public async Task <IActionResult> UploadImage(IFormFile file, [FromForm] string name, [FromForm] string tags)
{
if (file == null)
{
file = Request.Form.Files[0];
}
ImageOutput output = new ImageOutput();
if (file != null)
{
if (file.Length > 0)
{
//验证是否是图片
if (ImageValidation.IsCheck(file))
{
ImageInput input = new ImageInput();
input.File = file;
input.Name = name;
input.Tags = tags;
ImageHandleService handleService = new ImageHandleService();
//处理图片
output = await handleService.Processing(input, Request);
return(Ok(output));
}
}
}
return(BadRequest("图片上传失败！"));
}
public void GivenAThreeByThreeInputAndATwoByTwoFilter_WhenTheFilterIsSlid_ItShouldReturnAMappedRepresentationOfTheNextSection()
{
StrideBasedSlideRetrievalStrategy strategy = new StrideBasedSlideRetrievalStrategy();
Position position = new Position(0, 0, 1);
double[,] matrix = new double[4, 4];
matrix[0, 0] = 0;
matrix[0, 1] = 1;
matrix[0, 2] = 2;
matrix[1, 0] = 3;
matrix[1, 1] = 4;
matrix[1, 2] = 5;
matrix[2, 0] = 6;
matrix[2, 1] = 7;
matrix[2, 2] = 8;
ImageInput input = new ImageInput(new TwoDimensionalMapper(), new Configuration());
input.SetNumericRepresentation(matrix);
Slider slider = new Slider(position, 2, 2, 4, true);
double[] slide = strategy.GetSlide(input, slider);
double[] expected = { 0, 1, 3, 4 };
Assert.IsTrue(Enumerable.SequenceEqual(expected, slide));
}
public void GivenAFourByFourInputAndATwoByTwoFilter_WhenTheNeuronIsActivated_ItShouldReturnAFeatureMap()
{
FeatureMapNeuronActivationStrategy strategy = new FeatureMapNeuronActivationStrategy(MockDotProduct(), new Configuration());
double[,] matrix = new double[3, 3];
matrix[0, 0] = 0;
matrix[0, 1] = 1;
matrix[0, 2] = 2;
matrix[1, 0] = 3;
matrix[1, 1] = 4;
matrix[1, 2] = 5;
matrix[2, 0] = 6;
matrix[2, 1] = 7;
matrix[2, 2] = 8;
ImageInput input = new ImageInput(new TwoDimensionalMapper(), new Configuration());
input.SetNumericRepresentation(matrix);
double[] mockFilter = new double[4];
double[] featureMap = strategy.Activate(input, mockFilter);
double[] expected = { 0.3, 2.7, 6.2, 1.9 };
Assert.IsTrue(Enumerable.SequenceEqual(expected, featureMap));
}
public void GivenAnInputSubsectionAndAFilter_WhenAFeatureMapPartIsCalculated_ItShouldCallTheDotProductConvoluteFunction()
{
double[,] inputSubsection = new double[3, 3];
inputSubsection[0, 0] = 0;
inputSubsection[0, 1] = 1;
inputSubsection[1, 0] = 2;
inputSubsection[1, 1] = 4;
double[] filter = { 0.1, 0.2 };
ImageInput input = new ImageInput(new TwoDimensionalMapper(), new Configuration());
input.SetNumericRepresentation(inputSubsection);
Mock <IDotProductConvolutionStrategy> dotProductMock = new Mock <IDotProductConvolutionStrategy>();
dotProductMock.SetupSequence(x => x.Calculate(It.IsAny <double[]>(), It.IsAny <double[]>()))
.Returns(0.3).Returns(2.7)
.Returns(6.2).Returns(1.9)
.Returns(3.4).Returns(0.8);
FeatureMapNeuronActivationStrategy strategy = new FeatureMapNeuronActivationStrategy(dotProductMock.Object, new Configuration());
double part = strategy.ConvolveSubSection(input.GetNumericRepresentation(), filter);
dotProductMock.Verify(c => c.Calculate(It.IsAny <double[]>(), It.IsAny <double[]>()), Times.Exactly(1));
}
public void GivenAFourByFourInputAndATwoByTwoFilter_WhenTheFilterIsSlidFromTheEnd_ItShouldReturnARepresentationOfTheLeftestSectionOneLevelDown()
{
StrideBasedSlideRetrievalStrategy strategy = new StrideBasedSlideRetrievalStrategy();
Position position = new Position(2, 0, 1);
double[,] matrix = new double[4, 4];
matrix[0, 0] = 0;
matrix[0, 1] = 1;
matrix[0, 2] = 2;
matrix[0, 3] = 3;
matrix[1, 0] = 4;
matrix[1, 1] = 5;
matrix[1, 2] = 6;
matrix[1, 3] = 7;
matrix[2, 0] = 8;
matrix[2, 1] = 9;
matrix[2, 2] = 10;
matrix[2, 3] = 11;
matrix[3, 0] = 12;
matrix[3, 1] = 13;
matrix[3, 2] = 14;
matrix[3, 3] = 15;
ImageInput input = new ImageInput(new TwoDimensionalMapper(), new Configuration());
input.SetNumericRepresentation(matrix);
Slider slider = new Slider(position, 2, 2, 4, true);
double[] slide = strategy.GetSlide(input, slider);
double[] expected = { 2, 3, 6, 7 };
Assert.IsTrue(Enumerable.SequenceEqual(expected, slide));
}
public void GivenAnIImageInput_WhenTheImageInputIsSplit_ItShouldReturnAListOfSmallerImageInputs()
{
Mock <IConfiguration> config = new Mock <IConfiguration>();
config.Setup(x => x.GetValue(It.IsAny <string>())).Returns("2");
ImageInput imageInput = new ImageInput(new TwoDimensionalMapper(), config.Object);
double[,] matrix = new double[4, 4];
matrix[0, 0] = 0;
matrix[0, 1] = 1;
matrix[0, 2] = 2;
matrix[0, 3] = 3;
matrix[1, 0] = 4;
matrix[1, 1] = 5;
matrix[1, 2] = 6;
matrix[1, 3] = 7;
matrix[2, 0] = 8;
matrix[2, 1] = 9;
matrix[2, 2] = 10;
matrix[2, 3] = 11;
matrix[3, 0] = 12;
matrix[3, 1] = 13;
matrix[3, 2] = 14;
matrix[3, 3] = 15;
imageInput.SetNumericRepresentation(matrix);
List <double[]> result = imageInput.GetSplitSubsections();
Assert.IsTrue(result[0].SequenceEqual(new double[] { 0, 1, 4, 5 }));
Assert.IsTrue(result[1].SequenceEqual(new double[] { 2, 3, 6, 7 }));
Assert.IsTrue(result[2].SequenceEqual(new double[] { 8, 9, 12, 13 }));
Assert.IsTrue(result[3].SequenceEqual(new double[] { 10, 11, 14, 15 }));
}
public IActionResult PostImage(ImageInput image)
{
var imageProduct = new ImageMv();
imageProduct.CreateBy = Guid.Parse("a845b16a-4ca6-48e2-4ca6-08d817450c1a");
imageProduct.ProductId = image.ProductId;
