public static async Task<ImgurEntity> UploadImgur(IRandomAccessStream fileStream)
{
try
{
var imageData = new byte[fileStream.Size];
for (int i = 0; i < imageData.Length; i++)
{
imageData[i] = (byte)fileStream.AsStreamForRead().ReadByte();
}
var theAuthClient = new HttpClient();
var request = new HttpRequestMessage(HttpMethod.Post, "https://api.imgur.com/3/image");
request.Headers.Authorization = new AuthenticationHeaderValue("Client-ID", "e5c018ac1f4c157");
var form = new MultipartFormDataContent();
var t = new StreamContent(fileStream.AsStream());
// TODO: See if this is the correct way to use imgur's v3 api. I can't see why we would still need to convert images to base64.
string base64Img = Convert.ToBase64String(imageData);
t.Headers.ContentType = new MediaTypeHeaderValue("image/jpeg");
form.Add(new StringContent(base64Img), @"image");
form.Add(new StringContent("file"), "type");
request.Content = form;
HttpResponseMessage response = await theAuthClient.SendAsync(request);
string responseString = await response.Content.ReadAsStringAsync();
if (responseString == null) return null;
var imgurEntity = JsonConvert.DeserializeObject<ImgurEntity>(responseString);
return imgurEntity;
}
catch (WebException)
{
}
catch (IOException)
{
return null;
}
return null;
}
public static String ExportToFile(IRandomAccessStream exportStream)
{
StringBuilder exportResults = new StringBuilder();
using (AppStreamWriter sw = new AppStreamWriter(exportStream.AsStream()))
{
LoadLessonsUnsorted();
//write Number of Lessons
sw.WriteLine(AppData.Lessons.Length.ToString());
int exportedLessons = 0;
int exportedWords = 0;
int exportedSentences = 0;
int exportedKanjis = 0;
foreach (Lesson lesson in AppData.Lessons)
{
sw.WriteLine(lesson.ToExportString());
switch (lesson.type)
{
case 0: exportedWords += WriteVocabLesson(sw, lesson); break;
case 1: exportedSentences += WriteInsertLesson(sw, lesson); break;
case 2: break;
case 3: exportedKanjis += WriteKanjiLesson(sw, lesson); break;
case 4: break;
}
++exportedLessons;
}
exportResults.AppendLine("Datenbank erfolgreich exportiert!");
exportResults.AppendLine("Exportierte Lektionen\t: " + exportedLessons);
exportResults.AppendLine("Exportierte Wörter\t: " + exportedWords);
exportResults.AppendLine("Exportierte Lückentexte\t: " + exportedSentences);
exportResults.AppendLine("Exportierte Kanjis\t\t: " + exportedKanjis);
}
AppData.Lessons = null;
AppData.Words = null;
AppData.Sentences = null;
AppData.Kanjis = null;
return exportResults.ToString();
}
/// <summary>
/// Copies an image from the internet (http protocol) locally to the AppData LocalFolder. This is used by some methods
/// (like the SecondaryTile constructor) that do not support referencing images over http but can reference them using
/// the ms-appdata protocol.
/// </summary>
/// <param name="internetUri">The path (URI) to the image on the internet</param>
/// <param name="uniqueName">A unique name for the local file</param>
/// <returns>Path to the image that has been copied locally</returns>
public static async Task <Uri> GetLocalImageAsync(string internetUri, string uniqueName)
{
if (string.IsNullOrEmpty(internetUri))
{
return(new Uri("ms-appx:///Assets/Square150x150Logo.scale-200.png", UriKind.Absolute));
}
using (var response = await HttpWebRequest.CreateHttp(internetUri).GetResponseAsync())
{
using (var stream = response.GetResponseStream())
{
var desiredName = string.Format("{0}.jpg", uniqueName);
StorageFile file = await ApplicationData.Current.LocalFolder.CreateFileAsync(desiredName, CreationCollisionOption.ReplaceExisting);
using (IRandomAccessStream filestream = await file.OpenAsync(FileAccessMode.ReadWrite))
{
await stream.CopyToAsync(filestream.AsStream());
return(new Uri(string.Format("ms-appdata:///local/{0}.jpg", uniqueName), UriKind.Absolute));
}
}
}
}
public async void ContinueFileSavePicker(FileSavePickerContinuationEventArgs args)
{
if ((args.ContinuationData["Operation"] as string) == "ExportDatabase" && args.File != null)
{
StorageFile file = args.File;
IRandomAccessStream fileStream = await file.OpenAsync(FileAccessMode.ReadWrite);
DataManager.ConnectToDatabase();
String exportStatus = DataManager.ExportToFile(fileStream.AsStream());
DataManager.CloseConnection();
fileStream.Dispose();
MessageBox.Show(exportStatus);
}
else
{
MessageBox.Show("Export fehlgeschlagen!");
}
exportDatabase = false;
}
public static async void Send(IRandomAccessStream stream)
{
if (stream == null)
{
Show("NoData");
return;
}
Show("Sending");
using (StreamSocket socket = new StreamSocket())
{
try
{
// 发起连接
await socket.ConnectAsync(new HostName(IP_CHE), LISTEN_PORT);
using (DataWriter writer = new DataWriter(socket.OutputStream))
{
// 先写个长度
var length = (uint)stream.AsStream().Length;
writer.WriteUInt32(length);
// 再传输Buffer
IBuffer buffer = await StreamToBuffer(stream);
writer.WriteBuffer(buffer);
await writer.StoreAsync();
Show("Sended");
// OnTakeAnother();
}
}
catch (Exception e)
{
Show(e.Message);
}
}
}
private async void getEmotion_Click(object sender, RoutedEventArgs e)
{
try
{
emotionResult = await emotionServiceClient.RecognizeAsync(imageStream.AsStream());
if (emotionResult != null)
{
output.Text = "your emotions are: \n" +
"Happiness: " + emotionResult[0].Scores.Happiness + "\n" +
"Sadness: " + emotionResult[0].Scores.Sadness + "\n" +
"Surprise: " + emotionResult[0].Scores.Surprise + "\n" +
"Fear: " + emotionResult[0].Scores.Fear + "\n" +
"Anger: " + emotionResult[0].Scores.Anger + "\n" +
"Contempt: " + emotionResult[0].Scores.Contempt + "\n" +
"Disgust: " + emotionResult[0].Scores.Disgust + "\n" +
"Neutral: " + emotionResult[0].Scores.Neutral + "\n";
}
}
catch
{
output.Text = "Error returning the emotion";
}
}
private async void getemotion_Click(object sender, RoutedEventArgs e)
{
try
{
emotionResult = await emotionServiceClient.RecognizeAsync(imageStream.AsStream());
if (emotionResult != null)
{
Microsoft.ProjectOxford.Common.Contract.EmotionScores score = emotionResult[0].Scores;
output.Text = "Your emotions are: \n" +
"Happiness: " + score.Happiness.ToString("0.00000") + "\n" +
"Sadness: " + score.Sadness.ToString("0.00000") + "\n" +
"Surprise: " + score.Surprise.ToString("0.00000") + "\n" +
"Fear: " + score.Fear.ToString("0.00000") + "\n" +
"Anger: " + score.Anger.ToString("0.00000") + "\n" +
"Disgust: " + score.Disgust.ToString("0.00000") + "\n" +
"Neutral: " + score.Neutral.ToString("0.00000") + "\n";
}
}
catch
{
output.Text = "Error calling emotion";
}
}
public static String ImportFromFile(IRandomAccessStream importStream)
{
StringBuilder importResults = new StringBuilder();
using (AppStreamReader sr = new AppStreamReader(importStream.AsStream()))
{
try
{
String line = sr.ReadLine();
do
{
String[] parts = line.Split('|');
int operation = Convert.ToInt32(parts[0]);
int itemCount = Convert.ToInt32(parts[1]);
String results = "";
switch (operation)
{
case 0: results = AddLessons(sr, itemCount); break;
case 1: results = UpdateLessons(sr, itemCount); break;
case 2: results = UpdateWords(sr, itemCount); break;
case 3: results = UpdateKanjis(sr, itemCount); break;
case 4: results = AddWords(sr, itemCount); break;
case 5: results = AddKanjis(sr, itemCount); break;
}
importResults.Append(results);
line = sr.ReadLine();
}
while (line != null);
context.SubmitChanges();
}
catch (Exception e)
{
importResults.Clear();
importResults.AppendLine("Import Fehlgeschlagen in Zeile: " + sr.CurrentLine);
importResults.AppendLine("System: " + e.Message);
}
}
return importResults.ToString();
}
private async void OnSelectImageButtonClicked(object sender, RoutedEventArgs e)
{
var picker = new FileOpenPicker();
picker.ViewMode = PickerViewMode.Thumbnail;
picker.SuggestedStartLocation = PickerLocationId.PicturesLibrary;
picker.FileTypeFilter.Add(".jpg");
picker.FileTypeFilter.Add(".jpeg");
picker.FileTypeFilter.Add(".png");
var file = await picker.PickSingleFileAsync();
if (file != null)
{
using (IRandomAccessStream stream = await file.OpenAsync(FileAccessMode.Read))
{
// Show the image
var image = new BitmapImage();
await image.SetSourceAsync(stream);
LoadedImage.Source = image;
stream.Seek(0L);
try
{
Progress.IsActive = true;
Overlay.Visibility = Visibility.Visible;
// Submit the image to the Custom Vision Service
CustomVisionPredictionClient client = new CustomVisionPredictionClient(
new ApiKeyServiceClientCredentials(_key),
new System.Net.Http.DelegatingHandler[] { }
);
client.Endpoint = _uri;
var result = await client.ClassifyImageAsync(_id, _name, stream.AsStream());
var prediction = result.Predictions.FirstOrDefault(x => x.TagName.ToLowerInvariant() == "hotdog");
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
// Show the results
if (prediction != null)
{
// If the results include a "hotdog" label, show the probability that it's a hot dog
await new MessageDialog($"Probability that it's a hot dog: {prediction.Probability:P1}").ShowAsync();
}
else
{
// If the results don't include a "hotdog" label, show all tags and probabilities
var builder = new StringBuilder();
foreach (var pred in result.Predictions)
{
builder.Append($"{pred.TagName}: {pred.Probability:P1}\n");
}
await new MessageDialog(builder.ToString()).ShowAsync();
}
}
catch (Exception ex)
{
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
await new MessageDialog(ex.Message).ShowAsync();
}
finally
