modify dll

deploy/cpp_dll/.clang-format

+# This file is used by clang-format to autoformat paddle source code
+#
+# The clang-format is part of llvm toolchain.
+# It need to install llvm and clang to format source code style.
+#
+# The basic usage is,
+#   clang-format -i -style=file PATH/TO/SOURCE/CODE
+#
+# The -style=file implicit use ".clang-format" file located in one of 
+# parent directory. 
+# The -i means inplace change.
+#
+# The document of clang-format is 
+#   http://clang.llvm.org/docs/ClangFormat.html
+#   http://clang.llvm.org/docs/ClangFormatStyleOptions.html
+---
+Language:        Cpp
+BasedOnStyle:  Google
+IndentWidth:     2
+TabWidth:        2
+ContinuationIndentWidth: 4
+AccessModifierOffset: -1  # The private/protected/public has no indent in class
+Standard:  Cpp11 
+AllowAllParametersOfDeclarationOnNextLine: true
+BinPackParameters: false
+BinPackArguments: false
+...

deploy/cpp_dll/C#_dll/WindowsFormsApp1.sln

+
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio Version 16
+VisualStudioVersion = 16.0.30204.135
+MinimumVisualStudioVersion = 10.0.40219.1
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "WindowsFormsApp1", "WindowsFormsApp1\WindowsFormsApp1.csproj", "{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}"
+EndProject
+Global
+	GlobalSection(SolutionConfigurationPlatforms) = preSolution
+		Debug|Any CPU = Debug|Any CPU
+		Debug|x64 = Debug|x64
+		Release|Any CPU = Release|Any CPU
+		Release|x64 = Release|x64
+	EndGlobalSection
+	GlobalSection(ProjectConfigurationPlatforms) = postSolution
+		{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}.Debug|x64.ActiveCfg = Debug|x64
+		{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}.Debug|x64.Build.0 = Debug|x64
+		{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}.Release|Any CPU.Build.0 = Release|Any CPU
+		{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}.Release|x64.ActiveCfg = Release|x64
+		{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}.Release|x64.Build.0 = Release|x64
+	EndGlobalSection
+	GlobalSection(SolutionProperties) = preSolution
+		HideSolutionNode = FALSE
+	EndGlobalSection
+	GlobalSection(ExtensibilityGlobals) = postSolution
+		SolutionGuid = {F9C00A5F-6C78-41A8-959B-6977B6C1D15E}
+	EndGlobalSection
+EndGlobal

deploy/cpp_dll/C#_dll/WindowsFormsApp1/App.config

+<?xml version="1.0" encoding="utf-8" ?>
+<configuration>
+    <startup> 
+        <supportedRuntime version="v4.0" sku=".NETFramework,Version=v4.7.2" />
+    </startup>
+</configuration>
\ No newline at end of file

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Form1.Designer.cs

+namespace WindowsFormsApp1
+{
+    partial class Form1
+    {
+        /// <summary>
+        /// 必需的设计器变量。
+        /// </summary>
+        private System.ComponentModel.IContainer components = null;
+
+        /// <summary>
+        /// 清理所有正在使用的资源。
+        /// </summary>
+        /// <param name="disposing">如果应释放托管资源，为 true；否则为 false。</param>
+        protected override void Dispose(bool disposing)
+        {
+            if (disposing && (components != null))
+            {
+                components.Dispose();
+            }
+            base.Dispose(disposing);
+        }
+
+        #region Windows 窗体设计器生成的代码
+
+        /// <summary>
+        /// 设计器支持所需的方法 - 不要修改
+        /// 使用代码编辑器修改此方法的内容。
+        /// </summary>
+        private void InitializeComponent()
+        {
+            this.button1 = new System.Windows.Forms.Button();
+            this.SuspendLayout();
+            // 
+            // button1
+            // 
+            this.button1.Location = new System.Drawing.Point(129, 72);
+            this.button1.Name = "button1";
+            this.button1.Size = new System.Drawing.Size(129, 74);
+            this.button1.TabIndex = 0;
+            this.button1.Text = "button1";
+            this.button1.UseVisualStyleBackColor = true;
+            this.button1.Click += new System.EventHandler(this.button1_Click);
+            // 
+            // Form1
+            // 
+            this.AutoScaleDimensions = new System.Drawing.SizeF(8F, 15F);
+            this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font;
+            this.ClientSize = new System.Drawing.Size(800, 450);
+            this.Controls.Add(this.button1);
+            this.Name = "Form1";
+            this.Text = "Form1";
+            this.ResumeLayout(false);
+
+        }
+
+        #endregion
+
+        private System.Windows.Forms.Button button1;
+    }
+}
+

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Form1.cs

+using System;
+using System.Collections.Generic;
+using System.ComponentModel;
+using System.Data;
+using System.Drawing;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using System.Windows.Forms;
+using System.Runtime.InteropServices;
+namespace WindowsFormsApp1
+{
+    public partial class Form1 : Form
+    {
+        public Form1()
+        {
+            InitializeComponent();
+        }
+        [DllImport("detector.dll", EntryPoint = "Loadmodel", CharSet = CharSet.Ansi)]
+        public static extern void test();
+        private void button1_Click(object sender, EventArgs e)
+        {
+            test();
+        }
+    }
+}

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Form1.resx

+<?xml version="1.0" encoding="utf-8"?>
+<root>
+  <!-- 
+    Microsoft ResX Schema 
+    
+    Version 2.0
+    
+    The primary goals of this format is to allow a simple XML format 
+    that is mostly human readable. The generation and parsing of the 
+    various data types are done through the TypeConverter classes 
+    associated with the data types.
+    
+    Example:
+    
+    ... ado.net/XML headers & schema ...
+    <resheader name="resmimetype">text/microsoft-resx</resheader>
+    <resheader name="version">2.0</resheader>
+    <resheader name="reader">System.Resources.ResXResourceReader, System.Windows.Forms, ...</resheader>
+    <resheader name="writer">System.Resources.ResXResourceWriter, System.Windows.Forms, ...</resheader>
+    <data name="Name1"><value>this is my long string</value><comment>this is a comment</comment></data>
+    <data name="Color1" type="System.Drawing.Color, System.Drawing">Blue</data>
+    <data name="Bitmap1" mimetype="application/x-microsoft.net.object.binary.base64">
+        <value>[base64 mime encoded serialized .NET Framework object]</value>
+    </data>
+    <data name="Icon1" type="System.Drawing.Icon, System.Drawing" mimetype="application/x-microsoft.net.object.bytearray.base64">
+        <value>[base64 mime encoded string representing a byte array form of the .NET Framework object]</value>
+        <comment>This is a comment</comment>
+    </data>
+                
+    There are any number of "resheader" rows that contain simple 
+    name/value pairs.
+    
+    Each data row contains a name, and value. The row also contains a 
+    type or mimetype. Type corresponds to a .NET class that support 
+    text/value conversion through the TypeConverter architecture. 
+    Classes that don't support this are serialized and stored with the 
+    mimetype set.
+    
+    The mimetype is used for serialized objects, and tells the 
+    ResXResourceReader how to depersist the object. This is currently not 
+    extensible. For a given mimetype the value must be set accordingly:
+    
+    Note - application/x-microsoft.net.object.binary.base64 is the format 
+    that the ResXResourceWriter will generate, however the reader can 
+    read any of the formats listed below.
+    
+    mimetype: application/x-microsoft.net.object.binary.base64
+    value   : The object must be serialized with 
+            : System.Runtime.Serialization.Formatters.Binary.BinaryFormatter
+            : and then encoded with base64 encoding.
+    
+    mimetype: application/x-microsoft.net.object.soap.base64
+    value   : The object must be serialized with 
+            : System.Runtime.Serialization.Formatters.Soap.SoapFormatter
+            : and then encoded with base64 encoding.
+
+    mimetype: application/x-microsoft.net.object.bytearray.base64
+    value   : The object must be serialized into a byte array 
+            : using a System.ComponentModel.TypeConverter
+            : and then encoded with base64 encoding.
+    -->
+  <xsd:schema id="root" xmlns="" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:msdata="urn:schemas-microsoft-com:xml-msdata">
+    <xsd:import namespace="http://www.w3.org/XML/1998/namespace" />
+    <xsd:element name="root" msdata:IsDataSet="true">
+      <xsd:complexType>
+        <xsd:choice maxOccurs="unbounded">
+          <xsd:element name="metadata">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" />
+              </xsd:sequence>
+              <xsd:attribute name="name" use="required" type="xsd:string" />
+              <xsd:attribute name="type" type="xsd:string" />
+              <xsd:attribute name="mimetype" type="xsd:string" />
+              <xsd:attribute ref="xml:space" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="assembly">
+            <xsd:complexType>
+              <xsd:attribute name="alias" type="xsd:string" />
+              <xsd:attribute name="name" type="xsd:string" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="data">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" msdata:Ordinal="1" />
+                <xsd:element name="comment" type="xsd:string" minOccurs="0" msdata:Ordinal="2" />
+              </xsd:sequence>
+              <xsd:attribute name="name" type="xsd:string" use="required" msdata:Ordinal="1" />
+              <xsd:attribute name="type" type="xsd:string" msdata:Ordinal="3" />
+              <xsd:attribute name="mimetype" type="xsd:string" msdata:Ordinal="4" />
+              <xsd:attribute ref="xml:space" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="resheader">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" msdata:Ordinal="1" />
+              </xsd:sequence>
+              <xsd:attribute name="name" type="xsd:string" use="required" />
+            </xsd:complexType>
+          </xsd:element>
+        </xsd:choice>
+      </xsd:complexType>
+    </xsd:element>
+  </xsd:schema>
+  <resheader name="resmimetype">
+    <value>text/microsoft-resx</value>
+  </resheader>
+  <resheader name="version">
+    <value>2.0</value>
+  </resheader>
+  <resheader name="reader">
+    <value>System.Resources.ResXResourceReader, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
+  </resheader>
+  <resheader name="writer">
+    <value>System.Resources.ResXResourceWriter, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
+  </resheader>
+</root>
\ No newline at end of file

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Program.cs

+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Threading.Tasks;
+using System.Windows.Forms;
+
+namespace WindowsFormsApp1
+{
+    static class Program
+    {
+        /// <summary>
+        /// 应用程序的主入口点。
+        /// </summary>
+        [STAThread]
+        static void Main()
+        {
+            Application.EnableVisualStyles();
+            Application.SetCompatibleTextRenderingDefault(false);
+            Application.Run(new Form1());
+        }
+    }
+}

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Properties/AssemblyInfo.cs

+using System.Reflection;
+using System.Runtime.CompilerServices;
+using System.Runtime.InteropServices;
+
+// 有关程序集的一般信息由以下
+// 控制。更改这些特性值可修改
+// 与程序集关联的信息。
+[assembly: AssemblyTitle("WindowsFormsApp1")]
+[assembly: AssemblyDescription("")]
+[assembly: AssemblyConfiguration("")]
+[assembly: AssemblyCompany("")]
+[assembly: AssemblyProduct("WindowsFormsApp1")]
+[assembly: AssemblyCopyright("Copyright ©  2020")]
+[assembly: AssemblyTrademark("")]
+[assembly: AssemblyCulture("")]
+
+// 将 ComVisible 设置为 false 会使此程序集中的类型
+//对 COM 组件不可见。如果需要从 COM 访问此程序集中的类型
+//请将此类型的 ComVisible 特性设置为 true。
+[assembly: ComVisible(false)]
+
+// 如果此项目向 COM 公开，则下列 GUID 用于类型库的 ID
+[assembly: Guid("39044b60-f2a8-4b9f-8e65-9f87baec83bd")]
+
+// 程序集的版本信息由下列四个值组成: 
+//
+//      主版本
+//      次版本
+//      生成号
+//      修订号
+//
+//可以指定所有这些值，也可以使用“生成号”和“修订号”的默认值
+//通过使用 "*"，如下所示:
+// [assembly: AssemblyVersion("1.0.*")]
+[assembly: AssemblyVersion("1.0.0.0")]
+[assembly: AssemblyFileVersion("1.0.0.0")]

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Properties/Resources.Designer.cs