//convert to image to base 64
var ms = new MemoryStream();
image.FileInput.CopyTo(ms);
var fileBytes = ms.ToArray();
string s = Convert.ToBase64String(fileBytes);
imageProduct.FileInput = s;
if (ImageBus.PostImage(imageProduct).Result)
{
TempData[ConstKey.Success] = "Add Success!";
}
else
{
TempData[ConstKey.Error] = "Fail, Try again !";
}
return(RedirectToAction("ForProduct", "ImageProduct", new { productId = image.ProductId }));
}
private void SendImage(object sender, RoutedEventArgs e)
{
foreach (string path in ImageInput.Text.Split(new char[] { '\r', '\n' }, StringSplitOptions.RemoveEmptyEntries))
{
m_vm.ImageProvider.SendImage(path);
}
ImageInput.Clear();
}
private void TemplateSet_Load(object sender, EventArgs e)
{
if (!ReferenceEquals(m_imageInput, null))
{
aqDisplayCreateModel.Image = ImageInput.Clone() as Bitmap;
aqDisplayCreateModel.FitToScreen();
aqDisplayCreateModel.Update();
}
}
public void GivenAnIImageInputIsInitialised_WhenThePositionIsRetrieved_ItShouldUseTheMapperToReturnAnArrayRepresentation()
{
Mock <ITwoDimensionalMapper> mapperMock = new Mock <ITwoDimensionalMapper>();
ImageInput imageInput = new ImageInput(mapperMock.Object, new Configuration());
double[] result = imageInput.GetNumericRepresentation();
mapperMock.Verify(c => c.GetArrayRepresentation(It.IsAny <double[, ]>()), Times.Exactly(1));
}
public List <double[]> Convolve(ImageInput imageSubsection, List <double[]> filters)
{
List <double[]> featureMaps = new List <double[]>();
foreach (double[] filter in filters)
{
featureMaps.Add(neuronActivationStrategy.Activate(imageSubsection, filter));
}
return(featureMaps);
}
public IActionResult UploadImageCad(ImageInput imageInput)
{
if (ModelState.IsValid)
{
var CurrentDate = DateTime.Now;
var UploadDate = CurrentDate.ToString("yyyyMMdd_hhmmss");
var userfileName = User.Identity.Name.ToString();
var RootFolder = _hostingEnvironment.WebRootPath;
var UsersFileLocation = "UsersDirectory";
//var RootFfolderString = "wwwroot";
var DxfFileExtension = ".dxf";
var UserDirectory = $"{_hostingEnvironment.WebRootPath}/{UsersFileLocation}/{userfileName}/{UploadDate}";
//var UserFilesDirectoryRelative = $"{RootFfolderString}/{UsersFileLocation}/{userfileName}/{UploadDate}";
var UserFilesDirectoryRelative = $"{UsersFileLocation}/{userfileName}/{UploadDate}";
// var ImageFileLocationPaths = new List<String>();
var uploads = Path.Combine(RootFolder, UsersFileLocation, userfileName, UploadDate);
//Check if user Directory exsists , if not creates new directory
var exsits = Directory.Exists(UserDirectory);
if (!exsits)
{
Directory.CreateDirectory(UserDirectory);
}
var filePathName = ContentDispositionHeaderValue.Parse(imageInput.ImageFile.ContentDisposition).FileName.Trim('"');
var fileExtention = Path.GetExtension(filePathName);
if (!(fileExtention == ".jpg" || fileExtention == ".JPG" || fileExtention == ".PNG" || fileExtention == ".png"))
{
return(RedirectToAction("ErrorPage"));
}
var fileName = Guid.NewGuid().ToString("N").Substring(0, 10);
var FileNameFull = fileName + fileExtention;
var StaticPath = Path.Combine(uploads, FileNameFull);
var StaticPathNameNoExtension = Path.Combine(uploads, fileName);
var RelativePaths = $"{UserFilesDirectoryRelative}/{fileName}" + $"{fileExtention}";
//the image will be saved with a unique filename
FileStream DestinationStream = new FileStream(StaticPath, FileMode.CreateNew);
imageInput.ImageFile.CopyTo(DestinationStream);
var DxfFileName = Guid.NewGuid().ToString("N").Substring(0, 10);
var DxfFileStaticPath = Path.Combine(uploads, DxfFileName);
var DxFRelativePaths = $"{UserFilesDirectoryRelative}/{DxfFileName}" + $"{DxfFileExtension}";
TempData["DxfFileStaticPath"] = DxfFileStaticPath;
TempData["DxFRelativePaths"] = DxFRelativePaths;
TempData["ImagePath"] = RelativePaths;
TempData["StaticImagePath"] = StaticPath;
TempData["FileNameFull"] = FileNameFull;
return(RedirectToAction("CanvasDrawer"));
}
else
{
return(View("Error"));
}
}
internal MediaInput(GroupCall groupCall, GroupCall room, TeamsMeeting teamsMeeting, RtmpStream rtmp, SrtStream srt, ParticipantInput participant, CommunicationCallIdentifierModel activePresenter, CommunicationCallIdentifierModel dominantSpeaker, CommunicationCallIdentifierModel screenShare, ImageInput image, MediaInputType?kind)
{
GroupCall = groupCall;
Room = room;
TeamsMeeting = teamsMeeting;
Rtmp = rtmp;
Srt = srt;
Participant = participant;
ActivePresenter = activePresenter;
DominantSpeaker = dominantSpeaker;
ScreenShare = screenShare;
Image = image;
Kind = kind;
}
public IActionResult DeleteFile(ImageInput lImage)
{
try
{
_propertyService.DeleteFiles(lImage.uri);
return(Ok());
}
catch (System.Exception e)
{
_logger.LogError(e, "error: {0}", e.Message);
return(BadRequest());
}
}
public void GivenAnIImageInput_WhenTheImageInputNumericRepresentationIsSet_ItShouldSetTheTotalRows()
{
ImageInput imageInput = new ImageInput(new TwoDimensionalMapper(), new Configuration());
double[,] numericRepresentation = new double[2, 2];
numericRepresentation[0, 0] = 1;
numericRepresentation[0, 1] = 2;
numericRepresentation[1, 0] = 3;
numericRepresentation[1, 1] = 4;
imageInput.SetNumericRepresentation(numericRepresentation);
Assert.AreEqual(2, imageInput.TotalRows);
}
public void GivenAnIImageInput_WhenTheImageInputNumericRepresentationIsSet_ItShouldReturnTheSetDataWhenRetrieved()
