66f4\u597d\u7684\u7cbe\u5ea6\u4e0e\u901f\u5ea6\u7684\u5e73\u8861\uff0c\u6211\u4eec\u57fa\u4e8e\u786c\u4ef6\u611f\u77e5\u795e\u7ecf\u7f51\u7edc\u8bbe\u8ba1\u601d\u60f3\uff0c\u4e3a YOLOv6 \u8bbe\u8ba1\u4e86\u4e00\u4e2a\u66f4\u6709\u6548\u7684\u7279\u5f81\u878d\u5408\u7f51\u7edc\u7ed3\u6784\u3002<\/p>\n\n\n\n<p>Rep-PAN \u57fa\u4e8e PAN<sup>[6]<\/sup>&nbsp;\u62d3\u6251\u65b9\u5f0f\uff0c\u7528 RepBlock \u66ff\u6362\u4e86 YOLOv5 \u4e2d\u4f7f\u7528\u7684 CSP-Block\uff0c\u540c\u65f6\u5bf9\u6574\u4f53 Neck \u4e2d\u7684\u7b97\u5b50\u8fdb\u884c\u4e86\u8c03\u6574\uff0c\u76ee\u7684\u662f\u5728\u786c\u4ef6\u4e0a\u8fbe\u5230\u9ad8\u6548\u63a8\u7406\u7684\u540c\u65f6\uff0c\u4fdd\u6301\u8f83\u597d\u7684\u591a\u5c3a\u5ea6\u7279\u5f81\u878d\u5408\u80fd\u529b\uff08Rep-PAN \u7ed3\u6784\u56fe\u5982\u4e0b\u56fe 5 \u6240\u793a\uff09\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p0.meituan.net\/travelcube\/c37c23c37fd094e05e8cab924659a9d9199592.png\" alt=\"\u56fe5 Rep-PAN \u7ed3\u6784\u56fe\"\/><figcaption>\u56fe5 Rep-PAN \u7ed3\u6784\u56fe<\/figcaption><\/figure>\n\n\n\n<h3 id=\"2-2-\u66f4\u7b80\u6d01\u9ad8\u6548\u7684-decoupled-head\">2.2 \u66f4\u7b80\u6d01\u9ad8\u6548\u7684 Decoupled Head<\/h3>\n\n\n\n<p>\u5728 YOLOv6 \u4e2d\uff0c\u6211\u4eec\u91c7\u7528\u4e86\u89e3\u8026\u68c0\u6d4b\u5934\uff08Decoupled Head\uff09\u7ed3\u6784\uff0c\u5e76\u5bf9\u5176\u8fdb\u884c\u4e86\u7cbe\u7b80\u8bbe\u8ba1\u3002\u539f\u59cb YOLOv5 \u7684\u68c0\u6d4b\u5934\u662f\u901a\u8fc7\u5206\u7c7b\u548c\u56de\u5f52\u5206\u652f\u878d\u5408\u5171\u4eab\u7684\u65b9\u5f0f\u6765\u5b9e\u73b0\u7684\uff0c\u800c YOLOX \u7684\u68c0\u6d4b\u5934\u5219\u662f\u5c06\u5206\u7c7b\u548c\u56de\u5f52\u5206\u652f\u8fdb\u884c\u89e3\u8026\uff0c\u540c\u65f6\u65b0\u589e\u4e86\u4e24\u4e2a\u989d\u5916\u7684 3&#215;3 \u7684\u5377\u79ef\u5c42\uff0c\u867d\u7136\u63d0\u5347\u4e86\u68c0\u6d4b\u7cbe\u5ea6\uff0c\u4f46\u4e00\u5b9a\u7a0b\u5ea6\u4e0a\u589e\u52a0\u4e86\u7f51\u7edc\u5ef6\u65f6\u3002<\/p>\n\n\n\n<p>\u56e0\u6b64\uff0c\u6211\u4eec\u5bf9\u89e3\u8026\u5934\u8fdb\u884c\u4e86\u7cbe\u7b80\u8bbe\u8ba1\uff0c\u540c\u65f6\u7efc\u5408\u8003\u8651\u5230\u76f8\u5173\u7b97\u5b50\u8868\u5f81\u80fd\u529b\u548c\u786c\u4ef6\u4e0a\u8ba1\u7b97\u5f00\u9500\u8fd9\u4e24\u8005\u7684\u5e73\u8861\uff0c\u91c7\u7528 Hybrid Channels \u7b56\u7565\u91cd\u65b0\u8bbe\u8ba1\u4e86\u4e00\u4e2a\u66f4\u9ad8\u6548\u7684\u89e3\u8026\u5934\u7ed3\u6784\uff0c\u5728\u7ef4\u6301\u7cbe\u5ea6\u7684\u540c\u65f6\u964d\u4f4e\u4e86\u5ef6\u65f6\uff0c\u7f13\u89e3\u4e86\u89e3\u8026\u5934\u4e2d 3&#215;3 \u5377\u79ef\u5e26\u6765\u7684\u989d\u5916\u5ef6\u65f6\u5f00\u9500\u3002\u901a\u8fc7\u5728 nano \u5c3a\u5bf8\u6a21\u578b\u4e0a\u8fdb\u884c\u6d88\u878d\u5b9e\u9a8c\uff0c\u5bf9\u6bd4\u76f8\u540c\u901a\u9053\u6570\u7684\u89e3\u8026\u5934\u7ed3\u6784\uff0c\u7cbe\u5ea6\u63d0\u5347 0.2% AP \u7684\u540c\u65f6\uff0c\u901f\u5ea6\u63d0\u53476.8%\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image is-resized\"><img