扫码算法更新

dll/model/detect-tiny.cfg

+[net]
+# Testing
+batch=1
+subdivisions=1
+# Training
+# batch=64
+# subdivisions=64
+width=608
+height=608
+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=21
+activation=linear
+
+
+
+[yolo]
+mask = 3,4,5
+anchors = 10,14,  23,27,  37,58,  81,82,  135,169,  344,319
+classes=2
+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=21
+activation=linear
+
+[yolo]
+mask = 0,1,2
+anchors = 10,14,  23,27,  37,58,  81,82,  135,169,  344,319
+classes=2
+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

@@ -214,6 +214,18 @@
     <EmbeddedResource Include="useControl\EquipControl.resx">
       <DependentUpon>EquipControl.cs</DependentUpon>
     </EmbeddedResource>
+    <None Include="model\detect-tiny.cfg">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Include="model\detect-tiny.weights">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Include="model\sr.caffemodel">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Include="model\sr.prototxt">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
     <None Include="Properties\Settings.settings">
       <Generator>SettingsSingleFileGenerator</Generator>
       <LastGenOutput>Settings.Designer.cs</LastGenOutput>

source/AssemblyLineClient/FrmLineStore.cs

@@ -223,8 +223,11 @@ namespace OnlineStore.AssemblyLine
                     if (Camera._cam != null)
                     {
                         Camera._cam.CloseAll();
-                    } 
-                    System.Environment.Exit(System.Environment.ExitCode);
+                    }
+                 
+                    //System.Environment.Exit(System.Environment.ExitCode);
+                    System.Diagnostics.Process.GetCurrentProcess().Kill();
+                    this.Close();
                 }
                 catch (Exception ex)
                 {

source/AssemblyLineClient/model/detect-tiny.cfg

+[net]
+# Testing
+batch=1
+subdivisions=1
+# Training
+# batch=64
+# subdivisions=64
+width=608
+height=608
+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=21
+activation=linear
+
+
+
+[yolo]
+mask = 3,4,5
+anchors = 10,14,  23,27,  37,58,  81,82,  135,169,  344,319
+classes=2
+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=21
+activation=linear
+
+[yolo]
+mask = 0,1,2
+anchors = 10,14,  23,27,  37,58,  81,82,  135,169,  344,319
+classes=2
+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

@@ -127,6 +127,9 @@
     <Content Include="halcon.dll">
       <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
     </Content>
+    <Content Include="libdecode.dll">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </Content>
     <Content Include="libdmtx.dll">
       <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
     </Content>
@@ -139,6 +142,9 @@
     <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/deviceLibrary/halcon/CodeManager.cs

@@ -138,7 +138,7 @@ namespace OnlineStore.DeviceLibrary
 
                         string r = "";
 
-                        List<CodeInfo> tlci = EyemDecode.Decoder(ref bmp);
+                        List<CodeInfo> tlci = EyemDecode.ModelDecoder(ref bmp);
                         bool eyemNoCode = false;
                         foreach (CodeInfo code in tlci)
                         {