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Revert "Direct evaluation of gaussian"

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This reverts commit 5e18cdea0a.

Reason for revert: ASAN
Original change's description:
> Direct evaluation of gaussian
> 
> The SVG(CSS) standard allows the 3 pass algorithm for sigma >= 2. But
> sigma < 2, the code must evaluate to the convolution. The old code used
> an interpolation scheme between windowed filters. This code directly
> evaluates the gaussian kernel for sigma < 2.
> 
> This code produces cleaner results, is 25% faster, and does not use a
> temporary memory buffer.
> 
> Change-Id: Ibd0caa73cadd06b637f55ba7bd4fefcfe7ac73db
> Reviewed-on: https://skia-review.googlesource.com/62540
> Commit-Queue: Herb Derby <herb@google.com>
> Reviewed-by: Mike Klein <mtklein@google.com>

TBR=mtklein@google.com,herb@google.com

Change-Id: I936077dfa659d71bc361339d98340c55545a1eb8
No-Presubmit: true
No-Tree-Checks: true
No-Try: true
Reviewed-on: https://skia-review.googlesource.com/72481
Reviewed-by: Brian Osman <brianosman@google.com>
Commit-Queue: Brian Osman <brianosman@google.com>
This commit is contained in:
Brian Osman 2017-11-16 19:09:57 +00:00 committed by Skia Commit-Bot
parent bc13605c62
commit a53d999007
4 changed files with 7 additions and 649 deletions
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5
bench/BlurBench.cpp
View File

@ -15,11 +15,9 @@
#define MINI 0.01f
#define SMALL SkIntToScalar(2)
#define REAL 0.5f
#define REAL 1.5f
#define BIG SkIntToScalar(10)
#define REALBIG 100.5f
// The value that produces a sigma of just over 2.
#define CUTOVER 2.6f
static const char* gStyleName[] = {
"normal",
@ -113,6 +111,5 @@ DEF_BENCH(return new BlurBench(BIG, kNormal_SkBlurStyle, SkBlurMaskFilter::kHigh
DEF_BENCH(return new BlurBench(REALBIG, kNormal_SkBlurStyle, SkBlurMaskFilter::kHighQuality_BlurFlag);)
DEF_BENCH(return new BlurBench(REAL, kNormal_SkBlurStyle, SkBlurMaskFilter::kHighQuality_BlurFlag);)
DEF_BENCH(return new BlurBench(CUTOVER, kNormal_SkBlurStyle, SkBlurMaskFilter::kHighQuality_BlurFlag);)
DEF_BENCH(return new BlurBench(0, kNormal_SkBlurStyle);)

3
src/core/SkGaussFilter.cpp
View File

@ -143,9 +143,10 @@ SkGaussFilter::SkGaussFilter(double sigma, Type type) {
}
}
int SkGaussFilter::filterDouble(double values[5]) const {
int SkGaussFilter::filterDouble(double* values) const {
for (int i = 0; i < fN; i++) {
values[i] = fBasis[i];
}
return fN;
}

6
src/core/SkGaussFilter.h
View File

@ -27,16 +27,10 @@ public:
int radius() const { return fN - 1; }
int width() const { return 2 * this->radius() + 1; }
// TODO: remove filterDouble and use the ranged-for loop interface.
// Take an array of values where the gaussian factors will be placed. Return the number of
// values filled.
int filterDouble(double values[5]) const;
// Allow a filter to be used in a C++ ranged-for loop.
const double* begin() const { return &fBasis[0]; }
const double* end() const { return &fBasis[fN]; }
private:
double fBasis[5];
int fN;