+//------------------------------------------------------------------------------
+// <auto-generated>
+//     此代码由工具生成。
+//     运行时版本: 4.0.30319.42000
+//
+//     对此文件的更改可能导致不正确的行为，如果
+//     重新生成代码，则所做更改将丢失。
+// </auto-generated>
+//------------------------------------------------------------------------------
+
+namespace WindowsFormsApp1.Properties
+{
+
+
+    /// <summary>
+    ///   强类型资源类，用于查找本地化字符串等。
+    /// </summary>
+    // 此类是由 StronglyTypedResourceBuilder
+    // 类通过类似于 ResGen 或 Visual Studio 的工具自动生成的。
+    // 若要添加或删除成员，请编辑 .ResX 文件，然后重新运行 ResGen
+    // (以 /str 作为命令选项)，或重新生成 VS 项目。
+    [global::System.CodeDom.Compiler.GeneratedCodeAttribute("System.Resources.Tools.StronglyTypedResourceBuilder", "4.0.0.0")]
+    [global::System.Diagnostics.DebuggerNonUserCodeAttribute()]
+    [global::System.Runtime.CompilerServices.CompilerGeneratedAttribute()]
+    internal class Resources
+    {
+
+        private static global::System.Resources.ResourceManager resourceMan;
+
+        private static global::System.Globalization.CultureInfo resourceCulture;
+
+        [global::System.Diagnostics.CodeAnalysis.SuppressMessageAttribute("Microsoft.Performance", "CA1811:AvoidUncalledPrivateCode")]
+        internal Resources()
+        {
+        }
+
+        /// <summary>
+        ///   返回此类使用的缓存 ResourceManager 实例。
+        /// </summary>
+        [global::System.ComponentModel.EditorBrowsableAttribute(global::System.ComponentModel.EditorBrowsableState.Advanced)]
+        internal static global::System.Resources.ResourceManager ResourceManager
+        {
+            get
+            {
+                if ((resourceMan == null))
+                {
+                    global::System.Resources.ResourceManager temp = new global::System.Resources.ResourceManager("WindowsFormsApp1.Properties.Resources", typeof(Resources).Assembly);
+                    resourceMan = temp;
+                }
+                return resourceMan;
+            }
+        }
+
+        /// <summary>
+        ///   覆盖当前线程的 CurrentUICulture 属性
+        ///   使用此强类型的资源类的资源查找。
+        /// </summary>
+        [global::System.ComponentModel.EditorBrowsableAttribute(global::System.ComponentModel.EditorBrowsableState.Advanced)]
+        internal static global::System.Globalization.CultureInfo Culture
+        {
+            get
+            {
+                return resourceCulture;
+            }
+            set
+            {
+                resourceCulture = value;
+            }
+        }
+    }
+}

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Properties/Resources.resx

+<?xml version="1.0" encoding="utf-8"?>
+<root>
+  <!-- 
+    Microsoft ResX Schema 
+    
+    Version 2.0
+    
+    The primary goals of this format is to allow a simple XML format 
+    that is mostly human readable. The generation and parsing of the 
+    various data types are done through the TypeConverter classes 
+    associated with the data types.
+    
+    Example:
+    
+    ... ado.net/XML headers & schema ...
+    <resheader name="resmimetype">text/microsoft-resx</resheader>
+    <resheader name="version">2.0</resheader>
+    <resheader name="reader">System.Resources.ResXResourceReader, System.Windows.Forms, ...</resheader>
+    <resheader name="writer">System.Resources.ResXResourceWriter, System.Windows.Forms, ...</resheader>
+    <data name="Name1"><value>this is my long string</value><comment>this is a comment</comment></data>
+    <data name="Color1" type="System.Drawing.Color, System.Drawing">Blue</data>
+    <data name="Bitmap1" mimetype="application/x-microsoft.net.object.binary.base64">
+        <value>[base64 mime encoded serialized .NET Framework object]</value>
+    </data>
+    <data name="Icon1" type="System.Drawing.Icon, System.Drawing" mimetype="application/x-microsoft.net.object.bytearray.base64">
+        <value>[base64 mime encoded string representing a byte array form of the .NET Framework object]</value>
+        <comment>This is a comment</comment>
+    </data>
+                
+    There are any number of "resheader" rows that contain simple 
+    name/value pairs.
+    
+    Each data row contains a name, and value. The row also contains a 
+    type or mimetype. Type corresponds to a .NET class that support 
+    text/value conversion through the TypeConverter architecture. 
+    Classes that don't support this are serialized and stored with the 
+    mimetype set.
+    
+    The mimetype is used for serialized objects, and tells the 
+    ResXResourceReader how to depersist the object. This is currently not 
+    extensible. For a given mimetype the value must be set accordingly:
+    
+    Note - application/x-microsoft.net.object.binary.base64 is the format 
+    that the ResXResourceWriter will generate, however the reader can 
+    read any of the formats listed below.
+    
+    mimetype: application/x-microsoft.net.object.binary.base64
+    value   : The object must be serialized with 
+            : System.Serialization.Formatters.Binary.BinaryFormatter
+            : and then encoded with base64 encoding.
+    
+    mimetype: application/x-microsoft.net.object.soap.base64
+    value   : The object must be serialized with 
+            : System.Runtime.Serialization.Formatters.Soap.SoapFormatter
+            : and then encoded with base64 encoding.
+
+    mimetype: application/x-microsoft.net.object.bytearray.base64
+    value   : The object must be serialized into a byte array 
+            : using a System.ComponentModel.TypeConverter
+            : and then encoded with base64 encoding.
+    -->
+  <xsd:schema id="root" xmlns="" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:msdata="urn:schemas-microsoft-com:xml-msdata">
+    <xsd:element name="root" msdata:IsDataSet="true">
+      <xsd:complexType>
+        <xsd:choice maxOccurs="unbounded">
+          <xsd:element name="metadata">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" />
+              </xsd:sequence>
+              <xsd:attribute name="name" type="xsd:string" />
+              <xsd:attribute name="type" type="xsd:string" />
+              <xsd:attribute name="mimetype" type="xsd:string" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="assembly">
+            <xsd:complexType>
+              <xsd:attribute name="alias" type="xsd:string" />
+              <xsd:attribute name="name" type="xsd:string" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="data">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" msdata:Ordinal="1" />
+                <xsd:element name="comment" type="xsd:string" minOccurs="0" msdata:Ordinal="2" />
+              </xsd:sequence>
+              <xsd:attribute name="name" type="xsd:string" msdata:Ordinal="1" />
+              <xsd:attribute name="type" type="xsd:string" msdata:Ordinal="3" />
+              <xsd:attribute name="mimetype" type="xsd:string" msdata:Ordinal="4" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="resheader">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" msdata:Ordinal="1" />
+              </xsd:sequence>
+              <xsd:attribute name="name" type="xsd:string" use="required" />
+            </xsd:complexType>
+          </xsd:element>
+        </xsd:choice>
+      </xsd:complexType>
+    </xsd:element>
+  </xsd:schema>
+  <resheader name="resmimetype">
+    <value>text/microsoft-resx</value>
+  </resheader>
+  <resheader name="version">
+    <value>2.0</value>
+  </resheader>
+  <resheader name="reader">
+    <value>System.Resources.ResXResourceReader, System.Windows.Forms, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
+  </resheader>
+  <resheader name="writer">
+    <value>System.Resources.ResXResourceWriter, System.Windows.Forms, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
+  </resheader>
+</root>
\ No newline at end of file

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Properties/Settings.Designer.cs

+//------------------------------------------------------------------------------
+// <auto-generated>
+//     This code was generated by a tool.
+//     Runtime Version:4.0.30319.42000
+//
+//     Changes to this file may cause incorrect behavior and will be lost if
+//     the code is regenerated.
+// </auto-generated>
+//------------------------------------------------------------------------------
+
+namespace WindowsFormsApp1.Properties
+{
+
+
+    [global::System.Runtime.CompilerServices.CompilerGeneratedAttribute()]
+    [global::System.CodeDom.Compiler.GeneratedCodeAttribute("Microsoft.VisualStudio.Editors.SettingsDesigner.SettingsSingleFileGenerator", "11.0.0.0")]
+    internal sealed partial class Settings : global::System.Configuration.ApplicationSettingsBase
+    {
+
+        private static Settings defaultInstance = ((Settings)(global::System.Configuration.ApplicationSettingsBase.Synchronized(new Settings())));
+
+        public static Settings Default
+        {
+            get
+            {
+                return defaultInstance;
+            }
+        }
+    }
+}

deploy/cpp_dll/C#_dll/WindowsFormsApp1/Properties/Settings.settings

+<?xml version='1.0' encoding='utf-8'?>
+<SettingsFile xmlns="http://schemas.microsoft.com/VisualStudio/2004/01/settings" CurrentProfile="(Default)">
+  <Profiles>
+    <Profile Name="(Default)" />
+  </Profiles>
+  <Settings />
+</SettingsFile>

deploy/cpp_dll/C#_dll/WindowsFormsApp1/WindowsFormsApp1.csproj

+<?xml version="1.0" encoding="utf-8"?>
+<Project ToolsVersion="15.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+  <Import Project="$(MSBuildExtensionsPath)\$(MSBuildToolsVersion)\Microsoft.Common.props" Condition="Exists('$(MSBuildExtensionsPath)\$(MSBuildToolsVersion)\Microsoft.Common.props')" />
+  <PropertyGroup>
+    <Configuration Condition=" '$(Configuration)' == '' ">Debug</Configuration>
+    <Platform Condition=" '$(Platform)' == '' ">AnyCPU</Platform>
+    <ProjectGuid>{39044B60-F2A8-4B9F-8E65-9F87BAEC83BD}</ProjectGuid>
+    <OutputType>WinExe</OutputType>
+    <RootNamespace>WindowsFormsApp1</RootNamespace>
+    <AssemblyName>WindowsFormsApp1</AssemblyName>
+    <TargetFrameworkVersion>v4.7.2</TargetFrameworkVersion>
+    <FileAlignment>512</FileAlignment>
+    <AutoGenerateBindingRedirects>true</AutoGenerateBindingRedirects>
+    <Deterministic>true</Deterministic>
+  </PropertyGroup>
+  <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Debug|AnyCPU' ">
+    <PlatformTarget>AnyCPU</PlatformTarget>
+    <DebugSymbols>true</DebugSymbols>
+    <DebugType>full</DebugType>
+    <Optimize>false</Optimize>
+    <OutputPath>bin\Debug\</OutputPath>
+    <DefineConstants>DEBUG;TRACE</DefineConstants>
+    <ErrorReport>prompt</ErrorReport>
+    <WarningLevel>4</WarningLevel>
+  </PropertyGroup>
+  <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Release|AnyCPU' ">
+    <PlatformTarget>AnyCPU</PlatformTarget>
+    <DebugType>pdbonly</DebugType>
+    <Optimize>true</Optimize>
+    <OutputPath>bin\Release\</OutputPath>
+    <DefineConstants>TRACE</DefineConstants>
+    <ErrorReport>prompt</ErrorReport>
+    <WarningLevel>4</WarningLevel>
+  </PropertyGroup>
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)' == 'Debug|x64'">
+    <DebugSymbols>true</DebugSymbols>
+    <OutputPath>bin\x64\Debug\</OutputPath>
+    <DefineConstants>DEBUG;TRACE</DefineConstants>
+    <DebugType>full</DebugType>
+    <PlatformTarget>x64</PlatformTarget>
+    <LangVersion>7.3</LangVersion>
+    <ErrorReport>prompt</ErrorReport>
+    <CodeAnalysisRuleSet>MinimumRecommendedRules.ruleset</CodeAnalysisRuleSet>
+    <Prefer32Bit>true</Prefer32Bit>
+  </PropertyGroup>
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)' == 'Release|x64'">
+    <OutputPath>bin\x64\Release\</OutputPath>
+    <DefineConstants>TRACE</DefineConstants>
+    <Optimize>true</Optimize>
+    <DebugType>pdbonly</DebugType>
+    <PlatformTarget>x64</PlatformTarget>
+    <LangVersion>7.3</LangVersion>
+    <ErrorReport>prompt</ErrorReport>
+    <CodeAnalysisRuleSet>MinimumRecommendedRules.ruleset</CodeAnalysisRuleSet>
+    <Prefer32Bit>true</Prefer32Bit>
+  </PropertyGroup>
+  <ItemGroup>
+    <Reference Include="System" />
+    <Reference Include="System.Core" />
+    <Reference Include="System.Xml.Linq" />
+    <Reference Include="System.Data.DataSetExtensions" />
+    <Reference Include="Microsoft.CSharp" />
+    <Reference Include="System.Data" />
+    <Reference Include="System.Deployment" />
+    <Reference Include="System.Drawing" />
+    <Reference Include="System.Net.Http" />
+    <Reference Include="System.Windows.Forms" />
+    <Reference Include="System.Xml" />
+  </ItemGroup>
+  <ItemGroup>
+    <Compile Include="Form1.cs">
+      <SubType>Form</SubType>
+    </Compile>
+    <Compile Include="Form1.Designer.cs">
+      <DependentUpon>Form1.cs</DependentUpon>
+    </Compile>
+    <Compile Include="Program.cs" />
+    <Compile Include="Properties\AssemblyInfo.cs" />
+    <EmbeddedResource Include="Form1.resx">
+      <DependentUpon>Form1.cs</DependentUpon>
+    </EmbeddedResource>
+    <EmbeddedResource Include="Properties\Resources.resx">
+      <Generator>ResXFileCodeGenerator</Generator>
+      <LastGenOutput>Resources.Designer.cs</LastGenOutput>
+      <SubType>Designer</SubType>
+    </EmbeddedResource>
+    <Compile Include="Properties\Resources.Designer.cs">
+      <AutoGen>True</AutoGen>
+      <DependentUpon>Resources.resx</DependentUpon>
+    </Compile>
+    <None Include="Properties\Settings.settings">
+      <Generator>SettingsSingleFileGenerator</Generator>
+      <LastGenOutput>Settings.Designer.cs</LastGenOutput>
+    </None>
+    <Compile Include="Properties\Settings.Designer.cs">
+      <AutoGen>True</AutoGen>
+      <DependentUpon>Settings.settings</DependentUpon>
+      <DesignTimeSharedInput>True</DesignTimeSharedInput>
+    </Compile>
+  </ItemGroup>
+  <ItemGroup>
+    <None Include="App.config" />
+  </ItemGroup>
+  <Import Project="$(MSBuildToolsPath)\Microsoft.CSharp.targets" />
+</Project>
\ No newline at end of file

