MainPage.xaml.cs

using Plugin.Media;  
using Xamarin.Forms;  
using XamarinCognitive.Models;  
using Newtonsoft.Json;  
namespace XamarinCognitive  
{  
    public partial class MainPage : ContentPage  
    {  
        public string subscriptionKey = "26d1b6941e3a422c880639fdcdcf069b";  
  
        public string uriBase = "https://southeastasia.api.cognitive.microsoft.com/face/v1.0/detect";  
  
        public MainPage()  
        {  
            InitializeComponent();  
        }  
  
        async void btnPick_Clicked(object sender, System.EventArgs e)  
        {  
            await CrossMedia.Current.Initialize();  
            try  
            {  
                var file = await CrossMedia.Current.PickPhotoAsync(new Plugin.Media.Abstractions.PickMediaOptions  
                {  
                    PhotoSize = Plugin.Media.Abstractions.PhotoSize.Medium  
                });  
                if (file == null) return;  
                imgSelected.Source = ImageSource.FromStream(() => {  
                    var stream = file.GetStream();  
                    return stream;  
                });  
                MakeAnalysisRequest(file.Path);  
            }  
            catch (Exception ex)  
            {  
                string test = ex.Message;  
            }  
  
        }  
  
  
        public async void MakeAnalysisRequest(string imageFilePath)  
        {  
            HttpClient client = new HttpClient();  
            client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", subscriptionKey);  
  
            string requestParameters = "returnFaceId=true&returnFaceLandmarks=false" +  
                "&returnFaceAttributes=age,gender,headPose,smile,facialHair,glasses," +  
                "emotion,hair,makeup,occlusion,accessories,blur,exposure,noise";  
  
            string uri = uriBase + "?" + requestParameters;  
            HttpResponseMessage response;  
            byte[] byteData = GetImageAsByteArray(imageFilePath);  
  
            using (ByteArrayContent content = new ByteArrayContent(byteData))  
            {  
                content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");  
                response = await client.PostAsync(uri, content);  
  
                string contentString = await response.Content.ReadAsStringAsync();  
  
                List<ResponseModel> faceDetails = JsonConvert.DeserializeObject<List<ResponseModel>>(contentString);  
                if(faceDetails.Count!=0)  
                {  
                    lblHappiness.Text = "Happiness : " + faceDetails[0].faceAttributes.emotion.happiness;  
                    lblSadness.Text = "Sadness : " + faceDetails[0].faceAttributes.emotion.sadness;  
                    lblAnger.Text = "Anger : " + faceDetails[0].faceAttributes.emotion.anger;  
                    lblFear.Text = "Fear : " + faceDetails[0].faceAttributes.emotion.fear;  
                    lblNeutral.Text = "Neutral : " + faceDetails[0].faceAttributes.emotion.neutral;  
                    lblSurprise.Text = "Surprise : " + faceDetails[0].faceAttributes.emotion.surprise;  
                    lblDisgust.Text = "Disgust : " + faceDetails[0].faceAttributes.emotion.disgust;  
                    lblContempt.Text = "Contempt : " + faceDetails[0].faceAttributes.emotion.contempt;  
                }  
  
            }  
        }  
        public byte[] GetImageAsByteArray(string imageFilePath)  
        {  
            using (FileStream fileStream =  
                new FileStream(imageFilePath, FileMode.Open, FileAccess.Read))  
            {  
                BinaryReader binaryReader = new BinaryReader(fileStream);  
                return binaryReader.ReadBytes((int)fileStream.Length);  
            }  
        }  
    }  
}