扫码新算法更新

dll/model/detect-tiny.cfg

+[net]
+# Testing
+batch=1
+subdivisions=1
+# Training
+# batch=64
+# subdivisions=64
+width=960
+height=960
+channels=3
+momentum=0.9
+decay=0.0005
+angle=180
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.001
+burn_in=1000
+max_batches = 4000
+policy=steps
+steps=3200,3600
+scales=.1,.1
+
+[convolutional]
+batch_normalize=1
+filters=16
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=1
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+###########
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=18
+activation=linear
+
+
+
+[yolo]
+mask = 3,4,5
+anchors = 10,14,  23,27,  37,58,  81,82,  135,169,  344,319
+classes=1
+num=6
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = -1, 8
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=18
+activation=linear
+
+[yolo]
+mask = 0,1,2
+anchors = 10,14,  23,27,  37,58,  81,82,  135,169,  344,319
+classes=1
+num=6
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1

dll/model/sr.prototxt

+layer {
+  name: "data"
+  type: "Input"
+  top: "data"
+  input_param {
+    shape {
+      dim: 1
+      dim: 1
+      dim: 224
+      dim: 224
+    }
+  }
+}
+layer {
+  name: "conv0"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv0"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "conv0/lrelu"
+  type: "ReLU"
+  bottom: "conv0"
+  top: "conv0"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/reduce"
+  type: "Convolution"
+  bottom: "conv0"
+  top: "db1/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/reduce/lrelu"
+  type: "ReLU"
+  bottom: "db1/reduce"
+  top: "db1/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/3x3"
+  type: "Convolution"
+  bottom: "db1/reduce"
+  top: "db1/3x3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 8
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/3x3/lrelu"
+  type: "ReLU"
+  bottom: "db1/3x3"
+  top: "db1/3x3"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/1x1"
+  type: "Convolution"
+  bottom: "db1/3x3"
+  top: "db1/1x1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/1x1/lrelu"
+  type: "ReLU"
+  bottom: "db1/1x1"
+  top: "db1/1x1"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/concat"
+  type: "Concat"
+  bottom: "conv0"
+  bottom: "db1/1x1"
+  top: "db1/concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "db2/reduce"
+  type: "Convolution"
+  bottom: "db1/concat"
+  top: "db2/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/reduce/lrelu"
+  type: "ReLU"
+  bottom: "db2/reduce"
+  top: "db2/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/3x3"
+  type: "Convolution"
+  bottom: "db2/reduce"
+  top: "db2/3x3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 8
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/3x3/lrelu"
+  type: "ReLU"
+  bottom: "db2/3x3"
+  top: "db2/3x3"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/1x1"
+  type: "Convolution"
+  bottom: "db2/3x3"
+  top: "db2/1x1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/1x1/lrelu"
+  type: "ReLU"
+  bottom: "db2/1x1"
+  top: "db2/1x1"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/concat"
+  type: "Concat"
+  bottom: "db1/concat"
+  bottom: "db2/1x1"
+  top: "db2/concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "upsample/reduce"
+  type: "Convolution"
+  bottom: "db2/concat"
+  top: "upsample/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "upsample/reduce/lrelu"
+  type: "ReLU"
+  bottom: "upsample/reduce"
+  top: "upsample/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "upsample/deconv"
+  type: "Deconvolution"
+  bottom: "upsample/reduce"
+  top: "upsample/deconv"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 32
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "upsample/lrelu"
+  type: "ReLU"
+  bottom: "upsample/deconv"
+  top: "upsample/deconv"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "upsample/rec"
+  type: "Convolution"
+  bottom: "upsample/deconv"
+  top: "upsample/rec"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "nearest"
+  type: "Deconvolution"
+  bottom: "data"
+  top: "nearest"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1
+    bias_term: false
+    pad: 0
+    kernel_size: 2
+    group: 1
+    stride: 2
+    weight_filler {
+      type: "constant"
+      value: 1.0
+    }
+  }
+}
+layer {
+  name: "Crop1"
+  type: "Crop"
+  bottom: "nearest"
+  bottom: "upsample/rec"
+  top: "Crop1"
+}
+layer {
+  name: "fc"
+  type: "Eltwise"
+  bottom: "Crop1"
+  bottom: "upsample/rec"
+  top: "fc"
+  eltwise_param {
+    operation: SUM
+  }
+}

