Initial QSfera import

Server/vendor/github.com/kovidgoyal/imaging/histogram.go

@@ -0,0 +1,57 @@
+package imaging
+
+import (
+	"image"
+	"sync"
+
+	"github.com/kovidgoyal/imaging/nrgba"
+)
+
+// Histogram returns a normalized histogram of an image.
+//
+// Resulting histogram is represented as an array of 256 floats, where
+// histogram[i] is a probability of a pixel being of a particular luminance i.
+func Histogram(img image.Image) [256]float64 {
+	var mu sync.Mutex
+	var histogram [256]float64
+	var total float64
+
+	w, h := img.Bounds().Dx(), img.Bounds().Dy()
+	if w == 0 || h == 0 {
+		return histogram
+	}
+	src := nrgba.NewNRGBAScanner(img)
+
+	if err := run_in_parallel_over_range(0, func(start, limit int) {
+		var tmpHistogram [256]float64
+		var tmpTotal float64
+		scanLine := make([]uint8, w*4)
+		for y := start; y < limit; y++ {
+			src.Scan(0, y, w, y+1, scanLine)
+			i := 0
+			for range w {
+				s := scanLine[i : i+3 : i+3]
+				r := s[0]
+				g := s[1]
+				b := s[2]
+				y := 0.299*float32(r) + 0.587*float32(g) + 0.114*float32(b)
+				tmpHistogram[int(y+0.5)]++
+				tmpTotal++
+				i += 4
+			}
+		}
+		mu.Lock()
+		for i := range 256 {
+			histogram[i] += tmpHistogram[i]
+		}
+		total += tmpTotal
+		mu.Unlock()
+	}, 0, h); err != nil {
+		panic(err)
+	}
+
+	for i := range 256 {
+		histogram[i] = histogram[i] / total
+	}
+	return histogram
+}