{
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
}
}
}
}
private async void button_LogIn_Click(object sender, RoutedEventArgs e)
{
tb_LogInResult.Text = "";
try
{
var memstream = new InMemoryRandomAccessStream();
//Define image format (JPEG)
ImageEncodingProperties imgFormat = ImageEncodingProperties.CreateJpeg();
//Capture Photo to random access memory stream
await mediaCapture.CapturePhotoToStreamAsync(imgFormat, memstream);
IRandomAccessStream stream = memstream.CloneStream();
if (stream != null)
{
if (!progressRing.IsActive)
{
progressRing.IsActive = true;
//Decode to bitmap format
BitmapDecoder decoder = await BitmapDecoder.CreateAsync(stream);
SoftwareBitmap bitmap = await decoder.GetSoftwareBitmapAsync();
SoftwareBitmap bitmap2 = SoftwareBitmap.Convert(bitmap, BitmapPixelFormat.Bgra8, BitmapAlphaMode.Premultiplied);
SoftwareBitmapSource bmpSrc = new SoftwareBitmapSource();
await bmpSrc.SetBitmapAsync(bitmap2);
//Set source for the image control to display the captured image
PhotoControl.Source = bmpSrc;
//Upload image to Azure blob and retrieve the image URL
string fileName = "temp" + DateTime.Now.ToString("ddMMyyyyhhmmtt") + ".png";
var imageUrl = await storageClient.uploadPhotoAsync("temp", fileName, stream.AsStream());
if (!(imageUrl is Exception))
{
//Detect face (if any) in the image
var FaceIDResponse = await faceClient.DetectFaceAsync(imageUrl.ToString());
if (FaceIDResponse.IsSuccessStatusCode)
{
//Detect face responds with face attributes if any face has been identified
var results = JsonConvert.DeserializeObject <DetectFace.FaceClass[]>(await FaceIDResponse.Content.ReadAsStringAsync());
//No face found in the image
if (results.ToArray().Count() == 0)
{
msg.Title = "Unable to register face!";
msg.Content = "No face found in the image, please try again!";
await msg.ShowAsync();
return;
}
//Add all Face IDs to a list
List <string> FaceIDList = new List <string>();
foreach (var item in results)
{
FaceIDList.Add(item.faceId);
}
//Check if the face matches any person in the person group with a confidence of 0.5F
var candidateResponse = await faceClient.IdentifyFaceAsync(0.5F, FaceIDList.ToArray(), 2, AppSettings.defaultPersonGroupID);
var responseContent = candidateResponse.Content.ReadAsStringAsync().Result;
if (candidateResponse.IsSuccessStatusCode)
{
//Identify function responds with a list of candidates to which the face matches and the confidence
var result = JsonConvert.DeserializeObject <IdentifyFaceResponseModel[]>(responseContent);
//Getting the candidate with highest confidence level
var candidate = result[0].candidates[0];
string personID = localSettings.Values["PersonId"].ToString();
//Check if the confidence level is greater than 0.5 and if the Person ID of
//the candidate does not match the person ID of the logged in user
if ((candidate.confidence > 0.5) && (candidate.personId == personID))
{
//Face matches - proceed to transaction
Frame.Navigate(typeof(TransactionPage));
}
else
{
//Face does not match
msg.Title = "Unable to log in!";
msg.Content = "Face does not match records or do not meet the required threshold!";
await msg.ShowAsync();
Frame.GoBack();
}
}
else
{
msg.Title = "Unable to log in!";
msg.Content = responseContent;
await msg.ShowAsync();
Frame.GoBack();
}
}
}
}
}
}
catch (Exception ex)
{
msg.Title = "Unable to log in!";
msg.Content = ex.Message;
await msg.ShowAsync();
}
progressRing.IsActive = false;
PhotoControl.Source = null;
}
public FileSummary(BitmapImage image, StorageFile file, IDictionary<string, object> properties, IRandomAccessStream stream)
{
JpegInfo exifInfo = ExifReader.ReadJpeg(stream.AsStream());
this.BasicData = new List<ExifDatum>
{
new ExifDatum("Name", file.Name),
new ExifDatum("Path", file.Path),
new ExifDatum("Created", file.DateCreated.ToString()),
new ExifDatum("Dimensions", image.PixelWidth.ToString() + "px by " + image.PixelHeight.ToString() + "px")
};
if (properties.ContainsKey("size"))
{
double num = double.Parse(properties["size"].ToString(), System.Globalization.CultureInfo.InvariantCulture);
this.BasicData.Add(new ExifDatum("Size", ConvertBitSize(num)));
}
this.ExifData = exifInfo
.GetType()
.GetRuntimeFields()
.Select(field => new ExifDatum(field, field.GetValue(exifInfo)))
.Where(datum => datum.DisplayValue != null)
.OrderBy(datum => datum.Name)
.ToList();
this.FullData = properties
.Where(field => field.Value != null && field.Key[0] != '{')
.Select(field => ConvertPairToDatum(field))
.OrderBy(datum => datum.Name)
.ToList();
}
private async void BTNpost_Click(object sender, RoutedEventArgs e)
{
PRGRSpost.ProgressStart();
String content = TXTBLKpost.Text;
if (content.Length > 1000)
{
Constants.BoxPage.ShowMessage("树洞内容不要太长");
return;
}
if ("".Equals(content) && HoleType == HoleInfo.TYPE_TEXT)
{
Constants.BoxPage.ShowMessage("不能没有树洞内容");
return;
}
List <Parameters> param = new List <Parameters>();
String type = "text";
switch (HoleType)
{
case 2:
{
type = "image";
}
break;
case 3:
{
type = "audio";
}
break;
}
param.Add(new Parameters("action", "dopost"));
switch (HoleType)
{
case 2:
{
type = "image";
try
{
var a = await file.OpenAsync(FileAccessMode.ReadWrite);
Stream stream = a.AsStream();
byte[] bts = Util.StreamToBytes(stream);
String bmp_str = Convert.ToBase64String(bts);
param.Add(new Parameters("data", bmp_str));
}
catch
{
Constants.BoxPage.ShowMessage("添加图像内容失败");
PRGRSpost.ProgressEnd();
return;
}
} break;
case 3:
{
type = "audio";
try
{
Stream stream = audioStream.AsStream();
byte[] bts = Util.StreamToBytes(stream);
String bmp_str = Convert.ToBase64String(bts);
param.Add(new Parameters("data", bmp_str));
param.Add(new Parameters("length", Length + ""));
}
catch
{
Constants.BoxPage.ShowMessage("添加音频内容失败");
PRGRSpost.ProgressEnd();
return;
}
} break;
}
param.Add(new Parameters("text", content));
param.Add(new Parameters("token", Constants.token));
param.Add(new Parameters("type", type));
Parameters result = await WebConnection.Connect(Constants.domain + "/pkuhelper/../services/pkuhole/api.php", param);
try
{
if (result.name != "200")
{
Constants.BoxPage.ShowMessage("发布失败");
PRGRSpost.ProgressEnd();
return;
}
JsonObject jsonObject = JsonObject.Parse(result.value);
int code;
try
{
code = (int)jsonObject.GetNamedNumber("code");
}
catch
{
code = int.Parse(jsonObject.GetNamedString("code"));
}
if (code != 0)
{
Constants.BoxPage.ShowMessage("发布失败");
PRGRSpost.ProgressEnd();
return;
}
else
{
Constants.BoxPage.ShowMessage("发布成功！");
PRGRSpost.ProgressEnd();
BTNback_Click(null, null);
//这里应该加入以后导航到发表的页面
return;
}
}
catch (Exception)
{
Constants.BoxPage.ShowMessage("发布失败");
PRGRSpost.ProgressEnd();
return;
}
}
public async Task <MapFile> GetFile()
{
//https://github.com/Microsoft/Windows-universal-samples/blob/e13cf5dca497ad661706d150a154830666913be4/Samples/PdfDocument/cs/Scenario1_Render.xaml.cs
var picker = new Windows.Storage.Pickers.FileOpenPicker();
picker.ViewMode = Windows.Storage.Pickers.PickerViewMode.Thumbnail;
picker.SuggestedStartLocation = Windows.Storage.Pickers.PickerLocationId.PicturesLibrary;
picker.FileTypeFilter.Add(".jpg");
picker.FileTypeFilter.Add(".jpeg");
picker.FileTypeFilter.Add(".png");
picker.FileTypeFilter.Add(".pdf");
picker.FileTypeFilter.Add(".svg");
StorageFile file = await picker.PickSingleFileAsync();
//return file;
MapFile mapFile = new MapFile();
if (file.FileType == ".pdf")
{
PdfDocument pdfDocument = await PdfDocument.LoadFromFileAsync(file);
using (PdfPage page = pdfDocument.GetPage(0))
{
using (var stream = new InMemoryRandomAccessStream())
{
await page.RenderToStreamAsync(stream);
BitmapImage bitmap = new BitmapImage();
await bitmap.SetSourceAsync(stream);
using (var stream2 = new InMemoryRandomAccessStream())
{
PdfPageRenderOptions options;
await page.RenderToStreamAsync(stream2);
//mapFile.MapBytes = new byte[bitmap.PixelHeight*bitmap.PixelWidth];
mapFile.MapBytes = new byte[(uint)stream2.AsStream().Length];
await stream2.AsStreamForRead().ReadAsync(mapFile.MapBytes, 0, mapFile.MapBytes.Length);
//WriteableBitmap writableBitmap = new WriteableBitmap(bitmap.PixelWidth, bitmap.PixelHeight);
//await writableBitmap.SetSourceAsync(stream2);
//mapFile.MapSoftwareImageSource = writableBitmap;
}
//
//mapFile.MapSoftwareImageSource.SetSource(stream2);
//BitmapDecoder decoder = await BitmapDecoder.CreateAsync(stream);
//mapFile.MapSoftwareImageSource = await decoder.GetSoftwareBitmapAsync();
mapFile.MapImageSource = bitmap;
}
}
}
//http://igrali.com/2015/12/24/how-to-render-svg-in-xaml-windows-10-uwp/
if (file.FileType == ".svg")
{
using (IRandomAccessStream stream = await file.OpenReadAsync())
{
//SvgImageSource svgImage = new SvgImageSource();
//await svgImage.SetSourceAsync(stream);
//mapFile.svgImageSource = svgImage;
string svgString = await Windows.Storage.FileIO.ReadTextAsync(file);
//mapFile.MapImageSource = svgImage;
mapFile.MapSvgSource = svgString;
mapFile.IsSvg = true;
}
}
if (file.FileType == ".jpg" || file.FileType == ".jpeg" || file.FileType == ".png")
{
using (IRandomAccessStream stream = await file.OpenReadAsync())
{
BitmapImage bitmap = new BitmapImage();
await bitmap.SetSourceAsync(stream);
mapFile.MapImageSource = bitmap;
}
using (IRandomAccessStream stream = await file.OpenReadAsync())
{
mapFile.MapBytes = new byte[(uint)stream.AsStream().Length];
await stream.AsStreamForRead().ReadAsync(mapFile.MapBytes, 0, mapFile.MapBytes.Length);