source/AssemblyLineClient/AssemblyLineClient.csproj

@@ -234,6 +234,18 @@
       <DependentUpon>Resources.resx</DependentUpon>
       <DesignTime>True</DesignTime>
     </Compile>
+    <Content Include="model\detect-tiny.cfg">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </Content>
+    <Content Include="model\detect-tiny.weights">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </Content>
+    <Content Include="model\sr.caffemodel">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </Content>
+    <Content Include="model\sr.prototxt">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </Content>
     <None Include="Properties\Settings.settings">
       <Generator>SettingsSingleFileGenerator</Generator>
       <LastGenOutput>Settings.Designer.cs</LastGenOutput>

source/AssemblyLineClient/FrmLineStore.cs

@@ -312,13 +312,14 @@ namespace OnlineStore.AssemblyLine
                     }
                     // CodeManager.CloseAllCamera();
                     //   RFIDManager.Close();
-                    System.Environment.Exit(System.Environment.ExitCode);
+                    //System.Environment.Exit(System.Environment.ExitCode);  
+                    System.Diagnostics.Process.GetCurrentProcess().Kill();
                 }
                 catch (Exception ex)
                 {
                     LogUtil.error("退出出错：", ex);
                 }
-                //this.Close();
+                this.Close();
             }
         }
         private void 显示ToolStripMenuItem_Click(object sender, EventArgs e)

source/AssemblyLineClient/model/detect-tiny.cfg

+[net]
+# Testing
+batch=1
+subdivisions=1
+# Training
+# batch=64
+# subdivisions=64
+width=960
+height=960
+channels=3
+momentum=0.9
+decay=0.0005
+angle=180
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.001
+burn_in=1000
+max_batches = 4000
+policy=steps
+steps=3200,3600
+scales=.1,.1
+
+[convolutional]
+batch_normalize=1
+filters=16
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=1
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=1
+pad=1
+activation=leaky
+
+###########
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=18
+activation=linear
+
+
+
+[yolo]
+mask = 3,4,5
+anchors = 10,14,  23,27,  37,58,  81,82,  135,169,  344,319
+classes=1
+num=6
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = -1, 8
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=18
+activation=linear
+
+[yolo]
+mask = 0,1,2
+anchors = 10,14,  23,27,  37,58,  81,82,  135,169,  344,319
+classes=1
+num=6
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1

