image recognition

recog.go

package main

import (
	"errors"
	"fmt"
	"image"
	"image/jpeg"
	"image/png"
	"log"
	"os"

	"github.com/k0kubun/pp"
	"github.com/muesli/smartcrop"
	"github.com/nfnt/resize"
)

type SubImager interface {
	SubImage(r image.Rectangle) image.Image
}

func writeImageToPng(img *image.Image, name string) {
	fso, err := os.Create(name)
	if err != nil {
		panic(err)
	}
	defer fso.Close()

	err = png.Encode(fso, (*img))
	if err != nil {
		panic(err)
	}
}

func writeImageToJpeg(img *image.Image, name string) {
	fso, err := os.Create(name)
	if err != nil {
		panic(err)
	}
	defer fso.Close()

	err = jpeg.Encode(fso, (*img), &jpeg.Options{Quality: 100})
	if err != nil {
		panic(err)
	}
}

func main() {
	fi, err := os.Open("fbda80a59cbe4875bf769ff30d94d3a0.jpg")
	if err != nil {
		log.Fatalf(err.Error())
	}

	defer fi.Close()

	img, _, err := image.Decode(fi)
	if err != nil {
		log.Fatalf(err.Error())
	}

	faceDetectionHaarCascade := "./haarcascade_frontalface_alt.xml"

	cropSettings := smartcrop.CropSettings{
		FaceDetection:                    true,
		FaceDetectionHaarCascadeFilepath: faceDetectionHaarCascade,
		InterpolationType:                resize.Bicubic,
		DebugMode:                        false,
	}
	analyzer := smartcrop.NewAnalyzerWithCropSettings(cropSettings)
	topCrop, err := analyzer.FindBestCrop(img, 400, 200)
	if err != nil {
		log.Fatalf(err.Error())
	}
	fmt.Printf("Top crop: %+v\n", topCrop)

	sub, ok := img.(SubImager)
	if ok {
		log.Print(pp.Sprint(img))
		cropImage := sub.SubImage(image.Rect(topCrop.X, topCrop.Y, topCrop.Width+topCrop.X, topCrop.Height+topCrop.Y))
		pp.Sprint(cropImage)
		writeImageToJpeg(&cropImage, "./smartcrop.jpg")
	} else {
		pp.Sprint("============")
		log.Fatal(errors.New("No SubImage support"))
	}
}