yolov5 gnconv yaml文件

以下是Yolov5中使用GNConv的示例yaml文件：

# Parameters
nc: 80  # number of classes
depth_multiple: 1.0  # model depth multiple
width_multiple: 1.0  # layer channel multiple

# Anchors
anchors:
  - [10,13, 16,30, 33,23]  # P3/8
  - [30,61, 62,45, 59,119]  # P4/16
  - [116,90, 156,198, 373,326]  # P5/32

# Model
backbone:
  # GNConv(3x3, 32, stride=2, groups=32, use_deform=True)
  - ['conv', 32, 3, 2, 'same', 'gn', 32, 'relu', True]
  # GNConv(3x3, 64, stride=2, groups=32, use_deform=True)
  - ['conv', 64, 3, 2, 'same', 'gn', 32, 'relu', True]
  # GNConv(3x3, 64, stride=1, groups=32, use_deform=True)
  - ['conv', 64, 3, 1, 'same', 'gn', 32, 'relu', True]

# Head
head:
  # GNConv(1x1, 128, groups=32, use_deform=True)
  - ['conv', 128, 1, 1, 'same', 'gn', 32, 'relu', True]
  - ['upsample', 'nearest']
  # GNConv(3x3, 128, groups=32, use_deform=True)
  - ['conv', 128, 3, 1, 'same', 'gn', 32, 'relu', True]
  # GNConv(1x1, 3*(nc+5), groups=32, use_deform=True)
  - ['conv', 3 * (nc + 5), 1, 1, 'same', 'gn', 32, '', True]

在这个示例中，GNConv被用作YoloV5的卷积层。 GNConv的参数包括卷积核大小，输出通道数，步幅，填充模式，分组数，激活函数类型和是否使用deformable convolution。