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test: included new benchmark tests

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esimov
2021-10-21 14:19:34 +03:00
parent a18c4ebad5
commit 7b6884c981
3 changed files with 156 additions and 45 deletions
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76
core/pigo_test.go
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@@ -5,6 +5,7 @@ import (
"io/ioutil"
"log"
"path/filepath"
"runtime"
"testing"
pigo "github.com/esimov/pigo/core"
@@ -68,43 +69,82 @@ func TestPigo_InputImageShouldBeGrayscale(t *testing.T) {
}
func TestPigo_Detector_ShouldDetectFace(t *testing.T) {
// Unpack the binary file. This will return the number of cascade trees,
// Unpack the facefinder binary cascade file. This will return the number of cascade trees,
// the tree depth, the threshold and the prediction from tree's leaf nodes.
classifier, err := p.Unpack(pigoCascade)
p, err := p.Unpack(pigoCascade)
if err != nil {
t.Fatalf("error reading the cascade file: %s", err)
}
// 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)
faces := p.RunCascade(*cParams, 0.0)
// Calculate the intersection over union (IoU) of two clusters.
faces = classifier.ClusterDetections(faces, 0.1)
faces = p.ClusterDetections(faces, 0.1)
if len(faces) == 0 {
t.Fatalf("face should've been detected")
}
}
func BenchmarkPigo(b *testing.B) {
func BenchmarkPigoUnpackCascade(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 {
log.Fatalf("Error reading the cascade file: %s", err)
}
var dets []pigo.Detection
b.ResetTimer()
for i := 0; i < b.N; i++ {
pixs := pigo.RgbToGrayscale(srcImg)
cParams.Pixels = pixs
// Unpack the facefinder binary cascade file.
_, err := pg.Unpack(pigoCascade)
if err != nil {
log.Fatalf("error reading the cascade file: %s", err)
}
}
}
func BenchmarkPigoFaceDetection(b *testing.B) {
var dets []pigo.Detection
pg := pigo.NewPigo()
p, err := pg.Unpack(pigoCascade)
if err != nil {
log.Fatalf("error reading the cascade file: %s", err)
}
pixs := pigo.RgbToGrayscale(srcImg)
cParams.Pixels = pixs
b.ResetTimer()
runtime.GC()
for i := 0; i < b.N; i++ {
// 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.
dets = classifier.RunCascade(*cParams, 0.0)
dets = p.RunCascade(*cParams, 0.0)
// Calculate the intersection over union (IoU) of two clusters.
dets = classifier.ClusterDetections(dets, 0.1)
dets = p.ClusterDetections(dets, 0.1)
}
_ = dets
}
func BenchmarkPigoClusterDetection(b *testing.B) {
var dets []pigo.Detection
pg := pigo.NewPigo()
p, err := pg.Unpack(pigoCascade)
if err != nil {
log.Fatalf("error reading the cascade file: %s", err)
}
pixs := pigo.RgbToGrayscale(srcImg)
cParams.Pixels = pixs
b.ResetTimer()
runtime.GC()
// 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.
dets = p.RunCascade(*cParams, 0.0)
for i := 0; i < b.N; i++ {
// Calculate the intersection over union (IoU) of two clusters.
dets = p.ClusterDetections(dets, 0.1)
}
_ = dets
}