一，準備工作

1.Afoge視訊引數類

using AForge.Video.DirectShow;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace FaceRecognization.Common
{
    public class CameraPara
    {
        /// <summary>
        /// 是否有攝像頭
        /// </summary>
 

        public bool HasVideoDevice { get; set; }
        /// <summary>
        /// 視訊源
        /// </summary>
        public VideoCaptureDevice VideoSource { get; set; }
        /// <summary>
        /// 視訊圖片的寬度
        /// </summary>
        public int FrameWidth { get; set; }
        /// <summary>
 

        /// 視訊圖片的高度
        /// </summary>
        public int FrameHeight { get; set; }
        /// <summary>
        /// 視訊圖片的位元組數
        /// </summary>
        public int ByteCount { get; set; }
        public CameraPara()
        {
            var videoDevices = new FilterInfoCollection(FilterCategory.VideoInputDevice);

            if
 
 (videoDevices.Count == 0)//沒有檢測到攝像頭
            {
                HasVideoDevice = false;
                return;
            }

            VideoSource = new VideoCaptureDevice(videoDevices[0].MonikerString);//連線第一個攝像頭
            var videoResolution = VideoSource.VideoCapabilities.First(ii => ii.FrameSize.Width == VideoSource.VideoCapabilities.Max(jj => jj.FrameSize.Width)); //獲取攝像頭最高的解析度

            FrameWidth = videoResolution.FrameSize.Width;
            FrameHeight = videoResolution.FrameSize.Height;
            ByteCount = videoResolution.BitCount / 8;
            VideoSource.VideoResolution = videoResolution;
            HasVideoDevice = true;
        }

    }
}

2.人臉識別相關的結構、類 和列舉

using System;
using System.Collections.Generic;
using System.Linq;
using System.Runtime.InteropServices;
using System.Text;
using System.Threading.Tasks;

namespace FaceRecognization.Face
{
    /// <summary>
    /// 人臉庫
    /// </summary>
    public class FaceLib
    {
        public List<Item> Items { get; set; } = new List<Item>();
        public class Item
        {
            /// <summary>
            /// 用於排序
            /// </summary>
            public long OrderId { get; set; }
            /// <summary>
            /// 檔名作為ID
            /// </summary>
            public string ID { get; set; }
            /// <summary>
            /// 人臉模型
            /// </summary>
            public FaceModel FaceModel { get; set; }
        }
    }
    /// <summary>
    /// 人臉識別結果
    /// </summary>
    public class FaceResult
    {
        //public int NotMatchedCount { get; set; }
        public string ID { get; set; }
        public float Score { get; set; }
        public System.Drawing.Rectangle Rectangle { get; set; }
        public int Age { get; set; }
        /// <summary>
        /// 0：男，1：女，其他：未知
        /// </summary>
        public int Gender { get; set; }
        public override string ToString()
        {

            string ret = "";
            if (!string.IsNullOrEmpty(ID))
                ret = ID + "，";
            ret += Age + "歲";
            if (Gender == 0)
                ret += "，男";
            else if (Gender == 1)
                ret += "，女";

            return ret + "," + Score;
        }
    }

    /// <summary>
    /// 人臉跟蹤、檢測、性別年齡評估和獲取人臉資訊的輸入引數
    /// </summary>
    [StructLayout(LayoutKind.Sequential)]
    public struct ImageData
    {
        public uint u32PixelArrayFormat;
        public int i32Width;
        public int i32Height;
        [MarshalAs(UnmanagedType.ByValArray, SizeConst = 4)]
        public IntPtr[] ppu8Plane;
        [MarshalAs(UnmanagedType.ByValArray, SizeConst = 4, ArraySubType = UnmanagedType.I4)]
        public int[] pi32Pitch;
    }
    /// <summary>
    /// 人臉跟蹤的結果
    /// </summary>
    [StructLayout(LayoutKind.Sequential)]
    internal struct TraceResult
    {
        [MarshalAs(UnmanagedType.I4)]
        public int nFace;
        [MarshalAs(UnmanagedType.I4)]
        public int lfaceOrient;
        public IntPtr rcFace;
    }
    /// <summary>
    /// 人臉檢測的結果
    /// </summary>
    [StructLayout(LayoutKind.Sequential)]
    internal struct DetectResult
    {
        [MarshalAs(UnmanagedType.I4)]
        public int nFace;
        public IntPtr rcFace;
        public IntPtr lfaceOrient;
    }

