Classifier always gives me some result about go-face HOT 21 CLOSED

dataImage := filepath.Join(DATA_DIR, "mix.jpg")

faces, err := rec.RecognizeFile(dataImage)
if err != nil {
	return err
}

var samples []face.Descriptor
var totalF []int32
for i, f := range faces {
	samples = append(samples, f.Descriptor)
	// Each face is unique on that image so goes to its own category.
	totalF = append(totalF, int32(i))
}

// Pass samples to the recognizer.
rec.SetSamples(samples, totalF)

// Now let's try to classify some not yet known image.

testData := filepath.Join(DATA_DIR, "sumit.jpg")
res, err := [rec.RecognizeSingleFile(testData)](url)
if err != nil {
	log.Println("Face not recorganise not the same person")
	return status.Errorf(
		codes.Internal,
		fmt.Sprintln(errormsg.ERR_FACE_NOT_REC))
}
if res == nil {
	log.Println("Not a sigle image")
	return status.Errorf(
		codes.Internal,
		fmt.Sprintln(errormsg.ERR_NOT_A_SINGLE_FACE))
}
id := rec.ClassifyThreshold(res.Descriptor, 0.6)
if id < 0 {
	log.Println("Can't classify")
	return status.Errorf(
		codes.Internal,
		fmt.Sprintln(errormsg.ERR_MSG_INTERNAL_SERVER))
}
log.Println("id", id)
log.Println("Image recorganise")

func compare_faces(samples []face.Descriptor, comp face.Descriptor, tolerance float32) int {
	res := face_distance(samples, comp)
	r := -1
	v := float32(1)

	for i, s := range res {
		t := euclidean_norm(s)
		if t < tolerance && t < v{
			v = t
			r = i
		}
	}

	return r
}

func face_distance(samples []face.Descriptor, comp face.Descriptor) []face.Descriptor {
	res := make([]face.Descriptor, len(samples))

	for i, s := range samples {
		for j, _ := range s {
			res[i][j] = samples[i][j] - comp[j]
		}
	}

	return res
}

func euclidean_norm(f face.Descriptor) float32 {
	var s float32
	for _, v := range f {
		s = s + v * v
	}

	return float32(math.Sqrt(float64(s)))
}