loading=\"lazy\" src=\"https:\/\/p0.meituan.net\/travelcube\/9a0fd7ba30522ce3ed24822e51b0e1a8109432.png\" alt=\"\u56fe6 Efficient Decoupled Head \u7ed3\u6784\u56fe\" width=\"690\" height=\"571\"\/><figcaption>\u56fe6 Efficient Decoupled Head \u7ed3\u6784\u56fe<\/figcaption><\/figure>\n\n\n\n<h3 id=\"2-3-\u66f4\u6709\u6548\u7684\u8bad\u7ec3\u7b56\u7565\">2.3 \u66f4\u6709\u6548\u7684\u8bad\u7ec3\u7b56\u7565<\/h3>\n\n\n\n<p>\u4e3a\u4e86\u8fdb\u4e00\u6b65\u63d0\u5347\u68c0\u6d4b\u7cbe\u5ea6\uff0c\u6211\u4eec\u5438\u6536\u501f\u9274\u4e86\u5b66\u672f\u754c\u548c\u4e1a\u754c\u5176\u4ed6\u68c0\u6d4b\u6846\u67b6\u7684\u5148\u8fdb\u7814\u7a76\u8fdb\u5c55\uff1aAnchor-free \u65e0\u951a\u8303\u5f0f \u3001SimOTA \u6807\u7b7e\u5206\u914d\u7b56\u7565\u4ee5\u53ca SIoU \u8fb9\u754c\u6846\u56de\u5f52\u635f\u5931\u3002<\/p>\n\n\n\n<p><strong>Anchor-free \u65e0\u951a\u8303\u5f0f<\/strong><\/p>\n\n\n\n<p>YOLOv6 \u91c7\u7528\u4e86\u66f4\u7b80\u6d01\u7684 Anchor-free \u68c0\u6d4b\u65b9\u6cd5\u3002\u7531\u4e8e Anchor-based\u68c0\u6d4b\u5668\u9700\u8981\u5728\u8bad\u7ec3\u4e4b\u524d\u8fdb\u884c\u805a\u7c7b\u5206\u6790\u4ee5\u786e\u5b9a\u6700\u4f73 Anchor \u96c6\u5408\uff0c\u8fd9\u4f1a\u4e00\u5b9a\u7a0b\u5ea6\u63d0\u9ad8\u68c0\u6d4b\u5668\u7684\u590d\u6742\u5ea6\uff1b\u540c\u65f6\uff0c\u5728\u4e00\u4e9b\u8fb9\u7f18\u7aef\u7684\u5e94\u7528\u4e2d\uff0c\u9700\u8981\u5728\u786c\u4ef6\u4e4b\u95f4\u642c\u8fd0\u5927\u91cf\u68c0\u6d4b\u7ed3\u679c\u7684\u6b65\u9aa4\uff0c\u4e5f\u4f1a\u5e26\u6765\u989d\u5916\u7684\u5ef6\u65f6\u3002\u800c Anchor-free \u65e0\u951a\u8303\u5f0f\u56e0\u5176\u6cdb\u5316\u80fd\u529b\u5f3a\uff0c\u89e3\u7801\u903b\u8f91\u66f4\u7b80\u5355\uff0c\u5728\u8fd1\u51e0\u5e74\u4e2d\u5e94\u7528\u6bd4\u8f83\u5e7f\u6cdb\u3002\u7ecf\u8fc7\u5bf9 Anchor-free \u7684\u5b9e\u9a8c\u8c03\u7814\uff0c\u6211\u4eec\u53d1\u73b0\uff0c\u76f8\u8f83\u4e8eAnchor-based \u68c0\u6d4b\u5668\u7684\u590d\u6742\u5ea6\u800c\u5e26\u6765\u7684\u989d\u5916\u5ef6\u65f6\uff0cAnchor-free \u68c0\u6d4b\u5668\u5728\u901f\u5ea6\u4e0a\u670951%\u7684\u63d0\u5347\u3002<\/p>\n\n\n\n<p><strong>SimOTA \u6807\u7b7e\u5206\u914d\u7b56\u7565<\/strong><\/p>\n\n\n\n<p>\u4e3a\u4e86\u83b7\u5f97\u66f4\u591a\u9ad8\u8d28\u91cf\u7684\u6b63\u6837\u672c\uff0cYOLOv6 \u5f15\u5165\u4e86 SimOTA&nbsp;<sup>[4]<\/sup>\u7b97\u6cd5\u52a8\u6001\u5206\u914d\u6b63\u6837\u672c\uff0c\u8fdb\u4e00\u6b65\u63d0\u9ad8\u68c0\u6d4b\u7cbe\u5ea6\u3002YOLOv5 \u7684\u6807\u7b7e\u5206\u914d\u7b56\u7565\u662f\u57fa\u4e8e Shape \u5339\u914d\uff0c\u5e76\u901a\u8fc7\u8de8\u7f51\u683c\u5339\u914d\u7b56\u7565\u589e\u52a0\u6b63\u6837\u672c\u6570\u91cf\uff0c\u4ece\u800c\u4f7f\u5f97\u7f51\u7edc\u5feb\u901f\u6536\u655b\uff0c\u4f46\u662f\u8be5\u65b9\u6cd5\u5c5e\u4e8e\u9759\u6001\u5206\u914d\u65b9\u6cd5\uff0c\u5e76\u4e0d\u4f1a\u968f\u7740\u7f51\u7edc\u8bad\u7ec3\u7684\u8fc7\u7a0b\u800c\u8c03\u6574\u3002<\/p>\n\n\n\n<p>\u8fd1\u5e74\u6765\uff0c\u4e5f\u51fa\u73b0\u4e0d\u5c11\u57fa\u4e8e\u52a8\u6001\u6807\u7b7e\u5206\u914d\u7684\u65b9\u6cd5\uff0c\u6