stevenbooru/vendor/src/github.com/disintegration/imaging/effects.go

188 lines
4.2 KiB
Go

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 {
// sigma parameter must be positive!
return Clone(img)
}
src := toNRGBA(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)
}
var dst *image.NRGBA
dst = blurHorizontal(src, kernel)
dst = blurVertical(dst, kernel)
return dst
}
func blurHorizontal(src *image.NRGBA, kernel []float64) *image.NRGBA {
radius := len(kernel) - 1
width := src.Bounds().Max.X
height := src.Bounds().Max.Y
dst := image.NewNRGBA(image.Rect(0, 0, width, height))
parallel(width, func(partStart, partEnd int) {
for x := partStart; x < partEnd; x++ {
start := x - radius
if start < 0 {
start = 0
}
end := x + radius
if end > width-1 {
end = width - 1
}
weightSum := 0.0
for ix := start; ix <= end; ix++ {
weightSum += kernel[absint(x-ix)]
}
for y := 0; y < height; y++ {
r, g, b, a := 0.0, 0.0, 0.0, 0.0
for ix := start; ix <= end; ix++ {
weight := kernel[absint(x-ix)]
i := y*src.Stride + ix*4
r += float64(src.Pix[i+0]) * weight
g += float64(src.Pix[i+1]) * weight
b += float64(src.Pix[i+2]) * weight
a += float64(src.Pix[i+3]) * weight
}
r = math.Min(math.Max(r/weightSum, 0.0), 255.0)
g = math.Min(math.Max(g/weightSum, 0.0), 255.0)
b = math.Min(math.Max(b/weightSum, 0.0), 255.0)
a = math.Min(math.Max(a/weightSum, 0.0), 255.0)
j := y*dst.Stride + x*4
dst.Pix[j+0] = uint8(r + 0.5)
dst.Pix[j+1] = uint8(g + 0.5)
dst.Pix[j+2] = uint8(b + 0.5)
dst.Pix[j+3] = uint8(a + 0.5)
}
}
})
return dst
}
func blurVertical(src *image.NRGBA, kernel []float64) *image.NRGBA {
radius := len(kernel) - 1
width := src.Bounds().Max.X
height := src.Bounds().Max.Y
dst := image.NewNRGBA(image.Rect(0, 0, width, height))
parallel(height, func(partStart, partEnd int) {
for y := partStart; y < partEnd; y++ {
start := y - radius
if start < 0 {
start = 0
}
end := y + radius
if end > height-1 {
end = height - 1
}
weightSum := 0.0
for iy := start; iy <= end; iy++ {
weightSum += kernel[absint(y-iy)]
}
for x := 0; x < width; x++ {
r, g, b, a := 0.0, 0.0, 0.0, 0.0
for iy := start; iy <= end; iy++ {
weight := kernel[absint(y-iy)]
i := iy*src.Stride + x*4
r += float64(src.Pix[i+0]) * weight
g += float64(src.Pix[i+1]) * weight
b += float64(src.Pix[i+2]) * weight
a += float64(src.Pix[i+3]) * weight
}
r = math.Min(math.Max(r/weightSum, 0.0), 255.0)
g = math.Min(math.Max(g/weightSum, 0.0), 255.0)
b = math.Min(math.Max(b/weightSum, 0.0), 255.0)
a = math.Min(math.Max(a/weightSum, 0.0), 255.0)
j := y*dst.Stride + x*4
dst.Pix[j+0] = uint8(r + 0.5)
dst.Pix[j+1] = uint8(g + 0.5)
dst.Pix[j+2] = uint8(b + 0.5)
dst.Pix[j+3] = uint8(a + 0.5)
}
}
})
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 {
// sigma parameter must be positive!
return Clone(img)
}
src := toNRGBA(img)
blurred := Blur(img, sigma)
width := src.Bounds().Max.X
height := src.Bounds().Max.Y
dst := image.NewNRGBA(image.Rect(0, 0, width, height))
parallel(height, func(partStart, partEnd int) {
for y := partStart; y < partEnd; y++ {
for x := 0; x < width; x++ {
i := y*src.Stride + x*4
for j := 0; j < 4; j++ {
k := i + j
val := int(src.Pix[k]) + (int(src.Pix[k]) - int(blurred.Pix[k]))
if val < 0 {
val = 0
} else if val > 255 {
val = 255
}
dst.Pix[k] = uint8(val)
}
}
}
})
return dst
}