odboy
99b9460bcd
- 修改 ImageDir 函数增加 darkScore 和 lightScore 参数 - 实现 BrightnessName 函数计算明暗等级 - 定义暗色和亮色阈值等级数组 - 在 organize.go 中集成图片明暗分析逻辑 - 使用 ITU-R BT.601 公式计算像素亮度 - 为大图实现自动采样加速分析 - 更新 README.md 文档说明明暗分类算法 - 在目录结构中体现明暗等级命名规则
68 lines
1.6 KiB
Go
68 lines
1.6 KiB
Go
package probe
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import (
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"image"
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"math"
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"os"
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_ "image/gif"
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_ "image/jpeg"
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_ "image/png"
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_ "golang.org/x/image/bmp"
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_ "golang.org/x/image/tiff"
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_ "golang.org/x/image/webp"
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)
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// AnalyzeBrightness 打开并解码图片，分析明暗程度。
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// darkScore: 暗色像素（亮度 < 80）占比；lightScore: 亮色像素（亮度 > 175）占比。
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func AnalyzeBrightness(filePath string) (darkScore float64, lightScore float64, err error) {
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f, err := os.Open(filePath)
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if err != nil {
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return 0, 0, err
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}
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defer f.Close()
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img, _, err := image.Decode(f)
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if err != nil {
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return 0, 0, err
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}
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dark, light := analyzeBrightness(img)
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return dark, light, nil
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}
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// analyzeBrightness 统计暗色/亮色像素占比（ITU-R BT.601 亮度公式），大图自动采样加速
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func analyzeBrightness(img image.Image) (darkScore float64, lightScore float64) {
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bounds := img.Bounds()
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totalPixels := bounds.Dx() * bounds.Dy()
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if totalPixels == 0 {
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return 0, 0
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}
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darkCount, lightCount, sampleCount := 0, 0, 0
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sampleStep := 1
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if totalPixels > 1_000_000 {
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sampleStep = int(math.Sqrt(float64(totalPixels) / 100_000))
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}
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for y := bounds.Min.Y; y < bounds.Max.Y; y += sampleStep {
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for x := bounds.Min.X; x < bounds.Max.X; x += sampleStep {
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r, g, b, _ := img.At(x, y).RGBA()
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r8 := uint8(r >> 8)
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g8 := uint8(g >> 8)
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b8 := uint8(b >> 8)
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brightness := 0.299*float64(r8) + 0.587*float64(g8) + 0.114*float64(b8)
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if brightness < 80 {
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darkCount++
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} else if brightness > 175 {
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lightCount++
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}
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sampleCount++
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}
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}
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if sampleCount == 0 {
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return 0, 0
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}
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return float64(darkCount) / float64(sampleCount), float64(lightCount) / float64(sampleCount)
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}
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