}
}
return(mapFile);
}
private async void OnSelectImageButtonClicked(object sender, RoutedEventArgs e)
{
var picker = new FileOpenPicker();
picker.ViewMode = PickerViewMode.Thumbnail;
picker.SuggestedStartLocation = PickerLocationId.PicturesLibrary;
picker.FileTypeFilter.Add(".jpg");
picker.FileTypeFilter.Add(".jpeg");
picker.FileTypeFilter.Add(".png");
var file = await picker.PickSingleFileAsync();
if (file != null)
{
using (IRandomAccessStream stream = await file.OpenAsync(FileAccessMode.Read))
{
// Show the image
var image = new BitmapImage();
await image.SetSourceAsync(stream);
LoadedImage.Source = image;
stream.Seek(0L);
try
{
Progress.IsActive = true;
Overlay.Visibility = Visibility.Visible;
// Submit the image to the Custom Vision Service
CustomVisionPredictionClient client = new CustomVisionPredictionClient()
{
ApiKey = _key,
Endpoint = _uri
};
var result = await client.ClassifyImageAsync(_id, _name, stream.AsStream());
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
// Show the result
var probability = result.Predictions.FirstOrDefault(x => x.TagName.ToLowerInvariant() == "hotdog").Probability;
if (probability > 0.90)
{
await new MessageDialog("It's a hot dog!").ShowAsync();
}
else
{
await new MessageDialog("Not a hot dog").ShowAsync();
}
}
catch (Exception ex)
{
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
await new MessageDialog(ex.Message).ShowAsync();
}
finally
{
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
}
}
}
}
public async void makeRecommendation(IRandomAccessStream ras)
{
var att = new FaceAttributeType[] { FaceAttributeType.Age, FaceAttributeType.Gender, FaceAttributeType.Smile, FaceAttributeType.FacialHair, FaceAttributeType.Emotion, FaceAttributeType.Glasses };
using (Stream s = ras.AsStream()) //File.OpenRead(imageFilePath))
{
var a = await FaceServiceClient.DetectAsync(s, returnFaceAttributes : att);
for (int i = 0; i < a.Length; i++)
{
Face face = a[i];
var features = face.FaceAttributes;
age = features.Age;
if (features.FacialHair.Moustache >= 0.4 || features.FacialHair.Beard >= 0.4 || features.FacialHair.Sideburns >= 0.4 && features.Gender == "male")
{
ResultTitle.Text = "Little Book of Beards";
BookCover.Source = new BitmapImage(new Uri("http://i357.photobucket.com/albums/oo17/nikisiasoco/bookOfBeards_zpsl7aqlwwa.jpg?t=1498900330"));
SummaryContent.Text = "A book for men, the manliest of men. Our bearded guardians, our stubbled knights.";
}
else if (age < 15)
{
ResultTitle.Text = "Twilight";
BookCover.Source = new BitmapImage(new Uri("http://i357.photobucket.com/albums/oo17/nikisiasoco/Twilightbook_zpszj9qzcry.jpg"));
SummaryContent.Text = "If you like apples, theres an apple on the cover. I guess.";
}
else if (age > 45)
{
ResultTitle.Text = "The Prince";
BookCover.Source = new BitmapImage(new Uri("http://i357.photobucket.com/albums/oo17/nikisiasoco/thePrince_zpsvxuexh1h.jpg"));
SummaryContent.Text = "Tyranny 101.";
}
else if (age < 50 && age > 16)
{
if (features.Emotion.Happiness > 0.5)
{
ResultTitle.Text = "You're Never Weird on the Internet";
BookCover.Source = new BitmapImage(new Uri("http://i357.photobucket.com/albums/oo17/nikisiasoco/funny_zpsehbxbjtg.jpg?t=1498958983"));
SummaryContent.Text = "This book is read by alot of happy adults.";
}
else
{
ResultTitle.Text = "Kafka on the Shore";
BookCover.Source = new BitmapImage(new Uri("http://i357.photobucket.com/albums/oo17/nikisiasoco/kafkaOntheShore_zpsl85mx39u.jpg"));
SummaryContent.Text = "You look like you have good taste.";
}
/*
* System.Diagnostics.Debug.WriteLine(features.FacialHair.Moustache);
* System.Diagnostics.Debug.WriteLine(features.FacialHair.Sideburns);
* System.Diagnostics.Debug.WriteLine(features.FacialHair.Beard);
* System.Diagnostics.Debug.WriteLine(age+"Age inside algorithm. If this works, my calculations are right");
*/
}
/*else
* {
* System.Diagnostics.Debug.WriteLine("It's still broken, you made a mistake.");
* }*/
}
}
}
public static async Task <Photo> ResizeJpeg(IRandomAccessStream chosenPhoto, uint size, string originalFileName, string localFileName, double?quality = null)
{
Photo photo = null;
var orientedPixelHeight = 0u;
var orientedPixelWidth = 0u;
//using (var sourceStream = chosenPhoto)
{
var decoder = await BitmapDecoder.CreateAsync(chosenPhoto);
if (decoder.DecoderInformation != null)
{
var maxDimension = Math.Max(decoder.PixelWidth, decoder.PixelHeight);
var scale = (double)size / maxDimension;
if (scale < 1.0)
{
var orientedScaledHeight = (uint)(decoder.OrientedPixelHeight * scale);
var orientedScaledWidth = (uint)(decoder.OrientedPixelWidth * scale);
var scaledHeight = (uint)(decoder.PixelHeight * scale);
var scaledWidth = (uint)(decoder.PixelWidth * scale);
var transform = new BitmapTransform {
ScaledHeight = scaledHeight, ScaledWidth = scaledWidth, InterpolationMode = BitmapInterpolationMode.Fant
};
var pixelData = await decoder.GetPixelDataAsync(
decoder.BitmapPixelFormat,
decoder.BitmapAlphaMode,
transform,
ExifOrientationMode.RespectExifOrientation,
ColorManagementMode.DoNotColorManage);
using (var destinationStream = new InMemoryRandomAccessStream())
{
var propertySet = new BitmapPropertySet();
if (quality.HasValue && quality > 0.0 && quality <= 1.0)
{
var qualityValue = new BitmapTypedValue(quality, Windows.Foundation.PropertyType.Single);
propertySet.Add("ImageQuality", qualityValue);
}
var encoder = await BitmapEncoder.CreateAsync(BitmapEncoder.JpegEncoderId, destinationStream, propertySet);
encoder.SetPixelData(decoder.BitmapPixelFormat, BitmapAlphaMode.Premultiplied, orientedScaledWidth, orientedScaledHeight, decoder.DpiX, decoder.DpiY, pixelData.DetachPixelData());
await encoder.FlushAsync();
var reader = new DataReader(destinationStream.GetInputStreamAt(0));
var bytes = new byte[destinationStream.Size];
await reader.LoadAsync((uint)destinationStream.Size);
reader.ReadBytes(bytes);
photo = new Photo
{
Bytes = bytes,
Width = (int)orientedScaledWidth,
Height = (int)orientedScaledHeight,
FileName = originalFileName
};
if (!string.IsNullOrEmpty(localFileName))
{
photo.File = await SaveToLocalFolderAsync(destinationStream.AsStream(), localFileName);
}
}
}
orientedPixelHeight = decoder.OrientedPixelHeight;
orientedPixelWidth = decoder.OrientedPixelWidth;
}
}
if (photo == null)
{
var reader = new DataReader(chosenPhoto.GetInputStreamAt(0));
var bytes = new byte[chosenPhoto.Size];
await reader.LoadAsync((uint)chosenPhoto.Size);
reader.ReadBytes(bytes);
photo = new Photo
{
Bytes = bytes,
Width = (int)orientedPixelWidth,
Height = (int)orientedPixelHeight,
FileName = originalFileName
};
if (!string.IsNullOrEmpty(localFileName))
{
photo.File = await SaveToLocalFolderAsync(chosenPhoto.AsStream(), localFileName);
}
}
chosenPhoto.Dispose();
return(photo);
}
private async void BackButton_Click()
{
MediaCapture _mediaCapture = new MediaCapture();
await _mediaCapture.InitializeAsync();
double val_res = 0.0;
double aro_res = 0.0;
Dictionary <int, Tuple <double, double> > imageData =
new Dictionary <int, Tuple <double, double> >();
Dictionary <string, Tuple <double, double> > emoData =
new Dictionary <string, Tuple <double, double> >();
emoData.Add("Neutral", Tuple.Create(4.98, 3.91));
emoData.Add("Sadness", Tuple.Create(2.33, 4.55));
emoData.Add("Disgust", Tuple.Create(3.5, 6.32));
emoData.Add("Anger", Tuple.Create(2.33, 8.46));
emoData.Add("Surprise", Tuple.Create(2.87, 8.11));
emoData.Add("Fear", Tuple.Create(2.11, 8.52));
emoData.Add("Happiness", Tuple.Create(7.09, 8.52));
imageData.Add(1, Tuple.Create(45.698, 56.948));
imageData.Add(2, Tuple.Create(2.951, 80.254));
imageData.Add(3, Tuple.Create(44.751, 46.579));
imageData.Add(4, Tuple.Create(58.107, 41.844));
imageData.Add(5, Tuple.Create(0.72, 92.402));
imageData.Add(6, Tuple.Create(6.758, 78.315));
imageData.Add(7, Tuple.Create(13.962, 72.308));
imageData.Add(8, Tuple.Create(5.666, 81.855));
imageData.Add(9, Tuple.Create(10.942, 68.792));
imageData.Add(10, Tuple.Create(5.095, 60.461));
imageData.Add(11, Tuple.Create(17.421, 79.824));
imageData.Add(12, Tuple.Create(3.675, 83.936));
imageData.Add(13, Tuple.Create(77.82, 13.285));
imageData.Add(14, Tuple.Create(81.301, 27.56));
imageData.Add(15, Tuple.Create(92.896, 32.971));
imageData.Add(16, Tuple.Create(95.341, 20.78));
imageData.Add(17, Tuple.Create(79.398, 20.647));
imageData.Add(18, Tuple.Create(92.759, 18.212));
imageData.Add(19, Tuple.Create(93.05, 16.782));
imageData.Add(20, Tuple.Create(93.076, 24.758));
imageData.Add(21, Tuple.Create(95.163, 29.304));
imageData.Add(22, Tuple.Create(95.167, 8.46));
imageData.Add(23, Tuple.Create(78.075, 35.561));
imageData.Add(24, Tuple.Create(86.7, 11.621));
imageData.Add(25, Tuple.Create(78.635, 20.068));
imageData.Add(26, Tuple.Create(71.86, 59.58));
imageData.Add(27, Tuple.Create(92.909, 22.847));
imageData.Add(28, Tuple.Create(35.436, 55.342));
imageData.Add(29, Tuple.Create(63.66, 45.324));
imageData.Add(30, Tuple.Create(56.168, 16.541));
for (int i = 1; i <= 3; i++)
{
textb.Text = "";
pic.Source = new BitmapImage(new Uri(this.BaseUri, "/Assets/" + i + ".bmp"));
await Task.Delay(TimeSpan.FromSeconds(2));
ImageEncodingProperties imgFormat = ImageEncodingProperties.CreateJpeg();
// a file to save a photo
StorageFile file = await ApplicationData.Current.LocalFolder.CreateFileAsync("Photo.jpg", CreationCollisionOption.ReplaceExisting);
