mirror of
https://github.com/stevenrobertson/cuburn.git
synced 2025-02-05 11:40:04 -05:00
Wavelet experiments
This commit is contained in:
Steven Robertson
parent
acbde65b9f
commit
964b11efdf
@ -2,6 +2,7 @@
|
|||||||
import numpy as np
|
import numpy as np
|
||||||
from numpy import float32 as f32, int32 as i32
|
from numpy import float32 as f32, int32 as i32
|
||||||
|
|
||||||
|
import pycuda.driver as cuda
|
||||||
import pycuda.compiler
|
import pycuda.compiler
|
||||||
from pycuda.gpuarray import vec
|
from pycuda.gpuarray import vec
|
||||||
|
|
||||||
@ -106,45 +107,142 @@ void logscale(float4 *pixbuf, float4 *outbuf, float k1, float k2) {
|
|||||||
outbuf[i] = pix;
|
outbuf[i] = pix;
|
||||||
}
|
}
|
||||||
|
|
||||||
// SS must be no greater than 4x
|
__device__ void fmav(float4 &dst, float4 src, float scale) {
|
||||||
|
dst.x += src.x * scale;
|
||||||
|
dst.y += src.y * scale;
|
||||||
|
dst.z += src.z * scale;
|
||||||
|
dst.w += src.w * scale;
|
||||||
|
}
|
||||||
|
|
||||||
|
// The 7-tap filters are missing the leading zero to compensate for delay. I
|
||||||
|
// have no frigging clue what the theory behind that is, but it seems to work.
|
||||||
|
__constant__ float daub97_lo[9] = {
|
||||||
|
0.03782845550726404f, -0.023849465019556843f, -0.11062440441843718f,
|
||||||
|
0.37740285561283066f, 0.8526986790088938f, 0.37740285561283066f,
|
||||||
|
-0.11062440441843718f, -0.023849465019556843f, 0.03782845550726404f
|
||||||
|
};
|
||||||
|
__constant__ float daub97_hi[9] = {
|
||||||
|
-0.06453888262869706f, 0.04068941760916406f,
|
||||||
|
0.41809227322161724f, -0.7884856164055829f, 0.41809227322161724f,
|
||||||
|
0.04068941760916406f, -0.06453888262869706f, 0.0f,
|
||||||
|
};
|
||||||
|
__constant__ float daub97_ilo[9] = {
|
||||||
|
-0.06453888262869706f, -0.04068941760916406f,
|
||||||
|
0.41809227322161724f, 0.7884856164055829f, 0.41809227322161724f,
|
||||||
|
-0.04068941760916406f, -0.06453888262869706f, 0.0f
|
||||||
|
};
|
||||||
|
__constant__ float daub97_ihi[9] = {
|
||||||
|
-0.03782845550726404f, -0.023849465019556843f, 0.11062440441843718f,
|
||||||
|
0.37740285561283066f, -0.8526986790088938f, 0.37740285561283066f,
|
||||||
|
0.11062440441843718f, -0.023849465019556843f, -0.03782845550726404f
|
||||||
|
};
|
||||||
|
|
||||||
|
/*
|
||||||
|
#define S 0.7071067811f
|
||||||
|
__constant__ float daub97[4][9] = {
|
||||||
|
{ 0, 0, 0, S, S}, {0, 0, 0, -S, S}, {0, 0, 0, S, S}, {0, 0, 0, S, -S}};
|
||||||
|
*/
|
||||||
|
|
||||||
|
texture<float4, cudaTextureType2D> conv_down_src;
|
||||||
__global__
|
__global__
|
||||||
void blur_density_h(float *scratch, const float4 *pixbuf, int astride) {
|
void conv_down(float4 *dst, int astride, int as_eff, int ah_eff,
|
||||||
// TODO: respect supersampling? configurable blur width?
