namespace SmartAdmin.Application.Photos.Commands
{
  public partial class AddPhotoCommand : IRequest<Result<int>>
  {
    public Stream Stream { get; set; }
    public string FileName { get; set; }
    public decimal Size { get; set; }
    public string Path { get; set; }

  }
  internal class AddPhotoCommandHandler : IRequestHandler<AddPhotoCommand, Result<int>>
  {
    private readonly IUnitOfWork unitOfWork;
    private readonly IPhotoService photoService;

    public AddPhotoCommandHandler(IUnitOfWork unitOfWork,
      IPhotoService photoService)
    {
      this.unitOfWork = unitOfWork;
      this.photoService = photoService;
    }
    public async Task<Result<int>> Handle(AddPhotoCommand request, CancellationToken cancellationToken)
    {
      var info = new DirectoryInfo(request.Path);
      if (!info.Exists)
      {
        info.Create();
      }
      using (FileStream outputFileStream = new FileStream(Path.Combine(request.Path,request.FileName), FileMode.Create))
      {
        request.Stream.CopyTo(outputFileStream);
        outputFileStream.Close();
      }
      var photo = new Photo()
      {
        Name = Path.GetFileNameWithoutExtension(request.FileName),
        Size = request.Size,
        Path = $"/photos/{request.FileName}",
      };
      this.photoService.Insert(photo);
      await this.unitOfWork.SaveChangesAsync();
      return await Result<int>.SuccessAsync(0, "保存成功");
    }

  }
}

 function predict() {
      const img = document.getElementById('photo-canvas');
      facemesh.predict(img).then(faces => {
        console.log(faces)
        if (faces) {
          const canvas = document.getElementById("photo-canvas");
          const photoId=canvas.getAttribute("photo-id");
          const photoName=canvas.getAttribute("photo-name");
          console.log(canvas)
          var draw = canvas.getContext("2d");
          var mesh = faces[0].scaledMesh;
          console.log(mesh);
          /* highlight facial landmark points on canvas board */
          draw.fillStyle = "#00FF00";
          for (i = 0; i < mesh.length; i++) {
            var [x, y, z] = mesh[i];
            draw.fillRect(Math.round(x), Math.round(y), 2, 2);
          }
          updateLandmarks(photoId,JSON.stringify(mesh));
          knnClassifier.addExample(mesh, photoName);
          canvas.setAttribute("photo-mesh", JSON.stringify(mesh));
          $('#testbutton').attr('disabled', false);
        }
      });
    }

   function updateLandmarks(id,landmarks){
     $.post('/Photos/Update',{Id:id,Landmarks:landmarks}).done(res=>{
      console.log(res);
      reload();
     }).fail(res=>{
      $.messager.alert('更新失败', res, 'error');
     })
    }　

let knnClassifier =ml5.KNNClassifier();
    function training(){
       $.messager.progress({msg:'training....'});
       $.get('/Photos/GetAll').done(res=>{
        for(let i=0;i<50;i++){
        res.map(item=>{
        if(item.Landmarks){
        knnClassifier.addExample(JSON.parse(item.Landmarks), item.Name);
        }
        });
        }
        $.messager.progress('close')
           if(knnClassifier.getNumLabels()>0){
           knnClassifier.classify(JSON.parse(res[2].Landmarks),(err,result)=>{
             console.log(result);
         })
       $('#testbutton').attr('disabled', false);
       }
       })
    }

function testPredict(){
      const img = document.getElementById('testphoto_img');
      facemesh.predict(img).then(faces => {
        console.log(faces)
        if (faces) {
          knnClassifier.classify(faces[0].scaledMesh,(err,result)=>{
          console.log(result);
          $.messager.alert('Result:',result.label);
          $('#testresult').text(result.label);
         })
        }
      });
    }