def local_laplacian(dtype=UInt(16), counter=[0]):
"Local Laplacian."
print 'local_laplacian', counter[0], dtype.maxval()
import halide
J = 8
s = '_laplacian%d'%counter[0]
downsample_counter=[0]
upsample_counter=[0]
def downsample(f):
downx, downy = Func('downx%d'%downsample_counter[0]+s), Func('downy%d'%downsample_counter[0]+s)
downsample_counter[0] += 1
downx[x,y] = (f[2*x-1, y] + 3.0*(f[2*x,y]+f[2*x+1,y]) + f[2*x+2,y])/8.0
downy[x,y] = (downx[x,2*y-1] + 3.0*(downx[x,2*y]+downx[x,2*y+1]) + downx[x,2*y+2])/8.0
return downy
def upsample(f):
upx, upy = Func('upx%d'%upsample_counter[0]+s), Func('upy%d'%upsample_counter[0]+s)
upsample_counter[0] += 1
upx[x,y] = 0.25 * f[(x/2)-1+2*(x%2),y] + 0.75 * f[x/2,y]
upy[x,y] = 0.25 * upx[x, (y/2) - 1 + 2*(y%2)] + 0.75 * upx[x,y/2]
return upy
levels = Uniform(int_t, 'levels'+s, 8)
alpha = Uniform(float_t, 'alpha'+s, 1.0) #1.0)
beta = Uniform(float_t, 'beta'+s, 1.0)
input = UniformImage(dtype, 3, 'input'+s)
x = Var('x'+s)
y = Var('y'+s)
c = Var('c'+s)
k = Var('k'+s)
fx = cast(float_t, x/256.0)
remap = Func('remap'+s)
remap[x] = (alpha/cast(float_t, levels-1))*fx*exp(-fx*fx/2.0)
floating = Func('floating'+s)
floating[x,y,c] = cast(float_t, input[x,y,c])/float(dtype.maxval())
clamped = Func('clamped'+s)
clamped[x,y,c] = floating[clamp(x,cast(int_t,0),cast(int_t,input.width()-1)),
clamp(y,cast(int_t,0),cast(int_t,input.height()-1)), c]
gray = Func('gray'+s)
gray[x,y] = 0.299*clamped[x,y,0]+0.587*clamped[x,y,1]+0.114*clamped[x,y,2]
gPyramid = [Func('gPyramid%d'%i+s) for i in range(J)]
idx = gray[x,y]*cast(float_t, levels-1)*256.0
idx = clamp(cast(int_t, idx), cast(int_t, 0), cast(int_t, (levels-1)*256))
gPyramid[0][x,y,k] = beta*gray[x,y] + remap[idx-256*k]
for j in range(1,J):
gPyramid[j][x,y,k] = downsample(gPyramid[j-1])[x,y,k]
lPyramid = [Func('lPyramid%d'%i+s) for i in range(J)]
lPyramid[J-1] = gPyramid[J-1]
for j in range(J-1)[::-1]:
lPyramid[j][x,y,k] = gPyramid[j][x,y,k] - upsample(gPyramid[j+1])[x,y,k]
inGPyramid = [Func('inGPyramid%d'%i+s) for i in range(J)]
inGPyramid[0] = gray
for j in range(1,J):
inGPyramid[j][x,y] = downsample(inGPyramid[j-1])[x,y]
outLPyramid = [Func('outLPyramid%d'%i+s) for i in range(J)]
for j in range(J):
level = inGPyramid[j][x,y]*cast(float_t, levels-1)
li = clamp(cast(int_t, level), cast(int_t, 0), cast(int_t, levels-2))
lf = level - cast(float_t, li)
outLPyramid[j][x,y] = (1.0-lf)*lPyramid[j][x,y,li] + lf*lPyramid[j][x,y,li+1]
outGPyramid = [Func('outGPyramid%d'%i+s) for i in range(J)]
outGPyramid[J-1] = outLPyramid[J-1]
for j in range(J-1)[::-1]:
outGPyramid[j][x,y] = upsample(outGPyramid[j+1])[x,y] + outLPyramid[j][x,y]
color = Func('color'+s)
color[x,y,c] = outGPyramid[0][x,y] * clamped[x,y,c] / gray[x,y]
output = Func('output'+s)
output[x,y,c] = cast(dtype, clamp(color[x,y,c], cast(float_t,0.0), cast(float_t,1.0))*float(dtype.maxval()))
halide.root_all(output)
#print 'Done with local_laplacian', counter[0]
counter[0] += 1
return (input, output, None)
def local_laplacian(dtype=UInt(16), counter=[0]):
"Local Laplacian."