    /// <summary>
    /// 人臉在圖片中的位置
    /// </summary>
    [StructLayout(LayoutKind.Sequential)]
    public struct FaceRect
    {
        public int left;
        public int top;
        public int right;
        public int bottom;
    }
    /// <summary>
    /// 獲取人臉特徵的輸入引數
    /// </summary>
    [StructLayout(LayoutKind.Sequential)]
    internal struct FaceFeatureInput
    {
        public FaceRect rcFace;
        public int lOrient;
    }
    /// <summary>
    /// 人臉特徵
    /// </summary>
    [StructLayout(LayoutKind.Sequential)]
    public struct FaceModel
    {
        public IntPtr pbFeature;
        [MarshalAs(UnmanagedType.I4)]
        public int lFeatureSize;
    }
    /// <summary>
    /// 性別和年齡評估的輸入引數
    /// </summary>
    [StructLayout(LayoutKind.Sequential)]
    internal struct EstimationInput
    {
        public IntPtr pFaceRectArray;
        public IntPtr pFaceOrientArray;
        public int lFaceNumber;
    }
    /// <summary>
    /// 性別和年齡評估的結果
    /// </summary>
    [StructLayout(LayoutKind.Sequential)]
    internal struct EstimationResult
    {
        public IntPtr pResult;
        public int lFaceNumber;
    }

    /// <summary>
    /// 錯誤程式碼
    /// </summary>
    public enum ErrorCode
    {
        /// <summary>
        /// 正確
        /// </summary>
        Ok = 0,

        /// <summary>
        /// 通用錯誤型別
        /// </summary>
        BasicBase = 0x0001,

        /// <summary>
        /// 錯誤原因不明
        /// </summary>
        Unknown = BasicBase,

        /// <summary>
        /// 無效的引數
        /// </summary>
        InvalidParam = BasicBase + 1,

        /// <summary>
        /// 引擎不支援
        /// </summary>
        Unsupported = BasicBase + 2,

        /// <summary>
        /// 記憶體不足
        /// </summary>
        NoMemory = BasicBase + 3,

        /// <summary>
        /// 狀態錯誤
        /// </summary>
        BadState = BasicBase + 4,

        /// <summary>
        /// 使用者取消相關操作
        /// </summary>
        UserCancel = BasicBase + 5,

        /// <summary>
        /// 操作時間過期
        /// </summary>
        Expired = BasicBase + 6,

        /// <summary>
        /// 使用者暫停操作
        /// </summary>
        UserPause = BasicBase + 7,

        /// <summary>
        /// 緩衝上溢
        /// </summary>
        BufferOverflow = BasicBase + 8,

        /// <summary>
        /// 緩衝下溢
        /// </summary>
        BufferUnderflow = BasicBase + 9,

        /// <summary>
        /// 存貯空間不足
        /// </summary>
        NoDiskspace = BasicBase + 10,

        /// <summary>
        /// 元件不存在
        /// </summary>
        ComponentNotExist = BasicBase + 11,

        /// <summary>
        /// 全域性資料不存在
        /// </summary>
        GlobalDataNotExist = BasicBase + 12,

        /// <summary>
        /// Free SDK通用錯誤型別
        /// </summary>
        SdkBase = 0x7000,

        /// <summary>
        /// 無效的App Id
        /// </summary>
        InvalidAppId = SdkBase + 1,

        /// <summary>
        /// 無效的SDK key
        /// </summary>
        InvalidSdkId = SdkBase + 2,

        /// <summary>
        /// AppId和SDKKey不匹配
        /// </summary>
        InvalidIdPair = SdkBase + 3,

        /// <summary>
        /// SDKKey 和使用的SDK 不匹配
        /// </summary>
        MismatchIdAndSdk = SdkBase + 4,

        /// <summary>
        /// 系統版本不被當前SDK所支援
        /// </summary>
        SystemVersionUnsupported = SdkBase + 5,