|
int vert, float xo, float yo) {
|
||||||
int x = blockIdx.x * blockDim.x + threadIdx.x;
|
int xi = blockIdx.x * blockDim.x + threadIdx.x;
|
||||||
if (x > astride) return;
|
int yi = blockIdx.y;
|
||||||
int y = blockIdx.y;
|
|
||||||
const float *dsrc =
|
|
||||||
reinterpret_cast<const float*>(&pixbuf[astride * y]) + 3;
|
|
||||||
|
|
||||||
float den = 0.0f;
|
float4 lo = make_float4(0, 0, 0, 0);
|
||||||
|
float4 hi = make_float4(0, 0, 0, 0);
|
||||||
|
|
||||||
den += dsrc[4*max(0, x-2)] * 0.00135f;
|
if (vert) {
|
||||||
den += dsrc[4*max(0, x-1)] * 0.1573f;
|
if (xi >= as_eff) return;
|
||||||
den += dsrc[4*x] * 0.6827f;
|
float x = xi - xo, y = yi * 2 - yo;
|
||||||
den += dsrc[4*min(astride-1, x+1)] * 0.1573f;
|
|
||||||
den += dsrc[4*min(astride-1, x+2)] * 0.00135f;
|
#pragma unroll
|
||||||
scratch[astride * y + x] = den;
|
for (int i = 0; i < 9; i++) {
|
||||||
|
float4 src = tex2D(conv_down_src, x, y);
|
||||||
|
fmav(lo, src, daub97_lo[i]);
|
||||||
|
fmav(hi, src, daub97_hi[i]);
|
||||||
|
y -= 1.0f;
|
||||||
|
if (y < 0) y += ah_eff;
|
||||||
|
}
|
||||||
|
dst[(yi + ah_eff / 2) * astride + xi] = hi;
|
||||||
|
} else {
|
||||||
|
if (xi >= as_eff / 2) return;
|
||||||
|
float x = xi * 2 - xo, y = yi - yo;
|
||||||
|
|
||||||
|
#pragma unroll
|
||||||
|
for (int i = 0; i < 9; i++) {
|
||||||
|
float4 src = tex2D(conv_down_src, x, y);
|
||||||
|
fmav(lo, src, daub97_lo[i]);
|
||||||
|
fmav(hi, src, daub97_hi[i]);
|
||||||
|
x -= 1.0f;
|
||||||
|
if (x < 0) x += as_eff;
|
||||||
|
}
|
||||||
|
dst[yi * astride + xi + as_eff / 2] = hi;
|
||||||
|
}
|
||||||
|
dst[yi * astride + xi] = lo;
|
||||||
|
}
|
||||||
|
|
||||||
|
texture<float4, cudaTextureType2D> conv_up_src_lo;
|
||||||
|
texture<float4, cudaTextureType2D> conv_up_src_hi;
|
||||||
|
__global__
|
||||||
|
void conv_up(float4 *dst, int astride, int as_eff,
|
||||||
|
int vert, int xo, int yo) {
|
||||||
|
int xi = blockIdx.x * blockDim.x + threadIdx.x;
|
||||||
|
int yi = blockIdx.y;
|
||||||
|
if (xi >= as_eff) return;
|
||||||
|
|
||||||
|
float4 out = make_float4(0, 0, 0, 0);
|
||||||
|
if (vert) {
|
||||||
|
float x = xi, y = yi / 2;
|
||||||
|
for (int i = ~yi & 1; i < 9; i+=2) {
|
||||||
|
fmav(out, tex2D(conv_up_src_lo, x, y), daub97_ilo[8-i]);
|
||||||
|
fmav(out, tex2D(conv_up_src_hi, x, y), daub97_ihi[8-i]);
|
||||||
|
y += 1.0f;
|
||||||
|
if (y >= gridDim.y / 2) y = 0.0f;
|
||||||
|
}
|
||||||
|
} else {
|
||||||
|
float x = xi / 2, y = yi;
|
||||||
|
for (int i = ~xi & 1; i < 9; i+=2) {
|
||||||
|
fmav(out, tex2D(conv_up_src_lo, x, y), daub97_ilo[8-i]);
|
||||||
|
fmav(out, tex2D(conv_up_src_hi, x, y), daub97_ihi[8-i]);
|
||||||
|
x += 1.0f;
|
||||||
|
if (x >= as_eff / 2) x = 0.0f;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
xi += xo;
|
||||||
|
yi += yo;
|
||||||
|
if (xi >= as_eff) xi -= as_eff;
|
||||||
|
if (yi >= gridDim.y) yi -= gridDim.y;
|
||||||
|
dst[yi * astride + xi] = out;
|
||||||
}
|
}
|
||||||
|
|
||||||
__global__
|
__global__
|
||||||
void blur_density_v(float4 *pixbuf, const float *scratch,
|
void simple_thresh(float4 *buf, int astride, float thr, int min_x, int min_y) {
|
||||||
int astride, int aheight) {
|
|
||||||
// TODO: respect supersampling? configurable blur width?