{
ImageInput imageInput = new ImageInput(new TwoDimensionalMapper(), new Configuration());
double[,] numericRepresentation = new double[2, 2];
numericRepresentation[0, 0] = 1;
numericRepresentation[0, 1] = 2;
numericRepresentation[1, 0] = 3;
numericRepresentation[1, 1] = 4;
imageInput.SetNumericRepresentation(numericRepresentation);
double[] result = imageInput.GetNumericRepresentation();
double[] expected = { 1, 2, 3, 4 };
Assert.IsTrue(result.SequenceEqual(expected));
}
public void GivenAnImageSubsectionAndThreeFilters_WhenConvolutionOccurs_ItShouldReturinAListOfFeatureMaps()
{
Mock <IFeatureMapNeuronActivationStrategy> mock = new Mock <IFeatureMapNeuronActivationStrategy>();
mock.SetupSequence(x => x.Activate(It.IsAny <ImageInput>(), It.IsAny <double[]>()))
.Returns(new double[4] {
0.2, 1.3, 0.8, 3.1
})
.Returns(new double[4] {
0.8, 5.2, 1.1, 1.1
})
.Returns(new double[4] {
0.1, 1.1, 0.5, 0.4
});
ImageInput input = new ImageInput(new TwoDimensionalMapper(), new Configuration());
input.SetNumericRepresentation(new double[4, 4]);
List <double[]> filters = new List <double[]>()
{
new double[2], new double[2], new double[2]
};
Convolution convolution = new Convolution(mock.Object);
List <double[]> result = convolution.Convolve(input, filters);
List <double[]> expectation = new List <double[]>();
expectation.Add(new double[4] {
0.2, 1.3, 0.8, 3.1
});
expectation.Add(new double[4] {
0.8, 5.2, 1.1, 1.1
});
expectation.Add(new double[4] {
0.1, 1.1, 0.5, 0.4
});
Assert.IsTrue(expectation[0].SequenceEqual(result[0]));
Assert.IsTrue(expectation[1].SequenceEqual(result[1]));
Assert.IsTrue(expectation[2].SequenceEqual(result[2]));
}
private static string SaveImageOnServer(ImageInput input)
{
if (string.IsNullOrEmpty(input?.ImageId) || input.Image == null)
{
return(null);
}
var dir = Directory.GetCurrentDirectory();
var path = FilesPath + PicturesPath;
var dbpath = DbFilesPath + PicturesPath;
var folder = input.Type == FileType.Jpeg ? PicturesPathJpeg : PicturesPathWebp;
var extension = input.Type == FileType.Jpeg ? ".jpeg" : ".webp";
var samePath = folder + "/" + input.ImageId + extension;
var result = dbpath + samePath;
var imagePath = dir + path + samePath;
if (!Directory.Exists(dir + path))
{
Directory.CreateDirectory(dir + path);
}
if (!Directory.Exists(dir + path + folder))
{
Directory.CreateDirectory(dir + path + folder);
}
try
{
var img = System.Drawing.Image.FromStream(new MemoryStream(input.Image));
img.Save(imagePath, System.Drawing.Imaging.ImageFormat.Jpeg);
}
catch
{
return(null);
}
return(result);
}
public void GivenAnInputSubsectionAndAFilter_WhenAFeatureMapPartIsCalculated_ItShouldReturnTheDotProduct()
{
double[,] inputSubsection = new double[3, 3];
inputSubsection[0, 0] = 0;
inputSubsection[0, 1] = 1;
inputSubsection[1, 0] = 2;
inputSubsection[1, 1] = 4;
double[] filter = { 0.1, 0.2 };
ImageInput input = new ImageInput(new TwoDimensionalMapper(), new Configuration());
input.SetNumericRepresentation(inputSubsection);
FeatureMapNeuronActivationStrategy strategy = new FeatureMapNeuronActivationStrategy(MockDotProduct(), new Configuration());
double part = strategy.ConvolveSubSection(input.GetNumericRepresentation(), filter);
Assert.AreEqual(0.3, part);
}
public double[] GetSlide(ImageInput input, Slider slider)
{
int initialIndex = indexCalculator.GetIndex(input.TotalColumns, slider.Position.X, slider.Position.Y);
int skipCount = initialIndex;
int filterDimensions = slider.SliderWidth * slider.SliderHeight;
int maximumIndex = filterDimensions + initialIndex + slider.SliderHeight;
double[] newSlide = new double[0];
while (skipCount < maximumIndex)
{
newSlide = newSlide.Concat(input.GetNumericRepresentation()
.Select(i => i)
.Skip(skipCount)
.Take(slider.SliderWidth))
.ToArray();
skipCount += input.TotalColumns;
}
return(newSlide);
}
public async Task <bool> pushImage(ImageInput input)
{
var config = this.Configuration.GetSection("Key")["containerName"];
try
{
var blob = blobService.GetBlob("sessionGuid", config);
if (blob != null)
{
var fileName = input.user.Id + "/" + input.user.Id + "-" + input.sessionGuid + "/" + input.imageName;
await blobService.UploadFileBlob(fileName, input.image, config);
}
return(true);
}
catch (Exception ex)
{
_logger.LogError(ex.Message);
return(false);
}
}
public void GivenAFourByFourInputAndAThreeByThreeFilter_WhenTheFilterIsSlid_ItShouldReturnAMappedRepresentationOfTheNextSection()
{
Mock <IConfiguration> configuration = new Mock <IConfiguration>();
configuration.Setup(x => x.GetValue(It.IsAny <String>())).Returns("3");
StrideBasedSlideRetrievalStrategy strategy = new StrideBasedSlideRetrievalStrategy();
Position position = new Position(0, 0, 1);
double[,] matrix = new double[4, 4];
matrix[0, 0] = 0;
matrix[0, 1] = 1;
matrix[0, 2] = 2;
matrix[0, 3] = 3;
matrix[1, 0] = 4;
matrix[1, 1] = 5;
matrix[1, 2] = 6;
matrix[1, 3] = 7;
matrix[2, 0] = 8;
matrix[2, 1] = 9;
matrix[2, 2] = 10;
matrix[2, 3] = 11;
matrix[3, 0] = 12;
matrix[3, 1] = 13;
matrix[3, 2] = 14;
matrix[3, 3] = 15;
ImageInput input = new ImageInput(new TwoDimensionalMapper(), new Configuration());
input.SetNumericRepresentation(matrix);
Slider slider = new Slider(position, 3, 3, 4, true);
double[] slide = strategy.GetSlide(input, slider);