await _mediaCapture.CapturePhotoToStorageFileAsync(imgFormat, file);
IRandomAccessStream imageStream = await file.OpenAsync(FileAccessMode.Read);
double resul_val = 0.0;
double resul_aro = 0.0;
emotionresult = await emotionserviceclient.RecognizeAsync(imageStream.AsStream());
if (emotionresult != null)
{
try
{
var score = emotionresult[0].Scores;
double max = 0.0;
max = Math.Max(max, score.Anger);
max = Math.Max(max, score.Happiness);
max = Math.Max(max, score.Sadness);
max = Math.Max(max, score.Surprise);
max = Math.Max(max, score.Neutral);
max = Math.Max(max, score.Disgust);
max = Math.Max(max, score.Fear);
double[] emo = { score.Anger, score.Disgust, score.Fear, score.Happiness, score.Neutral, score.Surprise, score.Sadness };
if (max == emo[0])
{
textb.Text = "Your primary emotion is: Anger";
}
else
{
if (max == emo[1])
{
textb.Text = "Your primary emotion is: Disgust";
}
else
{
if (max == emo[2])
{
textb.Text = "Your primary emotion is: Fear";
}
else
{
if (max == emo[3])
{
textb.Text = "Your primary emotion is: Happiness";
}
else
{
if (max == emo[4])
{
textb.Text = "Your primary emotion is: Neutral";
}
else
{
if (max == emo[5])
{
textb.Text = "Your primary emotion is: Surprise";
}
else
{
textb.Text = "Your primary emotion is: Sadness";
}
}
}
}
}
}
resul_val = (emoData["Anger"].Item1 * score.Anger +
emoData["Happiness"].Item1 * score.Happiness +
emoData["Sadness"].Item1 * score.Sadness +
emoData["Surprise"].Item1 * score.Surprise +
emoData["Neutral"].Item1 * score.Neutral +
emoData["Disgust"].Item1 * score.Disgust +
emoData["Fear"].Item1 * score.Fear) * 100 / 9;
resul_aro = (emoData["Anger"].Item2 * score.Anger +
emoData["Happiness"].Item2 * score.Happiness +
emoData["Sadness"].Item2 * score.Sadness +
emoData["Surprise"].Item2 * score.Surprise +
emoData["Neutral"].Item2 * score.Neutral +
emoData["Disgust"].Item2 * score.Disgust +
emoData["Fear"].Item2 * score.Fear) * 100 / 9;
}
catch (IndexOutOfRangeException) { textb.Text = "No face detected"; }
double val = imageData[i].Item1;
double aro = imageData[i].Item2;
val_res += (resul_val - val) / (30);
aro_res += (resul_aro - aro) / (30);
await Task.Delay(TimeSpan.FromSeconds(2));
}
}
String ans = "";
if (val_res < 35)
{
ans += "The quality of your response is normal";
}
else
{
if (val_res < 50)
{
ans += "The quality of your response shows slight deviations from ideal values";
}
else
{
ans += "The quality of your response is highly deviated from ideal values";
}
}
if (aro_res < 35)
{
ans += "\nThe intensity of your response is normal";
}
else
{
if (aro_res < 50)
{
ans += "\nThe intensity of your response shows slight deviations from ideal values";
}
else
{
ans += "\nThe intensity of your response is highly deviated from ideal values";
}
}
Frame.Navigate(typeof(result), ans);
}
public static Journal GetJournal(IRandomAccessStream stream)
{
if ( stream == null )
{
return null;
}
else
{
var Reader=new StreamReader(stream . AsStream());
var Doc=XDocument . Parse(Reader . ReadToEnd());
Journal journal;
try
{
journal = (from Jou in Doc . Descendants("Journal")
select new Journal
{
Name = ( string ) Jou . Attribute("Name") ,
ListOfAuthor = from Aut in Jou . Descendants("Author")
select new Author
{
FirstName = ( string ) Aut . Attribute("FirstName") ,
FamilyName = ( string ) Aut . Attribute("FamilyName") ,
EmailAddress = ( string ) Aut . Attribute("EmailAddress") ,
Introduction = ( string ) Aut . Attribute("Introduction")
} ,
ListOfIssue = from Iss in Jou . Descendants("Issue")
select new Issue
{
Number = ( long ) Iss . Attribute("Number") ,
PublishTime = Convert . ToDateTime(( string ) Iss . Attribute("PublishTime")) ,
Price = ( decimal ) Iss . Attribute("Price") ,
ListOfArticle = from Art in Iss . Descendants("Article")
select new Article
{
Title = ( string ) Art . Attribute("Title") ,
TextLine = from Lin in Art . Descendants("Text") . FirstOrDefault() . Descendants("Line")
select ( string ) Lin . Attribute("Run") ,
ListOfAuthorName = from Aut in Art . Descendants("AuthorName")
select ( string ) Aut . Attribute("FirstName") + " " + ( string ) Aut . Attribute("FamilyName") ,
}
}
}) . First();
}
catch ( System . Exception )
{
return null;
}
foreach ( var Aut in journal . ListOfAuthor )
{
foreach ( var Iss in journal . ListOfIssue )
{
foreach ( var Art in Iss . ListOfArticle )
{
foreach ( var aut in Art . ListOfAuthor )
{
if ( Aut == aut )
{
Aut . ArticleHaveContribute . Add(Art);
}
}
}
}
}
return journal;
}
}
public Task <string> UploadPictureAsync(IRandomAccessStream stream)
{
return(UploadPictureAsync(stream.AsStream()));
}
public async void ContinueFileOpenPicker(FileOpenPickerContinuationEventArgs args)
{
//Import data
if ((args.ContinuationData["Operation"] as string) == "UpdateDatabase" &&
args.Files != null &&
args.Files.Count > 0)
{
StorageFile file = args.Files[0];
if (file.Name.EndsWith("poyo"))
{
IRandomAccessStream fileStream = await file.OpenAsync(FileAccessMode.Read);
DataManager.ConnectToDatabase();
List <Lesson> lessons;
int kanjiRound;
int vocabRound;
String importStatus = DataManager.ImportFromFile(fileStream.AsStream(), out lessons, out vocabRound, out kanjiRound);
if (MessageBox.Show(importStatus, "Import", MessageBoxButton.OKCancel) == MessageBoxResult.OK)
{
String updateStatus = DataManager.UpdateDatabase(lessons);
AppSettings.VocabRound = vocabRound;
AppSettings.KanjiRound = kanjiRound;
AppSettings.SaveSettings();
MessageBox.Show(updateStatus);
}
else
{
MessageBox.Show("Import Abgebrochen");
}
DataManager.CloseConnection();
fileStream.Dispose();
}
}
//Add New Content
else if ((args.ContinuationData["Operation"] as string) == "AddContent" &&
args.Files != null &&
args.Files.Count > 0)
{
StorageFile file = args.Files[0];
if (file.Name.EndsWith("nya"))
{
IRandomAccessStream fileStream = await file.OpenAsync(FileAccessMode.Read);
DataManager.ConnectToDatabase();
String updateStatus = DataManager.AddContentFromFile(fileStream.AsStream());
DataManager.CloseConnection();
fileStream.Dispose();
MessageBox.Show(updateStatus);
}
}
updateDatabase = false;
}
private async void button_addface_Click(object sender, RoutedEventArgs e)
{
//Disable all buttons while processing
button_addface.IsEnabled = false;
button_addPhoto.IsEnabled = false;
//Upload function
var storageUri = await storageClient.uploadPhotoAsync(AppSettings.defaultPersonGroupID, Guid.NewGuid().ToString() + ".png", stream.AsStream());
//If exception is returned, display error message
if (storageUri is Exception)
{
var ex = storageUri as Exception;
msg.Title = "Unable to upload photo!";
msg.Content = ex.Message;
await msg.ShowAsync();
}
else if (storageUri as string != "")
{
//Add person face using Face API
//Upload to Azure Blob returns a Uri reference to the image
string Uri = storageUri.ToString();
//Check if this face has already been registered with another user
bool faceExist = await CheckFaceExistsAsync(Uri);
//If the face has not been registered with another account then add face to the person
if (!faceExist)
{
//Get Person ID of the logged in user from local settings
var personId = localSettings.Values["PersonId"].ToString();
//Add Person Face to this Person
var result = await faceClient.CreatePersonFaceAsync(AppSettings.defaultPersonGroupID, personId, Uri);
if (result.IsSuccessStatusCode)
{
var responseContent = await result.Content.ReadAsStringAsync();
//Deserialize response to PersistedFace object
var persistedFace = JsonConvert.DeserializeObject <PersistedFace>(responseContent);
if (persistedFace != null)
{
msg.Title = "Success!";
msg.Content = "Face registered successfully";
//Upload the registered image to Azure blob storage, with the persisted ID
await storageClient.uploadPhotoAsync(AppSettings.defaultPersonGroupID, persistedFace.persistedFaceId + ".png", stream.AsStream());
await msg.ShowAsync();
//Reset image control
PhotoControl.Source = null;
//Save user face details to face table in Azure
var res = await storageClient.AddUserFaceAsync(localSettings.Values["UserName"].ToString(), localSettings.Values["PersonId"].ToString(), Uri, persistedFace.persistedFaceId);
}
}
else
{
msg.Title = "Unable to register face!";
msg.Content = await result.Content.ReadAsStringAsync();
await msg.ShowAsync();
}
}
}
//Train Person Group after adding photo
await faceClient.TrainPersonGroupAsync(AppSettings.defaultPersonGroupID);
//Enable all buttons
button_addface.IsEnabled = true;
button_addPhoto.IsEnabled = true;
//Display last three photos in image control
DisplayLatestPhotos();
}
private async void btnCheckEmotion_Click(object sender, RoutedEventArgs e)
{
try
{
txtFinalEmotion.Text = "";
// txtEmotionInfo.Text = "";
//if( txtEmotionInfo.Text != null || txtFinalEmotion.Text != null )
//{
// txtFinalEmotion.Text = "Please Click Another Photograph";
// txtEmotionInfo.Text = "";
// imgFace.Source = null;
// return;
//}
if (imageStream == null)
{
txtFinalEmotion.Text = "Please Click Another Photograph";
txtEmotionInfo.Text = "";
imgFace.Source = null;
return;
}
// Raw Image Stream as API needs a raw Image Stream
emotionResult = await emotionServiceClient.RecognizeAsync(imageStream.AsStream());
if (emotionResult != null)
{
// emotionResult will contain info. of all the faces & their Emotion
// But we need only 1 Image so we select emotionResult[0]
// Scores contain all the different Emotions like anger, sadness etc.