deploy/cpp_dll/C#_dll/WindowsFormsApp1/bin/x64/Debug/WindowsFormsApp1.exe.config

+<?xml version="1.0" encoding="utf-8" ?>
+<configuration>
+    <startup> 
+        <supportedRuntime version="v4.0" sku=".NETFramework,Version=v4.7.2" />
+    </startup>
+</configuration>
\ No newline at end of file

deploy/cpp_dll/C#_dll/WindowsFormsApp1/obj/Debug/.NETFramework,Version=v4.7.2.AssemblyAttributes.cs

+// <autogenerated />
+using System;
+using System.Reflection;
+[assembly: global::System.Runtime.Versioning.TargetFrameworkAttribute(".NETFramework,Version=v4.7.2", FrameworkDisplayName = ".NET Framework 4.7.2")]

deploy/cpp_dll/C#_dll/WindowsFormsApp1/obj/x64/Debug/.NETFramework,Version=v4.7.2.AssemblyAttributes.cs

+// <autogenerated />
+using System;
+using System.Reflection;
+[assembly: global::System.Runtime.Versioning.TargetFrameworkAttribute(".NETFramework,Version=v4.7.2", FrameworkDisplayName = ".NET Framework 4.7.2")]

deploy/cpp_dll/C#_dll/WindowsFormsApp1/obj/x64/Debug/WindowsFormsApp1.csproj.CoreCompileInputs.cache

+d63ae25ae22a16b1f83e8cb2d7c50f73cb438914

deploy/cpp_dll/C#_dll/WindowsFormsApp1/obj/x64/Debug/WindowsFormsApp1.csproj.FileListAbsolute.txt

+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\bin\x64\Debug\WindowsFormsApp1.exe.config
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\bin\x64\Debug\WindowsFormsApp1.exe
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\bin\x64\Debug\WindowsFormsApp1.pdb
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\obj\x64\Debug\WindowsFormsApp1.csprojAssemblyReference.cache
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\obj\x64\Debug\WindowsFormsApp1.Form1.resources
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\obj\x64\Debug\WindowsFormsApp1.Properties.Resources.resources
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\obj\x64\Debug\WindowsFormsApp1.csproj.GenerateResource.cache
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\obj\x64\Debug\WindowsFormsApp1.csproj.CoreCompileInputs.cache
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\obj\x64\Debug\WindowsFormsApp1.exe
+C:\Users\Zhiliang.Yu\Desktop\pp\WindowsFormsApp1\WindowsFormsApp1\obj\x64\Debug\WindowsFormsApp1.pdb