double[] expected = { 0, 1, 2, 4, 5, 6, 8, 9, 10 };
Assert.IsTrue(Enumerable.SequenceEqual(expected, slide));
}
public async Task <IActionResult> UploadImages(List <IFormFile> files)
{
if (files.Count == 0)
{
if (Request.Form.Files.Count > 0)
{
foreach (var item in Request.Form.Files)
{
files.Add(item);
}
}
}
if (files.Count > 0)
{
List <ImageInput> imageInputs = new List <ImageInput>();
foreach (var file in files)
{
if (file.Length > 0)
{
//验证是否是图片
if (ImageValidation.IsCheck(file))
{
ImageInput input = new ImageInput();
input.File = file;
input.Name = file.Name;
input.Tags = file.Name;
imageInputs.Add(input);
}
}
}
ImageHandleService handleService = new ImageHandleService();
//处理图片
var output = await handleService.ProcessingImages(imageInputs, Request);
return(Ok(output));
}
return(BadRequest("图片上传失败！"));
}
public double[] Activate(ImageInput input, double[] filter)
{
int stride = Int32.Parse(configuration.GetValue("Stride"));
int finalIndex = input.TotalColumns * input.TotalRows;
int filterWidth = Int32.Parse(configuration.GetValue("FilterWidth"));
int filterHeight = Int32.Parse(configuration.GetValue("FilterHeight"));
Position position = new Position(0, 0, stride);
Slider slider = new Slider(position, filterWidth, filterHeight, input.TotalColumns, true);
List <Double> featureMap = new List <double>();
int totalFeatureSections = (input.TotalRows - 1) * (input.TotalColumns - 1);
while (featureMap.Count() < totalFeatureSections)
{
slider.Slide();
double[] slide = this.slidingStrategy.GetSlide(input, slider);
featureMap.Add(this.ConvolveSubSection(slide, filter));
}
return(featureMap.ToArray());
}
public ActionResult CreateStep2(ImageView model)
{
var image = WebImage.GetImageFromRequest();
if (image != null)
{
if (image.Width > 500)
{
image.Resize(500, ((500 * image.Height) / image.Width));
}
var filename = Path.GetFileName(image.FileName);
image.Save(Path.Combine(BlogGlobals.TemporaryImageFolder, filename));
filename = Path.Combine(BlogGlobals.TemporaryImageFolder, filename);
model.ImageUrl = Url.Content(filename);
var imageInput = new ImageInput()
{
Image = model,
Width = image.Width,
Height = image.Height,
Top = image.Height * 0.1,
Left = image.Width * 0.9,
Right = image.Width * 0.9,
Bottom = image.Height * 0.9
};
return View("CreateStep2", imageInput);
}
return RedirectToAction("CreateStep1");
//return View("CreateStep1", model);
}
private void ImageInput_MouseMove(object sender, System.Windows.Forms.MouseEventArgs e)
{
toolTip1.SetToolTip(ImageInput, e.X.ToString() + ", " + e.Y.ToString());
Pen ppen = new Pen(mlinecolor, 1);
Graphics g;
ImageInput.Refresh();
try
{
g = ImageInput.CreateGraphics();
Rectangle rec = new Rectangle(e.X, e.Y, (int)(WindowSize * Convert.ToInt32(scalepercentage.Text) / 100), (int)(WindowSize * Convert.ToInt32(scalepercentage.Text) / 100));
g.DrawRectangle(ppen, rec);
current.X = e.X;
current.Y = e.Y;
ppen.Color = Color.Red;
g.DrawLine(ppen, ImageInput.Width / 2, ImageInput.Top, ImageInput.Width / 2, ImageInput.Height);
g.DrawLine(ppen, 0, ImageInput.Height / 2, ImageInput.Width, ImageInput.Height / 2);
ppen.Color = Color.LightBlue;
}
catch (Exception ex)
{
MessageBox.Show(ex.Message.ToString(), "Error", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
/// <summary>
/// This is used by child HighDimensionVisualizer windows
/// </summary>
private Tuple<UIElement, VectorInt> GetPreviewImage(ISOMInput input)
{
bool showHash = chkVisualizerShowHash.IsChecked.Value;
ImageInput nodeImage = input as ImageInput;
if (nodeImage == null)
{
// This is probably a node, instead of an input image (the nodes are sent as static control points)
nodeImage = new ImageInput(null, input.Weights, input.Weights);
showHash = true;
}
return GetPreviewImage(nodeImage, showHash, 80, false, -1);
}
internal static MediaInput DeserializeMediaInput(JsonElement element)
{
Optional <GroupCall> groupCall = default;
Optional <GroupCall> room = default;
Optional <TeamsMeeting> teamsMeeting = default;
Optional <RtmpStream> rtmp = default;
Optional <SrtStream> srt = default;
Optional <ParticipantInput> participant = default;
Optional <CommunicationCallIdentifierModel> activePresenter = default;
Optional <CommunicationCallIdentifierModel> dominantSpeaker = default;
Optional <CommunicationCallIdentifierModel> screenShare = default;
Optional <ImageInput> image = default;
Optional <MediaInputType> kind = default;
foreach (var property in element.EnumerateObject())
{
if (property.NameEquals("groupCall"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
groupCall = GroupCall.DeserializeGroupCall(property.Value);
continue;
}
if (property.NameEquals("room"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
room = GroupCall.DeserializeGroupCall(property.Value);
continue;
}
if (property.NameEquals("teamsMeeting"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
teamsMeeting = TeamsMeeting.DeserializeTeamsMeeting(property.Value);
continue;
}
if (property.NameEquals("rtmp"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
rtmp = RtmpStream.DeserializeRtmpStream(property.Value);
continue;
}
if (property.NameEquals("srt"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
srt = SrtStream.DeserializeSrtStream(property.Value);
continue;
}
if (property.NameEquals("participant"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