        /// <summary>
        /// SDK有效期過期，需要重新下載更新
        /// </summary>
        LicenceExpired = SdkBase + 6,

        /// <summary>
        /// Face Recognition錯誤型別
        /// </summary>
        FaceRecognitionBase = 0x12000,

        /// <summary>
        /// 無效的輸入記憶體
        /// </summary>
        InvalidMemoryInfo = FaceRecognitionBase + 1,

        /// <summary>
        /// 無效的輸入影象引數
        /// </summary>
        InvalidImageInfo = FaceRecognitionBase + 2,

        /// <summary>
        /// 無效的臉部資訊
        /// </summary>
        InvalidFaceInfo = FaceRecognitionBase + 3,

        /// <summary>
        /// 當前裝置無GPU可用
        /// </summary>
        NoGpuAvailable = FaceRecognitionBase + 4,

        /// <summary>
        /// 待比較的兩個人臉特徵的版本不一致
        /// </summary>
        MismatchedFeatureLevel = FaceRecognitionBase + 5
    }
    /// <summary>
    /// 臉部角度的檢測範圍
    /// </summary>
    public enum OrientPriority
    {
        /// <summary>
        /// 檢測 0 度（±45 度）方向
        /// </summary>
        Only0 = 0x1,

        /// <summary>
        /// 檢測 90 度（±45 度）方向
        /// </summary>
        Only90 = 0x2,

        /// <summary>
        /// 檢測 270 度（±45 度）方向
        /// </summary>
        Only270 = 0x3,

        /// <summary>
        /// 檢測 180 度（±45 度）方向
        /// </summary>
        Only180 = 0x4,

        /// <summary>
        /// 檢測 0， 90， 180， 270 四個方向,0 度更優先
        /// </summary>
        Ext0 = 0x5
    }

}

3.虹軟SDK的dll封裝

注意要把相應的dll複製的debug\Libs資料夾或release\Libs資料夾

using System;
using System.Collections.Generic;
using System.Linq;
using System.Runtime.InteropServices;
using System.Text;
using System.Threading.Tasks;

namespace FaceRecognization.Face
{
    internal class Detect
    {
        private const string DllPath = "Libs/libarcsoft_fsdk_face_detection.dll";
        /// <summary>
        /// 
        /// </summary>
        /// <param name="appId"></param>
        /// <param name="sdkKey"></param>
        /// <param name="memory"></param>
        /// <param name="memroySize"></param>
        /// <param name="engine"></param>
        /// <param name="orientPriority"></param>
        /// <param name="scale">最小人臉尺寸有效值範圍[2,50] 推薦值 16。該尺寸是人臉相對於所在圖片的長邊的佔比。例如，如果使用者想檢測到的最小人臉尺寸是圖片長度的 1/8，那麼這個 nScale 就應該設定為8</param>
        /// <param name="maxFaceNumber">使用者期望引擎最多能檢測出的人臉數有效值範圍[1,100]</param>
        /// <returns></returns>
        [DllImport(DllPath, EntryPoint = "AFD_FSDK_InitialFaceEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Init(string appId, string sdkKey, byte[] memory, int memroySize, out IntPtr engine, int orientPriority, int scale, int maxFaceNumber);
        [DllImport(DllPath, EntryPoint = "AFD_FSDK_StillImageFaceDetection", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Detection(IntPtr engine, ref ImageData imgData, out IntPtr pDetectResult);
        [DllImport(DllPath, EntryPoint = "AFD_FSDK_UninitialFaceEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Close(IntPtr engine);
    }
    internal class Trace
    {
        private const string DllPath = "Libs/libarcsoft_fsdk_face_tracking.dll";
        /// <summary>
        /// 
        /// </summary>
        /// <param name="appId"></param>
        /// <param name="sdkKey"></param>
        /// <param name="buffer"></param>
        /// <param name="bufferSize"></param>
        /// <param name="engine"></param>
        /// <param name="orientPriority"></param>
        /// <param name="scale">最小人臉尺寸有效值範圍[2,16] 推薦值 16。該尺寸是人臉相對於所在圖片的長邊的佔比。例如，如果使用者想檢測到的最小人臉尺寸是圖片長度的 1/8，那麼這個 nScale 就應該設定為8</param>
        /// <param name="faceNumber">使用者期望引擎最多能檢測出的人臉數有效值範圍[1,20]</param>
        /// <returns></returns>        
        [DllImport(DllPath, EntryPoint = "AFT_FSDK_InitialFaceEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Init(string appId, string sdkKey, byte[] buffer, int bufferSize, out IntPtr engine, int orientPriority, int scale, int faceNumber);
        [DllImport(DllPath, EntryPoint = "AFT_FSDK_FaceFeatureDetect", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Detection(IntPtr engine, ref ImageData imgData, out IntPtr pTraceResult);
        [DllImport(DllPath, EntryPoint = "AFT_FSDK_UninitialFaceEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Close(IntPtr engine);
    }