deploy/cpp_dll/CMakeLists.txt

+cmake_minimum_required(VERSION 3.0)
+project(PaddleX CXX C)
+
+option(WITH_MKL        "Compile demo with MKL/OpenBlas support,defaultuseMKL."          ON)
+option(WITH_GPU        "Compile demo with GPU/CPU, default use CPU."                    ON)
+option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static."   OFF)
+option(WITH_TENSORRT "Compile demo with TensorRT."   OFF)
+option(WITH_ENCRYPTION "Compile demo with encryption tool."   OFF)
+
+SET(TENSORRT_DIR "" CACHE PATH "Location of libraries")
+SET(PADDLE_DIR "" CACHE PATH "Location of libraries")
+SET(OPENCV_DIR "" CACHE PATH "Location of libraries")
+SET(ENCRYPTION_DIR"" CACHE PATH "Location of libraries")
+SET(CUDA_LIB "" CACHE PATH "Location of libraries")
+
+if (NOT WIN32)
+    set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
+    set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
+    set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/demo)
+else()
+    set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/paddlex_inference)
+    set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/paddlex_inference)
+    set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/paddlex_inference)
+endif()
+
+if (NOT WIN32)
+    SET(YAML_BUILD_TYPE ON CACHE BOOL "yaml build shared library.")
+else()
+    SET(YAML_BUILD_TYPE OFF CACHE BOOL "yaml build shared library.")
+endif()
+include(cmake/yaml-cpp.cmake)
+
+include_directories("${CMAKE_SOURCE_DIR}/")
+include_directories("${CMAKE_CURRENT_BINARY_DIR}/ext/yaml-cpp/src/ext-yaml-cpp/include")
+link_directories("${CMAKE_CURRENT_BINARY_DIR}/ext/yaml-cpp/lib")
+
+macro(safe_set_static_flag)
+    foreach(flag_var
+        CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
+        CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO)
+      if(${flag_var} MATCHES "/MD")
+        string(REGEX REPLACE "/MD" "/MT" ${flag_var} "${${flag_var}}")
+      endif(${flag_var} MATCHES "/MD")
+    endforeach(flag_var)
+endmacro()
+
+
+if (WITH_ENCRYPTION)
+add_definitions( -DWITH_ENCRYPTION=${WITH_ENCRYPTION})
+endif()
+
+if (WITH_MKL)
+    ADD_DEFINITIONS(-DUSE_MKL)
+endif()
+
+if (NOT DEFINED PADDLE_DIR OR ${PADDLE_DIR} STREQUAL "")
+    message(FATAL_ERROR "please set PADDLE_DIR with -DPADDLE_DIR=/path/paddle_influence_dir")
+endif()
+
+if (NOT DEFINED OPENCV_DIR OR ${OPENCV_DIR} STREQUAL "")
+    message(FATAL_ERROR "please set OPENCV_DIR with -DOPENCV_DIR=/path/opencv")
+endif()
+
+include_directories("${CMAKE_SOURCE_DIR}/")
+include_directories("${PADDLE_DIR}/")
+include_directories("${PADDLE_DIR}/third_party/install/protobuf/include")
+include_directories("${PADDLE_DIR}/third_party/install/glog/include")
+include_directories("${PADDLE_DIR}/third_party/install/gflags/include")
+include_directories("${PADDLE_DIR}/third_party/install/xxhash/include")
+if (EXISTS "${PADDLE_DIR}/third_party/install/snappy/include")
+    include_directories("${PADDLE_DIR}/third_party/install/snappy/include")
+endif()
+if(EXISTS "${PADDLE_DIR}/third_party/install/snappystream/include")
+    include_directories("${PADDLE_DIR}/third_party/install/snappystream/include")
+endif()
+include_directories("${PADDLE_DIR}/third_party/install/zlib/include")
+include_directories("${PADDLE_DIR}/third_party/boost")
+include_directories("${PADDLE_DIR}/third_party/eigen3")
+
+if (EXISTS "${PADDLE_DIR}/third_party/install/snappy/lib")
+    link_directories("${PADDLE_DIR}/third_party/install/snappy/lib")
+endif()
+if(EXISTS "${PADDLE_DIR}/third_party/install/snappystream/lib")
+    link_directories("${PADDLE_DIR}/third_party/install/snappystream/lib")
+endif()
+
+link_directories("${PADDLE_DIR}/third_party/install/zlib/lib")
+link_directories("${PADDLE_DIR}/third_party/install/protobuf/lib")
+link_directories("${PADDLE_DIR}/third_party/install/glog/lib")
+link_directories("${PADDLE_DIR}/third_party/install/gflags/lib")
+link_directories("${PADDLE_DIR}/third_party/install/xxhash/lib")
+link_directories("${PADDLE_DIR}/paddle/lib/")
+link_directories("${CMAKE_CURRENT_BINARY_DIR}")
+
+if (WIN32)
+  include_directories("${PADDLE_DIR}/paddle/fluid/inference")
+  include_directories("${PADDLE_DIR}/paddle/include")
+  link_directories("${PADDLE_DIR}/paddle/fluid/inference")
+  find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/build/ NO_DEFAULT_PATH)
+  unset(OpenCV_DIR CACHE)
+else ()
+  find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/share/OpenCV NO_DEFAULT_PATH)
+  include_directories("${PADDLE_DIR}/paddle/include")
+  link_directories("${PADDLE_DIR}/paddle/lib")
+endif ()
+include_directories(${OpenCV_INCLUDE_DIRS})
+
+if (WIN32)
+    add_definitions("/DGOOGLE_GLOG_DLL_DECL=")
+    set(CMAKE_C_FLAGS_DEBUG   "${CMAKE_C_FLAGS_DEBUG} /bigobj /MTd")
+    set(CMAKE_C_FLAGS_RELEASE  "${CMAKE_C_FLAGS_RELEASE} /bigobj /MT")
+    set(CMAKE_CXX_FLAGS_DEBUG  "${CMAKE_CXX_FLAGS_DEBUG} /bigobj /MTd")
+    set(CMAKE_CXX_FLAGS_RELEASE   "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT")
+    if (WITH_STATIC_LIB)
+        safe_set_static_flag()
+        add_definitions(-DSTATIC_LIB)
+    endif()
+else()
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g -o2 -fopenmp -std=c++11")
+    set(CMAKE_STATIC_LIBRARY_PREFIX "")
+endif()
+
+if (WITH_GPU)
+    if (NOT DEFINED CUDA_LIB OR ${CUDA_LIB} STREQUAL "")
+        message(FATAL_ERROR "please set CUDA_LIB with -DCUDA_LIB=/path/cuda/lib64")
+    endif()
+    if (NOT WIN32)
+        if (NOT DEFINED CUDNN_LIB)
+            message(FATAL_ERROR "please set CUDNN_LIB with -DCUDNN_LIB=/path/cudnn/")
+        endif()
+    endif(NOT WIN32)
+endif()
+
+
+if (NOT WIN32)
+  if (WITH_TENSORRT AND WITH_GPU)
+      include_directories("${TENSORRT_DIR}/include")
+      link_directories("${TENSORRT_DIR}/lib")
+  endif()
+endif(NOT WIN32)
+
+if (NOT WIN32)
+    set(NGRAPH_PATH "${PADDLE_DIR}/third_party/install/ngraph")
+    if(EXISTS ${NGRAPH_PATH})
+        include(GNUInstallDirs)
+        include_directories("${NGRAPH_PATH}/include")
+        link_directories("${NGRAPH_PATH}/${CMAKE_INSTALL_LIBDIR}")
+        set(NGRAPH_LIB ${NGRAPH_PATH}/${CMAKE_INSTALL_LIBDIR}/libngraph${CMAKE_SHARED_LIBRARY_SUFFIX})
+    endif()
+endif()
+
+if(WITH_MKL)
+  include_directories("${PADDLE_DIR}/third_party/install/mklml/include")
+  if (WIN32)
+    set(MATH_LIB ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.lib
+            ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.lib)
+  else ()
+    set(MATH_LIB ${PADDLE_DIR}/third_party/install/mklml/lib/libmklml_intel${CMAKE_SHARED_LIBRARY_SUFFIX}
+            ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5${CMAKE_SHARED_LIBRARY_SUFFIX})
+    execute_process(COMMAND cp -r ${PADDLE_DIR}/third_party/install/mklml/lib/libmklml_intel${CMAKE_SHARED_LIBRARY_SUFFIX} /usr/lib)
+  endif ()
+  set(MKLDNN_PATH "${PADDLE_DIR}/third_party/install/mkldnn")
+  if(EXISTS ${MKLDNN_PATH})
+    include_directories("${MKLDNN_PATH}/include")
+    if (WIN32)
+      set(MKLDNN_LIB ${MKLDNN_PATH}/lib/mkldnn.lib)
+    else ()
+      set(MKLDNN_LIB ${MKLDNN_PATH}/lib/libmkldnn.so.0)
+    endif ()
+  endif()
+else()
+  set(MATH_LIB ${PADDLE_DIR}/third_party/install/openblas/lib/libopenblas${CMAKE_STATIC_LIBRARY_SUFFIX})
+endif()
+
+if (WIN32)
+    if(EXISTS "${PADDLE_DIR}/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX}")
+        set(DEPS
+            ${PADDLE_DIR}/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+    else()
+        set(DEPS
+            ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+    endif()
+endif()
+
+if(WITH_STATIC_LIB)
+    set(DEPS
+        ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+else()
+    set(DEPS
+        ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
+endif()
+
+if (NOT WIN32)
+    set(DEPS ${DEPS}
+        ${MATH_LIB} ${MKLDNN_LIB}
+        glog gflags protobuf z xxhash yaml-cpp
+        )
+    if(EXISTS "${PADDLE_DIR}/third_party/install/snappystream/lib")
+        set(DEPS ${DEPS} snappystream)
+    endif()
+    if (EXISTS "${PADDLE_DIR}/third_party/install/snappy/lib")
+        set(DEPS ${DEPS} snappy)
+    endif()
+else()
+    set(DEPS ${DEPS}
+        ${MATH_LIB} ${MKLDNN_LIB}
+        glog gflags_static libprotobuf zlibstatic xxhash libyaml-cppmt)
+
+    set(DEPS ${DEPS} libcmt shlwapi)
+    if (EXISTS "${PADDLE_DIR}/third_party/install/snappy/lib")
+        set(DEPS ${DEPS} snappy)
+    endif()
+    if(EXISTS "${PADDLE_DIR}/third_party/install/snappystream/lib")
+        set(DEPS ${DEPS} snappystream)
+    endif()
+endif(NOT WIN32)
+
+if(WITH_GPU)
+  if(NOT WIN32)
+    if (WITH_TENSORRT)
+      set(DEPS ${DEPS} ${TENSORRT_DIR}/lib/libnvinfer${CMAKE_SHARED_LIBRARY_SUFFIX})
+      set(DEPS ${DEPS} ${TENSORRT_DIR}/lib/libnvinfer_plugin${CMAKE_SHARED_LIBRARY_SUFFIX})
+    endif()
+    set(DEPS ${DEPS} ${CUDA_LIB}/libcudart${CMAKE_SHARED_LIBRARY_SUFFIX})
+    set(DEPS ${DEPS} ${CUDNN_LIB}/libcudnn${CMAKE_SHARED_LIBRARY_SUFFIX})
+  else()
+    set(DEPS ${DEPS} ${CUDA_LIB}/cudart${CMAKE_STATIC_LIBRARY_SUFFIX} )
+    set(DEPS ${DEPS} ${CUDA_LIB}/cublas${CMAKE_STATIC_LIBRARY_SUFFIX} )
+    set(DEPS ${DEPS} ${CUDA_LIB}/cudnn${CMAKE_STATIC_LIBRARY_SUFFIX})
+  endif()
+endif()
+
+if(WITH_ENCRYPTION)
+  if(NOT WIN32)
+      include_directories("${ENCRYPTION_DIR}/include")
+      link_directories("${ENCRYPTION_DIR}/lib")
+      set(DEPS ${DEPS} ${ENCRYPTION_DIR}/lib/libpmodel-decrypt${CMAKE_SHARED_LIBRARY_SUFFIX})
+  else()
+    message(FATAL_ERROR "Encryption Tool don't support WINDOWS")
+  endif()
+endif()
+
+if (NOT WIN32)
+    set(EXTERNAL_LIB "-ldl -lrt -lgomp -lz -lm -lpthread")
+    set(DEPS ${DEPS} ${EXTERNAL_LIB})
+endif()
+
+set(DEPS ${DEPS} ${OpenCV_LIBS})
+add_library(paddlex_inference SHARED src/visualize src/transforms.cpp src/paddlex.cpp)
+ADD_DEPENDENCIES(paddlex_inference ext-yaml-cpp)
+target_link_libraries(paddlex_inference ${DEPS})
+
+add_executable(classifier demo/classifier.cpp src/transforms.cpp src/paddlex.cpp)
+ADD_DEPENDENCIES(classifier ext-yaml-cpp)
+target_link_libraries(classifier ${DEPS})
+
+add_library(detector SHARED demo/detector.cpp src/transforms.cpp src/paddlex.cpp src/visualize.cpp)
+ADD_DEPENDENCIES(detector ext-yaml-cpp)
+target_link_libraries(detector ${DEPS})
+
+add_executable(segmenter demo/segmenter.cpp src/transforms.cpp src/paddlex.cpp src/visualize.cpp)
+ADD_DEPENDENCIES(segmenter ext-yaml-cpp)
+target_link_libraries(segmenter ${DEPS})
+
+if (WIN32 AND WITH_MKL)
+    add_custom_command(TARGET classifier POST_BUILD
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.dll ./mklml.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.dll ./libiomp5md.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mkldnn/lib/mkldnn.dll ./mkldnn.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.dll ./release/mklml.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.dll ./release/libiomp5md.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mkldnn/lib/mkldnn.dll ./release/mkldnn.dll
+    )
+    add_custom_command(TARGET detector POST_BUILD
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.dll ./mklml.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.dll ./libiomp5md.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mkldnn/lib/mkldnn.dll ./mkldnn.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.dll ./release/mklml.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.dll ./release/libiomp5md.dll
+    )
+    add_custom_command(TARGET segmenter POST_BUILD
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.dll ./mklml.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.dll ./libiomp5md.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mkldnn/lib/mkldnn.dll ./mkldnn.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.dll ./release/mklml.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.dll ./release/libiomp5md.dll
+
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mkldnn/lib/mkldnn.dll ./release/mkldnn.dll
+    )
+
+endif()
+
+file(COPY  "${CMAKE_SOURCE_DIR}/include/paddlex/visualize.h"
+DESTINATION  "${CMAKE_BINARY_DIR}/include/"  )
+file(COPY  "${CMAKE_SOURCE_DIR}/include/paddlex/config_parser.h"
+DESTINATION  "${CMAKE_BINARY_DIR}/include/"  )
+file(COPY  "${CMAKE_SOURCE_DIR}/include/paddlex/transforms.h"
+DESTINATION  "${CMAKE_BINARY_DIR}/include/"  )
+file(COPY  "${CMAKE_SOURCE_DIR}/include/paddlex/results.h"
+DESTINATION  "${CMAKE_BINARY_DIR}/include/"  )
+file(COPY  "${CMAKE_SOURCE_DIR}/include/paddlex/paddlex.h"
+DESTINATION  "${CMAKE_BINARY_DIR}/include/"  )

deploy/cpp_dll/CMakeSettings.json

+{
+    "configurations": [
+        {
+            "name": "x64-Release",
+            "generator": "Ninja",
+            "configurationType": "RelWithDebInfo",
+            "inheritEnvironments": [ "msvc_x64_x64" ],
+            "buildRoot": "${projectDir}\\out\\build\\${name}",
+            "installRoot": "${projectDir}\\out\\install\\${name}",
+            "cmakeCommandArgs": "",
+            "buildCommandArgs": "-v",
+            "ctestCommandArgs": "",
+            "variables": [
+                {
+                    "name": "OPENCV_DIR",
+                    "value": "C:/projects/opencv",
+                    "type": "PATH"
+                },
+                {
+                    "name": "PADDLE_DIR",
+                    "value": "C:/projects/fluid_install_dir_win_cpu_1.6/fluid_install_dir_win_cpu_1.6",
+                    "type": "PATH"
+                },
+                {
+                    "name": "CMAKE_BUILD_TYPE",
+                    "value": "Release",
+                    "type": "STRING"
+                },
+                {
+                    "name": "WITH_STATIC_LIB",
+                    "value": "True",
+                    "type": "BOOL"
+                },
+                {
+                    "name": "WITH_MKL",
+                    "value": "True",
+                    "type": "BOOL"
+                },
+                {
+                    "name": "WITH_GPU",
+                    "value": "False",
+                    "type": "BOOL"
+                }
+            ]
+        }
+    ]
+}
\ No newline at end of file

deploy/cpp_dll/cmake/yaml-cpp.cmake

+find_package(Git REQUIRED)
+
+include(ExternalProject)
+
+message("${CMAKE_BUILD_TYPE}")
+
+ExternalProject_Add(
+        ext-yaml-cpp
+        URL https://bj.bcebos.com/paddlex/deploy/deps/yaml-cpp.zip
+        URL_MD5 9542d6de397d1fbd649ed468cb5850e6
+        CMAKE_ARGS
+        -DYAML_CPP_BUILD_TESTS=OFF
+        -DYAML_CPP_BUILD_TOOLS=OFF
+        -DYAML_CPP_INSTALL=OFF
+        -DYAML_CPP_BUILD_CONTRIB=OFF
+        -DMSVC_SHARED_RT=OFF
+        -DBUILD_SHARED_LIBS=${YAML_BUILD_TYPE}
+        -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}
+        -DCMAKE_CXX_FLAGS=${CMAKE_CXX_FLAGS}
+        -DCMAKE_CXX_FLAGS_DEBUG=${CMAKE_CXX_FLAGS_DEBUG}
+        -DCMAKE_CXX_FLAGS_RELEASE=${CMAKE_CXX_FLAGS_RELEASE}
+        -DCMAKE_LIBRARY_OUTPUT_DIRECTORY=${CMAKE_BINARY_DIR}/ext/yaml-cpp/lib
+        -DCMAKE_ARCHIVE_OUTPUT_DIRECTORY=${CMAKE_BINARY_DIR}/ext/yaml-cpp/lib
+        PREFIX "${CMAKE_BINARY_DIR}/ext/yaml-cpp"
+        # Disable install step
+        INSTALL_COMMAND ""
+        LOG_DOWNLOAD ON
+        LOG_BUILD 1
+)
+

