async Task MakeRequest(MediaFile file)
{
var client = new HttpClient();
// Request headers - replace this example key with your valid key.
client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "93800861ed354f2ab03e5e9d37600150");
// NOTE: You must use the same region in your REST call as you used to obtain your subscription keys.
// For example, if you obtained your subscription keys from westcentralus, replace "westus" in the
// URI below with "westcentralus".
string uri = "https://westus.api.cognitive.microsoft.com/emotion/v1.0/recognize?";
HttpResponseMessage response;
string responseContent;
// Request body. Try this sample with a locally stored JPEG image.
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
// This example uses content type "application/octet-stream".
// The other content types you can use are "application/json" and "multipart/form-data".
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(uri, content);
if (response.IsSuccessStatusCode)
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(uri, content);
responseContent = response.Content.ReadAsStringAsync().Result;
List <Face> Face = JsonConvert.DeserializeObject <List <Face> >(responseContent);
try {
TagLabel.Text = "Emotion shown is: " + (Face[0].getTop().Item2);
var locator = CrossGeolocator.Current;
locator.DesiredAccuracy = 1000;
var position = await locator.GetPositionAsync(TimeSpan.FromSeconds(10));
string plat = Convert.ToString(position.Latitude);
string plong = Convert.ToString(position.Longitude);
emmaptable emmapmodel = new emmaptable();
emmapmodel.Latitude = plat;
emmapmodel.Longitude = plong;
emmapmodel.Emotion = Face[0].getTop().Item2;
Debug.WriteLine((float)position.Latitude);
Debug.WriteLine((float)position.Longitude);
await AzureManager.AzureManagerInstance.PostEmotionInformation(emmapmodel);
}
catch (Exception e)
{
Debug.WriteLine("Error in face processing (detection/deserialisation/post)");
TagLabel.Text = "Cannot detect face. Please try again.";
}
}
file.Dispose();
}
}
public async Task PostEmotionInformation(emmaptable emotionmodel)
{
await this.emotiontable.InsertAsync(emotionmodel);
}