640
src/core/SkMaskBlurFilter.cpp
View File

@ -11,7 +11,6 @@
#include <climits>
#include "SkArenaAlloc.h"
#include "SkGaussFilter.h"
#include "SkNx.h"
#include "SkSafeMath.h"
@ -569,644 +568,8 @@ static SkMask prepare_destination(int radiusX, int radiusY, const SkMask& src) {
return dst;
}
#if !defined(SK_USE_LEGACY_INTERP_BLUR)
static constexpr uint16_t _____ = 0u;
static constexpr uint16_t kHalf = 0x80u;
static SK_ALWAYS_INLINE Sk8h load(const uint8_t* from, int width) {
uint8_t buffer[8];
if (width < 8) {
sk_bzero(buffer, sizeof(buffer));
for (int i = 0; i < width; i++) {
buffer[i] = from[i];
}
from = buffer;
}
auto v = SkNx_cast<uint16_t>(Sk8b::Load(from));
// Convert from 0-255 to 8.8 encoding.
return v << 8;
};
static SK_ALWAYS_INLINE void store(uint8_t* to, const Sk8h& v, int width) {
Sk8b b = SkNx_cast<uint8_t>(v >> 8);
if (width == 8) {
b.store(to);
} else {
uint8_t buffer[8];
b.store(buffer);
for (int i = 0; i < width; i++) {
to[i] = buffer[i];
}
}
};
// In all the blur_x_radius_N and blur_y_radius_N functions the gaussian values are encoded
// in 0.16 format, none of the values is greater than one. The incoming mask values are in 8.8
// format. The resulting multiply has a 8.24 format, by the mulhi truncates the lower 16 bits
// resulting in a 8.8 format.
//
// The blur_x_radius_N function below blur along a row of pixels using a kernel with radius N. This
// system is setup to minimize the number of multiplies needed.
//
// Explanation:
// Blurring a specific mask value is given by the following equation where D_n is the resulting
// mask value and S_n is the source value. The example below is for a filter with a radius of 1
// and a width of 3 (radius == (width-1)/2). The indexes for the source and destination are
// aligned. The filter is given by G_n where n is the symmetric filter value.
//
// D[n] = S[n-1]*G[1] + S[n]*G[0] + S[n+1]*G[1].
//
// We can start the source index at an offset relative to the destination separated by the
// radius. This results in a non-traditional restating of the above filter.
//
// D[n] = S[n]*G[1] + S[n+1]*G[0] + S[n+2]*G[1]
//
// If we look at three specific consecutive destinations the following equations result:
//
// D[5] = S[5]*G[1] + S[6]*G[0] + S[7]*G[1]
// D[7] = S[6]*G[1] + S[7]*G[0] + S[8]*G[1]
// D[8] = S[7]*G[1] + S[8]*G[0] + S[9]*G[1].
//
// In the above equations, notice that S[7] is used in all three. In particular, two values are
// used: S[7]*G[0] and S[7]*G[1]. So, S[7] is only multiplied twice, but used in D[5], D[6] and
// D[7].
//
// From the point of view of a source value we end up with the following three equations.
//
// Given S[7]:
// D[5] += S[7]*G[1]
// D[6] += S[7]*G[0]
// D[7] += S[7]*G[1]
//
// In General:
// D[n] += S[n]*G[1]
// D[n+1] += S[n]*G[0]
// D[n+2] += S[n]*G[1]
//
// Now these equations can be ganged using SIMD to form:
// D[n..n+7] += S[n..n+7]*G[1]
// D[n+1..n+8] += S[n..n+7]*G[0]
// D[n+2..n+9] += S[n..n+7]*G[1]
// The next set of values becomes.
// D[n+8..n+15] += S[n+8..n+15]*G[1]
// D[n+9..n+16] += S[n+8..n+15]*G[0]
