func warm(out, in draw.Image, opacity uint8, colors []color.Color) {
draw.Draw(out, out.Bounds(), image.Transparent, image.ZP, draw.Src)
bounds := in.Bounds()
collen := float64(len(colors))
wg := &sync.WaitGroup{}
for x := bounds.Min.X; x < bounds.Max.X; x++ {
wg.Add(1)
go func(x int) {
defer wg.Done()
for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
col := in.At(x, y)
_, _, _, alpha := col.RGBA()
if alpha > 0 {
percent := float64(alpha) / float64(0xffff)
template := colors[int((collen-1)*(1.0-percent))]
tr, tg, tb, ta := template.RGBA()
ta /= 256
outalpha := uint8(float64(ta) *
(float64(opacity) / 256.0))
outcol := color.NRGBA{
uint8(tr / 256),
uint8(tg / 256),
uint8(tb / 256),
uint8(outalpha)}
out.Set(x, y, outcol)
}
}
}(x)
}
wg.Wait()
}
func warm(out, in draw.Image, opacity uint8, colors []color.Color) {
bounds := in.Bounds()
collen := float64(len(colors))
wg := sync.WaitGroup{}
wg.Add(bounds.Dx())
for x := bounds.Min.X; x < bounds.Max.X; x++ {
go func(x int) {
defer wg.Done()
for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
col := in.At(x, y)
_, _, _, alpha := col.RGBA()
percent := float64(alpha) / float64(0xffff)
var outcol color.Color
if percent == 0 {
outcol = color.Transparent
} else {
template := colors[int((collen-1)*(1.0-percent))]
tr, tg, tb, ta := template.RGBA()
ta /= 256
outalpha := uint8(float64(ta) *
(float64(opacity) / 256.0))
outcol = color.NRGBA{
uint8(tr / 256),
uint8(tg / 256),
uint8(tb / 256),
uint8(outalpha)}
}
out.Set(x, y, outcol)
}
}(x)
}
wg.Wait()
}
// Apply the given color mapping to the specified image buffers.
func Apply(from, to *Rule, src, dst draw.Image) {
var x, y int
var r, g, b, a uint32
var sc color.Color
var dc color.RGBA
var pix pixel
rect := src.Bounds()
for y = 0; y < rect.Dy(); y++ {
for x = 0; x < rect.Dx(); x++ {
sc = src.At(x, y)
r, g, b, a = sc.RGBA()
pix.r = uint8(r >> 8)
pix.g = uint8(g >> 8)
pix.b = uint8(b >> 8)
pix.a = uint8(a >> 8)
// Check if the pixel matches the filter rule.
if !(match(pix.r, from.R) && match(pix.g, from.G) && match(pix.b, from.B) && match(pix.a, from.A)) {
dst.Set(x, y, sc)
continue
}
// Compute three different types of grayscale conversion.
// These can be applied by named references.
pix.average = uint8(((r + g + b) / 3) >> 8)
pix.lightness = uint8(((min(min(r, g), b) + max(max(r, g), b)) / 2) >> 8)
// For luminosity it is necessary to apply an inverse of the gamma
// function for the color space before calculating the inner product.
// Then you apply the gamma function to the reduced value. Failure to
// incorporate the gamma function can result in errors of up to 20%.
//
// For typical computer stuff, the color space is sRGB. The right
// numbers for sRGB are approx. 0.21, 0.72, 0.07. Gamma for sRGB
// is a composite function that approximates exponentiation by 1/2.2
//
// This is a rather expensive operation, but gives a much more accurate
// and satisfactory result than the average and lightness versions.
pix.luminosity = gammaSRGB(
0.212655*invGammaSRGB(pix.r) +
0.715158*invGammaSRGB(pix.g) +
0.072187*invGammaSRGB(pix.b))
// Transform color.
dc.R = transform(&pix, pix.r, to.R)
dc.G = transform(&pix, pix.g, to.G)
dc.B = transform(&pix, pix.b, to.B)
dc.A = transform(&pix, pix.a, to.A)
// Set new pixel.
dst.Set(x, y, dc)
}
}
}
// Blends src image (top layer) into dst image (bottom layer) using
// the BlendFunc provided by mode. BlendFunc is applied to each pixel
// where the src image overlaps the dst image and the result is stored
// in the original dst image, src image is unmutable.
func BlendImage(dst draw.Image, src image.Image, mode BlendFunc) {
// Obtain the intersection of both images.
inter := dst.Bounds().Intersect(src.Bounds())
// Apply BlendFuc to each pixel in the intersection.