b64\u7c7b\u65b9\u6cd5\u4f1a\u6839\u636e\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u7684\u7f51\u7edc\u8f93\u51fa\u6765\u5206\u914d\u6b63\u6837\u672c\uff0c\u4ece\u800c\u53ef\u4ee5\u4ea7\u751f\u66f4\u591a\u9ad8\u8d28\u91cf\u7684\u6b63\u6837\u672c\uff0c\u7ee7\u800c\u53c8\u4fc3\u8fdb\u7f51\u7edc\u7684\u6b63\u5411\u4f18\u5316\u3002\u4f8b\u5982\uff0cOTA<sup>[7]<\/sup>&nbsp;\u901a\u8fc7\u5c06\u6837\u672c\u5339\u914d\u5efa\u6a21\u6210\u6700\u4f73\u4f20\u8f93\u95ee\u9898\uff0c\u6c42\u5f97\u5168\u5c40\u4fe1\u606f\u4e0b\u7684\u6700\u4f73\u6837\u672c\u5339\u914d\u7b56\u7565\u4ee5\u63d0\u5347\u7cbe\u5ea6\uff0c\u4f46 OTA \u7531\u4e8e\u4f7f\u7528\u4e86Sinkhorn-Knopp \u7b97\u6cd5\u5bfc\u81f4\u8bad\u7ec3\u65f6\u95f4\u52a0\u957f\uff0c\u800c SimOTA<sup>[4]<\/sup>\u7b97\u6cd5\u4f7f\u7528 Top-K \u8fd1\u4f3c\u7b56\u7565\u6765\u5f97\u5230\u6837\u672c\u6700\u4f73\u5339\u914d\uff0c\u5927\u5927\u52a0\u5feb\u4e86\u8bad\u7ec3\u901f\u5ea6\u3002\u6545 YOLOv6 \u91c7\u7528\u4e86SimOTA \u52a8\u6001\u5206\u914d\u7b56\u7565\uff0c\u5e76\u7ed3\u5408\u65e0\u951a\u8303\u5f0f\uff0c\u5728 nano \u5c3a\u5bf8\u6a21\u578b\u4e0a\u5e73\u5747\u68c0\u6d4b\u7cbe\u5ea6\u63d0\u5347 1.3% AP\u3002<\/p>\n\n\n\n<p><strong>SIoU \u8fb9\u754c\u6846\u56de\u5f52\u635f\u5931<\/strong><\/p>\n\n\n\n<p>\u4e3a\u4e86\u8fdb\u4e00\u6b65\u63d0\u5347\u56de\u5f52\u7cbe\u5ea6\uff0cYOLOv6 \u91c7\u7528\u4e86 SIoU<sup>[9]<\/sup>&nbsp;\u8fb9\u754c\u6846\u56de\u5f52\u635f\u5931\u51fd\u6570\u6765\u76d1\u7763\u7f51\u7edc\u7684\u5b66\u4e60\u3002\u76ee\u6807\u68c0\u6d4b\u7f51\u7edc\u7684\u8bad\u7ec3\u4e00\u822c\u9700\u8981\u81f3\u5c11\u5b9a\u4e49\u4e24\u4e2a\u635f\u5931\u51fd\u6570\uff1a\u5206\u7c7b\u635f\u5931\u548c\u8fb9\u754c\u6846\u56de\u5f52\u635f\u5931\uff0c\u800c\u635f\u5931\u51fd\u6570\u7684\u5b9a\u4e49\u5f80\u5f80\u5bf9\u68c0\u6d4b\u7cbe\u5ea6\u4ee5\u53ca\u8bad\u7ec3\u901f\u5ea6\u4ea7\u751f\u8f83\u5927\u7684\u5f71\u54cd\u3002<\/p>\n\n\n\n<p>\u8fd1\u5e74\u6765\uff0c\u5e38\u7528\u7684\u8fb9\u754c\u6846\u56de\u5f52\u635f\u5931\u5305\u62ecIoU\u3001GIoU\u3001CIoU\u3001DIoU loss\u7b49\u7b49\uff0c\u8fd9\u4e9b\u635f\u5931\u51fd\u6570\u901a\u8fc7\u8003\u8651\u9884\u6d4b\u6846\u4e0e\u76ee\u6807\u6846\u4e4b\u524d\u7684\u91cd\u53e0\u7a0b\u5ea6\u3001\u4e2d\u5fc3\u70b9\u8ddd\u79bb\u3001\u7eb5\u6a2a\u6bd4\u7b49\u56e0\u7d20\u6765\u8861\u91cf\u4e24\u8005\u4e4b\u95f4\u7684\u5dee\u8ddd\uff0c\u4ece\u800c\u6307\u5bfc\u7f51\u7edc\u6700\u5c0f\u5316\u635f\u5931\u4ee5\u63d0\u5347\u56de\u5f52\u7cbe\u5ea6\uff0c\u4f46\u662f\u8fd9\u4e9b\u65b9\u6cd5\u90fd\u6ca1\u6709\u8003\u8651\u5230\u9884\u6d4b\u6846\u4e0e\u76ee\u6807\u6846\u4e4b\u95f4\u65b9\u5411\u7684\u5339\u914d\u6027\u3002SIoU \u635f\u5931\u51fd\u6570\u901a\u8fc7\u5f15\u5165\u4e86\u6240\u9700\u56de\u5f52\u4e4b\u95f4\u7684\u5411\u91cf\u89d2\u5ea6\uff0c\u91cd\u65b0\u5b9a\u4e49\u4e86\u8ddd\u79bb\u635f\u5931\uff0c\u6709\u6548\u964d\u4f4e\u4e86\u56de\u5f52\u7684\u81ea\u7531\u5ea6\uff0c\u52a0\u5feb\u7f51\u7edc\u6536\u655b\uff0c\u8fdb\u4e00\u6b65\u63d0\u5347\u4e86\u56de\u5f52\u7cbe\u5ea6\u3002\u901a\u8fc7\u5728 