deploy/cpp_dll/demo/classifier.cpp

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <glog/logging.h>
+
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+
+#include "include/paddlex/paddlex.h"
+
+DEFINE_string(model_dir, "", "Path of inference model");
+DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
+DEFINE_bool(use_trt, false, "Infering with TensorRT");
+DEFINE_int32(gpu_id, 0, "GPU card id");
+DEFINE_string(key, "", "key of encryption");
+DEFINE_string(image, "", "Path of test image file");
+DEFINE_string(image_list, "", "Path of test image list file");
+
+int main(int argc, char** argv) {
+  // Parsing command-line
+  google::ParseCommandLineFlags(&argc, &argv, true);
+
+  if (FLAGS_model_dir == "") {
+    std::cerr << "--model_dir need to be defined" << std::endl;
+    return -1;
+  }
+  if (FLAGS_image == "" & FLAGS_image_list == "") {
+    std::cerr << "--image or --image_list need to be defined" << std::endl;
+    return -1;
+  }
+
+  // 加载模型
+  PaddleX::Model model;
+  model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id, FLAGS_key);
+
+  // 进行预测
+  if (FLAGS_image_list != "") {
+    std::ifstream inf(FLAGS_image_list);
+    if (!inf) {
+      std::cerr << "Fail to open file " << FLAGS_image_list << std::endl;
+      return -1;
+    }
+    std::string image_path;
+    while (getline(inf, image_path)) {
+      PaddleX::ClsResult result;
+      cv::Mat im = cv::imread(image_path, 1);
+      model.predict(im, &result);
+      std::cout << "Predict label: " << result.category
+                << ", label_id:" << result.category_id
+                << ", score: " << result.score << std::endl;
+    }
+  } else {
+    PaddleX::ClsResult result;
+    cv::Mat im = cv::imread(FLAGS_image, 1);
+    model.predict(im, &result);
+    std::cout << "Predict label: " << result.category
+              << ", label_id:" << result.category_id
+              << ", score: " << result.score << std::endl;
+  }
+
+  return 0;
+}

deploy/cpp_dll/demo/detector.cpp

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <glog/logging.h>
+
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+
+#include "include/paddlex/paddlex.h"
+#include "include/paddlex/visualize.h"
+
+namespace PaddleX {
+std::string image;
+void PredictImage(std::string image, PaddleX::DetResult result);
+
+void Loadmodel() {
+  std::string model_dir = "E:\\0608\\inference_model";
+  std::string key = "";
+  std::string image_list = "";
+  std::string save_dir = "output";
+  int gpu_id = 0;
+  bool use_trt = 0;
+  bool use_gpu = 1;
+
+  // Load model and create a object detector
+
+  PaddleX::DetResult result;
+  PredictImage(image, result);
+}
+
+void PredictImage(std::string image, PaddleX::DetResult result) {
+  image = "E:\\0608\\pic\\test.jpg";
+  cv::Mat im = cv::imread(image, 1);
+
+  // PaddleX::DetResult* result;
+  std::string model_dir = "E:\\0608\\inference_model";
+  std::string key = "";
+  std::string image_list = "";
+
+  int gpu_id = 0;
+  bool use_trt = 0;
+  bool use_gpu = 1;
+  PaddleX::Model model;
+  model.Init(model_dir, use_gpu, use_trt, gpu_id, key);
+  model.predict(im, &result);
+  for (int i = 0; i < result.boxes.size(); ++i) {
+    std::cout << ", predict label: " << result.boxes[i].category
+              << ", label_id:" << result.boxes[i].category_id
+              << ", score: " << result.boxes[i].score
+              << ", box(xmin, ymin, w, h):(" << result.boxes[i].coordinate[0]
+              << ", " << result.boxes[i].coordinate[1] << ", "
+              << result.boxes[i].coordinate[2] << ", "
+              << result.boxes[i].coordinate[3] << ")" << std::endl;
+  }
+
+  // 可视化
+  auto colormap = PaddleX::GenerateColorMap(model.labels.size());
+  cv::Mat vis_img = PaddleX::Visualize(im, result, model.labels, colormap, 0.5);
+  std::string save_dir = "output";
+  std::string save_path = PaddleX::generate_save_path(save_dir, image);
+
+  cv::imwrite(save_path, vis_img);
+  // result->clear();
+  std::cout << "Visualized output saved as " << save_path << std::endl;
+}
+}  // namespace PaddleX
\ No newline at end of file

deploy/cpp_dll/demo/segmenter.cpp

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <glog/logging.h>
+
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+
+#include "include/paddlex/paddlex.h"
+#include "include/paddlex/visualize.h"
+
+DEFINE_string(model_dir, "", "Path of inference model");
+DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
+DEFINE_bool(use_trt, false, "Infering with TensorRT");
+DEFINE_int32(gpu_id, 0, "GPU card id");
+DEFINE_string(key, "", "key of encryption");
+DEFINE_string(image, "", "Path of test image file");
+DEFINE_string(image_list, "", "Path of test image list file");
+DEFINE_string(save_dir, "output", "Path to save visualized image");
+
+int main(int argc, char** argv) {
+  // 解析命令行参数
+  google::ParseCommandLineFlags(&argc, &argv, true);
+
+  if (FLAGS_model_dir == "") {
+    std::cerr << "--model_dir need to be defined" << std::endl;
+    return -1;
+  }
+  if (FLAGS_image == "" & FLAGS_image_list == "") {
+    std::cerr << "--image or --image_list need to be defined" << std::endl;
+    return -1;
+  }
+
+  // 加载模型
+  PaddleX::Model model;
+  model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id, FLAGS_key);
+
+  auto colormap = PaddleX::GenerateColorMap(model.labels.size());
+  // 进行预测
+  if (FLAGS_image_list != "") {
+    std::ifstream inf(FLAGS_image_list);
+    if (!inf) {
+      std::cerr << "Fail to open file " << FLAGS_image_list << std::endl;
+      return -1;
+    }
+    std::string image_path;
+    while (getline(inf, image_path)) {
+      PaddleX::SegResult result;
+      cv::Mat im = cv::imread(image_path, 1);
+      model.predict(im, &result);
+      // 可视化
+      cv::Mat vis_img =
+          PaddleX::Visualize(im, result, model.labels, colormap);
+      std::string save_path =
+          PaddleX::generate_save_path(FLAGS_save_dir, image_path);
+      cv::imwrite(save_path, vis_img);
+      result.clear();
+      std::cout << "Visualized output saved as " << save_path << std::endl;
+    }
+  } else {
+    PaddleX::SegResult result;
+    cv::Mat im = cv::imread(FLAGS_image, 1);
+    model.predict(im, &result);
+    // 可视化
+    cv::Mat vis_img = PaddleX::Visualize(im, result, model.labels, colormap);
+    std::string save_path =
+        PaddleX::generate_save_path(FLAGS_save_dir, FLAGS_image);
+    cv::imwrite(save_path, vis_img);
+    result.clear();
+    std::cout << "Visualized output saved as " << save_path << std::endl;
+  }
+
+  return 0;
+}

deploy/cpp_dll/include/paddlex/config_parser.h

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <iostream>
+#include <map>
+#include <string>
+#include <vector>
+
+#include "yaml-cpp/yaml.h"
+
+#ifdef _WIN32
+#define OS_PATH_SEP "\\"
+#else
+#define OS_PATH_SEP "/"
+#endif
+
+namespace PaddleX {
+
+// Inference model configuration parser
+class ConfigPaser {
+ public:
+  ConfigPaser() {}
+
+  ~ConfigPaser() {}
+
+  bool load_config(const std::string& model_dir,
+                   const std::string& cfg = "model.yml") {
+    // Load as a YAML::Node
+    YAML::Node config;
+    config = YAML::LoadFile(model_dir + OS_PATH_SEP + cfg);
+
+    if (config["Transforms"].IsDefined()) {
+      YAML::Node transforms_ = config["Transforms"];
+    } else {
+      std::cerr << "There's no field 'Transforms' in model.yml" << std::endl;
+      return false;
+    }
+    return true;
+  }
+
+  YAML::Node Transforms_;
+};
+
+}  // namespace PaddleDetection

deploy/cpp_dll/include/paddlex/paddlex.h

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <functional>
+#include <iostream>
+#include <numeric>
+
+#include "yaml-cpp/yaml.h"
+
+#ifdef _WIN32
+#define OS_PATH_SEP "\\"
+#else
+#define OS_PATH_SEP "/"
+#endif
+
+#include "paddle_inference_api.h"  // NOLINT
+
+#include "config_parser.h"
+#include "results.h"
+#include "transforms.h"
+
+#ifdef WITH_ENCRYPTION
+#include "paddle_model_decrypt.h"
+#include "model_code.h"
+#endif
+
+namespace PaddleX {
+extern "C" __declspec(dllexport) void Loadmodel();
+void Loadmodel();
+class Model {
+ public:
+  void Init(const std::string& model_dir,
+            bool use_gpu = false,
+            bool use_trt = false,
+            int gpu_id = 0,
+            std::string key = "") {
+    create_predictor(model_dir, use_gpu, use_trt, gpu_id, key);
+  }
+
+  void create_predictor(const std::string& model_dir,
+                        bool use_gpu = false,
+                        bool use_trt = false,
+                        int gpu_id = 0,
+                        std::string key = "");
+
+  bool load_config(const std::string& model_dir);
+
+  bool preprocess(const cv::Mat& input_im, ImageBlob* blob);
+
+  bool predict(const cv::Mat& im, ClsResult* result);
+
+  bool predict(const cv::Mat& im, DetResult* result);
+
+  bool predict(const cv::Mat& im, SegResult* result);
+
+  bool postprocess(SegResult* result);
+
+  bool postprocess(DetResult* result);
+
+  std::string type;
+  std::string name;
+  std::map<int, std::string> labels;
+  Transforms transforms_;
+  ImageBlob inputs_;
+  std::vector<float> outputs_;
+  std::unique_ptr<paddle::PaddlePredictor> predictor_;
+};
+}  // namespce of PaddleX

deploy/cpp_dll/include/paddlex/results.h

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <iostream>
+#include <string>
+#include <vector>
+
+namespace PaddleX {
+
+template <class T>
+struct Mask {
+  std::vector<T> data;
+  std::vector<int> shape;
+  void clear() {
+    data.clear();
+    shape.clear();
+  }
+};
+
+struct Box {
+  int category_id;
+  std::string category;
+  float score;
+  std::vector<float> coordinate;
+  Mask<float> mask;
+};
+
+class BaseResult {
+ public:
+  std::string type = "base";
+};
+
+class ClsResult : public BaseResult {
+ public:
+  int category_id;
+  std::string category;
+  float score;
+  std::string type = "cls";
+};
+
+class DetResult : public BaseResult {
+ public:
+  std::vector<Box> boxes;
+  int mask_resolution;
+  std::string type = "det";
+  void clear() { boxes.clear(); }
+};
+
+class SegResult : public BaseResult {
+ public:
+  Mask<int64_t> label_map;
+  Mask<float> score_map;
+  std::string type = "seg";
+  void clear() {
+    label_map.clear();
+    score_map.clear();
+  }
+};
+}  // namespace PaddleX