participant = ParticipantInput.DeserializeParticipantInput(property.Value);
continue;
}
if (property.NameEquals("activePresenter"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
activePresenter = CommunicationCallIdentifierModel.DeserializeCommunicationCallIdentifierModel(property.Value);
continue;
}
if (property.NameEquals("dominantSpeaker"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
dominantSpeaker = CommunicationCallIdentifierModel.DeserializeCommunicationCallIdentifierModel(property.Value);
continue;
}
if (property.NameEquals("screenShare"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
screenShare = CommunicationCallIdentifierModel.DeserializeCommunicationCallIdentifierModel(property.Value);
continue;
}
if (property.NameEquals("image"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
image = ImageInput.DeserializeImageInput(property.Value);
continue;
}
if (property.NameEquals("kind"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
kind = new MediaInputType(property.Value.GetString());
continue;
}
}
return(new MediaInput(groupCall.Value, room.Value, teamsMeeting.Value, rtmp.Value, srt.Value, participant.Value, activePresenter.Value, dominantSpeaker.Value, screenShare.Value, image.Value, Optional.ToNullable(kind)));
}
public IEnumerable <FaceFeature> FaceDetect([FromBody] ImageInput model)
{
return(faceDetectionModule.DetectFeatures(model.ImageUrl));
}
public async Task <IActionResult> UploadImageCad(ImageInput imageInput)
{
if (ModelState.IsValid)
{
var CurrentDate = DateTime.Now;
var UploadDate = CurrentDate.ToString("yyyyMMdd_hhmmss");
var userfileName = User.Identity.Name.ToString();
var RootFolder = _hostingEnvironment.WebRootPath;
var UsersFileLocation = "UsersDirectory";
var DxfFileExtension = ".dxf";
//var RootFfolderString = "wwwroot";
var UserDirectory = $"{_hostingEnvironment.WebRootPath}/{UsersFileLocation}/{userfileName}/{UploadDate}";
//var UserFilesDirectoryRelative = $"{RootFfolderString}/{UsersFileLocation}/{userfileName}/{UploadDate}";
var UserFilesDirectoryRelative = $"{UsersFileLocation}/{userfileName}/{UploadDate}";
// var ImageFileLocationPaths = new List<String>();
var uploads = Path.Combine(RootFolder, UsersFileLocation, userfileName, UploadDate);
//Check if user Directory exsists , if not creates new directory
var exsits = Directory.Exists(UserDirectory);
if (!exsits)
{
Directory.CreateDirectory(UserDirectory);
}
var filePathName = ContentDispositionHeaderValue.Parse(imageInput.ImageFile.ContentDisposition).FileName.Trim('"');
var fileExtention = Path.GetExtension(filePathName);
if (!(fileExtention == ".jpg" || fileExtention == ".JPG" || fileExtention == ".PNG" || fileExtention == ".png"))
{
return(RedirectToAction("ErrorPage"));
}
var fileName = Guid.NewGuid().ToString("N").Substring(0, 10);
var FileNameFull = fileName + fileExtention;
var StaticPath = Path.Combine(uploads, FileNameFull);
var StaticPathNameNoExtension = Path.Combine(uploads, fileName);
var RelativePaths = $"{UserFilesDirectoryRelative}/{fileName}" + $"{fileExtention}";
//the image will be saved with a unique filename
FileStream DestinationStream = new FileStream(StaticPath, FileMode.CreateNew);
imageInput.ImageFile.CopyTo(DestinationStream);
var DxfFileName = Guid.NewGuid().ToString("N").Substring(0, 10);
var DxfFileStaticPath = Path.Combine(uploads, DxfFileName);
var DxFRelativePaths = $"{UserFilesDirectoryRelative}/{DxfFileName}" + $"{DxfFileExtension}";
//Function Here
//var ExcuationStatus = ModelBuilder(StaticPathNameNoExtension);
var ExcuationStatus = 0;
var currentUser = await _userManager.FindByNameAsync(User.Identity.Name);
if (ExcuationStatus == 0)
{
var DxfFile = new DxfFile
{
FileName = FileNameFull,
StaticFilePath = DxfFileStaticPath + DxfFileExtension,
RelativeFilePath = DxfFileExtension,
FK_ApplicatioUserId = currentUser.Id,
UploadedTime = CurrentDate
};
repo.Add(DxfFile);
}
else
{
return(RedirectToAction("ErrorPage"));
}
//var ImageFileLocationArray = ImageFileLocationPaths.ToArray();
return(RedirectToAction("UploadCompelete"));
}
else
{
return(View("Error"));
}
}
/// <summary>
/// This creates an image, and any other descriptions
/// </summary>
private static Tuple<UIElement, VectorInt> GetPreviewImage(ImageInput image, bool showHash, int imageSize, bool showPerImageDistance, double imageDistPercent)
{
const int ALIASMULT = 20;
#region image
BitmapSource bitmap;
if (showHash)
{
#region hash
int width, height;
bool isColor = false;
double widthHeight = Math.Sqrt(image.Weights_Orig.Length);
if (widthHeight.ToInt_Floor() == widthHeight.ToInt_Ceiling())
{
// Black and white, 2D
width = height = widthHeight.ToInt_Floor();
}
else
{
double widthHeight2 = Math.Sqrt(image.Weights_Orig.Length / 3);
if (widthHeight2.ToInt_Floor() == widthHeight2.ToInt_Ceiling())
{
// Color, 2D
isColor = true;
width = height = widthHeight2.ToInt_Floor();
}
else
{
// Black and white, 1D
width = image.Weights_Orig.Length;
height = 1;
}
}
//double? maxValue = image.Weights_Orig.Max() > 1d ? (double?)null : 1d;
//Convolution2D conv = new Convolution2D(image.Weights_Orig, width, height, false);
//bitmap = Convolutions.GetBitmap_Aliased(conv, absMaxValue: maxValue, negPosColoring: ConvolutionResultNegPosColoring.BlackWhite, forcePos_WhiteBlack: false);
if (isColor)
{