if (emotionResult.Length == 0)
{
txtFinalEmotion.Text = "NO Emotions Returned :(";
btnCheckEmotion.IsEnabled = false;
}
Scores arrEmotion = emotionResult[0].Scores;
StringBuilder stringBuilder = new StringBuilder(" Your Emotions Are : \n ");
stringBuilder.Append("Happiness : " + arrEmotion.Happiness + "\n");
stringBuilder.Append("Anger : " + arrEmotion.Anger + "\n");
stringBuilder.Append("Contempt : " + arrEmotion.Contempt + "\n");
stringBuilder.Append("Disgust : " + arrEmotion.Disgust + "\n");
stringBuilder.Append("Fear : " + arrEmotion.Fear + "\n");
stringBuilder.Append("Surprise : " + arrEmotion.Surprise + "\n");
stringBuilder.Append("Neutral : " + arrEmotion.Neutral + "\n");
stringBuilder.Append("Sadness : " + arrEmotion.Sadness + "\n");
txtEmotionInfo.Text = stringBuilder.ToString();
StringBuilder stringBuilder2 = new StringBuilder("The Emotion you are feeling is : ");
if (arrEmotion.Happiness >= 0.4)
{
stringBuilder2.Append(" Happy ");
}
if (arrEmotion.Anger >= 0.4)
{
stringBuilder2.Append(" Angry ");
}
if (arrEmotion.Contempt >= 0.4)
{
stringBuilder2.Append(" Contempt ");
}
if (arrEmotion.Disgust >= 0.4)
{
stringBuilder2.Append(" Disgust ");
}
if (arrEmotion.Fear >= 0.4)
{
stringBuilder2.Append(" Scared ");
}
if (arrEmotion.Surprise >= 0.4)
{
stringBuilder2.Append(" Surprised ");
}
if (arrEmotion.Neutral >= 0.4)
{
stringBuilder2.Append(" Neutral ");
}
if (arrEmotion.Sadness >= 0.4)
{
stringBuilder2.Append(" Sad ");
}
txtFinalEmotion.Text = stringBuilder2.ToString();
// imgFace.Source = null;
imageStream = null;
photo = null;
btnCheckEmotion.IsEnabled = false;
}
}
catch (HttpRequestException e2)
{
txtFinalEmotion.Text = "Issue with Establishing a Connection with the API";
txtEmotionInfo.Text = "Error Returning the Emotion";
}
catch (Exception e1)
{
txtEmotionInfo.Text = "Error Returning the Emotion";
}
}
/// <summary>
/// 读取wav文件
/// </summary>
/// <param name="filename"></param>
private async Task <wav> WaveAccess(string filename)
{
try
{
byte[] riff = new byte[4];
byte[] riffSize = new byte[4];
byte[] waveID = new byte[4];
byte[] junkID = new byte[4];
bool hasjunk = false;
byte[] junklength = new byte[4];
byte[] fmtID = new byte[4];
byte[] cksize = new byte[4];
uint waveType = 0;
byte[] channel = new byte[2];
byte[] sample_rate = new byte[4];
byte[] bytespersec = new byte[4];
byte[] blocklen_sample = new byte[2];
byte[] bitNum = new byte[2];
byte[] unknown = new byte[2];
byte[] dataID = new byte[4]; //52
byte[] dataLength = new byte[4]; //56 个字节
//string longFileName = filepath;
//FileStream fstream = new FileStream(filename, FileMode.Open);
//Windows.Storage.StorageFolder s = Windows.ApplicationModel.Package.Current.InstalledLocation;
//FileStream fs;
//StorageFolder storageFolder = Package.Current.InstalledLocation;
//StorageFolder storageFolder = ApplicationData.Current.LocalFolder;
//StorageFile storageFile = await storageFolder.GetFileAsync(filename);
//IRandomAccessStream fileStream = await storageFile.OpenAsync(FileAccessMode.Read);
//Stream s = fileStream.AsStream();
//Stream s = fs.ReadAsync
StorageFolder storageFolder = ApplicationData.Current.LocalFolder;
StorageFile storageFile = await storageFolder.GetFileAsync(filename);
IRandomAccessStream fileStream = await storageFile.OpenAsync(FileAccessMode.Read);
Stream s = fileStream.AsStream();
BinaryReader bread = new BinaryReader(s);
//BinaryReader bread = new BinaryReader(fs);
riff = bread.ReadBytes(4); // RIFF
if (BitConverter.ToUInt32(bytesReserve(riff), 0) != 0x52494646)
{
Exception e = new Exception("该文件不是WAVE文件");
throw e;
}
riffSize = bread.ReadBytes(4); // 文件剩余长度
if (BitConverter.ToUInt32(riffSize, 0) != bread.BaseStream.Length - bread.BaseStream.Position)
{
//Exception e = new Exception("该WAVE文件损坏，文件长度与标记不一致");
//throw e;
}
waveID = bread.ReadBytes(4);
if (BitConverter.ToUInt32(bytesReserve(waveID), 0) != 0x57415645)
{
Exception e = new Exception("该文件不是WAVE文件");
throw e;
}
byte[] tmp = bread.ReadBytes(4);
if (BitConverter.ToUInt32(bytesReserve(tmp), 0) == 0x4A554E4B)
{
//包含junk标记的wav
junkID = tmp;
hasjunk = true;
junklength = bread.ReadBytes(4);
uint junklen = BitConverter.ToUInt32(junklength, 0);
//将不要的junk部分读出
bread.ReadBytes((int)junklen);
//读fmt 标记
fmtID = bread.ReadBytes(4);
}
else if (BitConverter.ToUInt32(bytesReserve(tmp), 0) == 0x666D7420)
{
fmtID = tmp;
}
else
{
Exception e = new Exception("无法找到WAVE文件的junk和fmt标记");
throw e;
}
if (BitConverter.ToUInt32(bytesReserve(fmtID), 0) != 0x666D7420)
{
//fmt 标记
Exception e = new Exception("无法找到WAVE文件fmt标记");
throw e;
}
cksize = bread.ReadBytes(4);
uint p_data_start = BitConverter.ToUInt32(cksize, 0);
int p_wav_start = (int)p_data_start + 8;
waveType = bread.ReadUInt16();
if (waveType != 1)
{
// 非pcm格式，暂不支持
Exception e = new Exception("WAVE文件不是pcm格式，暂时不支持");
throw e;
}
//声道数
channel = bread.ReadBytes(2);
//采样频率
sample_rate = bread.ReadBytes(4);
int fs = (int)BitConverter.ToUInt32(sample_rate, 0);
//每秒钟字节数
bytespersec = bread.ReadBytes(4);
//每次采样的字节大小，2为单声道，4为立体声道
blocklen_sample = bread.ReadBytes(2);
//每个声道的采样精度，默认16bit
bitNum = bread.ReadBytes(2);
tmp = bread.ReadBytes(2);
//寻找da标记
while (BitConverter.ToUInt16(bytesReserve(tmp), 0) != 0x6461)
{
tmp = bread.ReadBytes(2);
}
tmp = bread.ReadBytes(2);
if (BitConverter.ToUInt16(bytesReserve(tmp), 0) != 0x7461)
{
//ta标记
Exception e = new Exception("无法找到WAVE文件data标记");
throw e;
}
//wav数据byte长度
uint DataSize = bread.ReadUInt32();
//计算样本数
long NumSamples = (long)DataSize / 2;
if (NumSamples == 0)
{
NumSamples = (bread.BaseStream.Length - bread.BaseStream.Position) / 2;
}
//if (BitConverter.ToUInt32(notDefinition, 0) == 18)
//{
// unknown = bread.ReadBytes(2);
//}
//dataID = bread.ReadBytes(4);
Int16[] data = new Int16[NumSamples];
for (int i = 0; i < NumSamples; i++)
{
//读入2字节有符号整数
data[i] = bread.ReadInt16();
}
s.Dispose();
//fstream.Close();
//fstream.Dispose();
bread.Dispose();
wav wave = new wav();
wave.wavs = data;
wave.fs = fs;
return(wave);
}
catch (System.Exception ex)
{
//return null;
throw ex;
}
}
private async void getEmotion_Click(object sender, RoutedEventArgs e)
{
try
{
emotionResult = await emotionServiceClient.RecognizeAsync(imageStream.AsStream());
if (emotionResult != null)
{
Scores score = emotionResult[0].Scores;
output.Text = "Your emotions are: \n" +
"Happiness: " + score.Happiness + "\n" +
"Sadness: " + score.Sadness + "\n" +
"Surprise: " + score.Surprise + "\n" +
"Fear: " + score.Fear + "\n" +
"Anger:" + score.Anger + "\n" +
"Contempt:" + score.Contempt + "\n" +
"Disgust:" + score.Disgust + "\n" +
"Neutral:" + score.Neutral + "\n";
if (score.Happiness > score.Sadness && score.Happiness > score.Surprise && score.Happiness > score.Fear && score.Happiness > score.Anger && score.Happiness > score.Contempt && score.Happiness > score.Disgust &&
score.Happiness > score.Neutral)
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("You are Happy");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
media1.Play();
}
else if (score.Sadness > score.Happiness && score.Sadness > score.Surprise && score.Sadness > score.Fear && score.Sadness > score.Anger && score.Sadness > score.Contempt && score.Sadness > score.Disgust &&
score.Sadness > score.Neutral)
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("You are Sad");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
media2.Play();
}
else if (score.Surprise > score.Happiness && score.Surprise > score.Sadness && score.Surprise > score.Fear && score.Surprise > score.Anger && score.Surprise > score.Contempt && score.Surprise > score.Disgust &&
score.Surprise > score.Neutral)
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("You are Surprised");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
media4.Play();
}
else if (score.Fear > score.Happiness && score.Fear > score.Sadness && score.Fear > score.Surprise && score.Fear > score.Anger && score.Fear > score.Contempt && score.Fear > score.Disgust &&
score.Fear > score.Neutral)
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("You are Frightened");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
