based on new-yolov1-pytorch project
2.4 IoU Loss
IoU Loss
| Model | mAP(07test) | LogFile |
|---|---|---|
| FPN/MultiHeadFPN | 0.7149 | eval_log/log_eval_myYOLOWithFPNMultiPred_with_sam_for_3_head_142 |
| IoULoss replace origin txtytwth loss | 0.558 | log_myYOLOWithFPNMultiPredWithIoULoss_iouweight10_yolo_160 |
| 添加中心点距离最近的target assign机制，避免按label顺序匹配gt object对应的特征点，IoULoss replace origin txtytwth loss | 0.571 | log_myYOLOWithFPNMultiPredWithIoULoss_iouweight10_targetassian_by_min_dist_yolo_160 |
GIoULoss
| Model | mAP(07test) | LogFile |
|---|---|---|
| FPN/MultiHeadFPN | 0.7149 | eval_log/log_eval_myYOLOWithFPNMultiPred_with_sam_for_3_head_142 |
| GIoULoss replace origin txtytwth loss | 0.6674 | log_myYOLOWithFPNMultiPredWithGIoULoss_SGD_iouweight1_tvgiouloss_sum_target_assign_by_min_dist_yolo_130 |
DIoULoss
CIoULoss
SIoULoss
EIoULoss
Luxury IoU Loss:
| condition | mAP |
| txtytwth_iou_weightsum_loss = txtytwth_loss + giou_loss * 1 |