bitmap = UtilityWPF.GetBitmap_Aliased_RGB(image.Weights_Orig, width, height, width * ALIASMULT, height * ALIASMULT);
}
else
{
bitmap = UtilityWPF.GetBitmap_Aliased(image.Weights_Orig, width, height, width * ALIASMULT, height * ALIASMULT);
}
#endregion
}
else
{
bitmap = UtilityWPF.GetBitmap(image.Image.Filename);
}
bitmap = UtilityWPF.ResizeImage(bitmap, imageSize, true);
Image imageCtrl = new Image()
{
Source = bitmap,
};
#endregion
if (!showPerImageDistance)
{
// Nothing else needed, just return the image
return new Tuple<UIElement, VectorInt>(imageCtrl, new VectorInt(bitmap.PixelWidth, bitmap.PixelHeight));
}
StackPanel retVal = new StackPanel();
retVal.Children.Add(imageCtrl);
retVal.Children.Add(GetPercentVisual(bitmap.PixelWidth, 10, imageDistPercent));
return new Tuple<UIElement, VectorInt>(retVal, new VectorInt(bitmap.PixelWidth, bitmap.PixelHeight + 10));
}
private void DoSimple(ImageInput[] inputs)
{
SOMRules rules = GetSOMRules();
NodeDisplayLayout layout = (NodeDisplayLayout)cboSimpleNodeLayout.SelectedItem;
bool returnEmptyNodes = layout == NodeDisplayLayout.Disk_All;
SOMResult result = SelfOrganizingMaps.TrainSOM(inputs, rules, true, returnEmptyNodes);
SimpleColorScheme scheme = (SimpleColorScheme)cboSimpleOutputColor.SelectedItem;
var getNodeColor = new Func<SOMNode, Color>(o => GetColor(o.Weights, scheme));
// Show results
switch (layout)
{
case NodeDisplayLayout.Disk_All:
ShowResults_Disk(panelDisplay, result, getNodeColor);
break;
case NodeDisplayLayout.Disk_NonZero:
result = SelfOrganizingMaps.ArrangeNodes_LikesAttract(result);
ShowResults_Disk(panelDisplay, result, getNodeColor);
break;
case NodeDisplayLayout.Blobs:
var events = new SelfOrganizingMapsWPF.BlobEvents(Polygon_MouseMove, Polygon_MouseLeave, null);
SelfOrganizingMapsWPF.ShowResults2D_Blobs(panelDisplay, result, getNodeColor, events);
// This is for the manual manipulate buttons
_nodes = result.Nodes;
_imagesByNode = result.InputsByNode;
_wasEllipseTransferred = false;
break;
//case NodeDisplayLayout.Grid_UniformSize:
// throw new ApplicationException("finish this");
// //ShowResults_Grid(panelDisplay, nodes, (SimpleColorScheme)cboSimpleOutputColor.SelectedItem, positions.GridCellSize);
// break;
default:
throw new ApplicationException("Unknown SimpleNodeLayout: " + layout.ToString());
}
}
/// <summary>
/// 处理图片
/// </summary>
/// <param name="imageInput"></param>
/// <returns></returns>
public async Task <ImageOutput> Processing(ImageInput imageInput, HttpRequest request)
{
TempStorageOperation tempStorage = new TempStorageOperation();
//IStorageService _StorageService = new LocalStorageService();
//输出结果对象
ImageOutput imageOutput = new ImageOutput();
imageOutput.Id = Guid.NewGuid().ToString();
imageOutput.Name = imageInput.Name;
imageOutput.Tags = imageInput.Tags;
imageOutput.Length = imageInput.File.Length;
imageOutput.Type = imageInput.File.ContentType;
imageOutput.FileName = imageOutput.Id + "." + imageInput.File.ContentType.Split("/")[1];
imageOutput.Url = Core.StorageOperation.GetUrl(imageOutput.FileName);
imageOutput.Path = Core.StorageOperation.GetPath();
//写入临时文件夹
var tempFilePath = await tempStorage.Write(imageInput.File, imageOutput.Id);
foreach (Core.Interface.IStorageService item in _StorageService)
{
await item.CopyDirectory(tempStorage.GetTempPath(imageOutput.Id), Core.StorageOperation.GetSavePath(), true);
}
//复制目录
//保存Json文件
JsonFile jsonFile = new JsonFile();
jsonFile.Id = imageOutput.Id;
jsonFile.CreateTime = DateTime.Now;
jsonFile.Name = imageOutput.Name;
jsonFile.Tags = imageOutput.Tags;
jsonFile.Url = imageOutput.Url;
jsonFile.FileName = imageOutput.FileName;
//创建处理作业
var task = new List <JsonFileValues>();
//预览图
task.Add(new JsonFileValues()
{
Key = "Medium", Status = "0", Value = ""
});
//缩略图
task.Add(new JsonFileValues()
{
Key = "Small", Status = "0", Value = ""
});
jsonFile.Values = task;
await jsonFile.SaveAs(tempStorage.GetJsonFilePath(jsonFile.Id));
//开始处理任务
await StartJob(jsonFile, tempFilePath);
//复制目录
foreach (Core.Interface.IStorageService item in _StorageService)
{
await item.CopyDirectory(tempStorage.GetTempPath(jsonFile.Id), Core.StorageOperation.GetSavePath(), true);
}
//删除临时目录
await tempStorage.Delete(jsonFile.Id);
//返回结果
return(imageOutput);
}
private Canvas DrawVoronoi(VoronoiResult2D voronoi, Color[] colors, SOMNode[] nodes, ImageInput[][] images, int imageWidth, int imageHeight)
{
const double MARGINPERCENT = 1.05;
#region transform
var aabb = Math2D.GetAABB(voronoi.EdgePoints);
aabb = Tuple.Create((aabb.Item1.ToVector() * MARGINPERCENT).ToPoint(), (aabb.Item2.ToVector() * MARGINPERCENT).ToPoint());
TransformGroup transform = new TransformGroup();
transform.Children.Add(new TranslateTransform(-aabb.Item1.X, -aabb.Item1.Y));
transform.Children.Add(new ScaleTransform(imageWidth / (aabb.Item2.X - aabb.Item1.X), imageHeight / (aabb.Item2.Y - aabb.Item1.Y)));
#endregion
Canvas retVal = new Canvas();
for (int cntr = 0; cntr < voronoi.ControlPoints.Length; cntr++)
{
#region polygon
Polygon polygon = new Polygon();
if (voronoi.EdgesByControlPoint[cntr].Length < 3)
{
throw new ApplicationException("Expected at least three edge points");
}
Edge2D[] edges = voronoi.EdgesByControlPoint[cntr].Select(o => voronoi.Edges[o]).ToArray();
Point[] edgePoints = Edge2D.GetPolygon(edges, 1d);
edgePoints = edgePoints.