    internal class Match
    {
        private const string DllPath = "Libs/libarcsoft_fsdk_face_recognition.dll";
        [DllImport(DllPath, EntryPoint = "AFR_FSDK_InitialEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Init(string appId, string sdkKey, byte[] buffer, int bufferSize, out IntPtr engine);
        [DllImport(DllPath, EntryPoint = "AFR_FSDK_ExtractFRFeature", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int ExtractFeature(IntPtr engine, ref ImageData imageData, ref FaceFeatureInput faceFeatureInput, out FaceModel pFaceModels);
        [DllImport(DllPath, EntryPoint = "AFR_FSDK_FacePairMatching", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int FacePairMatch(IntPtr engine, ref FaceModel faceModel1, ref FaceModel faceModel2, out float score);
        [DllImport(DllPath, EntryPoint = "AFR_FSDK_UninitialEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Close(IntPtr engine);
    }
    internal class Age
    {
        private const string DllPosition = "libs/libarcsoft_fsdk_age_estimation.dll";

        [DllImport(DllPosition, EntryPoint = "ASAE_FSDK_InitAgeEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Init(string appId, string sdkKey, byte[] buffer, int bufferSize, out IntPtr engine);
        [DllImport(DllPosition, EntryPoint = "ASAE_FSDK_AgeEstimation_StaticImage", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int EstimationStatic(IntPtr engine, ref ImageData imgData, ref EstimationInput estimationInputInput, out EstimationResult pAgeResult);
        [DllImport(DllPosition, EntryPoint = "ASAE_FSDK_AgeEstimation_Preview", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int EstimationPreview(IntPtr engine, ref ImageData imgData, ref EstimationInput estimationInputInput, out EstimationResult pAgeResult);
        [DllImport(DllPosition, EntryPoint = "ASAE_FSDK_UninitAgeEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Close(IntPtr engine);
    }
    internal class Gender
    {
        private const string DllPosition = "libs/libarcsoft_fsdk_gender_estimation.dll";

        [DllImport(DllPosition, EntryPoint = "ASGE_FSDK_InitGenderEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Init(string appId, string sdkKey, byte[] buffer, int bufferSize, out IntPtr engine);
        [DllImport(DllPosition, EntryPoint = "ASGE_FSDK_GenderEstimation_StaticImage", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int EstimationStatic(IntPtr engine, ref ImageData imgData, ref EstimationInput estimationInputInput, out EstimationResult pGenderResult);
        [DllImport(DllPosition, EntryPoint = "ASGE_FSDK_GenderEstimation_Preview", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int EstimationPreview(IntPtr engine, ref ImageData imgData, ref EstimationInput estimationInputInput, out EstimationResult pGenderResesult);
        [DllImport(DllPosition, EntryPoint = "ASGE_FSDK_UninitGenderEngine", CallingConvention = CallingConvention.Cdecl, CharSet = CharSet.Ansi)]
        public static extern int Close(IntPtr engine);
    }
}