// D[n+10..n+17] += S[n+8..n+15]*G[1]
// You can see that the D[n+8] and D[n+9] values overlap the two sets, using parts of both
// S[n..7] and S[n+8..n+15].
//
// Just one more transformation allows the code to maintain all working values in
// registers. I introduce the notation {0, S[n..n+7] * G[k]} to mean that the value where 0 is
// prepended to the array of values to form {0, S[n] * G[k], ..., S[n+7]*G[k]}.
//
// D[n..n+7] += S[n..n+7] * G[1]
// D[n..n+8] += {0, S[n..n+7] * G[0]}
// D[n..n+9] += {0, 0, S[n..n+7] * G[1]}
//
// Now we can encode D[n..n+7] in a single Sk8h register called d0, and D[n+8..n+15] in a
// register d8. In addition, S[0..n+7] becomes s0.
//
// The translation of the {0, S[n..n+7] * G[k]} is translated in the following way below.
//
// Sk8h v0 = s0*G[0]
// Sk8h v1 = s0*G[1]
// /* D[n..n+7] += S[n..n+7] * G[1] */
// d0 += v1;
// /* D[n..n+8] += {0, S[n..n+7] * G[0]} */
// d0 += {_____, v0[0], v0[1], v0[2], v0[3], v0[4], v0[5], v0[6]}
// d1 += {v0[7], _____, _____, _____, _____, _____, _____, _____}
// /* D[n..n+9] += {0, 0, S[n..n+7] * G[1]} */
// d0 += {_____, _____, v1[0], v1[1], v1[2], v1[3], v1[4], v1[5]}
// d1 += {v1[6], v1[7], _____, _____, _____, _____, _____, _____}
// Where we rely on the compiler to generate efficient code for the {____, n, ....} notation.
static SK_ALWAYS_INLINE void blur_x_radius_1(
const Sk8h& s0,
const Sk8h& g0, const Sk8h& g1, const Sk8h&, const Sk8h&, const Sk8h&,
Sk8h* d0, Sk8h* d8) {
auto v1 = s0.mulHi(g1);
auto v0 = s0.mulHi(g0);
// D[n..n+7] += S[n..n+7] * G[1]
*d0 += v1;
//D[n..n+8] += {0, S[n..n+7] * G[0]}
*d0 += Sk8h{_____, v0[0], v0[1], v0[2], v0[3], v0[4], v0[5], v0[6]};
*d8 += Sk8h{v0[7], _____, _____, _____, _____, _____, _____, _____};
// D[n..n+9] += {0, 0, S[n..n+7] * G[1]}
*d0 += Sk8h{_____, _____, v1[0], v1[1], v1[2], v1[3], v1[4], v1[5]};
*d8 += Sk8h{v1[6], v1[7], _____, _____, _____, _____, _____, _____};
}
static SK_ALWAYS_INLINE void blur_x_radius_2(
const Sk8h& s0,
const Sk8h& g0, const Sk8h& g1, const Sk8h& g2, const Sk8h&, const Sk8h&,
Sk8h* d0, Sk8h* d8) {
auto v0 = s0.mulHi(g0);
auto v1 = s0.mulHi(g1);
auto v2 = s0.mulHi(g2);
// D[n..n+7] += S[n..n+7] * G[2]
*d0 += v2;
// D[n..n+8] += {0, S[n..n+7] * G[1]}
*d0 += Sk8h{_____, v1[0], v1[1], v1[2], v1[3], v1[4], v1[5], v1[6]};
*d8 += Sk8h{v1[7], _____, _____, _____, _____, _____, _____, _____};
// D[n..n+9] += {0, 0, S[n..n+7] * G[0]}
*d0 += Sk8h{_____, _____, v0[0], v0[1], v0[2], v0[3], v0[4], v0[5]};
*d8 += Sk8h{v0[6], v0[7], _____, _____, _____, _____, _____, _____};
// D[n..n+10] += {0, 0, 0, S[n..n+7] * G[1]}
*d0 += Sk8h{_____, _____, _____, v1[0], v1[1], v1[2], v1[3], v1[4]};
*d8 += Sk8h{v1[5], v1[6], v1[7], _____, _____, _____, _____, _____};
// D[n..n+11] += {0, 0, 0, 0, S[n..n+7] * G[2]}
*d0 += Sk8h{_____, _____, _____, _____, v2[0], v2[1], v2[2], v2[3]};
*d8 += Sk8h{v2[4], v2[5], v2[6], v2[7], _____, _____, _____, _____};
}
static SK_ALWAYS_INLINE void blur_x_radius_3(
const Sk8h& s0,
const Sk8h& gauss0, const Sk8h& gauss1, const Sk8h& gauss2, const Sk8h& gauss3, const Sk8h&,
