| public DetectMultiScale ( OpenCvSharp.Mat image, int &rejectLevels, double &levelWeights, double scaleFactor = 1.1, int minNeighbors = 3, HaarDetectionType flags, Size minSize = null, Size maxSize = null, bool outputRejectLevels = false ) : Rect[] | ||
| image | OpenCvSharp.Mat | Matrix of the type CV_8U containing an image where objects are detected. |
| rejectLevels | int | |
| levelWeights | double | |
| scaleFactor | double | Parameter specifying how much the image size is reduced at each image scale. |
| minNeighbors | int | Parameter specifying how many neighbors each candidate rectangle should have to retain it. |
| flags | HaarDetectionType | Parameter with the same meaning for an old cascade as in the function cvHaarDetectObjects. /// It is not used for a new cascade. |
| minSize | Size | Minimum possible object size. Objects smaller than that are ignored. |
| maxSize | Size | Maximum possible object size. Objects larger than that are ignored. |
| outputRejectLevels | bool | |
| Résultat | Rect[] | |
public virtual Rect[] DetectMultiScale(
Mat image,
out int[] rejectLevels,
out double[] levelWeights,
double scaleFactor = 1.1,
int minNeighbors = 3,
HaarDetectionType flags = 0,
Size? minSize = null,
Size? maxSize = null,
bool outputRejectLevels = false)
{
if (disposed)
throw new ObjectDisposedException("CascadeClassifier");
if (image == null)
throw new ArgumentNullException(nameof(image));
image.ThrowIfDisposed();
Size minSize0 = minSize.GetValueOrDefault(new Size());
Size maxSize0 = maxSize.GetValueOrDefault(new Size());
using (var objectsVec = new VectorOfRect())
using (var rejectLevelsVec = new VectorOfInt32())
using (var levelWeightsVec = new VectorOfDouble())
{
NativeMethods.objdetect_CascadeClassifier_detectMultiScale2(
ptr, image.CvPtr, objectsVec.CvPtr, rejectLevelsVec.CvPtr, levelWeightsVec.CvPtr,
scaleFactor, minNeighbors, (int)flags, minSize0, maxSize0, outputRejectLevels ? 1 : 0);
rejectLevels = rejectLevelsVec.ToArray();
levelWeights = levelWeightsVec.ToArray();
return objectsVec.ToArray();
}
}
| CascadeClassifier::DetectMultiScale ( OpenCvSharp.Mat image, double scaleFactor = 1.1, int minNeighbors = 3, HaarDetectionType flags, Size minSize = null, Size maxSize = null ) : Rect[] |
/// <summary>
///
/// </summary>
/// <param name="cascade"></param>
/// <returns></returns>
private Mat DetectFace(CascadeClassifier cascade)
{
Mat result;
using (var src = new Mat(FilePath.Image.Yalta, ImreadModes.Color))
using (var gray = new Mat())
{
result = src.Clone();
Cv2.CvtColor(src, gray, ColorConversionCodes.BGR2GRAY);
// Detect faces
Rect[] faces = cascade.DetectMultiScale(
gray, 1.08, 2, HaarDetectionType.ScaleImage, new Size(30, 30));
// Render all detected faces
foreach (Rect face in faces)
{
var center = new Point
{
X = (int)(face.X + face.Width * 0.5),
Y = (int)(face.Y + face.Height * 0.5)
};
var axes = new Size
{
Width = (int)(face.Width * 0.5),
Height = (int)(face.Height * 0.5)
};
Cv2.Ellipse(result, center, axes, 0, 0, 360, new Scalar(255, 0, 255), 4);
}
}
return result;
}
