153 lines
3.4 KiB
Go
153 lines
3.4 KiB
Go
package cloudcover
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import (
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"image"
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"image/color"
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"math"
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"math/rand"
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"os"
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"time"
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log "github.com/sirupsen/logrus"
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)
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const (
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k = 2 // 聚类数目，2表示云和非云
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maxIters = 100 // 最大迭代次数
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tolerance = 1.0 // 聚类中心变化容忍度
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)
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type Pixel struct {
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r, g, b float64
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}
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func CloudPercentByKMeans(imagePath string) float64 {
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file, err := os.Open(imagePath)
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if err != nil {
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log.Errorf("无法打开图像: %v", err)
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return 0.0
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}
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defer file.Close()
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img, _, err := image.Decode(file)
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if err != nil {
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log.Errorf("无法解码图像: %v", err)
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return 0.0
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}
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bounds := img.Bounds()
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width, height := bounds.Max.X, bounds.Max.Y
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pixels := make([]Pixel, 0, width*height)
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for y := 0; y < height; y++ {
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for x := 0; x < width; x++ {
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r, g, b, _ := img.At(x, y).RGBA()
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pixels = append(pixels, Pixel{
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r: float64(r >> 8),
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g: float64(g >> 8),
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b: float64(b >> 8),
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})
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}
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}
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rand.Seed(time.Now().UnixNano())
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centroids := initializeCentroids(pixels)
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assignments := make([]int, len(pixels))
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for iter := 0; iter < maxIters; iter++ {
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for i, pixel := range pixels {
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assignments[i] = nearestCentroid(pixel, centroids)
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}
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newCentroids := updateCentroids(pixels, assignments)
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if hasConverged(centroids, newCentroids) {
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log.Printf("在第 %d 次迭代后收敛\n", iter+1)
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break
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}
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centroids = newCentroids
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}
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cloudPixels := 0
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totalPixels := width * height
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// 新增：检查哪个聚类的平均亮度更高，确保白色表示云
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cloudCluster := 0
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if centroids[1].r+centroids[1].g+centroids[1].b > centroids[0].r+centroids[0].g+centroids[0].b {
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cloudCluster = 1
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}
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outputImg := image.NewGray(bounds)
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for y := 0; y < height; y++ {
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for x := 0; x < width; x++ {
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i := y*width + x
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if assignments[i] == cloudCluster {
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outputImg.SetGray(x, y, color.Gray{Y: 255}) // 云区域
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cloudPixels++
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} else {
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outputImg.SetGray(x, y, color.Gray{Y: 0}) // 非云区域
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}
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}
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}
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cloudRatio := float64(cloudPixels) / float64(totalPixels)
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return cloudRatio
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}
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func initializeCentroids(pixels []Pixel) []Pixel {
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centroids := make([]Pixel, k)
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for i := range centroids {
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centroids[i] = pixels[rand.Intn(len(pixels))]
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}
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return centroids
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}
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func nearestCentroid(pixel Pixel, centroids []Pixel) int {
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minDist := math.Inf(1)
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bestIndex := 0
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for i, c := range centroids {
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dist := math.Sqrt(math.Pow(pixel.r-c.r, 2) + math.Pow(pixel.g-c.g, 2) + math.Pow(pixel.b-c.b, 2))
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if dist < minDist {
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minDist = dist
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bestIndex = i
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}
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}
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return bestIndex
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}
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func updateCentroids(pixels []Pixel, assignments []int) []Pixel {
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sums := make([]Pixel, k)
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counts := make([]int, k)
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for i, assignment := range assignments {
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sums[assignment].r += pixels[i].r
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sums[assignment].g += pixels[i].g
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sums[assignment].b += pixels[i].b
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counts[assignment]++
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}
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newCentroids := make([]Pixel, k)
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for i := range newCentroids {
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if counts[i] > 0 {
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newCentroids[i].r = sums[i].r / float64(counts[i])
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newCentroids[i].g = sums[i].g / float64(counts[i])
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newCentroids[i].b = sums[i].b / float64(counts[i])
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} else {
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newCentroids[i] = sums[i]
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}
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}
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return newCentroids
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}
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func hasConverged(oldCentroids, newCentroids []Pixel) bool {
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for i := range oldCentroids {
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if math.Abs(oldCentroids[i].r-newCentroids[i].r) > tolerance ||
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math.Abs(oldCentroids[i].g-newCentroids[i].g) > tolerance ||
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math.Abs(oldCentroids[i].b-newCentroids[i].b) > tolerance {
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return false
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}
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}
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return true
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}
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