Select(o => transform.Transform(o)).
ToArray();
foreach (Point point in edgePoints)
{
polygon.Points.Add(point);
}
polygon.Fill = new SolidColorBrush(colors[cntr]);
polygon.Stroke = new SolidColorBrush(UtilityWPF.OppositeColor(colors[cntr], false));
polygon.StrokeThickness = 1;
polygon.Tag = Tuple.Create(nodes[cntr], images[cntr]);
polygon.MouseMove += Polygon_MouseMove_OLD;
polygon.MouseLeave += Polygon_MouseLeave_OLD;
retVal.Children.Add(polygon);
#endregion
}
return retVal;
}
public ActionResult CreateStep3(ImageInput editor)
{
var image = new WebImage("~" + editor.Image.ImageUrl);
var height = image.Height;
var width = image.Width;
var tempUrl = editor.Image.ImageUrl;
var saveUrl = @BlogGlobals.SlideImageFolder + Path.GetFileName(image.FileName);
image.Crop((int)editor.Top, (int)editor.Left, (int)(height - editor.Bottom), (int)(width - editor.Right));
image.Resize(190, 190, true, false);
image.Save(saveUrl);
System.IO.File.Delete(Server.MapPath(tempUrl));
ViewBag.PostId = new SelectList(db.Posts, "PostId", "Title");
ViewBag.imageUrl = saveUrl;
Slide slide = new Slide();
return View("CreateStep3", slide);
}
private void DoConvolution2(ImageInput[] inputs, double maxSpreadPercent, int minNodeItemsForSplit)
{
SOMRules rules = GetSOMRules();
SOMResult result = SelfOrganizingMaps.TrainSOM(inputs, rules, maxSpreadPercent, true, false);
var getNodeColor = chkRandomNodeColors.IsChecked.Value ? _getNodeColor_Random : SelfOrganizingMapsWPF.GetNodeColor;
var events = new SelfOrganizingMapsWPF.BlobEvents(Polygon_MouseMove, Polygon_MouseLeave, null);
SelfOrganizingMapsWPF.ShowResults2D_Blobs(panelDisplay, result, getNodeColor, events);
// This is for the manual manipulate buttons
_nodes = result.Nodes;
_imagesByNode = result.InputsByNode;
_wasEllipseTransferred = false;
}
private void BuildOverlay2D(SOMNode node, ISOMInput[] images, bool showCount, bool showNodeHash, bool showImageHash, bool showSpread, bool showPerImageDistance)
{
const int IMAGESIZE = 80;
const int NODEHASHSIZE = 100;
const double SMALLFONT1 = 17;
const double LARGEFONT1 = 21;
const double SMALLFONT2 = 15;
const double LARGEFONT2 = 18;
const double SMALLFONT3 = 12;
const double LARGEFONT3 = 14;
const double SMALLLINE1 = .8;
const double LARGELINE1 = 1;
const double SMALLLINE2 = .5;
const double LARGELINE2 = .85;
const double SMALLLINE3 = .3;
const double LARGELINE3 = .7;
Canvas canvas = new Canvas();
List<Rect> rectangles = new List<Rect>();
#region cursor rectangle
var cursorRect = SelfOrganizingMapsWPF.GetMouseCursorRect(0);
rectangles.Add(cursorRect.Item1);
// This is just for debugging
//Rectangle cursorVisual = new Rectangle()
//{
// Width = cursorRect.Item1.Width,
// Height = cursorRect.Item1.Height,
// Fill = new SolidColorBrush(UtilityWPF.GetRandomColor(64, 192, 255)),
//};
//Canvas.SetLeft(cursorVisual, cursorRect.Item1.Left);
//Canvas.SetTop(cursorVisual, cursorRect.Item1.Top);
//canvas.Children.Add(cursorVisual);
#endregion
#region count text
if (showCount)
{
StackPanel textPanel = new StackPanel()
{
Orientation = Orientation.Horizontal,
};
// "images "
OutlinedTextBlock text = SelfOrganizingMapsWPF.GetOutlineText("images ", SMALLFONT1, SMALLLINE1);
text.Margin = new Thickness(0, 0, 4, 0);
textPanel.Children.Add(text);
// count
text = SelfOrganizingMapsWPF.GetOutlineText(images.Length.ToString("N0"), LARGEFONT1, LARGELINE1);
textPanel.Children.Add(text);
// Place on canvas
textPanel.Measure(new Size(double.PositiveInfinity, double.PositiveInfinity)); // aparently, the infinity is important to get an accurate desired size
Size textSize = textPanel.DesiredSize;
Rect textRect = SelfOrganizingMapsWPF.GetFreeSpot(textSize, new Point(0, 0), new Vector(0, 1), rectangles);
rectangles.Add(textRect);
Canvas.SetLeft(textPanel, textRect.Left);
Canvas.SetTop(textPanel, textRect.Top);
canvas.Children.Add(textPanel);
}
#endregion
#region spread
var nodeImages = images.Select(o => o.Weights);
var allImages = _imagesByNode.SelectMany(o => o).Select(o => o.Weights);
double nodeSpread = images.Length == 0 ? 0d : SelfOrganizingMaps.GetTotalSpread(nodeImages);
double totalSpread = SelfOrganizingMaps.GetTotalSpread(allImages);
if (showSpread && images.Length > 0)
{
double nodeStandDev = MathND.GetStandardDeviation(nodeImages);
double totalStandDev = MathND.GetStandardDeviation(allImages);
double percentSpread = nodeSpread / totalSpread;
double pecentStandDev = nodeStandDev / totalSpread;
Grid spreadPanel = new Grid()
{
Margin = new Thickness(2),
};
spreadPanel.ColumnDefinitions.Add(new ColumnDefinition() { Width = new GridLength(1, GridUnitType.Auto) });
spreadPanel.ColumnDefinitions.Add(new ColumnDefinition() { Width = new GridLength(4) });
