1 files changed, 165 insertions, 0 deletions
diff --git a/vendor/github.com/disintegration/imaging/effects.go b/vendor/github.com/disintegration/imaging/effects.go
new file mode 100644
index 0000000..b16781f
--- /dev/null
+++ b/vendor/github.com/disintegration/imaging/effects.go
@@ -0,0 +1,165 @@
+package imaging
+
+import (
+	"image"
+	"math"
+)
+
+func gaussianBlurKernel(x, sigma float64) float64 {
+	return math.Exp(-(x*x)/(2*sigma*sigma)) / (sigma * math.Sqrt(2*math.Pi))
+}
+
+// Blur produces a blurred version of the image using a Gaussian function.
+// Sigma parameter must be positive and indicates how much the image will be blurred.
+//
+// Usage example:
+//
+//	dstImage := imaging.Blur(srcImage, 3.5)
+//
+func Blur(img image.Image, sigma float64) *image.NRGBA {
+	if sigma <= 0 {
+		return Clone(img)
+	}
+
+	radius := int(math.Ceil(sigma * 3.0))
+	kernel := make([]float64, radius+1)
+
+	for i := 0; i <= radius; i++ {
+		kernel[i] = gaussianBlurKernel(float64(i), sigma)
+	}
+
+	return blurVertical(blurHorizontal(img, kernel), kernel)
+}
+
+func blurHorizontal(img image.Image, kernel []float64) *image.NRGBA {
+	src := newScanner(img)
+	dst := image.NewNRGBA(image.Rect(0, 0, src.w, src.h))
+	radius := len(kernel) - 1
+
+	parallel(0, src.h, func(ys <-chan int) {
+		scanLine := make([]uint8, src.w*4)
+		for y := range ys {
+			src.scan(0, y, src.w, y+1, scanLine)
+			for x := 0; x < src.w; x++ {
+				min := x - radius
+				if min < 0 {
+					min = 0
+				}
+				max := x + radius
+				if max > src.w-1 {
+					max = src.w - 1
+				}
+
+				var r, g, b, a, wsum float64
+				for ix := min; ix <= max; ix++ {
+					i := ix * 4
+					weight := kernel[absint(x-ix)]
+					wsum += weight
+					wa := float64(scanLine[i+3]) * weight
+					r += float64(scanLine[i+0]) * wa
+					g += float64(scanLine[i+1]) * wa
+					b += float64(scanLine[i+2]) * wa
+					a += wa
+				}
+				if a != 0 {
+					r /= a
+					g /= a
+					b /= a
+				}
+
+				j := y*dst.Stride + x*4
+				dst.Pix[j+0] = clamp(r)
+				dst.Pix[j+1] = clamp(g)
+				dst.Pix[j+2] = clamp(b)
+				dst.Pix[j+3] = clamp(a / wsum)
+			}
+		}
+	})
+
+	return dst
+}
+
+func blurVertical(img image.Image, kernel []float64) *image.NRGBA {
+	src := newScanner(img)
+	dst := image.NewNRGBA(image.Rect(0, 0, src.w, src.h))
+	radius := len(kernel) - 1
+
+	parallel(0, src.w, func(xs <-chan int) {
+		scanLine := make([]uint8, src.h*4)
+		for x := range xs {
+			src.scan(x, 0, x+1, src.h, scanLine)
+			for y := 0; y < src.h; y++ {
+				min := y - radius
+				if min < 0 {
+					min = 0
+				}
+				max := y + radius
+				if max > src.h-1 {
+					max = src.h - 1
+				}
+
+				var r, g, b, a, wsum float64
+				for iy := min; iy <= max; iy++ {
+					i := iy * 4
+					weight := kernel[absint(y-iy)]
+					wsum += weight
+					wa := float64(scanLine[i+3]) * weight
+					r += float64(scanLine[i+0]) * wa
+					g += float64(scanLine[i+1]) * wa
+					b += float64(scanLine[i+2]) * wa
+					a += wa
+				}
+				if a != 0 {
+					r /= a
+					g /= a
+					b /= a
+				}
+
+				j := y*dst.Stride + x*4
+				dst.Pix[j+0] = clamp(r)
+				dst.Pix[j+1] = clamp(g)
+				dst.Pix[j+2] = clamp(b)
+				dst.Pix[j+3] = clamp(a / wsum)
+			}
+		}
+	})
+
+	return dst
+}
+
+// Sharpen produces a sharpened version of the image.
+// Sigma parameter must be positive and indicates how much the image will be sharpened.
+//
+// Usage example:
+//
+//	dstImage := imaging.Sharpen(srcImage, 3.5)
+//
+func Sharpen(img image.Image, sigma float64) *image.NRGBA {
+	if sigma <= 0 {
+		return Clone(img)
+	}
+
+	src := newScanner(img)
+	dst := image.NewNRGBA(image.Rect(0, 0, src.w, src.h))
+	blurred := Blur(img, sigma)
+
+	parallel(0, src.h, func(ys <-chan int) {
+		scanLine := make([]uint8, src.w*4)
+		for y := range ys {
+			src.scan(0, y, src.w, y+1, scanLine)
+			j := y * dst.Stride
+			for i := 0; i < src.w*4; i++ {
+				val := int(scanLine[i])<<1 - int(blurred.Pix[j])
+				if val < 0 {
+					val = 0
+				} else if val > 0xff {
+					val = 0xff
+				}
+				dst.Pix[j] = uint8(val)
+				j++
+			}
+		}
+	})
+
+	return dst
+}