二、正式開始

1.新增一個Form，將Name改為“Main”，新增Load和FormClosing事件

2.拖一個Afoge.Controls.VideoSourcePlayer到Main，將Name改為“VideoPlayer”，新增Click事件；

3.拖一個PictureBox到Main，懶得改名字了，就叫“pictureBox1”；

4.拖一個Lable到Main，將Text改為“ID”；

5.拖一個TextBox到Main，將Name改為“TextBoxID”；

6.拖一個Button到Main，將Name改為ButtonRegister，將Text改為“註冊”，新增Click事件。

介面如下圖，從左到右，從上到下6個控制元件：

對應的程式碼為：

using AForge.Video.DirectShow;
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 FaceRecognization.Common;
using System.Runtime.InteropServices;
using System.Diagnostics;
using System.IO;
using System.Threading;
using System.Drawing.Imaging;

namespace FaceRecognization
{
    public partial class Main : Form
    {
        #region Property
        /// <summary>
        /// 儲存人臉資料的資料夾
        /// </summary>
        const string FeaturePath = "d:\\FeatureData";
        /// <summary>
        /// 虹軟SDK的AppId
        /// </summary>
        const string FaceAppId = "BKgqTWQPQQbomfqvyd2VJzTbzo5C4T5w4tzgN3GL6euK";
        /// <summary>
        /// 虹軟SDK人臉跟蹤的Key
        /// </summary>
        const string FaceTraceKey = "2Yqm2EcsJyBbJjSrirPSNoyHDRKCrS53XgUDeRRxtKyR";
        /// <summary>
        /// 虹軟SDK人臉檢測的Key
        /// </summary>
        const string FaceDetectKey = "2Yqm2EcsJyBbJjSrirPSNoyQNpaSJz19noCteLQ88SoG";
        /// <summary>
        /// 虹軟SDK人臉比對的Key
        /// </summary>
        const string FaceMatchKey = "2Yqm2EcsJyBbJjSrirPSNoyu2Rd4j1ydfwxwFX9vPmtY";
        /// <summary>
        /// 虹軟SDK年齡識別的Key
        /// </summary>
        const string FaceAgeKey = "2Yqm2EcsJyBbJjSrirPSNoz9ME9R4xnKU9yecD8Axu1D";
        /// <summary>
        /// 虹軟SDK性別識別的Key
        /// </summary>
        const string FaceGenderKey = "2Yqm2EcsJyBbJjSrirPSNozGWdQedYzhEUMw5FBegKVR";
        /// <summary>
        /// 快取大小
        /// </summary>
        const int BufferSize = 40 * 1024 * 1024;
        /// <summary>
        /// 人臉跟蹤的快取
        /// </summary>
        //byte[] _FaceTraceBuffer = new byte[BufferSize];
        /// <summary>
        /// 人臉檢測的快取
        /// </summary>
        byte[] _FaceDetectBuffer = new byte[BufferSize];
        /// <summary>
        /// 人臉比對的快取
        /// </summary>
        byte[] _FaceMatchBuffer = new byte[BufferSize];
        /// <summary>
        /// 年齡識別的快取
        /// </summary>
        //byte[] _FaceAgeBuffer = new byte[BufferSize];
        /// <summary>
        /// 性別識別的快取
        /// </summary>
        //byte[] _FaceGenderBuffer = new byte[BufferSize];
        /// <summary>
        /// 人臉跟蹤的引擎
        /// </summary>
        //IntPtr _FaceTraceEnginer = IntPtr.Zero;
        /// <summary>
        /// 人臉檢測的引擎
        /// </summary>
        IntPtr _FaceDetectEnginer = IntPtr.Zero;
        /// <summary>
        /// 人臉比對的引擎
        /// </summary>
        IntPtr _FaceMatchEngine = IntPtr.Zero;
        /// <summary>
        /// 年齡識別的引擎
        /// </summary>
        //IntPtr _FaceAgeEngine = IntPtr.Zero;
        /// <summary>
        /// 性別識別的引擎
        /// </summary>
        //IntPtr _FaceGenderEngine = IntPtr.Zero;
        /// <summary>
        /// 人臉庫字典
        /// </summary>
        Face.FaceLib _FaceLib = new Face.FaceLib();
        /// <summary>
        /// 攝像頭引數
        /// </summary>
        CameraPara _CameraPara = null;
        double _RateW, _RateH;
        private readonly ReaderWriterLockSlim _CacheLock = new ReaderWriterLockSlim();
        Face.FaceResult _FaceResult = new Face.FaceResult();
        System.Threading.CancellationTokenSource _CancellationTokenSource = new System.Threading.CancellationTokenSource();
        bool _RegisterClicked = false;
        byte[] _RegisterFeatureData = null;
        #endregion
        public Main()
        {
            InitializeComponent();
        }