print 'local_laplacian', counter[0], dtype.maxval()
import halide
J = 8
s = '_laplacian%d' % counter[0]
downsample_counter = [0]
upsample_counter = [0]
def downsample(f):
downx, downy = Func('downx%d' % downsample_counter[0] +
s), Func('downy%d' % downsample_counter[0] + s)
downsample_counter[0] += 1
downx[x, y] = (f[2 * x - 1, y] + 3.0 *
(f[2 * x, y] + f[2 * x + 1, y]) + f[2 * x + 2, y]) / 8.0
downy[x, y] = (downx[x, 2 * y - 1] + 3.0 *
(downx[x, 2 * y] + downx[x, 2 * y + 1]) +
downx[x, 2 * y + 2]) / 8.0
return downy
def upsample(f):
upx, upy = Func('upx%d' % upsample_counter[0] +
s), Func('upy%d' % upsample_counter[0] + s)
upsample_counter[0] += 1
upx[x, y] = 0.25 * f[(x / 2) - 1 + 2 * (x % 2), y] + 0.75 * f[x / 2, y]
upy[x,
y] = 0.25 * upx[x,
(y / 2) - 1 + 2 * (y % 2)] + 0.75 * upx[x, y / 2]
return upy
levels = Uniform(int_t, 'levels' + s, 8)
alpha = Uniform(float_t, 'alpha' + s, 1.0) #1.0)
beta = Uniform(float_t, 'beta' + s, 1.0)
input = UniformImage(dtype, 3, 'input' + s)
x = Var('x' + s)
y = Var('y' + s)
c = Var('c' + s)
k = Var('k' + s)
fx = cast(float_t, x / 256.0)
remap = Func('remap' + s)
remap[x] = (alpha / cast(float_t, levels - 1)) * fx * exp(-fx * fx / 2.0)
floating = Func('floating' + s)
floating[x, y, c] = cast(float_t, input[x, y, c]) / float(dtype.maxval())
clamped = Func('clamped' + s)
clamped[x, y, c] = floating[
clamp(x, cast(int_t, 0), cast(int_t,
input.width() - 1)),
clamp(y, cast(int_t, 0), cast(int_t,
input.height() - 1)), c]
gray = Func('gray' + s)
gray[x, y] = 0.299 * clamped[x, y, 0] + 0.587 * clamped[
x, y, 1] + 0.114 * clamped[x, y, 2]
gPyramid = [Func('gPyramid%d' % i + s) for i in range(J)]
idx = gray[x, y] * cast(float_t, levels - 1) * 256.0
idx = clamp(cast(int_t, idx), cast(int_t, 0),
cast(int_t, (levels - 1) * 256))
gPyramid[0][x, y, k] = beta * gray[x, y] + remap[idx - 256 * k]
for j in range(1, J):
gPyramid[j][x, y, k] = downsample(gPyramid[j - 1])[x, y, k]
lPyramid = [Func('lPyramid%d' % i + s) for i in range(J)]
lPyramid[J - 1] = gPyramid[J - 1]
for j in range(J - 1)[::-1]:
lPyramid[j][x, y, k] = gPyramid[j][x, y, k] - upsample(
gPyramid[j + 1])[x, y, k]
inGPyramid = [Func('inGPyramid%d' % i + s) for i in range(J)]
inGPyramid[0] = gray
for j in range(1, J):
inGPyramid[j][x, y] = downsample(inGPyramid[j - 1])[x, y]
outLPyramid = [Func('outLPyramid%d' % i + s) for i in range(J)]
for j in range(J):
level = inGPyramid[j][x, y] * cast(float_t, levels - 1)
li = clamp(cast(int_t, level), cast(int_t, 0), cast(int_t, levels - 2))
lf = level - cast(float_t, li)
outLPyramid[j][x, y] = (
1.0 - lf) * lPyramid[j][x, y, li] + lf * lPyramid[j][x, y, li + 1]
outGPyramid = [Func('outGPyramid%d' % i + s) for i in range(J)]
outGPyramid[J - 1] = outLPyramid[J - 1]
for j in range(J - 1)[::-1]:
