update

yolo/models/yolov8/yolov8_backbone.py

@@ -126,10 +126,10 @@ if __name__ == '__main__':
     class BaseConfig(object):
         def __init__(self) -> None:
             self.use_pretrained = True
-            self.width = 0.50
+            self.width = 0.25
             self.depth = 0.34
             self.ratio = 2.0
-            self.model_scale = "s"
+            self.model_scale = "n"
 
     cfg = BaseConfig()
     model = Yolov8Backbone(cfg)

yolo/models/yolov8/yolov8_head.py

@@ -105,7 +105,7 @@ if __name__=='__main__':
     class Yolov8BaseConfig(object):
         def __init__(self) -> None:
             # ---------------- Model config ----------------
-            self.width    = 0.50
+            self.width    = 0.25
             self.depth    = 0.34
             self.ratio    = 2.0
             self.reg_max  = 16
@@ -117,10 +117,10 @@ if __name__=='__main__':
             self.num_reg_head = 2
 
     cfg = Yolov8BaseConfig()
-    cfg.num_classes = 20
+    cfg.num_classes = 80
 
     # Build a head
-    fpn_dims = [128, 256, 512]
+    fpn_dims = [64, 128, 256]
     pyramid_feats = [torch.randn(1, fpn_dims[0], 80, 80),
                      torch.randn(1, fpn_dims[1], 40, 40),
                      torch.randn(1, fpn_dims[2], 20, 20)]

yolo/models/yolov8/yolov8_neck.py

@@ -44,8 +44,8 @@ if __name__=='__main__':
     from thop import profile
     
     # Build a head
-    in_dim  = 512
-    out_dim = 512
+    in_dim  = 256
+    out_dim = 256
     neck = SPPF(in_dim, out_dim)
 
     # Inference

yolo/models/yolov8/yolov8_pafpn.py

@@ -93,7 +93,7 @@ if __name__=='__main__':
     class Yolov8BaseConfig(object):
         def __init__(self) -> None:
             # ---------------- Model config ----------------
-            self.width    = 0.50
+            self.width    = 0.25
             self.depth    = 0.34
             self.ratio    = 2.0
             self.out_stride = [8, 16, 32]
@@ -104,7 +104,7 @@ if __name__=='__main__':
 
     cfg = Yolov8BaseConfig()
     # Build a head
-    in_dims  = [128, 256, 512]
+    in_dims  = [64, 128, 256]
     fpn = Yolov8PaFPN(cfg, in_dims)
 
     # Inference

yolo/models/yolov8/yolov8_pred.py

@@ -162,9 +162,9 @@ if __name__=='__main__':
     class Yolov8BaseConfig(object):
         def __init__(self) -> None:
             # ---------------- Model config ----------------
-            self.width    = 1.0
-            self.depth    = 1.0
-            self.ratio    = 1.0
+            self.width    = 0.25
+            self.depth    = 0.34
+            self.ratio    = 2.0
             self.reg_max  = 16
             self.out_stride = [8, 16, 32]
             self.max_stride = 32
@@ -172,8 +172,8 @@ if __name__=='__main__':
             ## Head
 
     cfg = Yolov8BaseConfig()
-    cfg.num_classes = 20
-    cls_dim = 128
+    cfg.num_classes = 80
+    cls_dim = 80
     reg_dim = 64
     # Build a pred layer
     pred = Yolov8DetPredLayer(cfg, cls_dim, reg_dim)