for y := inter.Min.Y; y < inter.Max.Y; y++ {
for x := inter.Min.X; x < inter.Max.X; x++ {
dst.Set(x, y, mode(dst.At(x, y), src.At(x, y)))
}
}
}
func (burkes) Draw(dst draw.Image, r image.Rectangle, src image.Image, sp image.Point) {
quantError0 := make([][3]int32, r.Dx()+4)
quantError1 := make([][3]int32, r.Dx()+4)
out := color.RGBA64{A: 0xffff}
for y := 0; y != r.Dy(); y++ {
for x := 0; x != r.Dx(); x++ {
sr, sg, sb, _ := src.At(sp.X+x, sp.Y+y).RGBA()
er, eg, eb := int32(sr), int32(sg), int32(sb)
er = clamp(er + quantError0[x+2][0]/32)
eg = clamp(eg + quantError0[x+2][1]/32)
eb = clamp(eb + quantError0[x+2][2]/32)
out.R = uint16(er)
out.G = uint16(eg)
out.B = uint16(eb)
dst.Set(r.Min.X+x, r.Min.Y+y, &out)
sr, sg, sb, _ = dst.At(r.Min.X+x, r.Min.Y+y).RGBA()
er -= int32(sr)
eg -= int32(sg)
eb -= int32(sb)
quantError0[x+3][0] += er * 8
quantError0[x+3][1] += eg * 8
quantError0[x+3][2] += eb * 8
quantError0[x+4][0] += er * 4
quantError0[x+4][1] += eg * 4
quantError0[x+4][2] += eb * 4
quantError1[x+0][0] += er * 2
quantError1[x+0][1] += eg * 2
quantError1[x+0][2] += eb * 2
quantError1[x+1][0] += er * 4
quantError1[x+1][1] += eg * 4
quantError1[x+1][2] += eb * 4
quantError1[x+2][0] += er * 8
quantError1[x+2][1] += eg * 8
quantError1[x+2][2] += eb * 8
quantError1[x+3][0] += er * 4
quantError1[x+3][1] += eg * 4
quantError1[x+3][2] += eb * 4
quantError1[x+4][0] += er * 2
quantError1[x+4][1] += eg * 2
quantError1[x+4][2] += eb * 2
}
// Recycle the quantization error buffers.
quantError0, quantError1 = quantError1, quantError0
for i := range quantError1 {
quantError1[i] = [3]int32{}
}
}
}
func noise(src draw.Image) {
orig := src.Bounds()
numToMod := (orig.Max.X * orig.Max.Y) / 2
for i := 0; i < numToMod; i++ {
x := rand.Intn(orig.Max.X)
y := rand.Intn(orig.Max.Y)
origColor := src.At(x, y).(color.RGBA)
origColor.R += 30
origColor.B += 30
origColor.G += 30
src.Set(x, y, origColor)
}
}
func DrawImage(src image.Image, dest draw.Image, tr MatrixTransform, op draw.Op, filter ImageFilter) {
bounds := src.Bounds()
x0, y0, x1, y1 := float64(bounds.Min.X), float64(bounds.Min.Y), float64(bounds.Max.X), float64(bounds.Max.Y)
tr.TransformRectangle(&x0, &y0, &x1, &y1)
var x, y, u, v float64
var c1, c2, cr color.Color
var r, g, b, a, ia, r1, g1, b1, a1, r2, g2, b2, a2 uint32
var color color.RGBA
for x = x0; x < x1; x++ {
for y = y0; y < y1; y++ {
u = x
v = y
tr.InverseTransform(&u, &v)
if bounds.Min.X <= int(u) && bounds.Max.X > int(u) && bounds.Min.Y <= int(v) && bounds.Max.Y > int(v) {
c1 = dest.At(int(x), int(y))
switch filter {
case LinearFilter:
c2 = src.At(int(u), int(v))
case BilinearFilter:
c2 = getColorBilinear(src, u, v)
case BicubicFilter:
c2 = getColorBicubic(src, u, v)
}
switch op {
case draw.Over:
r1, g1, b1, a1 = c1.RGBA()
r2, g2, b2, a2 = c2.RGBA()
ia = M - a2
r = ((r1 * ia) / M) + r2
g = ((g1 * ia) / M) + g2
b = ((b1 * ia) / M) + b2
a = ((a1 * ia) / M) + a2
color.R = uint8(r >> 8)
color.G = uint8(g >> 8)
color.B = uint8(b >> 8)
color.A = uint8(a >> 8)
cr = color
default:
cr = c2
}
dest.Set(int(x), int(y), cr)
}
}
}
}
func (z *Rasterizer) rasterizeOpOver(dst draw.Image, r image.Rectangle, src image.Image, sp image.Point) {
z.accumulateMask()
out := color.RGBA64{}
outc := color.Color(&out)
for y, y1 := 0, r.Max.Y-r.Min.Y; y < y1; y++ {
for x, x1 := 0, r.Max.X-r.Min.X; x < x1; x++ {
sr, sg, sb, sa := src.At(sp.X+x, sp.Y+y).RGBA()
ma := z.bufU32[y*z.size.X+x]
// This algorithm comes from the standard library's image/draw
// package.
