|
|
@@ -10,7 +10,7 @@
|
|
|
|
|
|
| Model | Batch | Scale | AP<sup>val<br>0.5:0.95 | AP<sup>val<br>0.5 | FLOPs<br><sup>(G) | Params<br><sup>(M) | Weight | Logs |
|
|
|
|-------------|-------|-------|------------------------|-------------------|-------------------|--------------------|--------|--------|
|
|
|
-| YOLOv5-AF-S | 1xb16 | 640 | | | 26.9 | 8.9 | | |
|
|
|
+| YOLOv5-AF-S | 1xb16 | 640 | 39.6 | 58.7 | 26.9 | 8.9 | [ckpt](https://github.com/yjh0410/YOLO-Tutorial-v5/releases/download/yolo_tutorial_ckpt/yolov5_af_s_coco.pth) | [log](https://github.com/yjh0410/YOLO-Tutorial-v5/releases/download/yolo_tutorial_ckpt/YOLOv5-AF-S-COCO.txt) |
|
|
|
|
|
|
- For training, we train redesigned YOLOv5-AF with 300 epochs on COCO. We also use the gradient accumulation.
|
|
|
- For data augmentation, we use the RandomAffine, RandomHSV, Mosaic and YOLOX's Mixup augmentation.
|