media5.Play();
}
else if (score.Anger > score.Happiness && score.Anger > score.Sadness && score.Anger > score.Fear && score.Anger > score.Surprise && score.Anger > score.Contempt && score.Anger > score.Disgust &&
score.Anger > score.Neutral)
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("You are Angry");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
}
else if (score.Contempt > score.Happiness && score.Contempt > score.Sadness && score.Contempt > score.Fear && score.Contempt > score.Anger && score.Contempt > score.Surprise && score.Contempt > score.Disgust &&
score.Contempt > score.Neutral)
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("You are Have feeling of contemped");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
}
else if (score.Disgust > score.Happiness && score.Disgust > score.Sadness && score.Disgust > score.Fear && score.Disgust > score.Anger && score.Disgust > score.Contempt && score.Disgust > score.Surprise &&
score.Disgust > score.Neutral)
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("You are feeling disgusting");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
}
else
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("You are felling neutral");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
media3.Play();
}
}
}
catch
{
SpeechSynthesizer synthesizer = new SpeechSynthesizer();
SpeechSynthesisStream SynthesisStream = await synthesizer.SynthesizeTextToStreamAsync("There is an Error Please Click the picture agaian");
//set source and start playing in syn audio stream.
media.AutoPlay = true;
media.SetSource(SynthesisStream, SynthesisStream.ContentType);
media.Play();
}
}
public static async Task<bool> addImages(IRandomAccessStream filestream)
{
bool success = false;
string serviceURL = "http://40.76.6.186:8888/member_register/shin";
string boundary = "---------------------------" + DateTime.Now.Ticks.ToString("x");
success = false;
//Rest request
HttpClient restClient = new HttpClient();
restClient.BaseAddress = new Uri("http://40.76.6.186:8888/member_register/shin");
restClient.DefaultRequestHeaders.TryAddWithoutValidation("Content-Type", "multipart/form-data; boundary=" + boundary);
//falta la autenticacion
// setAuthorization(restClient, service, WEBSERVICE_REQUEST_TYPE_POST);
// This is the postdata
MultipartFormDataContent content = new MultipartFormDataContent(boundary);
content.Add(new StringContent(boundary));
StringContent textPart = new StringContent("1234", Encoding.UTF8);
content.Add(textPart, "project");
StreamContent imagePart = new StreamContent(filestream.AsStream());
imagePart.Headers.Add("Content-Type", "image/jpeg");
content.Add(imagePart, "profile_picture", "111");
HttpRequestMessage req = new HttpRequestMessage(HttpMethod.Post, serviceURL);
req.Content = content;
HttpResponseMessage response = null;
string responseBodyAsText = "";
try
{
response = await restClient.SendAsync(req);
response.EnsureSuccessStatusCode();
responseBodyAsText = await response.Content.ReadAsStringAsync();
if (response.StatusCode == HttpStatusCode.Created)
{
success = true;
}
}
catch (Exception e)
{
string err = e.Message;
}
return success;
}
private async Task CreateTempFile()
{
tempFile = await ApplicationData.Current.TemporaryFolder.CreateFileAsync(Guid.NewGuid() + ".tmp", CreationCollisionOption.GenerateUniqueName);
rtStream = await tempFile.OpenAsync(FileAccessMode.ReadWrite);
var newStream = rtStream.AsStream();
var position = currentStream.Position;
currentStream.Position = 0;
await currentStream.CopyToAsync(newStream);
newStream.Position = position;
currentStream.Dispose();
currentStream = newStream;
}
public Stream OpenWrite(string path)
{
IRandomAccessStream streamWithContentType = OpenWriteStream(path);
return(streamWithContentType.AsStream());
}
private async void generate_Click(object sender, RoutedEventArgs e)
{
try
{
emotionResult = await emotionServiceClient.RecognizeAsync(imageStream.AsStream());
if (emotionResult != null)
{
string[] emo =
{
"Happy",
"Sad",
"Surprise",
"Anger",
"Fear",
"Contemp",
"Disgust",
"Neutral"
};
double[] anArray = { emotionResult[0].Scores.Happiness, emotionResult[0].Scores.Sadness, emotionResult[0].Scores.Surprise, emotionResult[0].Scores.Fear, emotionResult[0].Scores.Anger, emotionResult[0].Scores.Contempt, emotionResult[0].Scores.Disgust, emotionResult[0].Scores.Neutral };
// Finding max
double large = anArray.Max();
int p = Array.IndexOf(anArray, large);
confidencecheck.Text = "Highest : " + emo[p];
string myemo = emo[p];
if (myemo == emotion_u)
{
ar += 20;
myscore.Text = ar.ToString();
}
/*List<GraphHR2> lst2 = new List<GraphHR2>();
* //fix this, shift heart rate and stop watch time
* lst2.Add(new GraphHR2 { Emotion = "Happiness", Values = (emotionResult[0].Scores.Happiness) * 100 });
* lst2.Add(new GraphHR2 { Emotion = "Sadness", Values = (emotionResult[0].Scores.Sadness) * 100 });
* lst2.Add(new GraphHR2 { Emotion = "Surprise", Values = (emotionResult[0].Scores.Surprise) * 100 });
* lst2.Add(new GraphHR2 { Emotion = "Fear", Values = (emotionResult[0].Scores.Fear) * 100 });
* lst2.Add(new GraphHR2 { Emotion = "Anger", Values = (emotionResult[0].Scores.Anger) * 100 });
* lst2.Add(new GraphHR2 { Emotion = "Contempt", Values = (emotionResult[0].Scores.Contempt) * 100 });
* lst2.Add(new GraphHR2 { Emotion = "Disgust", Values = (emotionResult[0].Scores.Disgust) * 100 });
* lst2.Add(new GraphHR2 { Emotion = "Neutral", Values = (emotionResult[0].Scores.Neutral) * 100 });
* (ColumnChart.Series[0] as ColumnSeries).ItemsSource = lst2;
* (PieChart2.Series[0] as PieSeries).ItemsSource = lst2;
*
*
*
*
* if (emo[p] == "Neutral")
* {
* steps.Visibility = Visibility.Collapsed;
*
* confidencecheck.Text = "These type of people are hard to deal with.\n Try to deal with them in a funny way.\nPass a joke and give it a try.";
* Talk(confidencecheck.Text);
* }
* else if (emo[p] == "Surprise")
* {
* steps.Visibility = Visibility.Visible;
* image3.Visibility = Visibility.Collapsed;
* steps.Text = "";
* Talk(steps.Text);
* }
* else if (emo[p] == "Happiness")
* {
* steps.Visibility = Visibility.Visible;
* image3.Visibility = Visibility.Collapsed;
* steps.Text = "";
* Talk(steps.Text);
* }
* else if (emo[p] == "Fear")
* {
* steps.Visibility = Visibility.Visible;
* image3.Visibility = Visibility.Collapsed;
* steps.Text = "";
* Talk(steps.Text);
* }
* else if (emo[p] == "Angry")
* {
* steps.Visibility = Visibility.Visible;
* image3.Visibility = Visibility.Collapsed;
* steps.Text = "";
* Talk(steps.Text);
* }
* else if (emo[p] == "Sadness")
* {
* steps.Visibility = Visibility.Visible;
* image3.Visibility = Visibility.Collapsed;
* steps.Text = "";
* Talk(steps.Text);
* }
* else if (emo[p] == "Contempt")
* {
* steps.Visibility = Visibility.Visible;
* image3.Visibility = Visibility.Collapsed;
* steps.Text = "";
* Talk(steps.Text);
* }
* else if (emo[p] == "Disgust")
* {
* steps.Visibility = Visibility.Visible;
* image3.Visibility = Visibility.Collapsed;
* steps.Text = "";
* Talk(steps.Text);
* }*/
}
}
catch
{
confidencecheck.Text = "Error returning the emotion";
}
}
private async void OnSelectImageButtonClicked(object sender, RoutedEventArgs e)
{
var picker = new FileOpenPicker();
picker.ViewMode = PickerViewMode.Thumbnail;
picker.SuggestedStartLocation = PickerLocationId.PicturesLibrary;
picker.FileTypeFilter.Add(".jpg");
picker.FileTypeFilter.Add(".jpeg");
picker.FileTypeFilter.Add(".png");
var file = await picker.PickSingleFileAsync();
if (file != null)
{
using (IRandomAccessStream stream = await file.OpenAsync(FileAccessMode.Read))
{
// Delete existing face rectangles
DeleteFaceRectangles();
// Show the image
var image = new BitmapImage();
await image.SetSourceAsync(stream);
LoadedImage.Source = image;
Container.UpdateLayout();
var ratio = LoadedImage.ActualHeight / image.PixelHeight;
Progress.IsActive = true;
Overlay.Visibility = Visibility.Visible;
try
{
// Submit the image to the Face API
