fix bugs

config/yolov3_config.py

@@ -21,7 +21,6 @@ class Yolov3BaseConfig(object):
         self.bk_act   = 'silu'
         self.bk_norm  = 'BN'
         self.bk_depthwise = False
-        self.use_pretrained = False
         ## Neck
         self.neck_act       = 'silu'
         self.neck_norm      = 'BN'
@@ -123,7 +122,6 @@ class Yolov3SConfig(Yolov3BaseConfig):
         self.width = 0.50
         self.depth = 0.34
         self.scale = "s"
-        self.use_pretrained = True
 
         # ---------------- Data process config ----------------
         self.mosaic_prob = 1.0

config/yolov4_config.py

@@ -21,7 +21,6 @@ class Yolov4BaseConfig(object):
         self.bk_act   = 'silu'
         self.bk_norm  = 'BN'
         self.bk_depthwise = False
-        self.use_pretrained = False
         ## Neck
         self.neck_act       = 'silu'
         self.neck_norm      = 'BN'
@@ -123,7 +122,6 @@ class Yolov4SConfig(Yolov4BaseConfig):
         self.width = 0.50
         self.depth = 0.34
         self.scale = "s"
-        self.use_pretrained = True
 
         # ---------------- Data process config ----------------
         self.mosaic_prob = 1.0

models/yolov3/yolov3_head.py

@@ -97,8 +97,8 @@ class Yolov3DetHead(nn.Module):
         ## ----------- Network Parameters -----------
         self.multi_level_heads = nn.ModuleList(
             [DetHead(in_dim       = in_dims[level],
-                     cls_head_dim = cfg.head_dim,
-                     reg_head_dim = cfg.head_dim,
+                     cls_head_dim = round(cfg.head_dim * cfg.width),
+                     reg_head_dim = round(cfg.head_dim * cfg.width),
                      num_cls_head = cfg.num_cls_head,
                      num_reg_head = cfg.num_reg_head,
                      act_type     = cfg.head_act,

models/yolov3/yolov3_pred.py

@@ -117,8 +117,8 @@ class Yolov3DetPredLayer(nn.Module):
         # ----------- Network Parameters -----------
         ## pred layers
         self.multi_level_preds = nn.ModuleList(
-            [DetPredLayer(cls_dim      = cfg.head_dim,
-                          reg_dim      = cfg.head_dim,
+            [DetPredLayer(cls_dim      = round(cfg.head_dim * cfg.width),
+                          reg_dim      = round(cfg.head_dim * cfg.width),
                           stride       = cfg.out_stride[level],
                           anchor_sizes = cfg.anchor_size[level],
                           num_classes  = cfg.num_classes,)

models/yolov4/yolov4_head.py

@@ -97,8 +97,8 @@ class Yolov4DetHead(nn.Module):
         ## ----------- Network Parameters -----------
         self.multi_level_heads = nn.ModuleList(
             [DetHead(in_dim       = in_dims[level],
-                     cls_head_dim = cfg.head_dim,
-                     reg_head_dim = cfg.head_dim,
+                     cls_head_dim = round(cfg.head_dim * cfg.width),
+                     reg_head_dim = round(cfg.head_dim * cfg.width),
                      num_cls_head = cfg.num_cls_head,
                      num_reg_head = cfg.num_reg_head,
                      act_type     = cfg.head_act,

models/yolov4/yolov4_pred.py

@@ -118,8 +118,8 @@ class Yolov4DetPredLayer(nn.Module):
         # ----------- Network Parameters -----------
         ## pred layers
         self.multi_level_preds = nn.ModuleList(
-            [DetPredLayer(cls_dim      = cfg.head_dim,
-                          reg_dim      = cfg.head_dim,
+            [DetPredLayer(cls_dim      = round(cfg.head_dim * cfg.width),
+                          reg_dim      = round(cfg.head_dim * cfg.width),
                           stride       = cfg.out_stride[level],
                           anchor_sizes = cfg.anchor_size[level],
                           num_classes  = cfg.num_classes,)