spreadPanel.ColumnDefinitions.Add(new ColumnDefinition() { Width = new GridLength(1, GridUnitType.Auto) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(1, GridUnitType.Auto) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(2) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(1, GridUnitType.Auto) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(2) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(1, GridUnitType.Auto) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(2) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(1, GridUnitType.Auto) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(2) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(1, GridUnitType.Auto) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(2) });
spreadPanel.RowDefinitions.Add(new RowDefinition() { Height = new GridLength(1, GridUnitType.Auto) });
AddTextRow(spreadPanel, 0, "node stand dev", (pecentStandDev * 100).ToStringSignificantDigits(2) + "%", SMALLFONT2, LARGEFONT2, SMALLLINE2, LARGELINE2, true);
AddTextRow(spreadPanel, 2, "node spread", (percentSpread * 100).ToStringSignificantDigits(2) + "%", SMALLFONT2, LARGEFONT2, SMALLLINE2, LARGELINE2, false);
AddTextRow(spreadPanel, 4, "node stand dev", nodeStandDev.ToStringSignificantDigits(2), SMALLFONT3, LARGEFONT3, SMALLLINE3, LARGELINE3, true);
AddTextRow(spreadPanel, 6, "node spread", nodeSpread.ToStringSignificantDigits(2), SMALLFONT3, LARGEFONT3, SMALLLINE3, LARGELINE3, false);
AddTextRow(spreadPanel, 8, "total stand dev", totalStandDev.ToStringSignificantDigits(2), SMALLFONT3, LARGEFONT3, SMALLLINE3, LARGELINE3, true);
AddTextRow(spreadPanel, 10, "total spread", totalSpread.ToStringSignificantDigits(2), SMALLFONT3, LARGEFONT3, SMALLLINE3, LARGELINE3, false);
// Place on canvas
spreadPanel.Measure(new Size(double.PositiveInfinity, double.PositiveInfinity)); // aparently, the infinity is important to get an accurate desired size
Size spreadSize = spreadPanel.DesiredSize;
Rect spreadRect = SelfOrganizingMapsWPF.GetFreeSpot(spreadSize, new Point(0, 0), new Vector(0, 1), rectangles);
rectangles.Add(spreadRect);
Canvas.SetLeft(spreadPanel, spreadRect.Left);
Canvas.SetTop(spreadPanel, spreadRect.Top);
canvas.Children.Add(spreadPanel);
}
#endregion
double[] nodeCenter = images.Length == 0 ? node.Weights : MathND.GetCenter(nodeImages);
#region node hash
if (showNodeHash)
{
ImageInput nodeImage = new ImageInput(null, node.Weights, node.Weights);
double nodeDist = MathND.GetDistance(nodeImage.Weights, nodeCenter);
double nodeDistPercent = nodeSpread.IsNearZero() ? 1d : (nodeDist / nodeSpread); // if zero or one node, then spread will be zero
Tuple<UIElement, VectorInt> nodeCtrl = GetPreviewImage(nodeImage, true, NODEHASHSIZE, showPerImageDistance, nodeDistPercent);
// Place on canvas
Rect nodeRect = SelfOrganizingMapsWPF.GetFreeSpot(new Size(nodeCtrl.Item2.X, nodeCtrl.Item2.Y), new Point(0, 0), new Vector(0, -1), rectangles);
rectangles.Add(nodeRect);
Canvas.SetLeft(nodeCtrl.Item1, nodeRect.Left);
Canvas.SetTop(nodeCtrl.Item1, nodeRect.Top);
canvas.Children.Add(nodeCtrl.Item1);
}
#endregion
#region images
foreach (ImageInput image in images)
{
double imageDistPercent;
if (images.Length == 1)
{
imageDistPercent = 1;
}
else
{
imageDistPercent = MathND.GetDistance(image.Weights, nodeCenter) / nodeSpread;
}
// Create the image (and any other graphics for that image)
Tuple<UIElement, VectorInt> imageCtrl = GetPreviewImage(image, showImageHash, IMAGESIZE, showPerImageDistance, imageDistPercent);
// Find a spot for it
var imageRect = Enumerable.Range(0, 10).
Select(o =>
{
Vector direction = Math3D.GetRandomVector_Circular_Shell(1).ToVector2D();
Rect imageRect2 = SelfOrganizingMapsWPF.GetFreeSpot(new Size(imageCtrl.Item2.X, imageCtrl.Item2.Y), new Point(0, 0), direction, rectangles);
return new { Rect = imageRect2, Distance = new Vector(imageRect2.CenterX(), imageRect2.CenterY()).LengthSquared };
}).
OrderBy(o => o.Distance).
First().
Rect;
Canvas.SetLeft(imageCtrl.Item1, imageRect.Left);
Canvas.SetTop(imageCtrl.Item1, imageRect.Top);
// Add it
rectangles.Add(imageRect);
canvas.Children.Add(imageCtrl.Item1);
}
#endregion
Rect canvasAABB = Math2D.GetAABB(rectangles);
//NOTE: All the items are placed around zero zero, but that may not be half width and height (items may not be centered)
canvas.RenderTransform = new TranslateTransform(-canvasAABB.Left, -canvasAABB.Top);
panelOverlay.Children.Clear();
panelOverlay.Children.Add(canvas);
_overlayPolyStats = new OverlayPolygonStats(node, images, canvasAABB, cursorRect.Item2, canvas);
}
//TODO: Move this section to SelfOrganizingMaps.TrainKMeans()
private void DoKMeans(ImageInput[] inputs)
{
int numNodes = trkKMeansNumNodes.Value.ToInt_Round();
SOMResult result = SelfOrganizingMaps.TrainKMeans(inputs, numNodes, true);
var getNodeColor = chkRandomNodeColors.IsChecked.Value ? _getNodeColor_Random : SelfOrganizingMapsWPF.GetNodeColor;
var events = new SelfOrganizingMapsWPF.BlobEvents(Polygon_MouseMove, Polygon_MouseLeave, Polygon_Click);
SelfOrganizingMapsWPF.ShowResults2D_Blobs(panelDisplay, result, getNodeColor, events);
// This is for the manual manipulate buttons
_nodes = result.Nodes;
_imagesByNode = result.InputsByNode;
_wasEllipseTransferred = false;
}