outGPyramid[j][x, y] = upsample(
outGPyramid[j + 1])[x, y] + outLPyramid[j][x, y]
color = Func('color' + s)
color[x, y, c] = outGPyramid[0][x, y] * clamped[x, y, c] / gray[x, y]
output = Func('output' + s)
output[x, y, c] = cast(
dtype,
clamp(color[x, y, c], cast(float_t, 0.0), cast(float_t, 1.0)) *
float(dtype.maxval()))
halide.root_all(output)
#print 'Done with local_laplacian', counter[0]
counter[0] += 1
return (input, output, None)
def interpolate(dtype=UInt(16), counter=[0]):
"Fast interpolation using a pyramid."
import halide
s = '_interpolate%d'%counter[0]
counter[0] += 1
input = UniformImage(dtype, 3, 'input'+s)
x = Var('x'+s)
y = Var('y'+s)
c = Var('c'+s)
levels = 10
downsampled = [Func('downsampled%d'%i+s) for i in range(levels)]
interpolated = [Func('interpolated%d'%i+s) for i in range(levels)]
level_widths = [Uniform(int_t,'level_widths%d'%i+s) for i in range(levels)]
level_heights = [Uniform(int_t,'level_heights%d'%i+s) for i in range(levels)]
downsampled[0][x,y] = (input[x,y,0] * input[x,y,3],
input[x,y,1] * input[x,y,3],
input[x,y,2] * input[x,y,3],
input[x,y,3])
for l in range(1, levels):
clamped = Func('clamped%d'%l+s)
clamped[x,y,c] = downsampled[l-1][clamp(cast(int_t,x),cast(int_t,0),cast(int_t,level_widths[l-1]-1)),
clamp(cast(int_t,y),cast(int_t,0),cast(int_t,level_heights[l-1]-1)), c]
downx = Func('downx%d'%l+s)
downx[x,y,c] = (clamped[x*2-1,y,c] + 2.0 * clamped[x*2,y,c] + clamped[x*2+1,y,c]) / 4.0
downsampled[l][x,y,c] = (downx[x,y*2-1,c] + 2.0 * downx[x,y*2,c] + downx[x,y*2+1,c]) / 4.0
interpolated[levels-1][x,y,c] = downsampled[levels-1][x,y,c]
for l in range(levels-1)[::-1]:
upsampledx, upsampled = Func('upsampledx%d'%l+s), Func('upsampled%d'%l+s)
upsampledx[x,y,c] = 0.5 * (interpolated[l+1][x/2 + (x%2),y,c] + interpolated[l+1][x/2,y,c])
upsampled[x,y,c] = 0.5 * (upsampledx[x, y/2 + (y%2),c] + upsampledx[x,y/2,c])
interpolated[l][x,y,c] = downsampled[l][x,y,c] + (1.0 - downsampled[l][x,y,3]) * upsampled[x,y,c]
final = Func('final'+s)
final[x,y] = (interpolated[0][x,y,0] / interpolated[0][x,y,3],
interpolated[0][x,y,1] / interpolated[0][x,y,3],
interpolated[0][x,y,2] / interpolated[0][x,y,3],
1.0)
halide.root_all(final)
print 'interpolate: finished function setup'
def evaluate(in_png):
print 'interpolate evaluate'
width = in_png.width()
height = in_png.height()
print width, height
for l in range(levels):
level_widths[l].assign(width)
level_heights[l].assign(height)
width = width/2 + 1
height = height/2 + 1
print in_png.width(), in_png.height(), 'realizing'
out = final.realize(in_png.width(), in_png.height(), 4)
print 'evaluate realized, returning'
return out
print 'interpolate: returning'
return (input, final, evaluate)
def interpolate(dtype=UInt(16), counter=[0]):
"Fast interpolation using a pyramid."
