Golang's method to realize blurred background of pictures and face recognition

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:

1. Install goimageblur library
   Execute the following command to install goimageblur library:

go get github.com/internet-dev/ goimageblur

2. Introduce the library and necessary packages
   Introduce the goimageblur library and necessary packages into the code:

import (

"github.com/internet-dev/goimageblur"
"image"
_ "image/jpeg"
"os"

)

3. Open the image file
   Use the Open method of the os library to open the image file and check whether an error occurs:

file, err := os.Open(" input.jpg")
if err != nil {

// 错误处理

}

defer file.Close() // Close the file

4. Read the picture Information
   Use the Decode method of the image library to read the image information and check whether an error occurs:

img, _, err := image.Decode(file)
if err ! = nil {

// 错误处理

}

5. Achieving the background blur effect
   Use the Blur method of the goimageblur library to achieve the background blur effect of the image:

blurImg := goimageblur.Blur(img, 10) // The blur radius is 10

6. Save the blurred image
   Use the Encode method of the image library to save the blurred image as a file:

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:

1. Install go-opencv library
   Execute the following command to install go-opencv library:

go get -u -d gocv.io/x/gocv

cd $GOPATH/src/gocv.io/x/gocv

make install

2. Introduce libraries and necessary packages
   Introduce the go-opencv library and necessary packages into the code:

import (

"gocv.io/x/gocv"
"image"
_ "image/jpeg"
"os"

)

3. Open the image file
   Use The OpenVideoCapture method of the gocv library opens the image file and checks whether an error occurs:

file, err := gocv.OpenVideoCapture("input.jpg")
if err != nil {

// 错误处理

}

defer file.Close() //Close the file

4. Read the face classifier
   Use the NewCascadeClassifier method of the gocv library to read the person Face classifier file, which can be downloaded from the OpenCV official website:

faceCascade := gocv.NewCascadeClassifier()
if !faceCascade.Load("haarcascade_frontalface_default.xml") {

// 错误处理

}

5. Read image information
   Use the IMRead method of the gocv library to read the image information and check whether an error occurs:

img: = gocv.IMRead("input.jpg", gocv.IMReadColor)
if img.Empty() {

// 错误处理

}

6. Implement face recognition
   Use The DetectMultiScale method of the gocv library implements face recognition:

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)

}

7. Display recognition results
   Use IMShow of gocv library Method to display the recognition result:

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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