deploy/cpp_dll/include/paddlex/transforms.h

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <yaml-cpp/yaml.h>
+
+#include <memory>
+#include <string>
+#include <unordered_map>
+#include <utility>
+#include <vector>
+
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+namespace PaddleX {
+
+// Object for storing all preprocessed data
+class ImageBlob {
+ public:
+  // Original image height and width
+  std::vector<int> ori_im_size_ = std::vector<int>(2);
+  // Newest image height and width after process
+  std::vector<int> new_im_size_ = std::vector<int>(2);
+  // Image height and width before resize
+  std::vector<std::vector<int>> im_size_before_resize_;
+  // Reshape order
+  std::vector<std::string> reshape_order_;
+  // Resize scale
+  float scale = 1.0;
+  // Buffer for image data after preprocessing
+  std::vector<float> im_data_;
+
+  void clear() {
+    ori_im_size_.clear();
+    new_im_size_.clear();
+    im_size_before_resize_.clear();
+    reshape_order_.clear();
+    im_data_.clear();
+  }
+};
+
+// Abstraction of preprocessing opration class
+class Transform {
+ public:
+  virtual void Init(const YAML::Node& item) = 0;
+  virtual bool Run(cv::Mat* im, ImageBlob* data) = 0;
+};
+
+class Normalize : public Transform {
+ public:
+  virtual void Init(const YAML::Node& item) {
+    mean_ = item["mean"].as<std::vector<float>>();
+    std_ = item["std"].as<std::vector<float>>();
+  }
+
+  virtual bool Run(cv::Mat* im, ImageBlob* data);
+
+ private:
+  std::vector<float> mean_;
+  std::vector<float> std_;
+};
+
+class ResizeByShort : public Transform {
+ public:
+  virtual void Init(const YAML::Node& item) {
+    short_size_ = item["short_size"].as<int>();
+    if (item["max_size"].IsDefined()) {
+      max_size_ = item["max_size"].as<int>();
+    } else {
+      max_size_ = -1;
+    }
+  }
+  virtual bool Run(cv::Mat* im, ImageBlob* data);
+
+ private:
+  float GenerateScale(const cv::Mat& im);
+  int short_size_;
+  int max_size_;
+};
+
+class ResizeByLong : public Transform {
+ public:
+  virtual void Init(const YAML::Node& item) {
+    long_size_ = item["long_size"].as<int>();
+  }
+  virtual bool Run(cv::Mat* im, ImageBlob* data);
+
+ private:
+  int long_size_;
+};
+
+class Resize : public Transform {
+ public:
+  virtual void Init(const YAML::Node& item) {
+    if (item["target_size"].IsScalar()) {
+      height_ = item["target_size"].as<int>();
+      width_ = item["target_size"].as<int>();
+      interp_ = item["interp"].as<std::string>();
+    } else if (item["target_size"].IsSequence()) {
+      std::vector<int> target_size = item["target_size"].as<std::vector<int>>();
+      width_ = target_size[0];
+      height_ = target_size[1];
+    }
+    if (height_ <= 0 || width_ <= 0) {
+      std::cerr << "[Resize] target_size should greater than 0" << std::endl;
+      exit(-1);
+    }
+  }
+  virtual bool Run(cv::Mat* im, ImageBlob* data);
+
+ private:
+  int height_;
+  int width_;
+  std::string interp_;
+};
+
+class CenterCrop : public Transform {
+ public:
+  virtual void Init(const YAML::Node& item) {
+    if (item["crop_size"].IsScalar()) {
+      height_ = item["crop_size"].as<int>();
+      width_ = item["crop_size"].as<int>();
+    } else if (item["crop_size"].IsSequence()) {
+      std::vector<int> crop_size = item["crop_size"].as<std::vector<int>>();
+      width_ = crop_size[0];
+      height_ = crop_size[1];
+    }
+  }
+  virtual bool Run(cv::Mat* im, ImageBlob* data);
+
+ private:
+  int height_;
+  int width_;
+};
+
+class Padding : public Transform {
+ public:
+  virtual void Init(const YAML::Node& item) {
+    if (item["coarsest_stride"].IsDefined()) {
+      coarsest_stride_ = item["coarsest_stride"].as<int>();
+      if (coarsest_stride_ < 1) {
+        std::cerr << "[Padding] coarest_stride should greater than 0"
+                  << std::endl;
+        exit(-1);
+      }
+    }
+    if (item["target_size"].IsDefined()) {
+      if (item["target_size"].IsScalar()) {
+        width_ = item["target_size"].as<int>();
+        height_ = item["target_size"].as<int>();
+      } else if (item["target_size"].IsSequence()) {
+        width_ = item["target_size"].as<std::vector<int>>()[0];
+        height_ = item["target_size"].as<std::vector<int>>()[1];
+      }
+    }
+  }
+  virtual bool Run(cv::Mat* im, ImageBlob* data);
+
+ private:
+  int coarsest_stride_ = -1;
+  int width_ = 0;
+  int height_ = 0;
+};
+
+class Transforms {
+ public:
+  void Init(const YAML::Node& node, bool to_rgb = true);
+  std::shared_ptr<Transform> CreateTransform(const std::string& name);
+  bool Run(cv::Mat* im, ImageBlob* data);
+
+ private:
+  std::vector<std::shared_ptr<Transform>> transforms_;
+  bool to_rgb_ = true;
+};
+
+}  // namespace PaddleX

deploy/cpp_dll/include/paddlex/visualize.h

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <iostream>
+#include <map>
+#include <vector>
+#ifdef _WIN32
+#include <direct.h>
+#include <io.h>
+#else  // Linux/Unix
+#include <dirent.h>
+#include <sys/io.h>
+#include <sys/stat.h>
+#include <sys/types.h>
+#include <unistd.h>
+#endif
+#include <string>
+
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+#include "include/paddlex/results.h"
+
+#ifdef _WIN32
+#define OS_PATH_SEP "\\"
+#else
+#define OS_PATH_SEP "/"
+#endif
+
+namespace PaddleX {
+
+// Generate visualization colormap for each class
+std::vector<int> GenerateColorMap(int num_class);
+
+cv::Mat Visualize(const cv::Mat& img,
+                     const DetResult& results,
+                     const std::map<int, std::string>& labels,
+                     const std::vector<int>& colormap,
+                     float threshold = 0.5);
+
+cv::Mat Visualize(const cv::Mat& img,
+                     const SegResult& result,
+                     const std::map<int, std::string>& labels,
+                     const std::vector<int>& colormap);
+
+std::string generate_save_path(const std::string& save_dir,
+                               const std::string& file_path);
+}  // namespce of PaddleX

deploy/cpp_dll/scripts/bootstrap.sh

+# download pre-compiled paddle encrypt
+ENCRYPTION_URL=https://bj.bcebos.com/paddlex/tools/paddlex-encryption.zip
+if [ ! -d "./paddlex-encryption" ]; then
+    wget -c ${ENCRYPTION_URL}
+    unzip paddlex-encryption.zip
+    rm -rf paddlex-encryption.zip
+fi
+
+# download pre-compiled opencv lib
+OPENCV_URL=https://paddleseg.bj.bcebos.com/deploy/docker/opencv3gcc4.8.tar.bz2
+if [ ! -d "./deps/opencv3gcc4.8" ]; then
+    mkdir -p deps
+    cd deps
+    wget -c ${OPENCV_URL}
+    tar xvfj opencv3gcc4.8.tar.bz2
+    rm -rf opencv3gcc4.8.tar.bz2
+    cd ..
+fi

deploy/cpp_dll/scripts/build.sh

+# 是否使用GPU(即是否使用 CUDA)
+WITH_GPU=OFF
+# 使用MKL or openblas
+WITH_MKL=ON
+# 是否集成 TensorRT(仅WITH_GPU=ON 有效)
+WITH_TENSORRT=OFF
+# TensorRT 的路径
+TENSORRT_DIR=/path/to/TensorRT/
+# Paddle 预测库路径
+PADDLE_DIR=/docker/jiangjiajun/PaddleDetection/deploy/cpp/fluid_inference
+# Paddle 的预测库是否使用静态库来编译
+# 使用TensorRT时，Paddle的预测库通常为动态库
+WITH_STATIC_LIB=OFF
+# CUDA 的 lib 路径
+CUDA_LIB=/usr/local/cuda/lib64
+# CUDNN 的 lib 路径
+CUDNN_LIB=/usr/local/cuda/lib64
+
+# 是否加载加密后的模型 
+WITH_ENCRYPTION=ON
+# 加密工具的路径, 如果使用自带预编译版本可不修改
+sh $(pwd)/scripts/bootstrap.sh # 下载预编译版本的加密工具
+ENCRYPTION_DIR=$(pwd)/paddlex-encryption
+
+# OPENCV 路径, 如果使用自带预编译版本可不修改
+sh $(pwd)/scripts/bootstrap.sh  # 下载预编译版本的opencv
+OPENCV_DIR=$(pwd)/deps/opencv3gcc4.8/
+
+# 以下无需改动
+rm -rf build
+mkdir -p build
+cd build
+cmake .. \
+    -DWITH_GPU=${WITH_GPU} \
+    -DWITH_MKL=${WITH_MKL} \
+    -DWITH_TENSORRT=${WITH_TENSORRT} \
+    -DWITH_ENCRYPTION=${WITH_ENCRYPTION} \
+    -DTENSORRT_DIR=${TENSORRT_DIR} \
+    -DPADDLE_DIR=${PADDLE_DIR} \
+    -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
+    -DCUDA_LIB=${CUDA_LIB} \
+    -DCUDNN_LIB=${CUDNN_LIB} \
+    -DENCRYPTION_DIR=${ENCRYPTION_DIR} \
+    -DOPENCV_DIR=${OPENCV_DIR}
+make