dr, dg, db, da := dst.At(r.Min.X+x, r.Min.Y+y).RGBA()
a := 0xffff - (sa * ma / 0xffff)
out.R = uint16((dr*a + sr*ma) / 0xffff)
out.G = uint16((dg*a + sg*ma) / 0xffff)
out.B = uint16((db*a + sb*ma) / 0xffff)
out.A = uint16((da*a + sa*ma) / 0xffff)
dst.Set(r.Min.X+x, r.Min.Y+y, outc)
}
}
}
func (falseFloydSteinberg) Draw(dst draw.Image, r image.Rectangle, src image.Image, sp image.Point) {
quantErrorNext := make([][3]int32, r.Dx()+1)
out := color.RGBA64{A: 0xffff}
for y := 0; y != r.Dy(); y++ {
quantError := [3]int32{}
quantErrorNext[0] = [3]int32{}
for x := 0; x != r.Dx(); x++ {
sr, sg, sb, _ := src.At(sp.X+x, sp.Y+y).RGBA()
er, eg, eb := int32(sr), int32(sg), int32(sb)
er = clamp(er + (quantErrorNext[x][0]+quantError[0])/16)
eg = clamp(eg + (quantErrorNext[x][1]+quantError[1])/16)
eb = clamp(eb + (quantErrorNext[x][2]+quantError[2])/16)
out.R = uint16(er)
out.G = uint16(eg)
out.B = uint16(eb)
dst.Set(r.Min.X+x, r.Min.Y+y, &out)
sr, sg, sb, _ = dst.At(r.Min.X+x, r.Min.Y+y).RGBA()
er -= int32(sr)
eg -= int32(sg)
eb -= int32(sb)
quantError[0] = er * 3
quantError[1] = eg * 3
quantError[2] = eb * 3
quantErrorNext[x+0][0] += er * 3
quantErrorNext[x+0][1] += eg * 3
quantErrorNext[x+0][2] += eb * 3
quantErrorNext[x+1][0] = er * 2
quantErrorNext[x+1][1] = eg * 2
quantErrorNext[x+1][2] = eb * 2
}
}
}
// Copy an images outer edge of pixels and "bleeds" them to the edge of the image
func bleed(im draw.Image, amount int) {
// TODO refactor
outer := im.Bounds()
inner := image.Rect(outer.Min.X+amount, outer.Min.Y+amount, outer.Max.X-amount, outer.Max.Y-amount)
// Top left
col := im.At(inner.Min.X, inner.Min.Y)
for x := 0; x < amount; x++ {
for y := 0; y < amount; y++ {
im.Set(x, y, col)
}
}
// Top edge
for x := inner.Min.X; x < inner.Max.X; x++ {
col := im.At(x, amount)
for y := 0; y < amount; y++ {
im.Set(x, y, col)
}
}
// Top right
col = im.At(inner.Max.X-1, inner.Min.Y)
for x := 1; x <= amount; x++ {
for y := 0; y < amount; y++ {
im.Set(outer.Max.X-x, y, col)
}
}
// Right edge
for y := amount; y < inner.Max.X; y++ {
col := im.At(inner.Max.X-1, y)
for x := 1; x <= amount; x++ {
im.Set(outer.Max.X-x, y, col)
}
}
// Bottom right
col = im.At(inner.Max.X-1, inner.Max.Y-1)
for x := 1; x <= amount; x++ {
for y := 1; y <= amount; y++ {
im.Set(outer.Max.X-x, outer.Max.Y-y, col)
}
}
// Bottom edge
for x := amount; x < inner.Max.X; x++ {
col := im.At(x, inner.Max.Y-1)
for y := 1; y <= amount; y++ {
im.Set(x, outer.Max.Y-y, col)
}
}
// Bottom left
col = im.At(inner.Min.X, inner.Max.Y-1)
for x := 0; x < amount; x++ {
for y := 1; y <= amount; y++ {
im.Set(x, outer.Max.Y-y, col)
}
}
// Left edge
for y := amount; y < inner.Max.Y; y++ {
col := im.At(amount, y)
for x := 0; x < amount; x++ {
im.Set(x, y, col)
}
}
}