|
|
||||||
int x = blockIdx.x * blockDim.x + threadIdx.x;
|
int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||||
if (x > astride) return;
|
|
||||||
int y = blockIdx.y;
|
int y = blockIdx.y;
|
||||||
const float *dsrc = scratch + x;
|
if (x >= astride || (x < min_x && y < min_y)) return;
|
||||||
|
|
||||||
float den = 0.0f;
|
float4 val = buf[y * astride + x];
|
||||||
|
float fact = 1.0f - expf(powf(fabsf(val.w), 1.2) * -0.2f);
|
||||||
|
val.x *= fact;
|
||||||
|
val.y *= fact;
|
||||||
|
val.z *= fact;
|
||||||
|
val.w *= fact;
|
||||||
|
buf[y * astride + x] = val;
|
||||||
|
}
|
||||||
|
|
||||||
den += dsrc[astride*max(0, y-2)] * 0.00135f;
|
__global__
|
||||||
den += dsrc[astride*max(0, y-1)] * 0.1573f;
|
void fma_buf(float4 *dst, const float4 *sub, int astride, float scale) {
|
||||||
den += dsrc[astride*y] * 0.6827f;
|
int x = blockIdx.x * blockDim.x + threadIdx.x;
|
||||||
den += dsrc[astride*min(astride-1, y+1)] * 0.1573f;
|
int i = blockIdx.y * astride + x;
|
||||||
den += dsrc[astride*min(astride-1, y+2)] * 0.00135f;
|
if (x >= astride) return;
|
||||||
|
float4 d = dst[i], s = sub[i];
|
||||||
float *ddst = reinterpret_cast<float*>(&pixbuf[astride * y + x]) + 3;
|
d.x += s.x * scale;
|
||||||
*ddst = min(*ddst, den);
|
d.y += s.y * scale;
|
||||||
|
d.z += s.z * scale;
|
||||||
|
d.w += s.w * scale;
|
||||||
|
dst[i] = d;
|
||||||
}
|
}
|
||||||
|
|
||||||
#define W 21 // Filter width (regardless of standard deviation chosen)
|
#define W 21 // Filter width (regardless of standard deviation chosen)
|
||||||
@ -280,23 +378,136 @@ class Filtering(object):
|
|||||||
|
|
||||||
def __init__(self):
|
def __init__(self):
|
||||||
self.init_mod()
|
self.init_mod()
|
||||||
|
self.scratch = None
|
||||||
|
|
||||||
def blur_density(self, ddst, dscratch, dim, stream=None):
|
def blur_density(self, ddst, dscratch, dim, stream=None):
|
||||||
blur_h = self.mod.get_function("blur_density_h")
|
blur_h = self.mod.get_function("blur_density_h")
|
||||||
blur_h(dscratch, ddst, i32(dim.astride), block=(192, 1, 1),
|
blur_h(dscratch, ddst, i32(dim.astride), block=(192, 1, 1),
|
||||||
grid=(dim.astride / 192, dim.ah), stream=stream)
|
grid=(1 + dim.astride / 192, dim.ah), stream=stream)
|
||||||
blur_v = self.mod.get_function("blur_density_v")
|
blur_v = self.mod.get_function("blur_density_v")
|
||||||
blur_v(ddst, dscratch, i32(dim.astride), i32(dim.ah), block=(192, 1, 1),
|
blur_v(ddst, dscratch, i32(dim.astride), i32(dim.ah), block=(192, 1, 1),
|
||||||
grid=(dim.astride / 192, dim.ah), stream=stream)
|
grid=(1 + dim.astride / 192, dim.ah), stream=stream)
|
||||||
|
|
||||||
def de(self, ddst, dsrc, gnm, dim, tc, stream=None):
|
def de(self, ddst, dsrc, gnm, dim, tc, stream=None):
|
||||||
|
from cuburn.render import argset
|
||||||
|
print dim.ah
|
||||||
|
np.set_printoptions(linewidth=160, precision=4)
|
