pigo

Overview ¶

Package pigo is a lightweight pure Go face detection, pupil/eyes localization and facial landmark points detection library based on Pixel Intensity Comparison-based Object detection paper (https://arxiv.org/pdf/1305.4537.pdf). Is platform agnostic and does not require any external dependencies and third party modules.

Face detection API example ¶

First you need to load and parse the binary classifier, then convert the image to grayscale mode and finally to run the cascade function which returns a slice containing the row, column, scale and the detection score.

cascadeFile, err := ioutil.ReadFile("/path/to/cascade/file")
if err != nil {
	log.Fatalf("Error reading the cascade file: %v", err)
}

src, err := pigo.GetImage("/path/to/image")
if err != nil {
	log.Fatalf("Cannot open the image file: %v", err)
}

pixels := pigo.RgbToGrayscale(src)
cols, rows := src.Bounds().Max.X, src.Bounds().Max.Y

cParams := pigo.CascadeParams{
	MinSize:     fd.minSize,
	MaxSize:     fd.maxSize,
	ShiftFactor: fd.shiftFactor,
	ScaleFactor: fd.scaleFactor,

	ImageParams: pigo.ImageParams{
		Pixels: pixels,
		Rows:   rows,
		Cols:   cols,
		Dim:    cols,
	},
}

pigo := 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 := pigo.Unpack(cascadeFile)
if err != nil {
	log.Fatalf("Error reading the cascade file: %s", err)
}

angle := 0.0 // cascade rotation angle. 0.0 is 0 radians and 1.0 is 2*pi radians

// 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, angle)

// Calculate the intersection over union (IoU) of two clusters.
dets = classifier.ClusterDetections(dets, 0.2)

For pupil/eyes localization and facial landmark points detection API example check the source code.