Extend flploc benchmark tests

This commit is contained in:
esimov
2019-10-14 12:18:50 +03:00
parent 01dc9b6d5a
commit 3bcbd8862e
3 changed files with 94 additions and 8 deletions

View File

@@ -74,3 +74,59 @@ func TestFlploc_LandmarkPointsFinderShouldReturnDetectionPoints(t *testing.T) {
t.Fatalf("should have been detected facial landmark points: %s", err)
}
}
func BenchmarkFlploc(b *testing.B) {
pg := pigo.NewPigo()
// Unpack the binary file. This will return the number of cascade trees,
// the tree depth, the threshold and the prediction from tree's leaf nodes.
classifier, err := pg.Unpack(pigoCascade)
if err != nil {
b.Fatalf("error reading the cascade file: %s", err)
}
pl := pigo.PuplocCascade{}
plc, err := pl.UnpackCascade(puplocCascade)
if err != nil {
b.Fatalf("error reading the cascade file: %s", err)
}
var faces []pigo.Detection
b.ResetTimer()
for i := 0; i < b.N; i++ {
pixs := pigo.RgbToGrayscale(srcImg)
cParams.Pixels = pixs
// Run the classifier over the obtained leaf nodes and return the detection results.
// The result contains quadruplets representing the row, column, scale and detection score.
faces = classifier.RunCascade(*cParams, 0.0)
// Calculate the intersection over union (IoU) of two clusters.
faces = classifier.ClusterDetections(faces, 0.1)
for _, face := range faces {
if face.Scale > 50 {
// left eye
puploc := &pigo.Puploc{
Row: face.Row - int(0.075*float32(face.Scale)),
Col: face.Col - int(0.175*float32(face.Scale)),
Scale: float32(face.Scale) * 0.25,
Perturbs: 50,
}
leftEye := plc.RunDetector(*puploc, *imgParams, 0.0, false)
// right eye
puploc = &pigo.Puploc{
Row: face.Row - int(0.075*float32(face.Scale)),
Col: face.Col + int(0.185*float32(face.Scale)),
Scale: float32(face.Scale) * 0.25,
Perturbs: 50,
}
rightEye := plc.RunDetector(*puploc, *imgParams, 0.0, false)
plc.FindLandmarkPoints(leftEye, rightEye, *imgParams, 63, "left")
}
}
}
_ = faces
}