train YOLOv5-S

README.md

@@ -122,7 +122,7 @@ python train.py --cuda -d coco --root path/to/COCO -v yolov1 -bs 16 --max_epoch
 
 | Model         |   Backbone         | Scale | Epoch |  FPS  | AP<sup>val<br>0.5:0.95 | AP<sup>val<br>0.5 | FLOPs<br><sup>(G) | Params<br><sup>(M) | Weight |
 |---------------|--------------------|-------|-------|-------|------------------------|-------------------|-------------------|--------------------|--------|
-| YOLOv5-N      | CSPDarkNet-N       |  640  |  250  |       |                        |                   |   7.7             |   2.4              |  |
+| YOLOv5-N      | CSPDarkNet-N       |  640  |  250  |       |         29.8           |       47.1        |   7.7             |   2.4              |  |
 | YOLOv5-S      | CSPDarkNet-S       |  640  |  250  |       |                        |                   |   27.1            |   9.0              |  |
 | YOLOv5-M      | CSPDarkNet-M       |  640  |  250  |       |                        |                   |   74.3            |   25.4             |  |
 | YOLOv5-L      | CSPDarkNet-L       |  640  |  250  |       |         46.7           |       65.5        |   155.6           |   54.2             | [ckpt](https://github.com/yjh0410/PyTorch_YOLO_Tutorial/releases/download/yolo_tutorial_ckpt/yolov5_l_coco.pth) |

config/yolov7_config.py

@@ -4,7 +4,7 @@ yolov7_cfg = {
     'yolov7_t':{
         # input
         'trans_type': 'yolov5_tiny',
-        'multi_scale': [0.5, 1.5], # 320 -> 640
+        'multi_scale': [0.5, 1.5], # 320 -> 960
         # model
         'backbone': 'elannet_tiny',
         'pretrained': True,
@@ -62,7 +62,7 @@ yolov7_cfg = {
     'yolov7_l':{
         # input
         'trans_type': 'yolov5_large',
-        'multi_scale': [0.5, 1.25], # 320 -> 640
+        'multi_scale': [0.5, 1.25], # 320 -> 800
         # model
         'backbone': 'elannet_large',
         'pretrained': True,

train.sh

@@ -3,7 +3,7 @@ python train.py \
         --cuda \
         -d coco \
         --root /mnt/share/ssd2/dataset/ \
-        -m yolov4_t \
+        -m yolov5_s \
         -bs 16 \
         -size 640 \
         --wp_epoch 1 \