source/AssemblyLineClient/model/sr.prototxt

+layer {
+  name: "data"
+  type: "Input"
+  top: "data"
+  input_param {
+    shape {
+      dim: 1
+      dim: 1
+      dim: 224
+      dim: 224
+    }
+  }
+}
+layer {
+  name: "conv0"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv0"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "conv0/lrelu"
+  type: "ReLU"
+  bottom: "conv0"
+  top: "conv0"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/reduce"
+  type: "Convolution"
+  bottom: "conv0"
+  top: "db1/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/reduce/lrelu"
+  type: "ReLU"
+  bottom: "db1/reduce"
+  top: "db1/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/3x3"
+  type: "Convolution"
+  bottom: "db1/reduce"
+  top: "db1/3x3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 8
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/3x3/lrelu"
+  type: "ReLU"
+  bottom: "db1/3x3"
+  top: "db1/3x3"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/1x1"
+  type: "Convolution"
+  bottom: "db1/3x3"
+  top: "db1/1x1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/1x1/lrelu"
+  type: "ReLU"
+  bottom: "db1/1x1"
+  top: "db1/1x1"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/concat"
+  type: "Concat"
+  bottom: "conv0"
+  bottom: "db1/1x1"
+  top: "db1/concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "db2/reduce"
+  type: "Convolution"
+  bottom: "db1/concat"
+  top: "db2/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/reduce/lrelu"
+  type: "ReLU"
+  bottom: "db2/reduce"
+  top: "db2/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/3x3"
+  type: "Convolution"
+  bottom: "db2/reduce"
+  top: "db2/3x3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 8
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/3x3/lrelu"
+  type: "ReLU"
+  bottom: "db2/3x3"
+  top: "db2/3x3"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/1x1"
+  type: "Convolution"
+  bottom: "db2/3x3"
+  top: "db2/1x1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/1x1/lrelu"
+  type: "ReLU"
+  bottom: "db2/1x1"
+  top: "db2/1x1"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/concat"
+  type: "Concat"
+  bottom: "db1/concat"
+  bottom: "db2/1x1"
+  top: "db2/concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "upsample/reduce"
+  type: "Convolution"
+  bottom: "db2/concat"
+  top: "upsample/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "upsample/reduce/lrelu"
+  type: "ReLU"
+  bottom: "upsample/reduce"
+  top: "upsample/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "upsample/deconv"
+  type: "Deconvolution"
+  bottom: "upsample/reduce"
+  top: "upsample/deconv"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 32
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "upsample/lrelu"
+  type: "ReLU"
+  bottom: "upsample/deconv"
+  top: "upsample/deconv"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "upsample/rec"
+  type: "Convolution"
+  bottom: "upsample/deconv"
+  top: "upsample/rec"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "nearest"
+  type: "Deconvolution"
+  bottom: "data"
+  top: "nearest"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1
+    bias_term: false
+    pad: 0
+    kernel_size: 2
+    group: 1
+    stride: 2
+    weight_filler {
+      type: "constant"
+      value: 1.0
+    }
+  }
+}
+layer {
+  name: "Crop1"
+  type: "Crop"
+  bottom: "nearest"
+  bottom: "upsample/rec"
+  top: "Crop1"
+}
+layer {
+  name: "fc"
+  type: "Eltwise"
+  bottom: "Crop1"
+  bottom: "upsample/rec"
+  top: "fc"
+  eltwise_param {
+    operation: SUM
+  }
+}

source/DeviceLibrary/DeviceLibrary.csproj

@@ -125,12 +125,18 @@
     <Content Include="halcon.dll">
       <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
     </Content>
+    <Content Include="libdecode.dll">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </Content>
     <Content Include="libdmtx.dll">
       <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
     </Content>
     <Content Include="opencv_world420.dll">
       <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
     </Content>
+    <Content Include="tbb.dll">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </Content>
     <Content Include="zxing.dll">
       <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
     </Content>

source/DeviceLibrary/assemblyLine/FeedingEquip_InStore.cs

@@ -1323,8 +1323,10 @@ namespace OnlineStore.DeviceLibrary
             BatchAxis.AbsMove(MoveInfo, targetPosition, Config.BatchAxis_P4Speed);
         }
 
+        private Task YuScanTask = null;
         private void YuScanCode()
         {
+            YuScanTask = null;
             bool isScan = ConfigAppSettings.GetIntValue(Setting_Init.NeedScanCode).Equals(1);
             //TODO 此处需要等待空托盘 
             if (MoveInfo.ShelfNoTray.Equals(false) && isScan)
@@ -1335,7 +1337,7 @@ namespace OnlineStore.DeviceLibrary
                 List<string> bijiaoList = new List<string>(LastCodeList);
                 try
                 {
-                    Task<List<string>> scanTask = Task.Factory.StartNew(delegate
+                    YuScanTask = Task.Factory.StartNew(delegate
                     {
                         Thread.Sleep(100);
                         NextCodeList = CodeManager.CameraScan(Config.GetCameraList(), Name.Trim()+"预扫码");
@@ -1391,6 +1393,9 @@ namespace OnlineStore.DeviceLibrary
         {
             if (CylinderIsOk(IO_Type.SL_MoveCylinder_Take, IO_Type.SL_MoveCylinder_Give))
             {
+                if (YuScanTask == null || YuScanTask.IsCompleted)
+                {
+                    ClearTimeoutAlarm("预扫码结束超时");
                     MoveInfo.NextMoveStep(LineMoveStep.FI_13_ScanCode);
                     bool isScan = ConfigAppSettings.GetIntValue(Setting_Init.NeedScanCode).Equals(1);
 
