Golang 画像処理: 画像の凸包検出と輪郭フィッティングを実行する方法

package main

import (
    "fmt"
    "image"
    "image/color"
    "image/draw"
    "image/jpeg"
    "log"
    "os"

    "github.com/disintegration/imaging"
    "github.com/llgcode/draw2d/draw2dimg"
    "github.com/nfnt/resize"
)

func ConvexHullDetection(inputPath, outputPath string) {
    // 加载图像
    inputImg, err := imaging.Open(inputPath)
    if err != nil {
        log.Fatal(err)
    }

    // 将图像大小调整为指定尺寸
    resizedImg := resize.Resize(800, 0, inputImg, resize.Lanczos3)

    // 将图像转换为灰度图
    grayImg := imaging.Grayscale(resizedImg)

    // 二值化处理
    binaryImg := imaging.AdjustContrast(grayImg, 20)

    // 构建图像的矩形区域
    rectangle := image.Rect(0, 0, binaryImg.Bounds().Size().X, binaryImg.Bounds().Size().Y)

    // 创建画布
    canvas := image.NewRGBA(rectangle)
    draw.Draw(canvas, canvas.Bounds(), binaryImg, image.Point{}, draw.Src)

    // 构建凸包路径
    path := draw2dimg.NewGraphicsPath()

    // 遍历每个像素点
    bounds := binaryImg.Bounds()
    for x := bounds.Min.X; x < bounds.Max.X; x++ {
        for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
            // 获取像素值
            r, _, _, _ := canvas.At(x, y).RGBA()

            // 如果像素为黑色，则添加到凸包路径中
            if r < 65535/2 {
                path.LineTo(float64(x), float64(y))
            }
        }
    }

    // 进行凸包检测
    path.Close()
    hull := path.ConvexHull()

    // 绘制凸包
    context := draw2dimg.NewGraphicContext(canvas)
    context.SetStrokeColor(color.RGBA{R: 255, G: 0, B: 0, A: 255})
    context.SetLineWidth(2)
    for _, point := range hull {
        context.LineTo(float64(point.X), float64(point.Y))
    }
    context.Stroke()

    // 保存图像
    outputFile, err := os.Create(outputPath)
    if err != nil {
        log.Fatal(err)
    }
    defer outputFile.Close()

    err = jpeg.Encode(outputFile, canvas, &jpeg.Options{Quality: 100})
    if err != nil {
        log.Fatal(err)
    }
}

func main() {
    inputPath := "input.jpg"
    outputPath := "output.jpg"
    ConvexHullDetection(inputPath, outputPath)
    fmt.Println("凸包检测完成！")
}

package main

import (
    "fmt"
    "image"
    "image/color"
    "image/draw"
    "image/jpeg"
    "log"
    "os"

    "github.com/disintegration/imaging"
    "github.com/llgcode/draw2d/draw2dimg"
    "github.com/nfnt/resize"
)

func ContourFitting(inputPath, outputPath string) {
    // 加载图像
    inputImg, err := imaging.Open(inputPath)
    if err != nil {
        log.Fatal(err)
    }

    // 将图像大小调整为指定尺寸
    resizedImg := resize.Resize(800, 0, inputImg, resize.Lanczos3)

    // 将图像转换为灰度图
    grayImg := imaging.Grayscale(resizedImg)

    // 二值化处理
    binaryImg := imaging.AdjustContrast(grayImg, 20)

    // 构建图像的矩形区域
    rectangle := image.Rect(0, 0, binaryImg.Bounds().Size().X, binaryImg.Bounds().Size().Y)

    // 创建画布
    canvas := image.NewRGBA(rectangle)
    draw.Draw(canvas, canvas.Bounds(), binaryImg, image.Point{}, draw.Src)

    // 构建轮廓路径
    path := draw2dimg.NewGraphicsPath()

    // 遍历每个像素点
    bounds := binaryImg.Bounds()
    for x := bounds.Min.X; x < bounds.Max.X; x++ {
        for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
            // 获取像素值
            r, _, _, _ := canvas.At(x, y).RGBA()

            // 如果像素为黑色，则添加到轮廓路径中
            if r < 65535/2 {
                path.LineTo(float64(x), float64(y))
            }
        }
    }

    // 进行轮廓拟合
    fitting := path.FitPath(5)

    // 绘制轮廓
    context := draw2dimg.NewGraphicContext(canvas)
    context.SetStrokeColor(color.RGBA{R: 255, G: 0, B: 0, A: 255})
    context.SetLineWidth(2)
    for _, bezier := range fitting {
        context.CubicBezierTo(
            float64(bezier.Control1.X), float64(bezier.Control1.Y),
            float64(bezier.Control2.X), float64(bezier.Control2.Y),
            float64(bezier.To.X), float64(bezier.To.Y))
    }
    context.Stroke()

    // 保存图像
    outputFile, err := os.Create(outputPath)
    if err != nil {
        log.Fatal(err)
    }
    defer outputFile.Close()

    err = jpeg.Encode(outputFile, canvas, &jpeg.Options{Quality: 100})
    if err != nil {
        log.Fatal(err)
    }
}

func main() {
    inputPath := "input.jpg"
    outputPath := "output.jpg"
    ContourFitting(inputPath, outputPath)
    fmt.Println("轮廓拟合完成！")
}