Sk8h* d0, Sk8h* d8) {
auto v0 = s0.mulHi(gauss0);
auto v1 = s0.mulHi(gauss1);
auto v2 = s0.mulHi(gauss2);
auto v3 = s0.mulHi(gauss3);
// D[n..n+7] += S[n..n+7] * G[3]
*d0 += v3;
// D[n..n+8] += {0, S[n..n+7] * G[2]}
*d0 += Sk8h{_____, v2[0], v2[1], v2[2], v2[3], v2[4], v2[5], v2[6]};
*d8 += Sk8h{v2[7], _____, _____, _____, _____, _____, _____, _____};
// D[n..n+9] += {0, 0, S[n..n+7] * G[1]}
*d0 += Sk8h{_____, _____, v1[0], v1[1], v1[2], v1[3], v1[4], v1[5]};
*d8 += Sk8h{v1[6], v1[7], _____, _____, _____, _____, _____, _____};
// D[n..n+10] += {0, 0, 0, S[n..n+7] * G[0]}
*d0 += Sk8h{_____, _____, _____, v0[0], v0[1], v0[2], v0[3], v0[4]};
*d8 += Sk8h{v0[5], v0[6], v0[7], _____, _____, _____, _____, _____};
// D[n..n+11] += {0, 0, 0, 0, S[n..n+7] * G[1]}
*d0 += Sk8h{_____, _____, _____, _____, v1[0], v1[1], v1[2], v1[3]};
*d8 += Sk8h{v1[4], v1[5], v1[6], v1[7], _____, _____, _____, _____};
// D[n..n+12] += {0, 0, 0, 0, 0, S[n..n+7] * G[2]}
*d0 += Sk8h{_____, _____, _____, _____, _____, v2[0], v2[1], v2[2]};
*d8 += Sk8h{v2[3], v2[4], v2[5], v2[6], v2[7], _____, _____, _____};
// D[n..n+13] += {0, 0, 0, 0, 0, 0, S[n..n+7] * G[3]}
*d0 += Sk8h{_____, _____, _____, _____, _____, _____, v3[0], v3[1]};
*d8 += Sk8h{v3[2], v3[3], v3[4], v3[5], v3[6], v3[7], _____, _____};
}
static SK_ALWAYS_INLINE void blur_x_radius_4(
const Sk8h& s0,
const Sk8h& gauss0,
const Sk8h& gauss1,
const Sk8h& gauss2,
const Sk8h& gauss3,
const Sk8h& gauss4,
Sk8h* d0, Sk8h* d8) {
auto v0 = s0.mulHi(gauss0);
auto v1 = s0.mulHi(gauss1);
auto v2 = s0.mulHi(gauss2);
auto v3 = s0.mulHi(gauss3);
auto v4 = s0.mulHi(gauss4);
// D[n..n+7] += S[n..n+7] * G[4]
*d0 += v4;
// D[n..n+8] += {0, S[n..n+7] * G[3]}
*d0 += Sk8h{_____, v3[0], v3[1], v3[2], v3[3], v3[4], v3[5], v3[6]};
*d8 += Sk8h{v3[7], _____, _____, _____, _____, _____, _____, _____};
// D[n..n+9] += {0, 0, S[n..n+7] * G[2]}
*d0 += Sk8h{_____, _____, v2[0], v2[1], v2[2], v2[3], v2[4], v2[5]};
*d8 += Sk8h{v2[6], v2[7], _____, _____, _____, _____, _____, _____};
// D[n..n+10] += {0, 0, 0, S[n..n+7] * G[1]}
*d0 += Sk8h{_____, _____, _____, v1[0], v1[1], v1[2], v1[3], v1[4]};
*d8 += Sk8h{v1[5], v1[6], v1[7], _____, _____, _____, _____, _____};
// D[n..n+11] += {0, 0, 0, 0, S[n..n+7] * G[0]}
*d0 += Sk8h{_____, _____, _____, _____, v0[0], v0[1], v0[2], v0[3]};
*d8 += Sk8h{v0[4], v0[5], v0[6], v0[7], _____, _____, _____, _____};
// D[n..n+12] += {0, 0, 0, 0, 0, S[n..n+7] * G[1]}
*d0 += Sk8h{_____, _____, _____, _____, _____, v1[0], v1[1], v1[2]};
*d8 += Sk8h{v1[3], v1[4], v1[5], v1[6], v1[7], _____, _____, _____};
// D[n..n+13] += {0, 0, 0, 0, 0, 0, S[n..n+7] * G[2]}
*d0 += Sk8h{_____, _____, _____, _____, _____, _____, v2[0], v2[1]};
*d8 += Sk8h{v2[2], v2[3], v2[4], v2[5], v2[6], v2[7], _____, _____};
// D[n..n+14] += {0, 0, 0, 0, 0, 0, 0, S[n..n+7] * G[3]}
*d0 += Sk8h{_____, _____, _____, _____, _____, _____, _____, v3[0]};
*d8 += Sk8h{v3[1], v3[2], v3[3], v3[4], v3[5], v3[6], v3[7], _____};
// D[n..n+15] += {0, 0, 0, 0, 0, 0, 0, 0, S[n..n+7] * G[4]}
*d8 += v4;
}
using BlurX = decltype(blur_x_radius_1);
