In our previous posts we did the following:
In this post we will look at verifying faces to people. Let’s do a few things first.
We will add a new Image control to the form next to our original Image1 control. We will call this Image 2. We will move our TextBlock1 to the right. We will also add 2 buttons:
- Delete
- Verify
Finally we will add a new TextBox to display our results of verification.
First, we will delete our existing people groups in storage, in order to start with a clean slate. We can do this with the following code:
// Get list of all people groups
IList<PersonGroup> persongroupList = await faceClient.PersonGroup.ListAsync();
foreach (PersonGroup pg in persongroupList)
{
// Delete person group
await faceClient.PersonGroup.DeleteAsync(pg.PersonGroupId);
}
MessageBox.Show("Delete completed.");
Next, we will create a new group and person, and attach a face to that person using the code from our People, Groups and Persisted Faces tutorial. We will do this using the Create Person button.
try
{
// Create Person group
string persongroupName = "My People Group";
string persongroupPersonGroupId = Guid.NewGuid().ToString();
await faceClient.PersonGroup.CreateAsync(persongroupPersonGroupId, persongroupName);
// Create person
string personName = "Bob Smith";
string personId = Guid.NewGuid().ToString();
Person p = await faceClient.PersonGroupPerson.CreateAsync(persongroupPersonGroupId, personName);
using (Stream imageFileStream = File.OpenRead(imageFilePath))
{
await faceClient.PersonGroupPerson.AddFaceFromStreamAsync(
persongroupPersonGroupId, p.PersonId, imageFileStream);
}
}
catch (APIErrorException f)
{
MessageBox.Show(f.Message);
}
catch (Exception e)
{
MessageBox.Show(e.Message, "Error");
}
We now have a face, person and group created based on a photo we have selected.
Now, we will select another photo and determine if that person is the same as the person we first selected. We can do this on the Verify button, using the VerifyFaceToPersonAsync method.
var dialog = new Microsoft.Win32.OpenFileDialog();
dialog.Filter = "JPG (*.jpg)|*.jpg";
bool? result = dialog.ShowDialog(this);
if (!(bool)result)
{
return;
}
string filePath = dialog.FileName;
Uri uriSource = new Uri(filePath);
BitmapImage source = new BitmapImage();
source.BeginInit();
source.CacheOption = BitmapCacheOption.None;
source.UriSource = uriSource;
source.EndInit();
Image2.Source = source;
faceList = await UploadAndDetectFaces(filePath);
bool found = false;
double Confidence = 0;
IList<PersonGroup> persongroupList = await faceClient.PersonGroup.ListAsync();
foreach (PersonGroup pg in persongroupList)
{
if (pg.Name == "My People Group")
{
// List all the people in this group
IList<Person> people = await faceClient.PersonGroupPerson.ListAsync(pg.PersonGroupId);
foreach (Person person in people)
{
// Compare Face Id created from upload with Person
VerifyResult vr = await faceClient.Face.VerifyFaceToPersonAsync(faceList[0].FaceId.Value, person.PersonId, pg.PersonGroupId);
Confidence = vr.Confidence;
}
}
}
if (Confidence > 0)
{
txtConfidence.Text = "The confidence is: " + Confidence.ToString();
}
else
{
txtConfidence.Text = "Person not found";
}
We will first upload the 2nd image and send it to Azure to detect the face. We can do that using our UploadAndDetectFaces method. We will then find our group, and for all people in that group use VerifyFaceToPersonAsync. We will get the confidence and display it in our TextBox.
Start the app:
Click on Delete:
Click on Create Person to select a person:
Click on Verify to select a 2nd person. We can see the confidence of these 2 faces belonging to the same person, is 0.84316, or 84%:
The full code:
using Microsoft.Azure.CognitiveServices.Vision.Face;
using Microsoft.Azure.CognitiveServices.Vision.Face.Models;
using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows;
using System.Windows.Controls;
using System.Windows.Data;
using System.Windows.Documents;
using System.Windows.Input;
using System.Windows.Media;
using System.Windows.Media.Imaging;
using System.Windows.Navigation;
using System.Windows.Shapes;
namespace Carl.FaceAPI
{
///
<summary>
/// Interaction logic for MainWindow.xaml
/// </summary>
public partial class MainWindow : Window
{
private const string subscriptionKey = "yourkey";
private const string baseUri =
"https://yourregion.api.cognitive.microsoft.com/";
