Table 1.
mAP scores associated with different confidence thresholds set in YOLO at different IoU thresholds.
| mAP accuracy per IoU threshold | |||||
|---|---|---|---|---|---|
| IoU threshold | Confidence threshold | Recall | True positive | False positive | mAP |
| 0.7 | 84.03% | 20 838 | 3959 | 57.56% | |
| 0.65 | 79.30% | 23 347 | 6093 | 63.57% | |
| 0.6 | 74.14% | 25 398 | 8858 | 68.19% | |
| 0.55 | 69.34% | 26 942 | 11 911 | 71.44% | |
| 0.5 | 64.74% | 28 140 | 15 321 | 73.79% | |
| 0.45 | 60.36% | 29 094 | 19 099 | 75.55% | |
| 0.4 | 56.18% | 29 828 | 23 261 | 76.80% | |
| IoU threshold at 0.5 | 0.35 | 52.03% | 30 404 | 28 026 | 77.71% |
| 0.33 | 50.42% | 30 592 | 30 073 | 78.00% | |
| 0.3 | 48.02% | 308 85 | 33 422 | 78.42% | |
| 0.25 | 44.00% | 31 295 | 39 827 | 78.97% | |
| 0.2 | 39.86% | 31 685 | 47 801 | 79.45% | |
| 0.15 | 35.28% | 32 060 | 58 811 | 79.87% | |
| 0.1 | 30.08% | 32 422 | 75 336 | 80.21% | |
| 0.7 | 84.74% | 21 014 | 3783 | 58.32% | |
| 0.65 | 79.99% | 23 549 | 5891 | 64.45% | |
| 0.6 | 74.75% | 25 604 | 8648 | 69.12% | |
| 0.55 | 69.90% | 27 162 | 11 691 | 72.42% | |
| 0.5 | 65.23% | 28 353 | 15 108 | 74.78% | |
| 0.45 | 60.79% | 29 298 | 18 895 | 76.53% | |
| 0.4 | 56.58% | 30 039 | 23 050 | 77.80% | |
| IoU threshold at 0.1 | 0.35 | 52.38% | 30 604 | 27 822 | 78.71% |
| 0.33 | 50.75% | 30 789 | 29 876 | 78.99% | |
| 0.3 | 79.41% | 31 082 | 33 225 | 79.41% | |
| 0.25 | 44.27% | 31 387 | 39 635 | 79.96% | |
| 0.2 | 40.11% | 31 880 | 47 606 | 80.45% | |
| 0.15 | 35.49% | 32 255 | 58 616 | 80.87% | |
| 0.1 | 30.27% | 32 625 | 75 133 | 81.22% | |
Notes. Notice how when the confidence threshold decreases the mAP increases but so too does the true negative and positive rate. The challenge is to find a balance between metrics for optimised performance in terms of accuracy.
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