|
public Detect ( Byte>.Image |
||
| image | Byte>.Image | The image to detect objects in |
| overlapThreshold | float | Threshold for the non-maximum suppression algorithm, Use default value of 0.5 |
| return | Emgu.CV.Structure.MCvObjectDetection[] | |
static void Run()
{
using (Mat image = CvInvoke.Imread("cat.jpg", LoadImageType.AnyColor | LoadImageType.AnyDepth))
using (LatentSvmDetector detector = new LatentSvmDetector(new string[] { "cat.xml" }))
{
Stopwatch watch = Stopwatch.StartNew();
MCvObjectDetection[] regions = detector.Detect(image, 0.5f);
watch.Stop();
foreach (MCvObjectDetection region in regions)
{
CvInvoke.Rectangle(image, region.Rect, new MCvScalar(0, 0, 255));
}
ImageViewer.Show(image, String.Format("Object detected in {0} milliseconds", watch.ElapsedMilliseconds));
}
}
public void TestLatenSVM()
{
using (LatentSvmDetector detector = new LatentSvmDetector(new string[] { EmguAssert.GetFile("cat.xml") }))
{
String[] files = new String[] { "cat.png"};
for (int idx = 0; idx < files.Length; idx++)
using (Mat img = EmguAssert.LoadMat(files[idx]))
{
MCvObjectDetection[] results = detector.Detect(img, 0.5f);
if (results.Length >= 0)
{
double maxScore = results[0].Score;
Rectangle result = results[0].Rect;
for (int i = 1; i < results.Length; ++i)
{
if (results[i].Score > maxScore)
{
maxScore = results[i].Score;
result = results[i].Rect;
}
}
CvInvoke.Rectangle(img, result, new MCvScalar(0, 0, 255));
//Emgu.CV.UI.ImageViewer.Show(img);
}
}
}
}