FaceClient client = new FaceClient(
new ApiKeyServiceClientCredentials(_key),
new System.Net.Http.DelegatingHandler[] { }
);
client.Endpoint = _uri;
IList <FaceAttributeType> attributes = new FaceAttributeType[]
{
FaceAttributeType.Gender,
FaceAttributeType.Age,
FaceAttributeType.Emotion,
FaceAttributeType.Glasses,
FaceAttributeType.FacialHair
};
stream.Seek(0L);
var faces = await client.Face.DetectWithStreamAsync(stream.AsStream(), true, false, attributes);
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
foreach (var face in faces)
{
// Highlight the face with a Rectangle
var rect = new Rectangle();
rect.Width = face.FaceRectangle.Width * ratio;
rect.Height = face.FaceRectangle.Height * ratio;
var x = (face.FaceRectangle.Left * ratio) + ((Container.ActualWidth - LoadedImage.ActualWidth) / 2.0);
var y = (face.FaceRectangle.Top * ratio) + ((Container.ActualHeight - LoadedImage.ActualHeight) / 2.0);
rect.Margin = new Thickness(x, y, 0, 0);
rect.HorizontalAlignment = HorizontalAlignment.Left;
rect.VerticalAlignment = VerticalAlignment.Top;
rect.Fill = new SolidColorBrush(Colors.Transparent);
rect.Stroke = new SolidColorBrush(Colors.Red);
rect.StrokeThickness = 2.0;
rect.Tag = face.FaceId;
rect.PointerEntered += (s, args) =>
{
// Change the rectangle border to yellow when the pointer enters it
rect.Stroke = new SolidColorBrush(Colors.Yellow);
};
rect.PointerExited += (s, args) =>
{
// Change the rectangle border to red when the pointer exits it
rect.Stroke = new SolidColorBrush(Colors.Red);
};
rect.PointerPressed += async(s, args) =>
{
// Display information about a face when it is clicked
var id = (Guid)((Rectangle)s).Tag;
var selected = faces.Where(f => f.FaceId == id).First();
var gender = selected.FaceAttributes.Gender;
var age = selected.FaceAttributes.Age;
var beard = selected.FaceAttributes.FacialHair.Beard > 0.50 ? "Yes" : "No";
var moustache = selected.FaceAttributes.FacialHair.Moustache > 0.50 ? "Yes" : "No";
var glasses = selected.FaceAttributes.Glasses;
// Use reflection to enumerate Emotion properties
var props = selected.FaceAttributes.Emotion.GetType()
.GetProperties()
.Where(pi => pi.PropertyType == typeof(double) && pi.GetGetMethod() != null)
.Select(pi => new
{
pi.Name,
Value = (double)pi.GetGetMethod().Invoke(selected.FaceAttributes.Emotion, null)
});
// Determine the dominant emotion
var max = props.Max(p => p.Value);
var emotion = props.Single(p => p.Value == max).Name;
// Show the results
var message = $"Gender: {gender}\nAge: {age}\nBeard: { beard}\nMoustache: {moustache}\nGlasses: {glasses}\nEmotion: {emotion}";
await new MessageDialog(message).ShowAsync();
};
Container.Children.Add(rect);
}
}
catch (Exception ex)
{
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
await new MessageDialog(ex.Message).ShowAsync();
}
finally
{
Progress.IsActive = false;
Overlay.Visibility = Visibility.Collapsed;
}
}
}
}
public async void Open(string fileName)
{
var file = await KnownFolders.MusicLibrary.CreateFileAsync( fileName, CreationCollisionOption.ReplaceExisting );
stream = await file.OpenAsync( FileAccessMode.ReadWrite );
binaryWriter = new BinaryWriter( stream.AsStream() );
dataSize = 0;
WriteWaveHeader( 0 );
disposed = false;
}
public static async Task <ImageFormat> DetectImageFormat(this IRandomAccessStream randomAccessStream)
{
await using var stream = randomAccessStream.AsStream();
using var image = Image.FromStream(stream);
return(image.RawFormat);
}
private async void getEmotion_Click(object sender, RoutedEventArgs e)
{
try
{
emotionResults = await emotionService.RecognizeAsync(imageStream.AsStream());
faceRects = await UploadAndDetectFaces(photo.Path, photo);
//Desenho um quadrado nas posicoes identificadas do rosto
var property = await photo.Properties.GetImagePropertiesAsync();
var writeableBmp = BitmapFactory.New((int)property.Width, (int)property.Height);
using (writeableBmp.GetBitmapContext())
{
//Load bitmap from image file
using (var fileStream = await photo.OpenAsync(FileAccessMode.Read))
{
writeableBmp = await BitmapFactory.New(1, 1).FromStream(fileStream, BitmapPixelFormat.Bgra8);
}
}
if (faceRects != null && faceRects.Length > 0)
{
foreach (var face in faceRects)
{
writeableBmp.DrawRectangle(face.Left, face.Top,
face.Left + face.Width,
face.Top + face.Height, Colors.Yellow);
}
debug.Text = "Rostos identificados: " + faceRects.Length;
}
//Sobrescreve com uma nova contendo as marcacoes
image.Source = writeableBmp;
output.Text = "";
if (emotionResults != null)
{
int i = 0;
foreach (var p in emotionResults)
{
var score = p.Scores;
output.Text += "Your Emotions are for photo #" + i + " : \n" +
"Feliz: " + String.Format("{0:0.##}", score.Happiness * 100) + " %" + "\n" +
"Tristeza: " + String.Format("{0:0.##}", score.Sadness * 100) + " %" + "\n" +
"Surpreso: " + String.Format("{0:0.##}", score.Surprise * 100) + " %" + "\n" +
"Raiva: " + String.Format("{0:0.##}", score.Anger * 100) + " %" + "\n" +
"Desprezo: " + String.Format("{0:0.##}", score.Contempt * 100) + " %" + "\n" +
"Desgosto: " + String.Format("{0:0.##}", score.Disgust * 100) + " %" + "\n" +
"Medo: " + String.Format("{0:0.##}", score.Fear * 100) + " %" + "\n" +
"Neutro: " + String.Format("{0:0.##}", score.Neutral * 100) + " %" + "\n";
i++;
}
}
}
catch (Exception ex)
{
output.Text = "Erro: Check Emotions \n" + ex.Message + "\n";
}
}
async Task finishEnrollment()
{
if (btnRecordEnroll.IsEnabled == false)
{
return; // if user clicks and then comes timer event
}
btnRecordEnroll.Content = "Start record enrollment";
btnRecordEnroll.IsEnabled = false;
await CaptureMedia.StopRecordAsync();
Stream str = AudioStream.AsStream();
str.Seek(0, SeekOrigin.Begin);
_speakerId = Guid.Parse((lbProfiles.SelectedItem as ListBoxItem).Content.ToString());
OperationLocation processPollingLocation;
try
{
processPollingLocation = await _serviceClient.EnrollAsync(str, _speakerId);
}
catch (EnrollmentException vx)
{
txtInfo.Text = vx.Message;
CleanAfter();
return;
}
catch (Exception vx)
{
txtInfo.Text = vx.Message;
CleanAfter();
return;
}
EnrollmentOperation enrollmentResult = null;
int numOfRetries = 10;
TimeSpan timeBetweenRetries = TimeSpan.FromSeconds(5.0);
while (numOfRetries > 0)
{
await Task.Delay(timeBetweenRetries);
enrollmentResult = await _serviceClient.CheckEnrollmentStatusAsync(processPollingLocation);
if (enrollmentResult.Status == Status.Succeeded)
{
break;
}
else if (enrollmentResult.Status == Status.Failed)
{
txtInfo.Text = enrollmentResult.Message;
CleanAfter();
return;
}
numOfRetries--;
}
if (numOfRetries <= 0)
{
txtInfo.Text = "Identification operation timeout";
}
else
{
txtInfo.Text = "Enrollment done. " + enrollmentResult.Status + Environment.NewLine + " Remaining Speech Time " + enrollmentResult.ProcessingResult.RemainingEnrollmentSpeechTime;
}
CleanAfter();
}
private async void takePhoto_Click(object sender, RoutedEventArgs e)
{
// camera code to handle capture, storage and display of photo
try
{
photo = await captureUI.CaptureFileAsync(CameraCaptureUIMode.Photo);
if (photo == null)
{
return;
}
else
{
imageStream = await photo.OpenAsync(FileAccessMode.Read);
BitmapDecoder decoder = await BitmapDecoder.CreateAsync(imageStream);
SoftwareBitmap softwareBitmap = await decoder.GetSoftwareBitmapAsync();
SoftwareBitmap softwareBitmapBGR8 = SoftwareBitmap.Convert(softwareBitmap, BitmapPixelFormat.Bgra8, BitmapAlphaMode.Premultiplied);
SoftwareBitmapSource bitmapSource = new SoftwareBitmapSource();
await bitmapSource.SetBitmapAsync(softwareBitmapBGR8);
image.Source = bitmapSource;
}
}
catch (Exception)
{
textBlock.Text = "Error taking the picture";
//throw;
}
// emotion code, grabs elements returned from emotionservice and displays results
try
{
emotionResult = await emotionServiceClient.RecognizeAsync(imageStream.AsStream());
if (emotionResult != null)
{
EmotionScores scores = emotionResult[0].Scores;
textBlock.Text = "According to a robot, your emotions are: \n\n" +
"Happiness: " + scores.Happiness + "\n" +
"Sadness: " + scores.Sadness + "\n" +
"Fear: " + scores.Fear + "\n" +