YOLOv6s \u4e0a\u91c7\u7528 SIoU loss \u8fdb\u884c\u5b9e\u9a8c\uff0c\u5bf9\u6bd4 CIoU loss\uff0c\u5e73\u5747\u68c0\u6d4b\u7cbe\u5ea6\u63d0\u5347 0.3% AP\u3002<\/p>\n\n\n\n<h2 id=\"3-\u5b9e\u9a8c\u7ed3\u679c\">3. \u5b9e\u9a8c\u7ed3\u679c<\/h2>\n\n\n\n<p>\u7ecf\u8fc7\u4ee5\u4e0a\u4f18\u5316\u7b56\u7565\u548c\u6539\u8fdb\uff0cYOLOv6 \u5728\u591a\u4e2a\u4e0d\u540c\u5c3a\u5bf8\u4e0b\u7684\u6a21\u578b\u5747\u53d6\u5f97\u4e86\u5353\u8d8a\u7684\u8868\u73b0\u3002\u4e0b\u8868 1 \u5c55\u793a\u4e86 YOLOv6-nano \u7684\u6d88\u878d\u5b9e\u9a8c\u7ed3\u679c\uff0c\u4ece\u5b9e\u9a8c\u7ed3\u679c\u53ef\u4ee5\u770b\u51fa\uff0c\u6211\u4eec\u81ea\u4e3b\u8bbe\u8ba1\u7684\u68c0\u6d4b\u7f51\u7edc\u5728\u7cbe\u5ea6\u548c\u901f\u5ea6\u4e0a\u90fd\u5e26\u6765\u4e86\u5f88\u5927\u7684\u589e\u76ca\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p0.meituan.net\/travelcube\/fff97f675528a63e610ff858460713cc244523.png\" alt=\"\u88681 YOLOv6-nano \u6d88\u878d\u5b9e\u9a8c\u7ed3\u679c\"\/><figcaption>\u88681 YOLOv6-nano \u6d88\u878d\u5b9e\u9a8c\u7ed3\u679c<\/figcaption><\/figure>\n\n\n\n<p>\u4e0b\u8868 2 \u5c55\u793a\u4e86 YOLOv6 \u4e0e\u5f53\u524d\u4e3b\u6d41\u7684\u5176\u4ed6 YOLO \u7cfb\u5217\u7b97\u6cd5\u76f8\u6bd4\u8f83\u7684\u5b9e\u9a8c\u7ed3\u679c\u3002\u4ece\u8868\u683c\u4e2d\u53ef\u4ee5\u770b\u5230\uff1a<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p0.meituan.net\/travelcube\/bc0e60516ae0bcad1c111d7c0c5c3b9e335568.png\" alt=\"\u88682 YOLOv6\u5404\u5c3a\u5bf8\u6a21\u578b\u6027\u80fd\u4e0e\u5176\u4ed6\u6a21\u578b\u7684\u6bd4\u8f83\"\/><figcaption>\u88682 YOLOv6\u5404\u5c3a\u5bf8\u6a21\u578b\u6027\u80fd\u4e0e\u5176\u4ed6\u6a21\u578b\u7684\u6bd4\u8f83<\/figcaption><\/figure>\n\n\n\n<ul><li>YOLOv6-nano \u5728 COCO val \u4e0a \u53d6\u5f97\u4e86 35.0% AP \u7684\u7cbe\u5ea6\uff0c\u540c\u65f6\u5728 T4 \u4e0a\u4f7f\u7528 TRT FP16 batchsize=32 \u8fdb\u884c\u63a8\u7406\uff0c\u53ef\u8fbe\u5230 1242FPS \u7684\u6027\u80fd\uff0c\u76f8\u8f83\u4e8e YOLOv5-nano \u7cbe\u5ea6\u63d0\u5347 7% AP\uff0c\u901f\u5ea6\u63d0\u5347 85%\u3002<\/li><li>YOLOv6-tiny \u5728 COCO val \u4e0a \u53d6\u5f97\u4e86 41.3% AP \u7684\u7cbe\u5ea6\uff0c \u540c\u65f6\u5728 T4 \u4e0a\u4f7f\u7528 TRT FP16 batchsize=32 \u8fdb\u884c\u63a8\u7406\uff0c\u53ef\u8fbe\u5230 602FPS \u7684\u6027\u80fd\uff0c\u76f8\u8f83\u4e8e YOLOv5-s \u7cbe\u5ea6\u63d0\u5347 3.9% AP\uff0c\u901f\u5ea6\u63d0\u5347 29.4%\u3002<\/li><li>YOLOv6-s \u5728 COCO val \u4e0a \u53d6\u5f97\u4e86 43.1% AP \u7684\u7cbe\u5ea6\uff0c \u540c\u65f6\u5728 T4 \u4e0a\u4f7f\u7528 TRT FP16 batchsize=32 \u8fdb\u884c\u63a8\u7406\uff0c\u53ef\u8fbe\u5230 520FPS \u7684\u6027\u80fd\uff0c\u76f8\u8f83\u4e8e YOLOX-s \u7cbe\u5ea6\u63d0\u5347 2.6% AP\uff0c\u901f\u5ea6\u63d0\u5347 38.6%\uff1b\u76f8\u8f83\u4e8e PP-YOLOE-s \u7cbe\u5ea6\u63d0\u5347 0.4% AP\u7684\u6761\u4ef6\u4e0b\uff0c\u5728T4\u4e0a\u4f7f\u7528 TRT FP16 \u8fdb\u884c\u5355 batch \u63a8\u7406\uff0c\u901f\u5ea6\u63d0\u5347 