deploy/cpp_dll/src/paddlex.cpp

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "include/paddlex/paddlex.h"
+
+namespace PaddleX {
+
+void Model::create_predictor(const std::string& model_dir,
+                             bool use_gpu,
+                             bool use_trt,
+                             int gpu_id,
+                             std::string key) {
+  // 读取配置文件
+  if (!load_config(model_dir)) {
+    std::cerr << "Parse file 'model.yml' failed!" << std::endl;
+    exit(-1);
+  }
+  paddle::AnalysisConfig config;
+  std::string model_file = model_dir + OS_PATH_SEP + "__model__";
+  std::string params_file = model_dir + OS_PATH_SEP + "__params__";
+#ifdef WITH_ENCRYPTION
+  if (key != ""){
+    model_file = model_dir + OS_PATH_SEP + "__model__.encrypted";
+    params_file = model_dir + OS_PATH_SEP + "__params__.encrypted";
+    paddle_security_load_model(&config, key.c_str(), model_file.c_str(), params_file.c_str());
+  }
+#endif
+  if (key == ""){
+    config.SetModel(model_file, params_file);
+  }
+  if (use_gpu) {
+    config.EnableUseGpu(100, gpu_id);
+  } else {
+    config.DisableGpu();
+  }
+  config.SwitchUseFeedFetchOps(false);
+  config.SwitchSpecifyInputNames(true);
+  // 开启内存优化
+  config.EnableMemoryOptim();
+  if (use_trt) {
+    config.EnableTensorRtEngine(
+        1 << 20 /* workspace_size*/,
+        32 /* max_batch_size*/,
+        20 /* min_subgraph_size*/,
+        paddle::AnalysisConfig::Precision::kFloat32 /* precision*/,
+        true /* use_static*/,
+        false /* use_calib_mode*/);
+  }
+  predictor_ = std::move(CreatePaddlePredictor(config));
+}
+
+bool Model::load_config(const std::string& model_dir) {
+  std::string yaml_file = model_dir + OS_PATH_SEP + "model.yml";
+  YAML::Node config = YAML::LoadFile(yaml_file);
+  type = config["_Attributes"]["model_type"].as<std::string>();
+  name = config["Model"].as<std::string>();
+  std::string version = config["version"].as<std::string>();
+  if (version[0] == '0') {
+    std::cerr << "[Init] Version of the loaded model is lower than 1.0.0, deployment "
+              << "cannot be done, please refer to "
+              << "https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/tutorials/deploy/upgrade_version.md "
+              << "to transfer version."
+              << std::endl;
+    return false;
+  }
+  bool to_rgb = true;
+  if (config["TransformsMode"].IsDefined()) {
+    std::string mode = config["TransformsMode"].as<std::string>();
+    if (mode == "BGR") {
+      to_rgb = false;
+    } else if (mode != "RGB") {
+      std::cerr << "[Init] Only 'RGB' or 'BGR' is supported for TransformsMode"
+                << std::endl;
+      return false;
+    }
+  }
+  // 构建数据处理流
+  transforms_.Init(config["Transforms"], to_rgb);
+  // 读入label list
+  labels.clear();
+  for (const auto& item : config["_Attributes"]["labels"]) {
+    int index = labels.size();
+    labels[index] = item.as<std::string>();
+  }
+  return true;
+}
+
+bool Model::preprocess(const cv::Mat& input_im, ImageBlob* blob) {
+  cv::Mat im = input_im.clone();
+  if (!transforms_.Run(&im, blob)) {
+    return false;
+  }
+  return true;
+}
+
+bool Model::predict(const cv::Mat& im, ClsResult* result) {
+  inputs_.clear();
+  if (type == "detector") {
+    std::cerr << "Loading model is a 'detector', DetResult should be passed to "
+                 "function predict()!"
+              << std::endl;
+    return false;
+  } else if (type == "segmenter") {
+    std::cerr << "Loading model is a 'segmenter', SegResult should be passed "
+                 "to function predict()!"
+              << std::endl;
+    return false;
+  }
+  // 处理输入图像
+  if (!preprocess(im, &inputs_)) {
+    std::cerr << "Preprocess failed!" << std::endl;
+    return false;
+  }
+  // 使用加载的模型进行预测
+  auto in_tensor = predictor_->GetInputTensor("image");
+  int h = inputs_.new_im_size_[0];
+  int w = inputs_.new_im_size_[1];
+  in_tensor->Reshape({1, 3, h, w});
+  in_tensor->copy_from_cpu(inputs_.im_data_.data());
+  predictor_->ZeroCopyRun();
+  // 取出模型的输出结果
+  auto output_names = predictor_->GetOutputNames();
+  auto output_tensor = predictor_->GetOutputTensor(output_names[0]);
+  std::vector<int> output_shape = output_tensor->shape();
+  int size = 1;
+  for (const auto& i : output_shape) {
+    size *= i;
+  }
+  outputs_.resize(size);
+  output_tensor->copy_to_cpu(outputs_.data());
+  // 对模型输出结果进行后处理
+  auto ptr = std::max_element(std::begin(outputs_), std::end(outputs_));
+  result->category_id = std::distance(std::begin(outputs_), ptr);
+  result->score = *ptr;
+  result->category = labels[result->category_id];
+}
+
+bool Model::predict(const cv::Mat& im, DetResult* result) {
+  result->clear();
+  inputs_.clear();
+  if (type == "classifier") {
+    std::cerr << "Loading model is a 'classifier', ClsResult should be passed "
+                 "to function predict()!"
+              << std::endl;
+    return false;
+  } else if (type == "segmenter") {
+    std::cerr << "Loading model is a 'segmenter', SegResult should be passed "
+                 "to function predict()!"
+              << std::endl;
+    return false;
+  }
+
+  // 处理输入图像
+  if (!preprocess(im, &inputs_)) {
+    std::cerr << "Preprocess failed!" << std::endl;
+    return false;
+  }
+
+  int h = inputs_.new_im_size_[0];
+  int w = inputs_.new_im_size_[1];
+  auto im_tensor = predictor_->GetInputTensor("image");
+  im_tensor->Reshape({1, 3, h, w});
+  im_tensor->copy_from_cpu(inputs_.im_data_.data());
+  if (name == "YOLOv3") {
+    auto im_size_tensor = predictor_->GetInputTensor("im_size");
+    im_size_tensor->Reshape({1, 2});
+    im_size_tensor->copy_from_cpu(inputs_.ori_im_size_.data());
+  } else if (name == "FasterRCNN" || name == "MaskRCNN") {
+    auto im_info_tensor = predictor_->GetInputTensor("im_info");
+    auto im_shape_tensor = predictor_->GetInputTensor("im_shape");
+    im_info_tensor->Reshape({1, 3});
+    im_shape_tensor->Reshape({1, 3});
+    float ori_h = static_cast<float>(inputs_.ori_im_size_[0]);
+    float ori_w = static_cast<float>(inputs_.ori_im_size_[1]);
+    float new_h = static_cast<float>(inputs_.new_im_size_[0]);
+    float new_w = static_cast<float>(inputs_.new_im_size_[1]);
+    float im_info[] = {new_h, new_w, inputs_.scale};
+    float im_shape[] = {ori_h, ori_w, 1.0};
+    im_info_tensor->copy_from_cpu(im_info);
+    im_shape_tensor->copy_from_cpu(im_shape);
+  }
+  // 使用加载的模型进行预测
+  predictor_->ZeroCopyRun();
+
+  std::vector<float> output_box;
+  auto output_names = predictor_->GetOutputNames();
+  auto output_box_tensor = predictor_->GetOutputTensor(output_names[0]);
+  std::vector<int> output_box_shape = output_box_tensor->shape();
+  int size = 1;
+  for (const auto& i : output_box_shape) {
+    size *= i;
+  }
+  output_box.resize(size);
+  output_box_tensor->copy_to_cpu(output_box.data());
+  if (size < 6) {
+    std::cerr << "[WARNING] There's no object detected." << std::endl;
+    return true;
+  }
+  int num_boxes = size / 6;
+  // 解析预测框box
+  for (int i = 0; i < num_boxes; ++i) {
+    Box box;
+    box.category_id = static_cast<int>(round(output_box[i * 6]));
+    box.category = labels[box.category_id];
+    box.score = output_box[i * 6 + 1];
+    float xmin = output_box[i * 6 + 2];
+    float ymin = output_box[i * 6 + 3];
+    float xmax = output_box[i * 6 + 4];
+    float ymax = output_box[i * 6 + 5];
+    float w = xmax - xmin + 1;
+    float h = ymax - ymin + 1;
+    box.coordinate = {xmin, ymin, w, h};
+    result->boxes.push_back(std::move(box));
+  }
+  // 实例分割需解析mask
+  if (name == "MaskRCNN") {
+    std::vector<float> output_mask;
+    auto output_mask_tensor = predictor_->GetOutputTensor(output_names[1]);
+    std::vector<int> output_mask_shape = output_mask_tensor->shape();
+    int masks_size = 1;
+    for (const auto& i : output_mask_shape) {
+      masks_size *= i;
+    }
+    int mask_pixels = output_mask_shape[2] * output_mask_shape[3];
+    int classes = output_mask_shape[1];
+    output_mask.resize(masks_size);
+    output_mask_tensor->copy_to_cpu(output_mask.data());
+    result->mask_resolution = output_mask_shape[2];
+    for (int i = 0; i < result->boxes.size(); ++i) {
+      Box* box = &result->boxes[i];
+      auto begin_mask =
+          output_mask.begin() + (i * classes + box->category_id) * mask_pixels;
+      auto end_mask = begin_mask + mask_pixels;
+      box->mask.data.assign(begin_mask, end_mask);
+      box->mask.shape = {static_cast<int>(box->coordinate[2]),
+                         static_cast<int>(box->coordinate[3])};
+    }
+  }
+}
+
+bool Model::predict(const cv::Mat& im, SegResult* result) {
+  result->clear();
+  inputs_.clear();
+  if (type == "classifier") {
+    std::cerr << "Loading model is a 'classifier', ClsResult should be passed "
+                 "to function predict()!"
+              << std::endl;
+    return false;
+  } else if (type == "detector") {
+    std::cerr << "Loading model is a 'detector', DetResult should be passed to "
+                 "function predict()!"
+              << std::endl;
+    return false;
+  }
+
+  // 处理输入图像
+  if (!preprocess(im, &inputs_)) {
+    std::cerr << "Preprocess failed!" << std::endl;
+    return false;
+  }
+
+  int h = inputs_.new_im_size_[0];
+  int w = inputs_.new_im_size_[1];
+  auto im_tensor = predictor_->GetInputTensor("image");
+  im_tensor->Reshape({1, 3, h, w});
+  im_tensor->copy_from_cpu(inputs_.im_data_.data());
+
+  // 使用加载的模型进行预测
+  predictor_->ZeroCopyRun();
+
+  // 获取预测置信度，经过argmax后的labelmap
+  auto output_names = predictor_->GetOutputNames();
+  auto output_label_tensor = predictor_->GetOutputTensor(output_names[0]);
+  std::vector<int> output_label_shape = output_label_tensor->shape();
+  int size = 1;
+  for (const auto& i : output_label_shape) {
+    size *= i;
+    result->label_map.shape.push_back(i);
+  }
+  result->label_map.data.resize(size);
+  output_label_tensor->copy_to_cpu(result->label_map.data.data());
+
+  // 获取预测置信度scoremap
+  auto output_score_tensor = predictor_->GetOutputTensor(output_names[1]);
+  std::vector<int> output_score_shape = output_score_tensor->shape();
+  size = 1;
+  for (const auto& i : output_score_shape) {
+    size *= i;
+    result->score_map.shape.push_back(i);
+  }
+  result->score_map.data.resize(size);
+  output_score_tensor->copy_to_cpu(result->score_map.data.data());
+
+  // 解析输出结果到原图大小
+  std::vector<uint8_t> label_map(result->label_map.data.begin(),
+                                 result->label_map.data.end());
+  cv::Mat mask_label(result->label_map.shape[1],
+                     result->label_map.shape[2],
+                     CV_8UC1,
+                     label_map.data());
+
+  cv::Mat mask_score(result->score_map.shape[2],
+                     result->score_map.shape[3],
+                     CV_32FC1,
+                     result->score_map.data.data());
+  int idx = 1;
+  int len_postprocess = inputs_.im_size_before_resize_.size();
+  for (std::vector<std::string>::reverse_iterator iter =
+           inputs_.reshape_order_.rbegin();
+       iter != inputs_.reshape_order_.rend();
+       ++iter) {
+    if (*iter == "padding") {
+      auto before_shape = inputs_.im_size_before_resize_[len_postprocess - idx];
+      inputs_.im_size_before_resize_.pop_back();
+      auto padding_w = before_shape[0];
+      auto padding_h = before_shape[1];
+      mask_label = mask_label(cv::Rect(0, 0, padding_w, padding_h));
+      mask_score = mask_score(cv::Rect(0, 0, padding_w, padding_h));
+    } else if (*iter == "resize") {
+      auto before_shape = inputs_.im_size_before_resize_[len_postprocess - idx];
+      inputs_.im_size_before_resize_.pop_back();
+      auto resize_w = before_shape[0];
+      auto resize_h = before_shape[1];
+      cv::resize(mask_label,
+                 mask_label,
+                 cv::Size(resize_h, resize_w),
+                 0,
+                 0,
+                 cv::INTER_NEAREST);
+      cv::resize(mask_score,
+                 mask_score,
+                 cv::Size(resize_h, resize_w),
+                 0,
+                 0,
+                 cv::INTER_NEAREST);
+    }
+    ++idx;
+  }
+  result->label_map.data.assign(mask_label.begin<uint8_t>(),
+                                mask_label.end<uint8_t>());
+  result->label_map.shape = {mask_label.rows, mask_label.cols};
+  result->score_map.data.assign(mask_score.begin<float>(),
+                                mask_score.end<float>());
+  result->score_map.shape = {mask_score.rows, mask_score.cols};
+}
+
+}  // namespce of PaddleX

