private static void DetectSqueezeNet(NcnnDotNet.OpenCV.Mat bgr, List <float> clsScores)
{
using (var squeezeNet = new Net())
{
if (Ncnn.IsSupportVulkan)
{
squeezeNet.Opt.UseVulkanCompute = true;
}
// the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
squeezeNet.LoadParam("squeezenet_v1.1.param");
squeezeNet.LoadModel("squeezenet_v1.1.bin");
using var @in = Mat.FromPixelsResize(bgr.Data, PixelType.Bgr, bgr.Cols, bgr.Rows, 227, 227);
var meanVals = new[] { 104f, 117f, 123f };
@in.SubstractMeanNormalize(meanVals, null);
using var ex = squeezeNet.CreateExtractor();
ex.Input("data", @in);
using var @out = new Mat();
ex.Extract("prob", @out);
clsScores.Capacity = @out.W;
for (var j = 0; j < @out.W; j++)
{
clsScores.Add(@out[j]);
}
}
}
public List <Face> DetectFaces(string imagePath)
{
List <Face> faces = new List <Face>()
{
};
float tolerance = 0.5f;
using (NcnnDotNet.OpenCV.Mat frame = NcnnDotNet.OpenCV.Cv2.ImRead(imagePath))
{
using (NcnnDotNet.Mat inMat = NcnnDotNet.Mat.FromPixels(frame.Data, NcnnDotNet.PixelType.Bgr2Rgb, frame.Cols, frame.Rows))
{
FaceInfo[] faceInfos = _centerFaceDetector.Detect(inMat, frame.Cols, frame.Rows, tolerance).ToArray();
foreach (FaceInfo detectedFace in faceInfos)
{
faces.Add(new Face((int)detectedFace.X1,
(int)detectedFace.Y1,
(int)detectedFace.X2 - (int)detectedFace.X1,
(int)detectedFace.Y2 - (int)detectedFace.Y1,
DrawPen));
}
}
}
return(faces);
}