||||||
|
|
||||||
k1 = f32(gnm.color.brightness(tc) * 268 / 256)
|
k1 = f32(gnm.color.brightness(tc) * 268 / 256)
|
||||||
# Old definition of area is (w*h/(s*s)). Since new scale 'ns' is now
|
# Old definition of area is (w*h/(s*s)). Since new scale 'ns' is now
|
||||||
# s/w, new definition is (w*h/(s*s*w*w)) = (h/(s*s*w))
|
# s/w, new definition is (w*h/(s*s*w*w)) = (h/(s*s*w))
|
||||||
area = dim.h / (gnm.camera.scale(tc) ** 2 * dim.w)
|
area = dim.h / (gnm.camera.scale(tc) ** 2 * dim.w)
|
||||||
k2 = f32(1.0 / (area * gnm.spp(tc)))
|
k2 = f32(1.0 / (area * gnm.spp(tc)))
|
||||||
|
|
||||||
if gnm.de.radius == 0:
|
# Stride in bytes, buffer size
|
||||||
|
sb = 16 * dim.astride
|
||||||
|
bs = sb * dim.ah
|
||||||
|
|
||||||
|
if self.scratch is None:
|
||||||
|
self.scratch = cuda.mem_alloc(bs)
|
||||||
|
self.hi = cuda.mem_alloc(bs)
|
||||||
|
q = np.zeros((dim.ah, dim.astride * 4), dtype=np.float32)
|
||||||
|
q[100:102,128:1024] = 1
|
||||||
|
#cuda.memcpy_htod(dsrc, q)
|
||||||
|
|
||||||
|
dsc = argset(cuda.ArrayDescriptor(), height=dim.ah,
|
||||||
|
width=dim.astride, format=cuda.array_format.FLOAT,
|
||||||
|
num_channels=4)
|
||||||
|
bl = (192, 1, 1)
|
||||||
|
gr = lambda x, y: (1 + dim.astride / (192 << x), dim.ah >> y)
|
||||||
|
|
||||||
|
def get_tref(name):
|
||||||
|
tref = self.mod.get_texref(name)
|
||||||
|
tref.set_filter_mode(cuda.filter_mode.POINT)
|
||||||
|
tref.set_address_mode(0, cuda.address_mode.WRAP)
|
||||||
|
tref.set_address_mode(1, cuda.address_mode.WRAP)
|
||||||
|
print tref.get_address_mode(0)
|
||||||
|
print tref.get_address_mode(1)
|
||||||
|
return tref
|
||||||
|
conv_down_src, conv_up_src_lo, conv_up_src_hi = map(get_tref,
|
||||||
|
['conv_down_src', 'conv_up_src_lo', 'conv_up_src_hi'])
|
||||||
|
|
||||||
|
conv_down = self.mod.get_function('conv_down')
|
||||||
|
conv_up = self.mod.get_function('conv_up')
|
||||||
|
|
||||||
|
memcpy = cuda.Memcpy2D()
|
||||||
|
memcpy.src_pitch = sb
|
||||||
|
memcpy.src_height = memcpy.dst_height = memcpy.height = dim.ah
|
||||||
|
memcpy.set_src_device(self.scratch)
|
||||||
|
memcpy.set_dst_device(self.hi)
|
||||||
|
|
||||||
|
STEPS=3
|
||||||
|
|
||||||
|
print dim
|
||||||
|
def th(x):
|
||||||
|
x = np.int64(x*1e6)
|
||||||
|
v = np.nonzero(x)[0]
|
||||||
|
print np.array((v, x[v]))
|
||||||
|
|
||||||
|
for xo, yo in [(0, 0), (1, 1), (3, 3), (1, 3), (3, 1), (2, 2), (0, 0)]:
|
||||||
|
for i in range(STEPS):
|
||||||
|
xon, yon = (xo, yo) if i == 0 else (0, 0)
|
||||||
|
as_eff, ah_eff = dim.astride >> i, dim.ah >> i
|
||||||
|
dsc.width, dsc.height = as_eff, ah_eff
|
||||||
|
conv_down_src.set_address_2d(dsrc, dsc, sb)
|
||||||
|
conv_down(self.scratch, i32(dim.astride),
|
||||||
|
i32(as_eff), i32(ah_eff), i32(1), f32(xon), f32(yon),
|
||||||
|
block=bl, grid=gr(i, i+1),
|
||||||
|
texrefs=[conv_down_src], stream=stream)
