static float[] GetEmbedding(Bitmap image)
{
var faces = _faceDetectorLight.Forward(image);
using var cropped = Imaging.Crop(image, faces.First());
var points = _faceLandmarksExtractor.Forward(cropped);
using var aligned = FaceLandmarksExtractor.Align(cropped, points);
return(_faceEmbedder.Forward(aligned));
}
/// <summary>
/// Returns face recognition results.
/// </summary>
/// <param name="image">Image</param>
/// <param name="rectangles">Rectangles</param>
/// <returns>Array</returns>
public float[][] Forward(Bitmap image, params Rectangle[] rectangles)
{
int length = rectangles.Length;
float[][] vector = new float[length][];
for (int i = 0; i < length; i++)
{
using var cropped = Imaging.Crop(image, rectangles[i]);
vector[i] = Forward(cropped);
}
return(vector);
}
static string[] GetEmotionAndBeauty(Bitmap image, Rectangle face)
{
using var cropped = Imaging.Crop(image, face);
var points = _faceLandmarksExtractor.Forward(cropped);
using var aligned = FaceLandmarksExtractor.Align(cropped, points);
var emotion = _faceEmotionClassifier.Forward(aligned);
var emotionLabel = FaceEmotionClassifier.Labels[emotion.Argmax()];
var beauty = _faceBautyClassifier.Forward(aligned);
var beautyLabel = $"{Math.Round(2 * beauty.Max(), 1)}/10.0";
Console.WriteLine($"--> classified as [{emotionLabel}] emotion and [{beautyLabel}] beauty");
return(new string[] { emotionLabel, beautyLabel });
}
static string[] GetRaceAndAge(Bitmap image, Rectangle face)
{
using var cropped = Imaging.Crop(image, face);
var points = _faceLandmarksExtractor.Forward(cropped);
using var aligned = FaceLandmarksExtractor.Align(cropped, points);
var race = _faceRaceClassifier.Forward(aligned);
var raceLabel = FaceRaceClassifier.Labels[race.Argmax()];
var age = _faceAgeClassifier.Forward(aligned);
var ageLabel = FaceAgeClassifier.Labels[age.Argmax()];
Console.WriteLine($"--> classified as [{raceLabel}] race and [{ageLabel}] age");
return(new string[] { raceLabel, ageLabel });
}
/// <summary>
/// Returns face landmarks.
/// </summary>
/// <param name="image">Image</param>
/// <param name="rectangles">Rectangles</param>
/// <returns>Points</returns>
public Point[][] Forward(Bitmap image, params Rectangle[] rectangles)
{
var length = rectangles.Length;
var vector = new Point[length][];
for (int i = 0; i < length; i++)
{
var rectangle = rectangles[i];
using var cropped = Imaging.Crop(image, rectangle);
var points = Forward(cropped);
var count = points.Length;
for (int j = 0; j < points.Length; j++)
{
points[j] = new Point(
points[j].X + rectangle.X,
points[j].Y + rectangle.Y);
}
vector[i] = points;
}
return(vector);
}
public override RanorexStepExecutionResponse Execute(Dictionary <string, object> arguments)
{
RanorexStepExecutionResponse stepResponse = new RanorexStepExecutionResponse();
try
{
RepoItemInfo repoItemInfo = null;
Ranorex.Unknown adapter = null;
string target = (string)arguments.GetValueOrDefault <string, object>("target");
int timeout = Convert.ToInt32(arguments.GetValueOrDefault <string, object>("timeout"));
bool retrieveImage = (bool)arguments.GetValueOrDefault <string, object>("retrieveImage");
System.Collections.IDictionary imageProps = (System.Collections.IDictionary)arguments["imageValidationProperties"];
System.Collections.IList attributes = (System.Collections.IList)arguments["attributes"];
if (timeout == default(int))
{
timeout = 10000;
}
if (target != default(string))
{
repoItemInfo = CreateItemInfo(repo, target, timeout);
adapter = CreateAdapter(repoItemInfo);
Dictionary <string, object> structuredData = new Dictionary <string, object>();
Dictionary <string, object> receivedAttributes = new Dictionary <string, object>();
foreach (System.Collections.IDictionary attribute in attributes)
{
string name = (string)attribute["header"];
string value = adapter.Element.GetAttributeValueText(name);
stepResponse.message += name + "=" + value + "\n";
receivedAttributes.Add(name, value);
}
structuredData.Add("attributes", receivedAttributes);
if (imageProps != null)
{
string validationMode = (string)imageProps["validationMode"];
if (validationMode != "NONE")
{
string image = (string)imageProps["imageData"];
int rectX = Convert.ToInt32(imageProps["clipX"]);
int rectY = Convert.ToInt32(imageProps["clipY"]);
int rectWidth = Convert.ToInt32(imageProps["clipWidth"]);
int rectHeight = Convert.ToInt32(imageProps["clipHeight"]);
try
{
CompressedImage compressedImage = new CompressedImage(image);
using (Bitmap bitmap = Imaging.Crop(compressedImage.Image, new Rectangle(rectX, rectY, rectWidth, rectHeight)))
{
compressedImage = new CompressedImage(bitmap);
}
if (validationMode == "CONTAINS_IMAGE")
{
Validate.ContainsImage(repoItemInfo, compressedImage, Imaging.FindOptions.Default);
}
else if (validationMode == "COMPARE_IMAGE")
{
Validate.ContainsImage(repoItemInfo, compressedImage, Imaging.FindOptions.Default);
}
structuredData.Add("imageValidated", "true");
stepResponse.message += "#imageValidated=true\n";
}
catch (ValidationException e)
{
structuredData.Add("imageValidated", "false");
stepResponse.message += "#imageValidated=false\n";
}
}
}
stepResponse.structuredData = structuredData;
if (retrieveImage)
{
stepResponse.image64 = GetImage64(adapter);
}
}
else
{
throw new Exception("No target defined!");
}
stepResponse.success = true;
}
catch (Exception e)
{
stepResponse.message = "Ranorex Exception: " + e.Message;
stepResponse.success = false;
}
return(stepResponse);
}