@@ -1440,6 +1445,13 @@ namespace OnlineStore.DeviceLibrary
                         InLog("料盘移栽" + MoveInfo.SLog + "：不需要扫码");
                     } 
                 }
+                else if (MoveInfo.IsTimeOut(60))
+                {
+                    WarnMsg = SecondMoveInfo.Name + "[" + SecondMoveInfo.MoveStep + "] 等待预扫码结束超时 [" + Math.Round(MoveInfo.StepSpan().TotalSeconds, 1) + "]秒";
+                    LogUtil.error(WarnMsg, DeviceID * 1000 + 21);
+                    Alarm(LineAlarmType.IoSingleTimeOut);
+                }
+            }
             else
             {
                 FI_12_MoveCylinder_Give();

source/DeviceLibrary/deviceLibrary/halcon/CodeManager.cs

@@ -45,6 +45,7 @@ namespace OnlineStore.DeviceLibrary
 
                 LoadCamera(false);
                 CodeLibrary.HDCodeLearnHelper.LoadConfig("", codeStr);
+                CodeLibrary.EyemDecode.InitModel();
             }
             catch (Exception ex)
             {
@@ -139,8 +140,9 @@ namespace OnlineStore.DeviceLibrary
 
                         string r = "";
 
-                        List<CodeInfo> tlci = EyemDecode.Decoder(ref bmp);
                         bool eyemNoCode = false;
+                        Task eyemtask = Task.Factory.StartNew(delegate {
+                            List<CodeInfo> tlci = EyemDecode.ModelDecoder(ref bmp);
                             foreach (CodeInfo code in tlci)
                             {
                                 LogUtil.info(deviceName + "  【" + cameraName + "】[eyemDecode]" + code.CodeType + "(X: " + code.X + "，Y: " + code.Y + ") " + code.CodeStr);
@@ -155,7 +157,17 @@ namespace OnlineStore.DeviceLibrary
                                     }
                                 }
                             }
-                        if (!findRightCode &&(!isPreScan))
+                        });
+                        //最多等待60秒
+                        bool taskResult = eyemtask.Wait(60000);
+                        if (!taskResult)
+                        {
+                            LogUtil.error(deviceName + "  【" + cameraName + "】eyem扫码超时");
+                            eyemNoCode = true;
+                        }
+                        if (!isPreScan)
+                        {
+                            if (!findRightCode)
                             {
                                 List<CodeInfo> cc = new List<CodeInfo>();
                                 eyemNoCode = true;
@@ -202,6 +214,7 @@ namespace OnlineStore.DeviceLibrary
 
                                 SaveImageToFile(deviceName, cameraName + nameStr, bmp);
                             }
+                        }
                         if (deviceName != "" || r != "")
                         {
                             LogUtil.info(deviceName + " 【" + cameraName + "】扫码完成【" + FormUtil.GetSpanStr(DateTime.Now - startTime) + "】[" + findRightCode + "]" + ScanCount + " ：" + r);
@@ -267,7 +280,7 @@ namespace OnlineStore.DeviceLibrary
         }
         private static void SaveImageToFile(string deviceName, string cameraName, Bitmap bitmap)
         {
-            string date = deviceName.Trim().Replace('_', '-') +"-"+ DateTime.Now.ToString("HH-mm-ss-") + DateTime.Now.Millisecond;
+            string date = deviceName.Trim().Replace('_', '-') +"-"+ DateTime.Now.ToString("yyyyMMdd-HHmmss") + DateTime.Now.Millisecond;
             string dire = @"D:\image\" + deviceName.Trim().Replace('_', '-') + @"\" + cameraName.Trim().Replace('_', '-').Replace(':', '-') + @"\";
             string iamgeName = date + ".bmp";
             try