        private void Main_Load(object sender, EventArgs e)
        {

            if (!Directory.Exists(FeaturePath))
                Directory.CreateDirectory(FeaturePath);

            foreach (var file in Directory.GetFiles(FeaturePath))
            {
                var info = new FileInfo(file);
                var data = File.ReadAllBytes(file);
                var faceModel = new Face.FaceModel
                {
                    lFeatureSize = data.Length,
                    pbFeature = Marshal.AllocHGlobal(data.Length)
                };

                Marshal.Copy(data, 0, faceModel.pbFeature, data.Length);
                _FaceLib.Items.Add(new Face.FaceLib.Item() { OrderId = 0, ID = info.Name.Replace(info.Extension, ""), FaceModel = faceModel });
            }
            _CameraPara = new Common.CameraPara();
            if (!_CameraPara.HasVideoDevice)
            {
                MessageBox.Show("沒有檢測到攝像頭");
                this.Close();
                return;
            }

            this.VideoPlayer.VideoSource = _CameraPara.VideoSource;
            this.VideoPlayer.Start();

            _RateH = 1.0 * this.VideoPlayer.Height / this._CameraPara.FrameHeight;
            _RateW = 1.0 *  
 

            
  
           

              
              
            
            
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 一，準備工作 
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怎麼使用Vin碼識別sdk/車架號識別sdk？
     
 關鍵詞：車架號識別；vin碼識別；汽車vin碼識別；汽車車架號識別；行駛證vin碼識別；行駛證車架識別；移動vin碼識別。 
一、汽車Vin碼識別sdk/車架號識別sdk： 
1、在保險行業、財險行業：從事理賠方面工作的朋友一定會經常遇到抄錄行駛證上的車架號（VIN碼）的情況； 
2、二手車行業的朋友也一定會 

  
 

    

    
    
新能源車牌識別sdk，這麼識別就對了？
     
  
 
 未來汽車的發展方向之一應該是新能源汽車，眼下我們就可以發現新能源汽車市場不斷地發展、市場不斷地壯大。對於這種異軍突起的車輛，我們如何區別對待，不光是在動力補給上有所不同，車牌號的樣式也要獨特化。新能源汽車必須要有專用車牌，而新能源汽車車牌識別技術也要有些改進才可。 
 易泊車牌識別SDK在智慧交通系 

  
 

    

    
    
怎麼使用Vin碼識別sdk/車架號識別sdk
     
 
							
							
							關鍵詞：車架號識別；vin碼識別；汽車vin碼識別；汽車車架號識別；行駛證vin碼識別；行駛證車架識別；移動vin碼識別。
一、汽車Vin碼識別sdk/車架號識別sdk：
1、在保險行業、財險行業：從事理賠方面工作的朋友一定會經常遇到抄錄行駛證上的車架號（VIN 

  
 

    

    
    
訊飛語音識別SDK整合 語音識別 語音合成 訊飛英語識別
     
 
							
							
							最近專案集成了訊飛語音識別功能，由此記錄簡單的整合流程



demo效果（logcat）



資源下載





1、首先用as建一個model （這個不用介紹）



2、登入訊飛開發者平臺，進入控制檯，建立應用生成appid


  1、 建立應用


 

  
 

    

    
    
Android開發學習之使用百度語音識別SDK實現語音識別(上)
     
 
                
        作為移動網際網路殺手級的互動方式，語音識別從問世以來就一直備受人們的關注，從IOS的Siri到國內的訊飛語音，語音識別技術在移動開發領域是最為充滿前景和希望的技術。Android作為一個移動作業系統，其本身就繼承了Google天生的搜尋基因，因此Androi 

  
 

    

    
    
C# 基於Arcface SDK實現人臉識別和註冊
     
 
                                        
                                                整個專案使用虹軟技術完成開發
一，準備工作
1.Afoge視訊引數類
using AForge.Video.DirectShow; 

