2022-06-06-组会

2022-06-06-组会

训练结果

跑完了ReDet的训练(基于DOTAv1.0)

训练结果日志:

ap为平均精度

2022-05-31 13:41:46,926 - mmrotate - INFO - Saving checkpoint at 12 epochs
2022-05-31 14:22:35,774 - mmrotate - INFO - 
+--------------------+-------+--------+--------+-------+
| class              | gts   | dets   | recall | ap    |
+--------------------+-------+--------+--------+-------+
| plane              | 18788 | 23259  | 0.896  | 0.799 |
| baseball-diamond   | 1087  | 2135   | 0.724  | 0.651 |
| bridge             | 4181  | 4962   | 0.584  | 0.470 |
| ground-track-field | 733   | 1090   | 0.618  | 0.556 |
| small-vehicle      | 58868 | 110625 | 0.841  | 0.748 |
| large-vehicle      | 43075 | 74399  | 0.905  | 0.842 |
| ship               | 76153 | 88620  | 0.869  | 0.805 |
| tennis-court       | 5923  | 9230   | 0.937  | 0.904 |
| basketball-court   | 1180  | 2564   | 0.770  | 0.700 |
| storage-tank       | 13670 | 15183  | 0.674  | 0.622 |
| soccer-ball-field  | 827   | 2764   | 0.625  | 0.472 |
| roundabout         | 973   | 1973   | 0.623  | 0.544 |
| harbor             | 15468 | 22735  | 0.791  | 0.687 |
| swimming-pool      | 3836  | 8011   | 0.794  | 0.644 |
| helicopter         | 1189  | 1946   | 0.807  | 0.765 |
+--------------------+-------+--------+--------+-------+
| mAP                |       |        |        | 0.681 |
+--------------------+-------+--------+--------+-------+
2022-05-31 14:22:35,861 - mmrotate - INFO - Exp name: redet_re50_refpn_1x_dota_le90.py
2022-05-31 14:22:35,861 - mmrotate - INFO - Epoch(val) [12][12800]	mAP: 0.6807

和论文中贴出来的结果表格的相比,总体mAP(平均精度均值)要少8个百分点:

初步分析是因为Batch Size不一样, GPU不一样,:

我租用的云服务器GPU是2080ti,因为第一次训练怕爆显存,我跑的时候batch_size设置成了1。

日志分析

分类损失和回归损失:

最终loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0228

总Loss函数损失:

最终总loss: 0.5917


本博客所有文章均采用 CC BY-NC-SA 4.0 协议 ,禁止商用,转载请注明出处!