// BlurX will only be one of the functions blur_x_radius_(1|2|3|4).
static SK_ALWAYS_INLINE void blur_row(
BlurX blur,
const Sk8h& g0, const Sk8h& g1, const Sk8h& g2, const Sk8h& g3, const Sk8h& g4,
const uint8_t* src, int srcW,
uint8_t* dst, int dstW) {
// Clear the buffer to handle summing wider than source.
Sk8h d0{kHalf}, d8{kHalf};
// Go by multiples of 8 in src.
int x = 0;
for (; x <= srcW - 8; x += 8) {
blur(load(src, 8), g0, g1, g2, g3, g4, &d0, &d8);
store(dst, d0, 8);
d0 = d8;
d8 = Sk8h{kHalf};
src += 8;
dst += 8;
}
// There are src values left, but the remainder of src values is not a multiple of 8.
int srcTail = srcW - x;
if (srcTail > 0) {
blur(load(src, srcTail), g0, g1, g2, g3, g4, &d0, &d8);
int dstTail = std::min(8, dstW - x);
store(dst, d0, dstTail);
d0 = d8;
dst += dstTail;
x += dstTail;
}
// There are dst mask values to complete.
int dstTail = dstW - x;
if (dstTail > 0) {
store(dst, d0, dstTail);
}
}
// BlurX will only be one of the functions blur_x_radius_(1|2|3|4).
static SK_ALWAYS_INLINE void blur_x_rect(
BlurX blur,
uint16_t* gauss,
const uint8_t* src, size_t srcStride, int srcW,
uint8_t* dst, size_t dstStride, int dstW, int dstH) {
Sk8h g0{gauss[0]},
g1{gauss[1]},
g2{gauss[2]},
g3{gauss[3]},
g4{gauss[4]};
// Blur *ALL* the rows.
for (int y = 0; y < dstH; y++) {
blur_row(blur, g0, g1, g2, g3, g4, src, srcW, dst, dstW);
src += srcStride;
dst += dstStride;
}
}
SK_ATTRIBUTE(noinline) static void direct_blur_x(
int radius, uint16_t* gauss,
const uint8_t* src, size_t srcStride, int srcW,
uint8_t* dst, size_t dstStride, int dstW, int dstH) {
switch (radius) {
case 1:
blur_x_rect(blur_x_radius_1, gauss, src, srcStride, srcW, dst, dstStride, dstW, dstH);
break;
case 2:
blur_x_rect(blur_x_radius_2, gauss, src, srcStride, srcW, dst, dstStride, dstW, dstH);
break;
case 3:
blur_x_rect(blur_x_radius_3, gauss, src, srcStride, srcW, dst, dstStride, dstW, dstH);
break;
case 4:
blur_x_rect(blur_x_radius_4, gauss, src, srcStride, srcW, dst, dstStride, dstW, dstH);
break;
default:
SkASSERTF(false, "The radius %d is not handled\n", radius);
}
}
// The operations of the blur_y_radius_N functions work on a theme similar to the blur_x_radius_N
// functions, but end up being simpler because there is no complicated shift of registers. We
// start with the non-traditional form of the gaussian filter. In the following r is the value
// when added generates the next value in the column.
//
// D[n+0r] = S[n+0r]*G[1]
// + S[n+1r]*G[0]
// + S[n+2r]*G[1]
//
// Expanding out in a way similar to blur_x_radius_N for specific values of n.
//
// D[n+0r] = S[n-2r]*G[1] + S[n-1r]*G[0] + S[n+0r]*G[1]
// D[n+1r] = S[n-1r]*G[1] + S[n+0r]*G[0] + S[n+1r]*G[1]
// D[n+2r] = S[n+0r]*G[1] + S[n+1r]*G[0] + S[n+2r]*G[1]
//
// We can see that S[n+0r] is in all three D[] equations, but is only multiplied twice. Now we
// can look at the calculation form the point of view of a source value.
//
// Given S[n+0r]:
// D[n+0r] += S[n+0r]*G[1];
// /* D[n+0r] is done and can be stored now. */
// D[n+1r] += S[n+0r]*G[0];
// D[n+2r] = S[n+0r]*G[1];