private readonly IFaceClient faceClient = new FaceClient(
new ApiKeyServiceClientCredentials(subscriptionKey),
new System.Net.Http.DelegatingHandler[] { });
IList<DetectedFace> faceList;
String[] faceDescriptions;
double resizeFactor;
public MainWindow()
{
InitializeComponent();
faceClient.Endpoint = baseUri;
}
private async void btnBrowse_Click(object sender, RoutedEventArgs e)
{
var dialog = new Microsoft.Win32.OpenFileDialog();
dialog.Filter = "JPG (*.jpg)|*.jpg";
bool? result = dialog.ShowDialog(this);
if (!(bool)result)
{
return;
}
string filePath = dialog.FileName;
Uri uriSource = new Uri(filePath);
BitmapImage source = new BitmapImage();
source.BeginInit();
source.CacheOption = BitmapCacheOption.None;
source.UriSource = uriSource;
source.EndInit();
Image1.Source = source;
faceList = await UploadAndDetectFaces(filePath);
if (faceList.Count > 0)
{
DrawingVisual visual = new DrawingVisual();
DrawingContext context = visual.RenderOpen();
context.DrawImage(source, new Rect(0, 0, source.Width, source.Height));
double dpi = source.DpiX;
resizeFactor = (dpi > 0) ? 96 / dpi : 1;
faceDescriptions = new String[faceList.Count];
for (int i = 0; i < faceList.Count; ++i)
{
DetectedFace face = faceList[i];
context.DrawRectangle(
Brushes.Transparent,
new Pen(Brushes.Green, 5),
new Rect(
face.FaceRectangle.Left * resizeFactor,
face.FaceRectangle.Top * resizeFactor,
face.FaceRectangle.Width * resizeFactor,
face.FaceRectangle.Height * resizeFactor
)
);
}
context.Close();
RenderTargetBitmap facewithRectangle = new RenderTargetBitmap(
(int)(source.PixelWidth * resizeFactor),
(int)(source.PixelHeight * resizeFactor),
96,
96,
PixelFormats.Default);
facewithRectangle.Render(visual);
Image1.Source = facewithRectangle;
}
}
private async Task<IList<DetectedFace>> UploadAndDetectFaces(string imageFilePath)
{
try
{
IList<FaceAttributeType> faceAttributes =
new FaceAttributeType[]
{
FaceAttributeType.Age,
FaceAttributeType.Blur,
FaceAttributeType.Emotion,
FaceAttributeType.FacialHair,
FaceAttributeType.Gender,
FaceAttributeType.Glasses,
FaceAttributeType.Hair,
FaceAttributeType.HeadPose,
FaceAttributeType.Makeup,
FaceAttributeType.Noise,
FaceAttributeType.Occlusion,
FaceAttributeType.Smile
};
using (Stream imageFileStream = File.OpenRead(imageFilePath))
{
IList<DetectedFace> faceList =
await faceClient.Face.DetectWithStreamAsync(
imageFileStream, true, false, faceAttributes);
return faceList;
}
}
catch (APIErrorException f)
{
MessageBox.Show(f.Message);
return new List<DetectedFace>();
}
catch (Exception e)
{
MessageBox.Show(e.Message, "Error");
return new List<DetectedFace>();
}
}
private void btnDetectAttributes_Click(object sender, RoutedEventArgs e)
{
ImageSource imageSource = Image1.Source;
BitmapSource bitmapSource = (BitmapSource)imageSource;
var scale = Image1.ActualWidth / (bitmapSource.PixelWidth / resizeFactor);
for (int i = 0; i < faceList.Count; ++i) { FaceRectangle fr = faceList[i].FaceRectangle; double left = fr.Left * scale; double top = fr.Top * scale; double width = fr.Width * scale; double height = fr.Height * scale; faceDescriptions[i] = FaceDescription(faceList[i]); TextBlock1.Text = TextBlock1.Text + string.Format("Person {0}: {1} \n", i.ToString(), faceDescriptions[i]); } } private string FaceDescription(DetectedFace face) { StringBuilder sb = new StringBuilder(); sb.Append(face.FaceAttributes.Gender); sb.Append(", "); sb.Append(face.FaceAttributes.Age); sb.Append(", "); sb.Append(String.Format("smile {0:F1}%, ", face.FaceAttributes.Smile * 100)); sb.Append("Emotion: "); Emotion emotionScores = face.FaceAttributes.Emotion; if (emotionScores.Anger >= 0.1f)
sb.Append(String.Format("anger {0:F1}%, ", emotionScores.Anger * 100));
if (emotionScores.Contempt >= 0.1f)
sb.Append(String.Format("contempt {0:F1}%, ", emotionScores.Contempt * 100));
if (emotionScores.Disgust >= 0.1f)
sb.Append(String.Format("disgust {0:F1}%, ", emotionScores.Disgust * 100));
if (emotionScores.Fear >= 0.1f)
sb.Append(String.Format("fear {0:F1}%, ", emotionScores.Fear * 100));
if (emotionScores.Happiness >= 0.1f)
sb.Append(String.Format("happiness {0:F1}%, ", emotionScores.Happiness * 100));
if (emotionScores.Neutral >= 0.1f)
sb.Append(String.Format("neutral {0:F1}%, ", emotionScores.Neutral * 100));
if (emotionScores.Sadness >= 0.1f)
sb.Append(String.Format("sadness {0:F1}%, ", emotionScores.Sadness * 100));
