图1 Ground Truth和Predictions
表1 TP和FP统计
| Images |
Predictions |
Confidence |
TP or FP |
| Images 1 |
Person1 |
87% |
FP |
| Images 1 |
Person2 |
80% |
FP |
| Images 1 |
Person3 |
78% |
TP |
| Images 2 |
Person4 |
75% |
TP |
| Images 2 |
Person5 |
52% |
FP |
| Images 2 |
Person6 |
74% |
FP |
| Images 3 |
Person7 |
20% |
TP |
| Images 3 |
Person8 |
68% |
FP |
| Images 3 |
Person9 |
95% |
TP |
| Images 3 |
Person10 |
81% |
TP |
| Images 4 |
Person11 |
90% |
TP |
| Images 4 |
Person12 |
45% |
FP |
| Images 4 |
Person13 |
15% |
FP |
| Images 5 |
Person14 |
98% |
TP |
| Images 5 |
Person15 |
25% |
FP |
| Images 5 |
Person16 |
44% |
FP |
| Images 6 |
Person17 |
43% |
FP |
| Images 6 |
Person18 |
60% |
TP |
| Images 6 |
Person19 |
70% |
TP |
| Images 6 |
Person20 |
84% |
FP |
| Images 7 |
Person21 |
39% |
TP |
| Images 7 |
Person22 |
92% |
TP |
| Images 8 |
Person23 |
36% |
TP |
| Images 8 |
Person24 |
94% |
FP |
| Images 8 |
Person25 |
33% |
FP |
表2 P和R统计
| Images |
Predictions |
Confidence |
TP |
FP |
Precision |
Recall |
| Images 5 |
Person14 |
98% |
1 |
0 |
1 |
0.0435 |
| Images 3 |
Person9 |
95% |
1 |
0 |
1 |
0.0870 |
| Images 8 |
Person24 |
94% |
0 |
1 |
0.6667 |
0.0870 |
| Images 7 |
Person22 |
92% |
1 |
0 |
0.7500 |
0.1304 |
| Images 4 |
Person11 |
90% |
1 |
0 |
0.8000 |
0.1739 |
| Images 1 |
Person1 |
87% |
0 |
1 |
0.6667 |
0.1739 |
| Images 6 |
Person20 |
84% |
0 |
1 |
0.5714 |
0.1739 |
| Images 3 |
Person10 |
81% |
1 |
0 |
0.6250 |
0.2174 |
| Images 1 |
Person2 |
80% |
0 |
1 |
0.5556 |
0.2174 |
| Images 1 |
Person3 |
78% |
1 |
0 |
0.6000 |
0.2609 |
| Images 2 |
Person4 |
75% |
1 |
0 |
0.6364 |
0.3043 |
| Images 2 |
Person6 |
74% |
0 |
1 |
0.5833 |
0.3043 |
| Images 6 |
Person19 |
70% |
1 |
0 |
0.6154 |
0.3478 |
| Images 3 |
Person8 |
68% |
0 |
1 |
0.5714 |
0.3478 |
| Images 6 |
Person18 |
60% |
1 |
0 |
0.6000 |
0.3913 |
| Images 2 |
Person5 |
52% |
0 |
1 |
0.5625 |
0.3913 |
| Images 4 |
Person12 |
45% |
0 |
1 |
0.5294 |
0.3913 |
| Images 5 |
Person16 |
44% |
0 |
1 |
0.5000 |
0.3913 |
| Images 6 |
Person17 |
43% |
0 |
1 |
0.4737 |
0.3913 |
| Images 7 |
Person21 |
39% |
1 |
0 |
0.5000 |
0.4348 |
| Images 8 |
Person23 |
36% |
1 |
0 |
0.5238 |
0.4783 |
| Images 8 |
Person25 |
33% |
0 |
1 |
0.5000 |
0.4783 |
| Images 5 |
Person15 |
25% |
0 |
1 |
0.4783 |
0.4783 |
| Images 3 |
Person7 |
20% |
1 |
0 |
0.5000 |
0.5217 |
| Images 4 |
Person13 |
15% |
0 |
1 |
0.4800 |
0.5217 |
通过表2的出了每个Person类别的准确率和召回率，画出PR曲线如图2.18所示。而AP值比较常用的是使用积分法计算。积分法的计算方法很简单，将PR曲线中的各个矩形面积进行相加即可得到AP值，即图2.19中A1 、A2、 A3、 A4、 A5 、A6、 A7的面积相加就是相应的AP值。通过计算可得：
图2.18 PR曲线
图2.19 积分法计算AP