71.3%\u3002<\/li><\/ul>\n\n\n\n<h2>\u5728\u6d77\u9762\u56fe\u7247\uff08\u81ea\u5df1\u7684\u8bad\u7ec3\u96c6\uff09\u4e0a\u7684\u8bad\u7ec3\uff1a<\/h2>\n\n\n\n<pre class=\"wp-block-code\"><code>is_coco: False\n# Classes\nnc: 10  # number of classes\nnames: &#91;'lighthouse',\n'sailboat',\n'buoy',\n'railbar',\n'cargoship',\n'navalvessels',\n'passengership',\n'dock',\n'submarine',\n'fishingboat']  # class names<\/code><\/pre>\n\n\n\n<p class=\"has-light-pink-background-color has-background\">yolov6s <strong>\u7ed3\u679c\uff1a&nbsp;coco_detection_metrics \u2014\u2014COCO\u68c0\u6d4b\u6307\u6807<\/strong><\/p>\n\n\n\n<p>Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.779<br>Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.992<br>Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.922<br>Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.661<br>Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.710<br>Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.817<br>Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.697<br>Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.801<br>Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.813<br>Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.686<br>Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.740<br>Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.847<\/p>\n\n\n\n<h3><strong>Average Precision (AP)\u548cAverage Recall (AR)\u7b49\u7b49\u8fd9\u4e9b\u90fd\u662f\u5565\u610f\u601d\uff1f<\/strong><\/h3>\n\n\n\n<ul><li><code>IoU=0.50<\/code>\u610f\u5473\u7740<code>IoU<\/code>\u5927\u4e8e0.5\u88ab\u8ba4\u4e3a\u662f\u68c0\u6d4b\u5230\u3002<\/li><li><code>IoU=0.50:0.95<\/code>\u610f\u5473\u7740<code>IoU<\/code>\u57280.5\u52300.95\u7684\u8303\u56f4\u5185\u88ab\u8ba4\u4e3a\u662f\u68c0\u6d4b\u5230\u3002<\/li><li>\u8d8a\u4f4e\u7684<code>IoU<\/code>\u9608\u503c\uff0c\u5219\u5224\u4e3a\u6b63\u786e\u68c0\u6d4b\u7684\u8d8a\u591a\uff0c\u76f8\u5e94\u7684\uff0c<code>Average Precision (AP)<\/code>\u4e5f\u5c31\u8d8a\u9ad8\u3002\u53c2\u8003\u4e0a\u9762\u7684\u7b2c\u4e8c\u7b2c\u4e09\u884c\u3002<\/li><li><code>small<\/code>\u8868\u793a\u6807\u6ce8\u7684\u6846\u9762\u79ef\u5c0f\u4e8e<code>32 * 32<\/code>\uff1b<\/li><li><code>medium<\/code>\u8868\u793a\u6807\u6ce8\u7684\u6846\u9762\u79ef\u540c\u65f6\u5c0f\u4e8e<code>96 * 96<\/code>\uff1b<\/li><li><code>large<\/code>\u8868\u793a\u6807\u6ce8\u7684\u6846\u9762\u79ef\u5927\u4e8e\u7b49\u4e8e<code>96 * 96<\/code>\uff1b<\/li><li><code>all<\/code>\u8868\u793a\u4e0d\u8bba\u5927\u5c0f\uff0c\u6211\u90fd\u8981\u3002<\/li><li><code>maxDets=100<\/code>\u8868\u793a\u6700\u5927\u68c0\u6d4b\u76ee\u6807\u6570\u4e3a100\u3002<\/li><\/ul>\n\n\n\n<h3><strong>&nbsp;Average Precision (AP)\u548cAverage Recall (AR)\u503c\u91cc\u9762\u6709-1\u662f\u4ec0\u4e48\u60c5\u51b5\uff1f<\/strong><\/h3>\n\n\n\n<p>\u53c2\u8003\uff1a<code>https:\/\/github.com\/cocodataset\/cocoapi\/blob\/master\/PythonAPI\/pycocotools\/cocoeval.py#L52<\/code><\/p>\n\n\n\n<p>\u6807\u6ce8\u91cc\u9762\u6ca1\u6709\u6b64\u7c7b\u578b\u7684\u76ee\u6807\u6846\uff0c\u5219<code>Average