|
|
@@ -145,8 +145,8 @@ python train.py --cuda -d coco --root path/to/COCO -m yolov1 -bs 16 --max_epoch
|
|
|
|----------|-------|-------|-------------------------|--------------------|------------------------|-------------------|-------------------|--------------------|--------|
|
|
|
| YOLOvx-N | 640 | 4xb32 | | | | | 9.1 | 2.4 | |
|
|
|
| YOLOvx-T | 640 | 4xb32 | | | | | 18.9 | 5.1 | |
|
|
|
-| YOLOvx-S | 640 | 4xb32 | | | | | 33.6 | 9.0 | |
|
|
|
-| YOLOvx-M | 640 | 8xb16 | | | | | 87.4 | 23.6 | |
|
|
|
+| YOLOvx-S | 640 | 8xb16 | | | | | 33.6 | 9.0 | |
|
|
|
+| YOLOvx-M | 640 | 8xb16 | 48.3 | 67.0 | 48.1 | 66.9 | 87.4 | 23.6 | [ckpt](https://github.com/yjh0410/PyTorch_YOLO_Tutorial/releases/download/yolo_tutorial_ckpt/yolovx_m_coco.pth) |
|
|
|
| YOLOvx-L | 640 | 8xb16 | 50.2 | 68.6 | 50.0 | 68.4 | 176.6 | 47.6 | [ckpt](https://github.com/yjh0410/PyTorch_YOLO_Tutorial/releases/download/yolo_tutorial_ckpt/yolovx_l_coco.pth) |
|
|
|
| YOLOvx-X | 640 | | | | | | | | |
|
|
|
|
|
|
@@ -156,12 +156,12 @@ python train.py --cuda -d coco --root path/to/COCO -m yolov1 -bs 16 --max_epoch
|
|
|
|
|
|
#### LODet: An Empirical Study of Designing Lightweight Object Detector
|
|
|
|
|
|
-| Model | Scale | AP<sup>test<br>0.5:0.95 | AP<sup>test<br>0.5 | AP<sup>val<br>0.5:0.95 | AP<sup>val<br>0.5 | FLOPs<br><sup>(G) | Params<br><sup>(M) | Weight |
|
|
|
-|-------|-------|-------------------------|--------------------|------------------------|-------------------|-------------------|--------------------|--------|
|
|
|
-| LODet | 320 | | | | | 1.05 | 1.20 | |
|
|
|
-| LODet | 416 | | | | | 1.78 | 1.20 | |
|
|
|
-| LODet | 512 | | | | | 2.70 | 1.20 | |
|
|
|
-| LODet | 640 | | | | | 4.21 | 1.20 | |
|
|
|
+| Model | Scale | AP<sup>val<br>0.5:0.95 | AP<sup>val<br>0.5 | FLOPs<br><sup>(G) | Params<br><sup>(M) | Weight |
|
|
|
+|-------|-------|------------------------|-------------------|-------------------|--------------------|--------|
|
|
|
+| LODet | 320 | | | 1.05 | 1.20 | |
|
|
|
+| LODet | 416 | | | 1.78 | 1.20 | |
|
|
|
+| LODet | 512 | | | 2.70 | 1.20 | |
|
|
|
+| LODet | 640 | | | 4.21 | 1.20 | |
|
|
|
|
|
|
#### Redesigned RT-DETR:
|
|
|
|
yjh0410