import halide
s = '_interpolate%d' % counter[0]
counter[0] += 1
input = UniformImage(dtype, 3, 'input' + s)
x = Var('x' + s)
y = Var('y' + s)
c = Var('c' + s)
levels = 10
downsampled = [Func('downsampled%d' % i + s) for i in range(levels)]
interpolated = [Func('interpolated%d' % i + s) for i in range(levels)]
level_widths = [
Uniform(int_t, 'level_widths%d' % i + s) for i in range(levels)
]
level_heights = [
Uniform(int_t, 'level_heights%d' % i + s) for i in range(levels)
]
downsampled[0][x, y] = (input[x, y, 0] * input[x, y, 3],
input[x, y, 1] * input[x, y, 3],
input[x, y, 2] * input[x, y, 3], input[x, y, 3])
for l in range(1, levels):
clamped = Func('clamped%d' % l + s)
clamped[x, y, c] = downsampled[l - 1][
clamp(cast(int_t, x), cast(int_t, 0
), cast(int_t, level_widths[l - 1] -
1)),
clamp(cast(int_t, y), cast(int_t, 0
), cast(int_t, level_heights[l - 1] -
1)), c]
downx = Func('downx%d' % l + s)
downx[x, y,
c] = (clamped[x * 2 - 1, y, c] + 2.0 * clamped[x * 2, y, c] +
clamped[x * 2 + 1, y, c]) / 4.0
downsampled[l][x, y,
c] = (downx[x, y * 2 - 1, c] + 2.0 * downx[x, y * 2, c]
+ downx[x, y * 2 + 1, c]) / 4.0
interpolated[levels - 1][x, y, c] = downsampled[levels - 1][x, y, c]
for l in range(levels - 1)[::-1]:
upsampledx, upsampled = Func('upsampledx%d' % l +
s), Func('upsampled%d' % l + s)
upsampledx[x, y,
c] = 0.5 * (interpolated[l + 1][x / 2 + (x % 2), y, c] +
interpolated[l + 1][x / 2, y, c])
upsampled[x, y,
c] = 0.5 * (upsampledx[x, y / 2 +
(y % 2), c] + upsampledx[x, y / 2, c])
interpolated[l][x, y, c] = downsampled[l][
x, y, c] + (1.0 - downsampled[l][x, y, 3]) * upsampled[x, y, c]
final = Func('final' + s)
final[x, y] = (interpolated[0][x, y, 0] / interpolated[0][x, y, 3],
interpolated[0][x, y, 1] / interpolated[0][x, y, 3],
interpolated[0][x, y, 2] / interpolated[0][x, y, 3], 1.0)
halide.root_all(final)
#print 'interpolate: finished function setup'
def evaluate(in_png):
#print 'interpolate evaluate'
width = in_png.width()
height = in_png.height()
print width, height
for l in range(levels):
level_widths[l].assign(width)
level_heights[l].assign(height)
width = width / 2 + 1
height = height / 2 + 1
print in_png.width(), in_png.height(), 'realizing'
out = final.realize(in_png.width(), in_png.height(), 4)
#print 'evaluate realized, returning'
return out
#print 'interpolate: returning'
return (input, final, evaluate)
