odboy
13bb195e1d
- 移除固定的明暗阈值等级数组，改用动态分档机制 - 引入 neutralMargin 常量，当两分差幅小于 0.15 时视为中性图 - 修改 BrightnessName 函数，实现三分法分类：bright_N、dark_N、mid - 新增 brightnessTier 辅助函数，将占比分档到最接近的 10% - 完全透明的像素(alpha=0)不再参与明暗统计计算 - 更新错误提示信息，明暗分析失败时按中性 mid 归类 - 调整 README 文档描述，同步更新明暗分类规则说明
72 lines
1.7 KiB
Go
72 lines
1.7 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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// 完全透明的像素（alpha=0）不计入统计。
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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, a := img.At(x, y).RGBA()
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if a == 0 {
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continue
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}
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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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