inceptionnet_golang_opencv.go

package main

import (
	"bufio"
	"gocv.io/x/gocv"
	"image"
	"image/color"
	"log"
	"os"
	"fmt"
)

func main(){
	input,_:=gocv.VideoCaptureDevice(0)
	defer input.Close()
	img:=gocv.NewMat()
	defer img.Close()
	model:=gocv.ReadNetFromTensorflow("./ssd_mobilenet/saved_model/saved_model.pb")

	window:=gocv.NewWindow("Person Tracker")
	defer window.Close()

	descriptions, err := readDescriptions("./data/coco_labels.txt")
	if err != nil {
		log.Printf("Error reading descriptions file: %v\n", descriptions)
		return
	}


	model.SetPreferableBackend(3) //openCV backend
	model.SetPreferableTarget(0) //0 for CPU and 4 for NVIDIA GPU(needs configuration)

	statusColor:=color.RGBA{
		R: 0,
		G: 255,
		B: 0,
		A: 0,
	}

	for{
		if ok:=input.Read(&img);!ok{
			log.Println("Device closed \n")
			return
		}

		if img.Empty(){
			continue
		}


		//convert image MATRIX to 224 x 224 blob
		blob:=gocv.BlobFromImage(img,1.0,image.Pt(224,224),gocv.NewScalar(0, 0, 0, 0), true, false)

		//feed blob into classifier
		model.SetInput(blob,"input")

		//Run a forward pass
		prob:=model.Forward("softmax2")

		//reshape results into 1*1000 matrix
		probMat:=prob.Reshape(1,1)

		//determine the most probable classificaton
		_,maxVal,_,maxLoc:=gocv.MinMaxLoc(probMat)

		//display classification
		desc:="Unknown"
		if maxLoc.X<1000{
			desc=descriptions[maxLoc.X]
		}
		status := fmt.Sprintf("description: %v, maxVal: %v\n", desc, maxVal)
		gocv.PutText(&img, status, image.Pt(10, 20), gocv.FontHersheyPlain, 1.2, statusColor, 2)



		blob.Close()
		prob.Close()
		probMat.Close()

		window.IMShow(img)
		window.IMShow(img)
		if window.WaitKey(1) >= 0 {
			break
		}
	}
}

// readDescriptions reads the descriptions from a file
// and returns a slice of its lines.
func readDescriptions(path string) ([]string, error) {
	file, err := os.Open(path)
	if err != nil {
		return nil, err
	}
	defer file.Close()

	var lines []string
	scanner := bufio.NewScanner(file)
	for scanner.Scan() {
		lines = append(lines, scanner.Text())
	}
	return lines, scanner.Err()
}