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Golang’s method of realizing blurred background and face recognition of images
Introduction:
Image processing is a very common requirement. In some application scenarios, We need to blur the background of the picture to highlight the subject. At the same time, face recognition is also widely used in areas such as face key point detection and face comparison. This article will introduce how to use Golang to implement image blur background and face recognition, and attach code examples to help readers better understand and apply it.
1. Blurred background of pictures
In Golang, we can use the third-party library goimageblur to achieve the blurred background effect of pictures. The following are the basic steps to use this library:
go get github.com/internet-dev/ goimageblur
import (
"github.com/internet-dev/goimageblur" "image" _ "image/jpeg" "os"
)
file, err := os.Open(" input.jpg")
if err != nil {
// 错误处理
}
defer file.Close() // Close the file
img, _, err := image.Decode(file)
if err ! = nil {
// 错误处理
}
blurImg := goimageblur.Blur(img, 10) // The blur radius is 10
outputFile, err := os.Create("output.jpg")
if err != nil {
// 错误处理
}
defer outputFile.Close( ) // Close the file
err = jpeg.Encode(outputFile, blurImg, nil)
if err != nil {
// 错误处理
}
In this way, we Implemented a method of blurring the background of images using Golang.
2. Face recognition
In Golang, we can use the third-party library go-opencv to implement face recognition. The following are the basic steps to use this library:
go get -u -d gocv.io/x/gocv
cd $GOPATH/src/gocv.io/x/gocv
make install
import (
"gocv.io/x/gocv" "image" _ "image/jpeg" "os"
)
file, err := gocv.OpenVideoCapture("input.jpg")
if err != nil {
// 错误处理
}
defer file.Close() //Close the file
faceCascade := gocv.NewCascadeClassifier()
if !faceCascade.Load("haarcascade_frontalface_default.xml") {
// 错误处理
}
img: = gocv.IMRead("input.jpg", gocv.IMReadColor)
if img.Empty() {
// 错误处理
}
grayImg := gocv.NewMat()
gocv.CvtColor(img, &grayImg, gocv.ColorBGRToGray)
faces : = faceCascade.DetectMultiScale(grayImg)
for _, face := range faces {
gocv.Rectangle(&img, face, color.RGBA{0, 255, 0, 0}, 3)
}
window := gocv.NewWindow("Face Detection")
window.IMShow(img)
gocv.WaitKey(0)
window.Close ()
In this way, we have implemented the method of using Golang for face recognition.
Conclusion:
This article introduces the method of using Golang to realize blurred background and face recognition of pictures, and attaches the corresponding code examples. By learning and applying these methods, we can better process images and apply them to actual projects. I hope this article can help readers better understand and use Golang for image processing and face recognition.
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