deploy/cpp_dll/src/transforms.cpp

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <iostream>
+#include <string>
+#include <vector>
+
+#include "include/paddlex/transforms.h"
+
+namespace PaddleX {
+
+std::map<std::string, int> interpolations = {{"LINEAR", cv::INTER_LINEAR},
+                                             {"NEAREST", cv::INTER_NEAREST},
+                                             {"AREA", cv::INTER_AREA},
+                                             {"CUBIC", cv::INTER_CUBIC},
+                                             {"LANCZOS4", cv::INTER_LANCZOS4}};
+
+bool Normalize::Run(cv::Mat* im, ImageBlob* data) {
+  for (int h = 0; h < im->rows; h++) {
+    for (int w = 0; w < im->cols; w++) {
+      im->at<cv::Vec3f>(h, w)[0] =
+          (im->at<cv::Vec3f>(h, w)[0] / 255.0 - mean_[0]) / std_[0];
+      im->at<cv::Vec3f>(h, w)[1] =
+          (im->at<cv::Vec3f>(h, w)[1] / 255.0 - mean_[1]) / std_[1];
+      im->at<cv::Vec3f>(h, w)[2] =
+          (im->at<cv::Vec3f>(h, w)[2] / 255.0 - mean_[2]) / std_[2];
+    }
+  }
+  return true;
+}
+
+float ResizeByShort::GenerateScale(const cv::Mat& im) {
+  int origin_w = im.cols;
+  int origin_h = im.rows;
+  int im_size_max = std::max(origin_w, origin_h);
+  int im_size_min = std::min(origin_w, origin_h);
+  float scale =
+      static_cast<float>(short_size_) / static_cast<float>(im_size_min);
+  if (max_size_ > 0) {
+    if (round(scale * im_size_max) > max_size_) {
+      scale = static_cast<float>(max_size_) / static_cast<float>(im_size_max);
+    }
+  }
+  return scale;
+}
+
+bool ResizeByShort::Run(cv::Mat* im, ImageBlob* data) {
+  data->im_size_before_resize_.push_back({im->rows, im->cols});
+  data->reshape_order_.push_back("resize");
+
+  float scale = GenerateScale(*im);
+  int width = static_cast<int>(scale * im->cols);
+  int height = static_cast<int>(scale * im->rows);
+  cv::resize(*im, *im, cv::Size(width, height), 0, 0, cv::INTER_LINEAR);
+
+  data->new_im_size_[0] = im->rows;
+  data->new_im_size_[1] = im->cols;
+  data->scale = scale;
+  return true;
+}
+
+bool CenterCrop::Run(cv::Mat* im, ImageBlob* data) {
+  int height = static_cast<int>(im->rows);
+  int width = static_cast<int>(im->cols);
+  if (height < height_ || width < width_) {
+    std::cerr << "[CenterCrop] Image size less than crop size" << std::endl;
+    return false;
+  }
+  int offset_x = static_cast<int>((width - width_) / 2);
+  int offset_y = static_cast<int>((height - height_) / 2);
+  cv::Rect crop_roi(offset_x, offset_y, width_, height_);
+  *im = (*im)(crop_roi);
+  data->new_im_size_[0] = im->rows;
+  data->new_im_size_[1] = im->cols;
+  return true;
+}
+
+bool Padding::Run(cv::Mat* im, ImageBlob* data) {
+  data->im_size_before_resize_.push_back({im->rows, im->cols});
+  data->reshape_order_.push_back("padding");
+
+  int padding_w = 0;
+  int padding_h = 0;
+  if (width_ > 1 & height_ > 1) {
+    padding_w = width_ - im->cols;
+    padding_h = height_ - im->rows;
+  } else if (coarsest_stride_ > 1) {
+    padding_h =
+        ceil(im->rows * 1.0 / coarsest_stride_) * coarsest_stride_ - im->rows;
+    padding_w =
+        ceil(im->cols * 1.0 / coarsest_stride_) * coarsest_stride_ - im->cols;
+  }
+
+  if (padding_h < 0 || padding_w < 0) {
+    std::cerr << "[Padding] Computed padding_h=" << padding_h
+              << ", padding_w=" << padding_w
+              << ", but they should be greater than 0." << std::endl;
+    return false;
+  }
+  cv::copyMakeBorder(
+      *im, *im, 0, padding_h, 0, padding_w, cv::BORDER_CONSTANT, cv::Scalar(0));
+  data->new_im_size_[0] = im->rows;
+  data->new_im_size_[1] = im->cols;
+  return true;
+}
+
+bool ResizeByLong::Run(cv::Mat* im, ImageBlob* data) {
+  if (long_size_ <= 0) {
+    std::cerr << "[ResizeByLong] long_size should be greater than 0"
+              << std::endl;
+    return false;
+  }
+  data->im_size_before_resize_.push_back({im->rows, im->cols});
+  data->reshape_order_.push_back("resize");
+  int origin_w = im->cols;
+  int origin_h = im->rows;
+
+  int im_size_max = std::max(origin_w, origin_h);
+  float scale =
+      static_cast<float>(long_size_) / static_cast<float>(im_size_max);
+  cv::resize(*im, *im, cv::Size(), scale, scale, cv::INTER_NEAREST);
+  data->new_im_size_[0] = im->rows;
+  data->new_im_size_[1] = im->cols;
+  data->scale = scale;
+  return true;
+}
+
+bool Resize::Run(cv::Mat* im, ImageBlob* data) {
+  if (width_ <= 0 || height_ <= 0) {
+    std::cerr << "[Resize] width and height should be greater than 0"
+              << std::endl;
+    return false;
+  }
+  if (interpolations.count(interp_) <= 0) {
+    std::cerr << "[Resize] Invalid interpolation method: '" << interp_ << "'"
+              << std::endl;
+    return false;
+  }
+  data->im_size_before_resize_.push_back({im->rows, im->cols});
+  data->reshape_order_.push_back("resize");
+
+  cv::resize(
+      *im, *im, cv::Size(width_, height_), 0, 0, interpolations[interp_]);
+  data->new_im_size_[0] = im->rows;
+  data->new_im_size_[1] = im->cols;
+  return true;
+}
+
+void Transforms::Init(const YAML::Node& transforms_node, bool to_rgb) {
+  transforms_.clear();
+  to_rgb_ = to_rgb;
+  for (const auto& item : transforms_node) {
+    std::string name = item.begin()->first.as<std::string>();
+    std::cout << "trans name: " << name << std::endl;
+    std::shared_ptr<Transform> transform = CreateTransform(name);
+    transform->Init(item.begin()->second);
+    transforms_.push_back(transform);
+  }
+}
+
+std::shared_ptr<Transform> Transforms::CreateTransform(
+    const std::string& transform_name) {
+  if (transform_name == "Normalize") {
+    return std::make_shared<Normalize>();
+  } else if (transform_name == "ResizeByShort") {
+    return std::make_shared<ResizeByShort>();
+  } else if (transform_name == "CenterCrop") {
+    return std::make_shared<CenterCrop>();
+  } else if (transform_name == "Resize") {
+    return std::make_shared<Resize>();
+  } else if (transform_name == "Padding") {
+    return std::make_shared<Padding>();
+  } else if (transform_name == "ResizeByLong") {
+    return std::make_shared<ResizeByLong>();
+  } else {
+    std::cerr << "There's unexpected transform(name='" << transform_name
+              << "')." << std::endl;
+    exit(-1);
+  }
+}
+
+bool Transforms::Run(cv::Mat* im, ImageBlob* data) {
+  // 按照transforms中预处理算子顺序处理图像
+  if (to_rgb_) {
+    cv::cvtColor(*im, *im, cv::COLOR_BGR2RGB);
+  }
+  (*im).convertTo(*im, CV_32FC3);
+  data->ori_im_size_[0] = im->rows;
+  data->ori_im_size_[1] = im->cols;
+  data->new_im_size_[0] = im->rows;
+  data->new_im_size_[1] = im->cols;
+  for (int i = 0; i < transforms_.size(); ++i) {
+    if (!transforms_[i]->Run(im, data)) {
+      std::cerr << "Apply transforms to image failed!" << std::endl;
+      return false;
+    }
+  }
+
+  // 将图像由NHWC转为NCHW格式
+  // 同时转为连续的内存块存储到ImageBlob
+  int h = im->rows;
+  int w = im->cols;
+  int c = im->channels();
+  (data->im_data_).resize(c * h * w);
+  float* ptr = (data->im_data_).data();
+  for (int i = 0; i < c; ++i) {
+    cv::extractChannel(*im, cv::Mat(h, w, CV_32FC1, ptr + i * h * w), i);
+  }
+  return true;
+}
+}  // namespace PaddleX

deploy/cpp_dll/src/visualize.cpp

+//   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "include/paddlex/visualize.h"
+
+namespace PaddleX {
+std::vector<int> GenerateColorMap(int num_class) {
+  auto colormap = std::vector<int>(3 * num_class, 0);
+  for (int i = 0; i < num_class; ++i) {
+    int j = 0;
+    int lab = i;
+    while (lab) {
+      colormap[i * 3] |= (((lab >> 0) & 1) << (7 - j));
+      colormap[i * 3 + 1] |= (((lab >> 1) & 1) << (7 - j));
+      colormap[i * 3 + 2] |= (((lab >> 2) & 1) << (7 - j));
+      ++j;
+      lab >>= 3;
+    }
+  }
+  return colormap;
+}
+
+cv::Mat Visualize(const cv::Mat& img,
+                     const DetResult& result,
+                     const std::map<int, std::string>& labels,
+                     const std::vector<int>& colormap,
+                     float threshold) {
+  cv::Mat vis_img = img.clone();
+  auto boxes = result.boxes;
+  for (int i = 0; i < boxes.size(); ++i) {
+    if (boxes[i].score < threshold) {
+      continue;
+    }
+    cv::Rect roi = cv::Rect(boxes[i].coordinate[0],
+                            boxes[i].coordinate[1],
+                            boxes[i].coordinate[2],
+                            boxes[i].coordinate[3]);
+
+    // 生成预测框和标题
+    std::string text = boxes[i].category;
+    int c1 = colormap[3 * boxes[i].category_id + 0];
+    int c2 = colormap[3 * boxes[i].category_id + 1];
+    int c3 = colormap[3 * boxes[i].category_id + 2];
+    cv::Scalar roi_color = cv::Scalar(c1, c2, c3);
+    text += std::to_string(static_cast<int>(boxes[i].score * 100)) + "%";
+    int font_face = cv::FONT_HERSHEY_SIMPLEX;
+    double font_scale = 0.5f;
+    float thickness = 0.5;
+    cv::Size text_size =
+        cv::getTextSize(text, font_face, font_scale, thickness, nullptr);
+    cv::Point origin;
+    origin.x = roi.x;
+    origin.y = roi.y;
+
+    // 生成预测框标题的背景
+    cv::Rect text_back = cv::Rect(boxes[i].coordinate[0],
+                                  boxes[i].coordinate[1] - text_size.height,
+                                  text_size.width,
+                                  text_size.height);
+
+    // 绘图和文字
+    cv::rectangle(vis_img, roi, roi_color, 2);
+    cv::rectangle(vis_img, text_back, roi_color, -1);
+    cv::putText(vis_img,
+                text,
+                origin,
+                font_face,
+                font_scale,
+                cv::Scalar(255, 255, 255),
+                thickness);
+
+    // 生成实例分割mask
+    if (boxes[i].mask.data.size() == 0) {
+      continue;
+    }
+    cv::Mat bin_mask(result.mask_resolution,
+                     result.mask_resolution,
+                     CV_32FC1,
+                     boxes[i].mask.data.data());
+    cv::resize(bin_mask,
+               bin_mask,
+               cv::Size(boxes[i].mask.shape[0], boxes[i].mask.shape[1]));
+    cv::threshold(bin_mask, bin_mask, 0.5, 1, cv::THRESH_BINARY);
+    cv::Mat full_mask = cv::Mat::zeros(vis_img.size(), CV_8UC1);
+    bin_mask.copyTo(full_mask(roi));
+    cv::Mat mask_ch[3];
+    mask_ch[0] = full_mask * c1;
+    mask_ch[1] = full_mask * c2;
+    mask_ch[2] = full_mask * c3;
+    cv::Mat mask;
+    cv::merge(mask_ch, 3, mask);
+    cv::addWeighted(vis_img, 1, mask, 0.5, 0, vis_img);
+  }
+  return vis_img;
+}
+
+cv::Mat Visualize(const cv::Mat& img,
+                     const SegResult& result,
+                     const std::map<int, std::string>& labels,
+                     const std::vector<int>& colormap) {
+  std::vector<uint8_t> label_map(result.label_map.data.begin(),
+                                 result.label_map.data.end());
+  cv::Mat mask(result.label_map.shape[0],
+               result.label_map.shape[1],
+               CV_8UC1,
+               label_map.data());
+  cv::Mat color_mask = cv::Mat::zeros(
+      result.label_map.shape[0], result.label_map.shape[1], CV_8UC3);
+  int rows = img.rows;
+  int cols = img.cols;
+  for (int i = 0; i < rows; i++) {
+    for (int j = 0; j < cols; j++) {
+      int category_id = static_cast<int>(mask.at<uchar>(i, j));
+      color_mask.at<cv::Vec3b>(i, j)[0] = colormap[3 * category_id + 0];
+      color_mask.at<cv::Vec3b>(i, j)[1] = colormap[3 * category_id + 1];
+      color_mask.at<cv::Vec3b>(i, j)[2] = colormap[3 * category_id + 2];
+    }
+  }
+  return color_mask;
+}
+
+std::string generate_save_path(const std::string& save_dir,
+                               const std::string& file_path) {
+  if (access(save_dir.c_str(), 0) < 0) {
+#ifdef _WIN32
+    mkdir(save_dir.c_str());
+#else
+    if (mkdir(save_dir.c_str(), S_IRWXU) < 0) {
+      std::cerr << "Fail to create " << save_dir << "directory." << std::endl;
+    }
+#endif
+  }
+  int pos = file_path.find_last_of(OS_PATH_SEP);
+  std::string image_name(file_path.substr(pos + 1));
+  return save_dir + OS_PATH_SEP + image_name;
+}
+}  // namespace of PaddleX

deploy/cpp_dll/test_dll.py

+from ctypes import *
+dll=CDLL("./detector.dll")
+print(dll.Loadmodel())
\ No newline at end of file