杂志上的传感器
研究文章

安全吗检测系统基于改进YOLOv7制造车间

表3

不同算法的性能在三个数据集。
数据集 方法 (%) (%) 地图(%) F1 (%)
Helmet-head 快RCNN 92.91 90.81 94.04 91.85
YOLOv5l 94.83 93.75 96.51 94.29
YOLOv5m 94.64 93.07 96.24 93.85
YOLOv5s 94.41 92.03 95.79 93.20
YOLOv5x 94.74 94.15 96.62 94.44
YOLOv7-tiny 92.94 90.86 95.09 91.89
YOLOv7-d6 92.40 88.03 93.72 90.16
YOLOv7-e6 94.11 92.22 96.08 93.16
YOLOv7-e6e 93.22 90.73 95.08 91.96
YOLOv7-w6 92.48 89.34 94.31 90.88
YOLOv7 94.71 94.02 97.15 94.36
YOLOv7-x 94.38 94.52 97.26 94.45
YOLOv7_ours 94.61 94.76 97.54 94.68
Helmet-data 快RCNN 88.65 0.8562 90.19 87.11
YOLOv5l 91.64 88.14 94.31 89.86
YOLOv5m 93.05 86.42 91.89 89.61
YOLOv5s 92.11 86.51 91.76 89.22
YOLOv5x 92.02 87.66 92.29 89.79
YOLOv7-tiny 90.83 88.53 92.94 89.67
YOLOv7-d6 91.55 86.95 92.21 89.19
YOLOv7-e6 92.38 85.36 91.73 88.73
YOLOv7-e6e 91.66 87.73 92.77 89.65
YOLOv7-w6 90.22 87.21 91.97 88.69
YOLOv7 92.73 89.59 94.06 91.13
YOLOv7-x 93.19 89.82 94.36 91.47
YOLOv7_ours 92.73 90.47 94.76 91.59
头盔 快RCNN 81.35 0.7373 80.59 77.35
YOLOv5l 85.24 72.75 79.01 78.50
YOLOv5m 89.72 69.14 77.69 78.10
YOLOv5s 86.32 69.67 77.51 77.11
YOLOv5x 85.36 74.01 79.41 79.28
YOLOv7-tiny 85.66 71.71 79.43 78.07
YOLOv7-d6 83.76 81.22 85.51 82.47
YOLOv7-e6 87.71 77.85 85.00 82.49
YOLOv7-e6e 86.62 78.13 84.14 82.16
YOLOv7-w6 85.33 79.27 83.17 82.19
YOLOv7 87.72 77.88 85.19 82.51
YOLOv7-x 86.11 76.45 83.97 80.99
YOLOv7_ours 87.54 80.40 85.98 83.82