  
 

    

    
    
【下載】推薦一款免費的人臉識別SDK
     
 firefly   linux   rk3399   ubuntu   開源硬件   人臉識別        現已進入刷臉的時代，例如，人臉支付、人臉識別的門禁、人流監控等等。如何在Firefly開源板上快速搭建DEMO，並快速產品化？為了讓更多產品可以用上人臉識別技術，Firefly推出了一款高性能人臉識別 

  
 

    

    
    
C#實現基於ffmpeg加虹軟的人臉識別
     
 ffmpeg   開源   基於   進行   space   包裝   php   c#   同時   基於ffmpeg和虹軟人臉識別庫的C#開源實現，對虹軟人臉識別庫進行了包裝，便於在C#中快速、安全的調用識別函數。同時，開源代碼中，包含完整的實現示例
 
http://pic.cnhubei.com 

  
 

    

    
    
Unity2018基於百度SDK的人臉識別
     
 
                百度AI 中人臉識別，也可以應用到遊戲裡面 下面給出 一張 圖百度api 下載 好sdk   後// 設定APPID/AK/SKvar APP_ID = "你的 App ID";var API_KEY = "你的 Api Key";var SECRET_KEY = "你的 S 

  
 

    

    
    
虹軟免費人臉識別SDK註冊指南
     
 開發者   管理   內容   單元   其他   疑問   登錄   ESS   標識   
成為開發者三步完成賬號的基本註冊與認證：STEP1:點擊註冊虹軟AI開放平臺右上角註冊選項，完成註冊流程。STEP2:首次使用，登錄後進入開發者中心，點擊賬號管理完成企業或者個人認證，若未進行實名認證，部分功能將受 

  
 

    

    
    
程序猿福利來啦，神目AI開放平臺免費送人臉識別SDK啦
     
 平臺   text   ffffff   程序   col   src   人臉識別   技術   ces   程序猿福利來啦，神目AI開放平臺免費送人臉識別SDK啦 

  
 

    

    
    
Android  虹軟免費人臉識別 SDK開發
     
 一次   tst   足夠   到手   柵格   roi   sta   開發   true   目前我們的應用內使用了 ArcFace 的人臉檢測功能，其他的我們並不了解，所以這裏就和大家分享一下我們的集成過程和一些使用心得集成ArcFace FD 的集成過程非常簡單在 ArcFace FD 的文檔上有說 

  
 

    

    
    
基於虹軟的Android的人臉識別SDK使用測試
     
 
                                        
                                                現在有很多人臉識別的技術我們可以拿來使用；但是個人認為還是離線端的SDK比較實用；所以個人一直在蒐集人臉識別的SDK；原來使用開源 

  
 

    

    
    
C#實現基於ffmpeg加虹軟的人臉識別demo及開發分享
     
 
                                        
                                                對開發庫的C#封裝，遮蔽使用細節，可以快速安全的呼叫人臉識別相關API。具體見github地址。新增對.NET Core的支援，在 

  
 

    

    
    
C# 虹軟SDK視訊人臉識別和註冊
     
 
                                        
                                                一，準備工作
1.Afoge視訊引數類
程式碼using AForge.Video.DirectShow;
using Syste 

  
 

    

    
    
SmileyFace——基於OpenCV的人臉人眼檢測、面部識別程序
     
 tro   識別   open   HR   tps   應用   動態   框圖   顯示   
項目地址
https://github.com/guoyaohua/SmileyFace
開發環境
Visual Studio 2010
MFC + OpenCV
功能描述

靜態圖像人臉檢測
視頻人臉追蹤檢測 

  
 

    

    
    
基於Triplet loss函數訓練人臉識別深度網絡（Open Face）
     
 驗證   ofo   擴大   沒有   detect   sent   euc   research   邏輯   Git:  http://cmusatyalab.github.io/openface/
FaceNet’s innovation comes from four distinct facto 

  
 

    

    
    
《基於剪下波變換的人臉表情識別》筆記
     
  
 
 【時間】2018.10.16 
 【題目】《基於剪下波變換的人臉表情識別》筆記 
 【論文連結】http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y2102266 
 概述 
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