Precision<\/code>\u548c<code>Average Recall<\/code>\u503c\u4e3a-1\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" width=\"910\" height=\"278\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-108.png\" alt=\"\" class=\"wp-image-5087\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-108.png 910w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-108-300x92.png 300w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-108-768x235.png 768w\" sizes=\"(max-width: 910px) 100vw, 910px\" \/><\/figure>\n\n\n\n<p><strong>Recall&nbsp; &nbsp;\u53ec\u56de\u7387\uff08\u67e5\u5168\u7387\uff09\u3002<\/strong>\u8868\u793a\u6b63\u786e\u8bc6\u522b\u7269\u4f53A\u7684\u4e2a\u6570\u5360\u6d4b\u8bd5\u96c6\u4e2d\u7269\u4f53A\u7684\u603b\u4e2a\u6570\u7684\u767e\u5206\u6570\uff0c\u5373\u6240\u6709\u6b63\u4f8b\u4e2d\u9884\u6d4b\u6b63\u786e\u7684\u6982\u7387\uff0cRecall =&nbsp;<strong>tpr&nbsp;<\/strong>= TP \/ (TP+<strong>FN<\/strong>)<\/p>\n\n\n\n<p><strong>Precision \u7cbe\u786e\u7387\uff08\u67e5\u51c6\u7387\uff09\u3002<\/strong>\u8868\u793a\u6b63\u786e\u8bc6\u522b\u7269\u4f53A\u7684\u4e2a\u6570\u5360\u603b\u8bc6\u522b\u51fa\u7684\u7269\u4f53\u4e2a\u6570n\u7684\u767e\u5206\u6570\uff0c\u5373\u9884\u6d4b\u4e3a\u6b63\u4f8b\u4e2d\u9884\u6d4b\u6b63\u786e\u7684\u6982\u7387\uff0cPrecision&nbsp;= TP \/ (TP+<strong>FP<\/strong>)<\/p>\n\n\n\n<p>\u4ee5\u4e0b12\u4e2a\u6307\u6807\u7528\u4e8e\u8868\u5f81COCO\u4e0a\u7269\u4f53\u68c0\u6d4b\u5668\u7684\u6027\u80fd\uff1a<\/p>\n\n\n\n<p><strong>Average Precision (AP):<\/strong><\/p>\n\n\n\n<p>AP&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; % AP at IoU=0.50:0.05:0.95&nbsp;<strong>(primary challenge metric)<\/strong><\/p>\n\n\n\n<p>APIoU=.50&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AP at IoU=0.50 (PASCAL VOC metric)<\/p>\n\n\n\n<p>APIoU=.75&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AP at IoU=0.75 (strict metric)<\/p>\n\n\n\n<p><strong>AP Across Scales:<\/strong><\/p>\n\n\n\n<p>APsmall&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AP for small objects: area &lt; 322<\/p>\n\n\n\n<p>APmedium&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AP for medium objects: 322 &lt; area &lt; 962<\/p>\n\n\n\n<p>APlarge&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AP for large objects: area &gt; 962<\/p>\n\n\n\n<p><strong>Average Recall (AR):<\/strong><\/p>\n\n\n\n<p>ARmax=1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AR given 1 detection per image<\/p>\n\n\n\n<p>ARmax=10&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AR given 10 detections per image<\/p>\n\n\n\n<p>ARmax=100&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AR given 100 detections per image<\/p>\n\n\n\n<p><strong>AR Across Scales:<\/strong><\/p>\n\n\n\n<p>ARsmall&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AR for small objects: area &lt; 