if (emotionScores.Surprise >= 0.1f)
sb.Append(String.Format("surprise {0:F1}%, ", emotionScores.Surprise * 100));
sb.Append(face.FaceAttributes.Glasses);
sb.Append(", ");
sb.Append("Hair: ");
if (face.FaceAttributes.Hair.Bald >= 0.01f)
sb.Append(String.Format("bald {0:F1}% ", face.FaceAttributes.Hair.Bald * 100));
IList<HairColor> hairColors = face.FaceAttributes.Hair.HairColor;
foreach (HairColor hairColor in hairColors)
{
if (hairColor.Confidence >= 0.1f)
{
sb.Append(hairColor.Color.ToString());
sb.Append(String.Format(" {0:F1}% ", hairColor.Confidence * 100));
}
}
sb.Append(string.Format("Blur: {0}", face.FaceAttributes.Blur.BlurLevel));
sb.Append(string.Format("Facial Hair: {0}", face.FaceAttributes.FacialHair.Beard));
sb.Append(string.Format("Head Pose: {0}", face.FaceAttributes.HeadPose.Roll));
sb.Append(string.Format("Makeup: {0}", face.FaceAttributes.Makeup.LipMakeup));
sb.Append(string.Format("Noise: {0}", face.FaceAttributes.Noise.NoiseLevel));
sb.Append(string.Format("Occlusion: {0}", face.FaceAttributes.Occlusion.ForeheadOccluded));
return sb.ToString();
}
private async void btnCreatePerson_Click(object sender, RoutedEventArgs e)
{
var dialog = new Microsoft.Win32.OpenFileDialog();
dialog.Filter = "JPG (*.jpg)|*.jpg";
bool? result = dialog.ShowDialog(this);
if (!(bool)result)
{
return;
}
string filePath = dialog.FileName;
Uri uriSource = new Uri(filePath);
BitmapImage source = new BitmapImage();
source.BeginInit();
source.CacheOption = BitmapCacheOption.None;
source.UriSource = uriSource;
source.EndInit();
Image1.Source = source;
CreatePersonandGroup(filePath);
}
private async void CreatePersonandGroup(string imageFilePath)
{
try
{
// Create Person group
string persongroupName = "My People Group";
string persongroupPersonGroupId = Guid.NewGuid().ToString();
await faceClient.PersonGroup.CreateAsync(persongroupPersonGroupId, persongroupName);
// Create person
string personName = "Bob Smith";
string personId = Guid.NewGuid().ToString();
Person p = await faceClient.PersonGroupPerson.CreateAsync(persongroupPersonGroupId, personName);
using (Stream imageFileStream = File.OpenRead(imageFilePath))
{
await faceClient.PersonGroupPerson.AddFaceFromStreamAsync(
persongroupPersonGroupId, p.PersonId, imageFileStream);
}
}
catch (APIErrorException f)
{
MessageBox.Show(f.Message);
}
catch (Exception e)
{
MessageBox.Show(e.Message, "Error");
}
}
private async void btnVerify_Click(object sender, RoutedEventArgs e)
{
var dialog = new Microsoft.Win32.OpenFileDialog();
dialog.Filter = "JPG (*.jpg)|*.jpg";
bool? result = dialog.ShowDialog(this);
if (!(bool)result)
{
return;
}
string filePath = dialog.FileName;
Uri uriSource = new Uri(filePath);
BitmapImage source = new BitmapImage();
source.BeginInit();
source.CacheOption = BitmapCacheOption.None;
source.UriSource = uriSource;
source.EndInit();
Image2.Source = source;
faceList = await UploadAndDetectFaces(filePath);
bool found = false;
double Confidence = 0;
IList<PersonGroup> persongroupList = await faceClient.PersonGroup.ListAsync();
foreach (PersonGroup pg in persongroupList)
{
if (pg.Name == "My People Group")
{
// List all the people in this group
IList<Person> people = await faceClient.PersonGroupPerson.ListAsync(pg.PersonGroupId);
foreach (Person person in people)
{
// Compare Face Id created from upload with Person
VerifyResult vr = await faceClient.Face.VerifyFaceToPersonAsync(faceList[0].FaceId.Value, person.PersonId, pg.PersonGroupId);
Confidence = vr.Confidence;
}
}
}
if (Confidence > 0)
{
txtConfidence.Text = "The confidence is: " + Confidence.ToString();
}
else
{
txtConfidence.Text = "Person not found";
}
}
private async void btnDelete_Click(object sender, RoutedEventArgs e)
{
// Get list of all people groups
IList<PersonGroup> persongroupList = await faceClient.PersonGroup.ListAsync();
foreach (PersonGroup pg in persongroupList)
{
// Delete person group
await faceClient.PersonGroup.DeleteAsync(pg.PersonGroupId);
}
MessageBox.Show("Delete completed.");
}
}
}
THANKS FOR READING. BEFORE YOU LEAVE, I NEED YOUR HELP.
I AM SPENDING MORE TIME THESE DAYS CREATING YOUTUBE VIDEOS TO HELP PEOPLE LEARN THE MICROSOFT POWER PLATFORM.
IF YOU WOULD LIKE TO SEE HOW I BUILD APPS, OR FIND SOMETHING USEFUL READING MY BLOG, I WOULD REALLY APPRECIATE YOU SUBSCRIBING TO MY YOUTUBE CHANNEL.
THANK YOU, AND LET'S KEEP LEARNING TOGETHER.
CARL
