How to use Golang to batch merge and splice multiple pictures

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Release: 2023-08-18 16:29:03
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How to use Golang to batch merge and splice multiple pictures

How to use Golang to batch merge and splice multiple pictures

In many image processing scenarios, we need to merge multiple pictures into one large picture or follow the Certain rules are followed for splicing. Using Golang to handle these operations can improve efficiency and make the code concise and easy to understand. This article will introduce how to use Golang to batch merge and splice multiple images, and provide corresponding code examples.

First, we need to install and import the relevant Golang libraries. In this article, we will use the "github.com/disintegration/imaging" library for image processing. You can use the following command to install the library:

go get -u github.com/disintegration/imaging
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Next, we will step by step introduce how to use Golang to merge and splice multiple images.

  1. Merge pictures

Merge pictures means splicing multiple pictures from top to bottom or left to right to form one big picture. The following code snippet demonstrates how to implement this function:

package main

import (
    "image"
    "image/draw"
    "image/jpeg"
    "log"
    "os"
    "strings"

    "github.com/disintegration/imaging"
)

func main() {
    // 定义合并后的图片尺寸
    width := 800
    height := 600

    // 读取需要合并的多张图片
    var images []image.Image
    for i := 1; i <= 5; i++ {
        filename := "image" + strconv.Itoa(i) + ".jpg"
        file, err := os.Open(filename)
        if err != nil {
            log.Fatal(err)
        }
        defer file.Close()

        img, err := jpeg.Decode(file)
        if err != nil {
            log.Fatal(err)
        }
        images = append(images, img)
    }

    // 创建合并后的图片
    merged := imaging.New(width, height, color.White)

    // 拷贝每张图片到合并后的图片中
    var posX, posY int
    for _, img := range images {
        merged = imaging.Paste(merged, img, image.Pt(posX, posY))
        posY += img.Bounds().Dy()
    }

    // 保存合并后的图片
    err := imaging.Save(merged, "merged.jpg")
    if err != nil {
        log.Fatal(err)
    }
}
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  1. Splicing pictures

Splicing pictures means arranging multiple pictures according to certain rules to form a Big picture. The following code snippet demonstrates how to implement this function:

package main

import (
    "image"
    "image/draw"
    "image/jpeg"
    "log"
    "os"
    "strings"

    "github.com/disintegration/imaging"
)

func main() {
    // 定义拼接后的图片尺寸
    width := 800
    height := 600

    // 读取需要拼接的多张图片
    var images []image.Image
    for i := 1; i <= 5; i++ {
        filename := "image" + strconv.Itoa(i) + ".jpg"
        file, err := os.Open(filename)
        if err != nil {
            log.Fatal(err)
        }
        defer file.Close()

        img, err := jpeg.Decode(file)
        if err != nil {
            log.Fatal(err)
        }
        images = append(images, img)
    }

    // 计算拼接后的图片尺寸
    cols := 2
    rows := (len(images) + 1) / cols
    canvas := imaging.New(width, height, color.White)

    // 拼接图片
    var posX, posY, count int
    for _, img := range images {
        if count%cols == 0 && count != 0 {
            posY += images[0].Bounds().Dy()
            posX = 0
        }
        canvas = imaging.Paste(canvas, img, image.Pt(posX, posY))
        posX += img.Bounds().Dx()
        count++
    }

    // 保存拼接后的图片
    err := imaging.Save(canvas, "stitched.jpg")
    if err != nil {
        log.Fatal(err)
    }
}
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In the above code, we assume that the images that need to be merged or spliced ​​are located in the current directory and named "image1.jpg", "image2.jpg" Wait, there are 5 pictures in total. You can modify the image file name and quantity in the code according to the actual situation.

Summary:
This article introduces how to use Golang to batch merge and splice multiple images, and provides corresponding code examples. By learning these techniques, you can easily work with multiple images and merge and stitch them as needed. I hope this article will be helpful to your image processing work!

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