322<\/p>\n\n\n\n<p>ARmedium&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AR for medium objects: 322 &lt; area &lt; 962<\/p>\n\n\n\n<p>ARlarge&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; % AR for large objects: area &gt; 962<\/p>\n\n\n\n<p>1\uff09\u9664\u975e\u53e6\u6709\u8bf4\u660e\uff0c\u5426\u5219AP\u548cAR\u5728\u591a\u4e2a\u4ea4\u6c47\u70b9\uff08IoU\uff09\u503c\u4e0a\u53d6\u5e73\u5747\u503c\u3002\u5177\u4f53\u6765\u8bf4\uff0c\u6211\u4eec\u4f7f\u752810\u4e2aIoU\u9608\u503c0.50\uff1a0.05\uff1a0.95\u3002\u8fd9\u662f\u5bf9\u4f20\u7edf\u7684\u4e00\u4e2a\u7a81\u7834\uff0c\u5176\u4e2dAP\u662f\u5728\u4e00\u4e2a\u5355\u4e00\u76840.50\u7684IoU\u4e0a\u8ba1\u7b97\u7684\uff08\u8fd9\u5bf9\u5e94\u4e8e\u6211\u4eec\u7684\u5ea6\u91cfAPIoU=.50 \uff09\u3002\u8d85\u8fc7\u5747\u503c\u7684IoUs\u80fd\u8ba9\u63a2\u6d4b\u5668\u66f4\u597d\u5b9a\u4f4d\uff08Averaging over IoUs rewards detectors with better localization.\uff09\u3002<\/p>\n\n\n\n<p>2\uff09<strong>AP\u662f\u6240\u6709\u7c7b\u522b\u7684\u5e73\u5747\u503c\u3002\u4f20\u7edf\u4e0a\uff0c\u8fd9\u88ab\u79f0\u4e3a\u201c\u5e73\u5747\u7cbe\u786e\u5ea6\u201d\uff08mAP\uff0cmean average precision\uff09\u3002\u6211\u4eec\u6ca1\u6709\u533a\u5206AP\u548cmAP\uff08\u540c\u6837\u662fAR\u548cmAR\uff09\uff0c\u5e76\u5047\u5b9a\u4ece\u4e0a\u4e0b\u6587\u4e2d\u53ef\u4ee5\u6e05\u695a\u5730\u770b\u51fa\u5dee\u5f02\u3002<\/strong><\/p>\n\n\n\n<p>3)<strong>AP<\/strong>\uff08\u6240\u670910\u4e2aIoU\u9608\u503c\u548c\u6240\u670980\u4e2a\u7c7b\u522b\u7684\u5e73\u5747\u503c\uff09\u5c06\u51b3\u5b9a\u8d62\u5bb6\u3002\u5728\u8003\u8651COCO\u6027\u80fd\u65f6\uff0c<strong>\u8fd9\u5e94\u8be5\u88ab\u8ba4\u4e3a\u662f\u6700\u91cd\u8981\u7684\u4e00\u4e2a\u6307\u6807<\/strong>\u3002<\/p>\n\n\n\n<p>4)\u5728COCO\u4e2d\uff0c\u6bd4\u5927\u7269\u4f53\u76f8\u6bd4\u6709\u66f4\u591a\u7684\u5c0f\u7269\u4f53\u3002\u5177\u4f53\u5730\u8bf4\uff0c\u5927\u7ea641\uff05\u7684\u7269\u4f53\u5f88\u5c0f\uff08\u9762\u79ef&lt;322\uff09\uff0c34\uff05\u662f\u4e2d\u7b49\uff08322 &lt; area &lt; 962)\uff09\uff0c24\uff05\u5927\uff08area &gt; 962\uff09\u3002\u6d4b\u91cf\u7684\u9762\u79ef\uff08area\uff09\u662f\u5206\u5272\u63a9\u7801\uff08segmentation&nbsp;<a href=\"https:\/\/so.csdn.net\/so\/search?q=mask&amp;spm=1001.2101.3001.7020\" target=\"_blank\" rel=\"noreferrer noopener\">mask<\/a>\uff09\u4e2d\u7684\u50cf\u7d20\u6570\u91cf\u3002<\/p>\n\n\n\n<p>5\uff09AR\u662f\u5728\u6bcf\u4e2a\u56fe\u50cf\u4e2d\u68c0\u6d4b\u5230\u56fa\u5b9a\u6570\u91cf\u7684\u6700\u5927\u53ec\u56de\uff08recall\uff09\uff0c\u5728\u7c7b\u522b\u548cIoU\u4e0a\u5e73\u5747\u3002AR\u4e0e\u63d0\u6848\u8bc4\u4f30\uff08<a href=\"http:\/\/arxiv.org\/abs\/1502.05082\" target=\"_blank\" rel=\"noreferrer noopener\">proposal