Files
pigo/examples/delaunay/pigo.go
2019-02-18 11:48:09 +02:00

206 lines
4.8 KiB
Go

package main
import "C"
import (
"image"
"image/color"
"io/ioutil"
"log"
"runtime"
"unsafe"
"github.com/esimov/pigo/core"
"github.com/esimov/triangle"
)
var (
cascade []byte
err error
p *pigo.Pigo
classifier *pigo.Pigo
)
type SubImager interface {
SubImage(r image.Rectangle) image.Image
}
type pixs struct {
rows, cols int
}
func main() {}
//export FindFaces
func FindFaces(pixels []uint8) uintptr {
px := &pixs{
rows: 480,
cols: 640,
}
proc := &triangle.Processor{
BlurRadius: 4,
SobelThreshold: 10,
PointsThreshold: 20,
MaxPoints: 100,
Wireframe: 0,
Noise: 0,
StrokeWidth: 1,
IsSolid: false,
Grayscale: false,
OutputToSVG: false,
OutputInWeb: false,
}
tri := &triangle.Image{*proc}
pointCh := make(chan uintptr)
dets := px.clusterDetection(pixels)
img := px.pixToImage(pixels)
tFaces := make([][]int, len(dets))
result := make([][]int, len(dets))
det := make([]int, 0, len(dets))
totalPixDim := 0
go func() {
for i := 0; i < len(dets); i++ {
if dets[i].Q >= 5.0 {
result[i] = append(result[i], dets[i].Row, dets[i].Col, dets[i].Scale)
rect := image.Rect(
dets[i].Col-dets[i].Scale/2,
dets[i].Row-dets[i].Scale/2,
dets[i].Scale,
dets[i].Scale,
)
subImg := img.(SubImager).SubImage(rect)
bounds := subImg.Bounds()
if bounds.Dx() > 1 && bounds.Dy() > 1 {
triRes, _, _, err := tri.Draw(subImg, false, func() {})
if err != nil {
log.Fatal(err.Error())
}
triPix := px.imgToPix(triRes)
tFaces[i] = append(tFaces[i], triPix...)
// Prepend the top left coordinates of the detected faces to the delaunay triangles.
tFaces[i] = append([]int{len(triPix), bounds.Min.X, bounds.Min.Y}, tFaces[i]...)
totalPixDim += len(triPix)
}
}
}
// Since in Go we cannot transfer a 2d array trough an array pointer
// we have to transform it into 1d array.
for _, v := range result {
det = append(det, v...)
}
// Convert the multidimmensional slice containing the triangulated images to 1d slice.
convTri := make([]int, 0, len(result)+totalPixDim)
for _, v := range tFaces {
convTri = append(convTri, v...)
}
// Include as a first slice element the number of detected faces.
// We need to transfer this value in order to define the Python array buffer length.
det = append([]int{len(result), 0, 0}, det...)
// Append the generated triangle slices to detected faces array.
det = append(det, convTri...)
// Convert the slice into an array pointer.
s := *(*[]int)(unsafe.Pointer(&det))
p := uintptr(unsafe.Pointer(&s[0]))
// Ensure `det` is not freed up by GC prematurely.
runtime.KeepAlive(det)
// return the pointer address
pointCh <- p
}()
return <-pointCh
}
// clusterDetection runs Pigo face detector core methods
// and returns a cluster with the detected faces coordinates.
func (px pixs) clusterDetection(pixels []uint8) []pigo.Detection {
cParams := pigo.CascadeParams{
MinSize: 20,
MaxSize: 1000,
ShiftFactor: 0.15,
ScaleFactor: 1.1,
ImageParams: pigo.ImageParams{
Pixels: pixels,
Rows: px.rows,
Cols: px.cols,
Dim: px.cols,
},
}
if len(cascade) == 0 {
cascade, err = ioutil.ReadFile("../../data/facefinder")
if err != nil {
log.Fatalf("Error reading the cascade file: %v", err)
}
// 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 = p.Unpack(cascade)
if err != nil {
log.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.
dets := classifier.RunCascade(cParams, 0.0)
// Calculate the intersection over union (IoU) of two clusters.
dets = classifier.ClusterDetections(dets, 0)
return dets
}
// pixToImage converts the pixel array to an image.
func (px pixs) pixToImage(pixels []uint8) image.Image {
width, height := px.cols, px.rows
img := image.NewRGBA(image.Rect(0, 0, width, height))
c := color.RGBA{
R: uint8(0),
G: uint8(0),
B: uint8(0),
A: uint8(255),
}
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
c.B = uint8(pixels[y*3+x])
c.G = uint8(pixels[y*3+x+1])
c.R = uint8(pixels[y*3+x+2])
img.SetRGBA(x, y, c)
}
}
return img
}
// imgToPix converts the image to a pixel array.
func (px pixs) imgToPix(img image.Image) []int {
bounds := img.Bounds()
x := bounds.Dx()
y := bounds.Dy()
pixels := make([]int, 0, x*y*3)
for i := bounds.Min.X; i < bounds.Max.X; i++ {
for j := bounds.Min.Y; j < bounds.Max.Y; j++ {
r, g, b, _ := img.At(i, j).RGBA()
pixels = append(pixels, int(r>>8), int(g>>8), int(b>>8), 255)
}
}
return pixels
}