mirror of
https://github.com/esimov/pigo.git
synced 2025-10-05 08:07:02 +08:00
99 lines
2.4 KiB
Go
99 lines
2.4 KiB
Go
package main
|
|
|
|
import "C"
|
|
|
|
import (
|
|
"io/ioutil"
|
|
"log"
|
|
"runtime"
|
|
"unsafe"
|
|
|
|
pigo "github.com/esimov/pigo/core"
|
|
)
|
|
|
|
var (
|
|
cascade []byte
|
|
err error
|
|
classifier *pigo.Pigo
|
|
)
|
|
|
|
func main() {}
|
|
|
|
//export FindFaces
|
|
func FindFaces(pixels []uint8) uintptr {
|
|
pointCh := make(chan uintptr)
|
|
|
|
dets := clusterDetection(pixels, 480, 640)
|
|
result := make([][]int, len(dets))
|
|
|
|
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)
|
|
}
|
|
}
|
|
|
|
det := make([]int, 0, len(result))
|
|
go func() {
|
|
// Since in Go we cannot transfer a 2d array through an array pointer
|
|
// we have to transform it into 1d array.
|
|
for _, v := range result {
|
|
det = append(det, 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...)
|
|
|
|
// Convert the slice into an array pointer.
|
|
s := *(*[]uint8)(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 clusterDetection(pixels []uint8, rows, cols int) []pigo.Detection {
|
|
cParams := pigo.CascadeParams{
|
|
MinSize: 100,
|
|
MaxSize: 600,
|
|
ShiftFactor: 0.15,
|
|
ScaleFactor: 1.1,
|
|
ImageParams: pigo.ImageParams{
|
|
Pixels: pixels,
|
|
Rows: rows,
|
|
Cols: cols,
|
|
Dim: cols,
|
|
},
|
|
}
|
|
|
|
if len(cascade) == 0 {
|
|
cascade, err = ioutil.ReadFile("../../cascade/facefinder")
|
|
if err != nil {
|
|
log.Fatalf("Error reading the cascade file: %s", err)
|
|
}
|
|
p := 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 = p.Unpack(cascade)
|
|
if err != nil {
|
|
log.Fatalf("Error unpacking 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
|
|
}
|