"Neutral: " + scores.Neutral;
if (scores.Neutral > 0.5)
{
textBlock.Text += "\n\nRobot says: \"Ah, I see we are more similar than I had thought, human.\"";
}
else
{
textBlock.Text += "\n\nRobot says: \"Your emotions will be your undoing, foolish bag of mostly water.\"";
}
}
}
catch (Exception)
{
textBlock.Text = "Error! Emotions not found. Bleep bloop.";
//throw;
}
}
private async void button_Click(object sender, RoutedEventArgs e)
{
int i, t;
float min;
try
{
photo = await captureUI.CaptureFileAsync(CameraCaptureUIMode.Photo);
if (photo == null)
{
return;
}
else
{
imageStream = await photo.OpenAsync(FileAccessMode.Read);
emotionResult = await emotionServiceClient.RecognizeAsync(imageStream.AsStream());
if (emotionResult != null)
{
Scores score = emotionResult[0].Scores;
float[] a = new float[7] {
score.Happiness, score.Sadness, score.Fear, score.Anger, score.Contempt, score.Disgust, score.Neutral
};
t = 0;
min = 0;
i = 0;
while (i < 6)
{
if (a[i] > min)
{
min = a[i];
t = i;
}
i++;
}
switch (t)
{
case 0:
BitmapImage happiness =
new BitmapImage(new Uri("ms-appx:///Assets/happiness.jpg"));
image.Source = happiness;
break;
case 1:
BitmapImage sadness =
new BitmapImage(new Uri("ms-appx:///Assets/sadness.jpg"));
image.Source = sadness;
break;
case 2:
BitmapImage fear =
new BitmapImage(new Uri("ms-appx:///Assets/fear.jpg"));
image.Source = fear;
break;
case 3:
BitmapImage anger =
new BitmapImage(new Uri("ms-appx:///Assets/angry.jpg"));
image.Source = anger;
break;
case 4:
BitmapImage contempt =
new BitmapImage(new Uri("ms-appx:///Assets/contempt.jpg"));
image.Source = contempt;
break;
case 5:
BitmapImage disgust =
new BitmapImage(new Uri("ms-appx:///Assets/disgust.jpg"));
image.Source = disgust;
break;
case 6:
BitmapImage neutral =
new BitmapImage(new Uri("ms-appx:///Assets/neutral.png"));
image.Source = neutral;
break;
}
}
}
}
catch
{
BitmapImage error = new BitmapImage(new Uri("ms-appx:///Assets/error.jpg"));
image.Source = error;
}
}
private async void Button_Click(object sender, RoutedEventArgs e)
{
ItemsNuevos.Clear();
cnvCanvasSelected.Children.Clear();
Items.Clear();
cnvCanvas.Children.Clear();
LoadingControl.IsLoading = true;
resultadosDistancia.Clear();
Windows.Storage.Pickers.FileOpenPicker openPicker = new Windows.Storage.Pickers.FileOpenPicker();
openPicker.SuggestedStartLocation = Windows.Storage.Pickers.PickerLocationId.Desktop;
openPicker.ViewMode = Windows.Storage.Pickers.PickerViewMode.Thumbnail;
openPicker.FileTypeFilter.Clear();
openPicker.FileTypeFilter.Add(".bmp");
openPicker.FileTypeFilter.Add(".png");
openPicker.FileTypeFilter.Add(".jpeg");
openPicker.FileTypeFilter.Add(".jpg");
storageFile = await openPicker.PickSingleFileAsync();
if (storageFile != null)
{
var stream = await storageFile.OpenAsync(FileAccessMode.Read);
randomAccessStreamImage = stream;
Stream streamImage = randomAccessStreamImage.AsStream();
byte[] b;
using (BinaryReader br = new BinaryReader(streamImage))
{
b = br.ReadBytes((int)streamImage.Length);
}
byte[] byteArray;
using (Windows.Storage.Streams.IRandomAccessStream fileStream = await storageFile.OpenAsync(Windows.Storage.FileAccessMode.Read))
{
Windows.UI.Xaml.Media.Imaging.BitmapImage bitmapImage = new Windows.UI.Xaml.Media.Imaging.BitmapImage();
bitmapImage.SetSource(fileStream);
width = bitmapImage.PixelWidth;
heigth = bitmapImage.PixelHeight;
if (width > 400)
{
constante = 1 / (width / 600);
width = width * constante;
heigth = heigth * constante;
}
byteArray = new byte[fileStream.AsStream().Length];
cnvCanvas.Width = (int)width;
cnvCanvas.Height = (int)heigth;
cnvCanvasSelected.Width = (int)width;
cnvCanvasSelected.Height = (int)heigth;
imagePreview.Width = (int)width;
imagePreview.Height = (int)heigth;
imagePreview.Source = bitmapImage;
imagePreview.Opacity = 0.4;
vsproject = vs.Last().ToString();
try
{
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", localSettings.Values["apiKeyCV"] as string);
ByteArrayContent bytearrayContent = new ByteArrayContent(b);
bytearrayContent.Headers.ContentType = new System.Net.Http.Headers.MediaTypeHeaderValue("application/octet-stream");
var projecto = vsproject;
var byteArrayNuevo = bytearrayContent;
var result = await client.PostAsync("https://southcentralus.api.cognitive.microsoft.com/customvision/v2.0/Prediction/" + vsproject + "/image", bytearrayContent);
if (result.IsSuccessStatusCode)
{
var response = result.Content.ReadAsStringAsync().Result;
dynamic obj = JsonConvert.DeserializeObject <dynamic>(response);
int contador = 0;
var dynamicImagePredict = obj.id;
idPredictedImage = (string)dynamicImagePredict;
foreach (var item in obj.predictions)
{
var resultadoCaja = item.boundingBox;
var resultadoTag = item.tagName;
if (item.probability * 100 >= 75)
{
imagePreview.Opacity = 1;
imagePreview.Visibility = Visibility.Visible;
dibujarCaja(resultadoCaja, resultadoTag, item.probability);
LoadingControl.IsLoading = false;
contador += 1;
}
;
}
txtResult.Text = "Se encontraron: " + contador.ToString() + " elementos";
SolidColorBrush solidColorBrushSalud = new SolidColorBrush(Windows.UI.Colors.Green);
txtResultSalud.Foreground = solidColorBrushSalud;
txtResultSalud.Text = "La salud del cultivo es OPTIMA";
}
}
catch (Exception ex)
{
var error = ex.Message.ToString();
throw;
}
}
}
}
/// <summary>
/// Load the family and their notes from local storage
/// </summary>
/// <returns>Null if there was no model to load, otherwise, the deserialized model</returns>
private async Task <Model> LoadModelAsync()
{
Model model = null;
InkStrokeContainer combinedStrokes = new InkStrokeContainer(); // To avoid managing individual files for every InkCanvas, we will combine all ink stroke information into one container
List <int> InkStrokesPerCanvas = new List <int>();
try
{
StorageFile modelDataFile = await ApplicationData.Current.LocalFolder.GetFileAsync(NOTES_MODEL_FILE);
using (IRandomAccessStream randomAccessStream = await modelDataFile.OpenAsync(FileAccessMode.ReadWrite))
{
// Load the model which contains the people and the note collection
try
{
DataContractJsonSerializer modelSerializer = new DataContractJsonSerializer(typeof(Model));
model = (Model)modelSerializer.ReadObject(randomAccessStream.AsStream());
}
catch (System.Runtime.Serialization.SerializationException)
{
System.Diagnostics.Debug.Assert(false, "Failed to load serialized model");
return(null);
}
}
// For each sticky note, load the number of inkstrokes it contains
StorageFile inkDataFile = await ApplicationData.Current.LocalFolder.GetFileAsync(NOTES_INK_FILE);
using (IInputStream inkStream = await inkDataFile.OpenSequentialReadAsync())
{
bool combinedStrokesExist = false;
DataReader reader = new DataReader(inkStream);
foreach (StickyNote n in model.StickyNotes)
{
await reader.LoadAsync(sizeof(int)); // You need to buffer the data before you can read from a DataReader.
int numberOfInkStrokes = reader.ReadInt32();
InkStrokesPerCanvas.Add(numberOfInkStrokes);
combinedStrokesExist |= numberOfInkStrokes > 0;
}
// Load the ink data
if (combinedStrokesExist)
{
await combinedStrokes.LoadAsync(inkStream);
}
} // using inkStream
} // try
catch (FileNotFoundException)
{
// No data to load. We'll start with a fresh model
return(null);
}
// Factor out the inkstrokes from the big container into each note
int allStrokesIndex = 0, noteIndex = 0;
IReadOnlyList <InkStroke> allStrokes = combinedStrokes.GetStrokes();
foreach (StickyNote n in model.StickyNotes)
{
// InkStrokeContainers can't be serialized using the default xml/json serialization.
// So create a new one and fill it up from the data we restored
n.Ink = new InkStrokeContainer();
// pull out the ink strokes that belong to this note
for (int i = 0; i < InkStrokesPerCanvas[noteIndex]; i++)
{
n.Ink.AddStroke(allStrokes[allStrokesIndex++].Clone());
}
++noteIndex;
}
return(model);
}
public async Task <Stream> ConvertToStream(StorageFile photoFile)
{
IRandomAccessStream stream = await photoFile.OpenAsync(FileAccessMode.Read);
return(stream.AsStream());
}