evaluation<\/a>\uff09\u4e2d\u4f7f\u7528\u7684\u540c\u540d\u5ea6\u91cf\u76f8\u5173\uff0c\u4f46\u662f\u6309\u7c7b\u522b\u8ba1\u7b97\u3002<\/p>\n\n\n\n<p>6\uff09\u6240\u6709\u5ea6\u91cf\u6807\u51c6\u5141\u8bb8\u6bcf\u4e2a\u56fe\u50cf\uff08\u5728\u6240\u6709\u7c7b\u522b\u4e2d\uff09\u6700\u591a100\u4e2a\u6700\u9ad8\u5f97\u5206\u68c0\u6d4b\u8fdb\u884c\u8ba1\u7b97\u3002<\/p>\n\n\n\n<p>7\uff09\u9664\u4e86IoU\u8ba1\u7b97\uff08\u5206\u522b\u5728\u6846\uff08box\uff09\u6216\u63a9\u7801\uff08mask\uff09\u4e0a\u6267\u884c\uff09\u4e4b\u5916\uff0c\u7528\u8fb9\u754c\u6846\u548c\u5206\u5272\u63a9\u7801\u68c0\u6d4b\u7684\u8bc4\u4f30\u5ea6\u91cf\u5728\u6240\u6709\u65b9\u9762\u662f\u76f8\u540c\u7684\u3002<\/p>\n\n\n\n<p class=\"has-light-pink-background-color has-background\">\u6d4b\u8bd5\u901f\u5ea6\uff1a<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" width=\"907\" height=\"146\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-109.png\" alt=\"\" class=\"wp-image-5093\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-109.png 907w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-109-300x48.png 300w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-109-768x124.png 768w\" sizes=\"(max-width: 907px) 100vw, 907px\" \/><\/figure>\n\n\n\n<p class=\"has-light-pink-background-color has-background\">img show\uff1a<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-110.png\" alt=\"\" class=\"wp-image-5097\" width=\"204\" height=\"178\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-110.png 524w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-110-300x262.png 300w\" sizes=\"(max-width: 204px) 100vw, 204px\" \/><\/figure><\/div>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-112.png\" alt=\"\" class=\"wp-image-5100\" width=\"204\" height=\"211\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-112.png 539w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-112-290x300.png 290w\" sizes=\"(max-width: 204px) 100vw, 204px\" \/><\/figure><\/div>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-113.png\" alt=\"\" class=\"wp-image-5101\" width=\"380\" height=\"384\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-113.png 506w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-113-297x300.png 297w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-113-120x120.png 120w\" sizes=\"(max-width: 380px) 100vw, 380px\" \/><\/figure><\/div>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-114.png\" alt=\"\" class=\"wp-image-5102\" width=\"277\" height=\"285\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-114.png 506w, http:\/\/139.9.1.231\/wp-content\/uploads\/2022\/07\/image-114-291x300.png 291w\" sizes=\"(max-width: 277px) 100vw, 277px\" \/><\/figure><\/div>\n","protected":false},"excerpt":{"rendered":"<p>\u591a\u5e74\u6765\uff0cYOLO&nbsp;\u7cfb\u5217\u4e00\u76f4\u662f\u9ad8\u6548\u76ee\u6807\u68c0\u6d4b\u7684\u884c\u4e1a\u6807\u51c6\u3002YOLO&nbsp;\u793e\u533a\u84ec\u52c3\u53d1\u5c55\uff0c\u4e30\u5bcc\u4e86\u5176\u5728\u4f17\u591a &hellip; <a href=\"http:\/\/139.9.1.231\/index.php\/2022\/07\/20\/yolov6\/\" class=\"more-link\">\u7ee7\u7eed\u9605\u8bfb<span class=\"screen-reader-text\">yolov6  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