Running Pigo in Python example

examples/python/pigo.go

@@ -0,0 +1,119 @@
+package main
+
+import "C"
+
+import (
+	"fmt"
+	"io/ioutil"
+	"log"
+	"reflect"
+	"runtime"
+	"unsafe"
+
+	"github.com/esimov/pigo/core"
+)
+
+var (
+	cascade    []byte
+	err        error
+	p          *pigo.Pigo
+	classifier *pigo.Pigo
+)
+
+func main() {}
+
+//export FindFaces
+func FindFaces(pixels []uint8) 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)
+		}
+	}
+	//fmt.Println(dets)
+	fmt.Println(result)
+
+	if len(result) > 0 {
+		det := make([]int, 0, len(result))
+		for _, v := range result {
+			det = append(det, v...)
+		}
+		det = append([]int{len(result), 0, 0}, det...)
+		fmt.Println(det)
+
+		s := *(*[]int)(unsafe.Pointer(&det))
+		p := uintptr(unsafe.Pointer(&s[0]))
+		return p
+
+		sh := &reflect.SliceHeader{
+			Data: p,
+			Len:  len(result),
+			Cap:  len(result),
+		}
+
+		data := *(*[][]int)(unsafe.Pointer(sh))
+
+		fmt.Println(data)
+
+		runtime.KeepAlive(result)
+		return uintptr(unsafe.Pointer(&data[0]))
+	}
+	return 0
+}
+
+func clusterDetection(pixels []uint8, rows, cols int) []pigo.Detection {
+	// cfp := *(*[]byte)(unsafe.Pointer(&cascadeFile))
+	// p := uintptr(unsafe.Pointer(&cfp[0]))
+
+	// size := len(cascadeFile)
+	// var data []byte
+
+	// sh := (*reflect.SliceHeader)(unsafe.Pointer(&data))
+	// sh.Data = p
+	// sh.Len = size
+	// sh.Cap = size
+
+	// fmt.Println(cascadeFile)
+	// fmt.Println(data)
+	// fmt.Println(uintptr(unsafe.Pointer(&cfp[0])))
+	fmt.Println("P:", len(pixels))
+	fmt.Println("DIM:", rows, cols)
+
+	cParams := pigo.CascadeParams{
+		MinSize:     20,
+		MaxSize:     1000,
+		ShiftFactor: 0.22,
+		ScaleFactor: 1.1,
+		ImageParams: pigo.ImageParams{
+			Pixels: pixels,
+			Rows:   rows,
+			Cols:   cols,
+			Dim:    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
+}