|
||||||
|
#cuda.memcpy_dtod_async(self.scratch, dsrc, bs, stream)
|
||||||
|
conv_down_src.set_address_2d(self.scratch, dsc, sb)
|
||||||
|
conv_down(dsrc, i32(dim.astride),
|
||||||
|
i32(as_eff), i32(ah_eff), i32(0), f32(xon), f32(yon),
|
||||||
|
block=bl, grid=gr(i+1, i),
|
||||||
|
texrefs=[conv_down_src], stream=stream)
|
||||||
|
#cuda.memcpy_dtod_async(dsrc, self.scratch, bs, stream)
|
||||||
|
#th(cuda.from_device_like(self.scratch, q).T[128])
|
||||||
|
cuda.memcpy_dtod_async(ddst, dsrc, bs, stream)
|
||||||
|
|
||||||
|
thresh = self.mod.get_function('simple_thresh')
|
||||||
|
thresh(dsrc, i32(dim.astride), f32(1),
|
||||||
|
i32(dim.astride >> STEPS), i32(dim.ah >> STEPS),
|
||||||
|
block=bl, grid=gr(0, 0), stream=stream)
|
||||||
|
|
||||||
|
for i in list(reversed(range(STEPS))):
|
||||||
|
xon, yon = (xo, yo) if i == 0 else (0, 0)
|
||||||
|
dsc.width, dsc.height = dim.astride >> i, dim.ah >> (i+1)
|
||||||
|
conv_up_src_lo.set_address_2d(dsrc, dsc, sb)
|
||||||
|
hi_addr = int(dsrc) + sb * (dim.ah >> (i+1))
|
||||||
|
conv_up_src_hi.set_address_2d(hi_addr, dsc, sb)
|
||||||
|
conv_up(self.scratch, i32(dim.astride), i32(dim.astride >> i),
|
||||||
|
i32(1), i32(xon), i32(yon),
|
||||||
|
block=bl, grid=gr(i, i), stream=stream,
|
||||||
|
texrefs=[conv_up_src_lo, conv_up_src_hi])
|
||||||
|
sb_2 = sb >> (i+1)
|
||||||
|
memcpy.dst_pitch = sb_2
|
||||||
|
memcpy.width_in_bytes = sb_2
|
||||||
|
memcpy.src_x_in_bytes = sb_2
|
||||||
|
memcpy(stream)
|
||||||
|
dsc.width, dsc.height = dim.astride >> (i+1), dim.ah >> i
|
||||||
|
conv_up_src_lo.set_address_2d(self.scratch, dsc, sb)
|
||||||
|
conv_up_src_hi.set_address_2d(self.hi, dsc, sb>>(i+1))
|
||||||
|
conv_up(dsrc, i32(dim.astride), i32(dim.astride >> i),
|
||||||
|
i32(0), i32(xon), i32(yon),
|
||||||
|
block=bl, grid=gr(i, i), stream=stream,
|
||||||
|
texrefs=[conv_up_src_lo, conv_up_src_hi])
|
||||||
|
#cuda.memcpy_dtod_async(dsrc, self.scratch, bs, stream)
|
||||||
|
|
||||||
|
#th(cuda.from_device_like(self.scratch, q).T[128])
|
||||||
|
cuda.memcpy_dtod_async(ddst, dsrc, bs, stream)
|
||||||
|
|
||||||
|
#y = cuda.from_device_like(self.scratch, q)
|
||||||
|
#print y[93:110,128].T
|
||||||
|
|
||||||
|
#print x[93:110,128].T + y[93:110,128].T
|
||||||
|
|
||||||
|
#fun = self.mod.get_function('fma_buf')
|
||||||
|
#fun(self.scratch, self.lo, i32(dim.astride), f32(1),
|
||||||
|
#block=bl, grid=gr, stream=stream)
|
||||||
|
#cuda.memcpy_dtod_async(ddst, self.scratch, bs, stream=stream)
|
||||||
|
#return
|
||||||
|
|
||||||
|
if gnm.de.radius(tc) == 0 or True:
|
||||||
nbins = dim.ah * dim.astride
|
nbins = dim.ah * dim.astride
|
||||||
fun = self.mod.get_function("logscale")
|
fun = self.mod.get_function("logscale")
|
||||||
t = fun(dsrc, ddst, k1, k2,
|
t = fun(dsrc, ddst, k1, k2,
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user