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Commit 10de6088 由 LN
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扫码算法更新。

1 个父辈 cb965c8f
内嵌 并排
正在显示 16 个修改的文件 包含 613 行增加 和 2 行删除
dll/CodeLibrary.dll
此文件类型无法预览
dll/eyemLib.dll
此文件类型无法预览
dll/libdecode.dll 0 → 100644
此文件类型无法预览
dll/tbb.dll 0 → 100644
此文件类型无法预览
source/AssemblyLineClient/AssemblyLineClient.csproj
......@@ -236,6 +236,18 @@
<EmbeddedResource Include="useControl\EquipControl.resx">
<DependentUpon>EquipControl.cs</DependentUpon>
</EmbeddedResource>
<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="packages.config" />
<None Include="Properties\Settings.settings">
<Generator>SettingsSingleFileGenerator</Generator>
......
source/AssemblyLineClient/FrmLineStore.cs
......@@ -236,7 +236,9 @@ namespace OnlineStore.AssemblyLine
{
Camera._cam.CloseAll();
}
System.Environment.Exit(System.Environment.ExitCode);
//System.Environment.Exit(System.Environment.ExitCode);
System.Diagnostics.Process.GetCurrentProcess().Kill();
}
catch (Exception ex)
{
......
source/AssemblyLineClient/model/detect-tiny.cfg 0 → 100644
[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=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 0 → 100644
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
......@@ -157,6 +157,9 @@
<Content Include="huichuan_x86\msvcr100d.dll">
<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
</Content>
<Content Include="libdecode.dll">
<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
</Content>
<Content Include="libdmtx.dll">
<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
</Content>
......@@ -175,6 +178,9 @@
<Content Include="system_config.xml">
<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
......@@ -44,6 +44,7 @@ namespace OnlineStore.DeviceLibrary
LoadCamera(false);
CodeLibrary.HDCodeLearnHelper.LoadConfig("", codeStr);
CodeLibrary.EyemDecode.InitModel();
}
catch (Exception ex)
{
......@@ -139,7 +140,7 @@ 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)
{
......
source/DeviceLibrary/libdecode.dll 0 → 100644
此文件类型无法预览
source/DeviceLibrary/tbb.dll 0 → 100644
此文件类型无法预览
source/LoadCVSLibrary/FileEncoding.cs
......@@ -11,8 +11,13 @@ namespace OnlineStore.LoadCSVLibrary
{
public static bool WriteFile(string filePath, string[] lines)
{
try
{
if (lines == null)
{
return false;
}
//备份保存
try
{
......
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