更新特征层大小的说明

Egrt · Feb 17, 2023 · d75036f · d75036f
1 parent 511cb53
commit d75036f
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Showing 2 changed files with 8 additions and 5 deletions.
diff --git a/nets/backbone.py b/nets/backbone.py
@@ -60,21 +60,24 @@ def __init__(self, transition_channels, block_channels, n, pretrained=False):
         #   输入图片是640, 640, 3
         #-----------------------------------------------#
         ids = [-1, -2, -3, -4]
-
+        # 640, 640, 3 => 320, 320, 64
         self.stem = Conv(3, transition_channels * 2, 3, 2)
-
+        # 320, 320, 64 => 160, 160, 128 => 160, 160, 128
         self.dark2 = nn.Sequential(
             Conv(transition_channels * 2, transition_channels * 4, 3, 2),
             Multi_Concat_Block(transition_channels * 4, block_channels * 2, transition_channels * 4, n=n, ids=ids),
         )
+        # 160, 160, 128 => 80, 80, 128 => 80, 80, 256
         self.dark3 = nn.Sequential(
             MP(),
             Multi_Concat_Block(transition_channels * 4, block_channels * 4, transition_channels * 8, n=n, ids=ids),
         )
+        # 80, 80, 256 => 40, 40, 256 => 40, 40, 512
         self.dark4 = nn.Sequential(
             MP(),
             Multi_Concat_Block(transition_channels * 8, block_channels * 8, transition_channels * 16, n=n, ids=ids),
         )
+        # 40, 40, 512 => 20, 20, 512 => 20, 20, 1024
         self.dark5 = nn.Sequential(
             MP(),
             Multi_Concat_Block(transition_channels * 16, block_channels * 16, transition_channels * 32, n=n, ids=ids),

diff --git a/nets/yolo.py b/nets/yolo.py
@@ -129,17 +129,17 @@ def forward(self, x):
         P5 = self.rep_conv_3(P5)
         #---------------------------------------------------#
         #   第三个特征层
-        #   y3=(batch_size, 75, 80, 80)
+        #   y3=(batch_size, 78, 80, 80)
         #---------------------------------------------------#
         out2 = self.yolo_head_P3(P3)
         #---------------------------------------------------#
         #   第二个特征层
-        #   y2=(batch_size, 75, 40, 40)
+        #   y2=(batch_size, 78, 40, 40)
         #---------------------------------------------------#
         out1 = self.yolo_head_P4(P4)
         #---------------------------------------------------#
         #   第一个特征层
-        #   y1=(batch_size, 75, 20, 20)
+        #   y1=(batch_size, 78, 20, 20)
         #---------------------------------------------------#
         out0 = self.yolo_head_P5(P5)