第一步:确定添加的位置,作为即插即用的注意力模块,可以添加到YOLOv5网络中的任何地方。 第二步:common.py构建 Eca_layer模块。 class Eca_layer(nn.Module): """Constructs a ECA module. Args: channel: Number of channels of the input feature map k_size: Adaptive selection of kernel size """ def...
加入G-ECA Layer结构能够使模型更为准确地捕捉适合于水稻病虫害识别的特征信息,从而使GE-DenseNet模型能够实现对不同水稻病虫害图像更为准确地识别,为及时防治病虫害,减少各类损失提供技术支持。 水稻生长过程中,可能会受到各种病虫害的影响,从而导致产量下降。因此,加强病虫害防治也是增加水稻粒重的重要手段之一。可以采...
具体实现步骤如下：1. 确定ECA注意力模块的添加位置，作为即插即用组件，适配YOLOv5网络中任意部分。2. 在common.py文件中构建Eca_layer模块。3. 将Eca_layer模块注册至yolo.py文件中。4. 修改yaml配置文件，以backbone模块为例，在C3模块之后加入ECA注意力层。5. 修改train.py文件，采用本文的yaml配...
核心代码 importtorchfromtorchimportnnfromtorch.nn.parameterimportParameterclasseca_layer(nn.Module):"""构建一个ECA模块。 Args: channel: 输入特征图的通道数 k_size: 自适应选择的卷积核大小 """def__init__(self, channel, k_size=3):super(eca_layer,self).__init__()self.avg_pool = nn.Adaptiv...
eca_layer_ (Conv1D) (None,512,1)5reshape_1[0][0] ___ activation_1 (Activation) (None,512,1)0eca_layer_[0][0] ___ reshape_
May 6, 2020 models cleanup eca layer May 16, 2021 .gitignore update eca_ns Oct 12, 2020 LICENSE BangguWu Sep 16, 2019 README.md Upload the poster. May 6, 2020 light_main.py first commit Sep 15, 2019 main.py first commit Sep 15, 2019 paras_flops.py first commit Sep 15, 2019 ...
#eca_layer import paddle import paddle.nn as nn class eca_layer(paddle.nn.Layer): """ 构建ECA模块 参数: channel :输入特征图的通道数 k_size :自适应卷积核的大小 """ def __init__(self,channel=1,k_size=3): super(eca_layer,self).__init__() self.avg_pool = nn.AdaptiveAvgPool2D...
class AlexNet_ECA(nn.Layer): def __init__(self,num_classes=10): super().__init__() self.features=nn.Sequential( nn.Conv2D(3,48, kernel_size=11, stride=4, padding=11//2), ECA(3), nn.ReLU(), nn.MaxPool2D(kernel_size=3,stride=2), nn.Conv2D(48,128, kernel_size=5, paddi...
self.eca = eca_layer(outplanes) if use_eca else None self.act2 = act_layer(inplace=True) self.downsample = downsample self.stride = stride @@ -167,6 +175,8 @@ def forward(self, x): if self.se is not None: out = self.se(out) if self.eca is not None: out = self.eca(...
classMCALayer(nn.Module):def__init__(self,inp,no_spatial=True):"""Constructs aMCAmodule.Args:inp:Numberofchannelsofthe input feature mapsno_spatial:whether to build channel dimension interactions"""super(MCALayer,self).__init__()lambd=1.5gamma=1temp=round(abs((math.log2(inp)-gamma)/lamb...