//
// Remember, by induction, that D[n+0r] == S[n-2r]*G[1] + S[n-1r]*G[0] before adding in
// S[n+0r]*G[1]. So, after the addition D[n+0r] has finished calculation and can be stored. Also,
// notice that D[n+2r] is receiving its first value from S[n+0r]*G[1] and is not added in. Notice
// how values flow in the following two iterations in source.
//
// D[n+0r] += S[n+0r]*G[1]
// D[n+1r] += S[n+0r]*G[0]
// D[n+2r] = S[n+0r]*G[1]
// /* ------- */
// D[n+1r] += S[n+1r]*G[1]
// D[n+2r] += S[n+1r]*G[0]
// D[n+3r] = S[n+1r]*G[1]
//
// Instead of using memory we can introduce temporaries d01 and d12. The update step changes
// to the following.
//
// answer = d01 + S[n+0r]*G[1]
// d01 = d12 + S[n+0r]*G[0]
// d12 = S[n+0r]*G[1]
// return answer
//
// Finally, this can be ganged into SIMD style.
// answer[0..7] = d01[0..7] + S[n+0r..n+0r+7]*G[1]
// d01[0..7] = d12[0..7] + S[n+0r..n+0r+7]*G[0]
// d12[0..7] = S[n+0r..n+0r+7]*G[1]
// return answer[0..7]
static SK_ALWAYS_INLINE Sk8h blur_y_radius_1(
const Sk8h& s0,
const Sk8h& g0, const Sk8h& g1, const Sk8h&, const Sk8h&, const Sk8h&,
Sk8h* d01, Sk8h* d12, Sk8h*, Sk8h*, Sk8h*, Sk8h*, Sk8h*, Sk8h*) {
auto v0 = s0.mulHi(g0);
auto v1 = s0.mulHi(g1);
Sk8h answer = *d01 + v1;
*d01 = *d12 + v0;
*d12 = v1 + kHalf;
return answer;
}
static SK_ALWAYS_INLINE Sk8h blur_y_radius_2(
const Sk8h& s0,
const Sk8h& g0, const Sk8h& g1, const Sk8h& g2, const Sk8h&, const Sk8h&,
Sk8h* d01, Sk8h* d12, Sk8h* d23, Sk8h* d34, Sk8h*, Sk8h*, Sk8h*, Sk8h*) {
auto v0 = s0.mulHi(g0);
auto v1 = s0.mulHi(g1);
auto v2 = s0.mulHi(g2);
Sk8h answer = *d01 + v2;
*d01 = *d12 + v1;
*d12 = *d23 + v0;
*d23 = *d34 + v1;
*d34 = v2 + kHalf;
return answer;
}
static SK_ALWAYS_INLINE Sk8h blur_y_radius_3(
const Sk8h& s0,
const Sk8h& g0, const Sk8h& g1, const Sk8h& g2, const Sk8h& g3, const Sk8h&,
Sk8h* d01, Sk8h* d12, Sk8h* d23, Sk8h* d34, Sk8h* d45, Sk8h* d56, Sk8h*, Sk8h*) {
auto v0 = s0.mulHi(g0);
auto v1 = s0.mulHi(g1);
auto v2 = s0.mulHi(g2);
auto v3 = s0.mulHi(g3);
Sk8h answer = *d01 + v3;
*d01 = *d12 + v2;
*d12 = *d23 + v1;
*d23 = *d34 + v0;
*d34 = *d45 + v1;
*d45 = *d56 + v2;
*d56 = v3 + kHalf;
return answer;
}
static SK_ALWAYS_INLINE Sk8h blur_y_radius_4(
const Sk8h& s0,
const Sk8h& g0, const Sk8h& g1, const Sk8h& g2, const Sk8h& g3, const Sk8h& g4,
Sk8h* d01, Sk8h* d12, Sk8h* d23, Sk8h* d34, Sk8h* d45, Sk8h* d56, Sk8h* d67, Sk8h* d78) {
auto v0 = s0.mulHi(g0);
auto v1 = s0.mulHi(g1);
auto v2 = s0.mulHi(g2);
auto v3 = s0.mulHi(g3);
auto v4 = s0.mulHi(g4);
Sk8h answer = *d01 + v4;
*d01 = *d12 + v3;
*d12 = *d23 + v2;
*d23 = *d34 + v1;
*d34 = *d45 + v0;
*d45 = *d56 + v1;
*d56 = *d67 + v2;
*d67 = *d78 + v3;
*d78 = v4 + kHalf;
return answer;
}
using BlurY = decltype(blur_y_radius_1);
// BlurY will be one of blur_y_radius_(1|2|3|4).
static SK_ALWAYS_INLINE void blur_column(
BlurY blur, int radius, int width,
const Sk8h& g0, const Sk8h& g1, const Sk8h& g2, const Sk8h& g3, const Sk8h& g4,
const uint8_t* src, size_t srcStride, int srcH,
uint8_t* dst, size_t dstStride) {
Sk8h d01{kHalf}, d12{kHalf}, d23{kHalf}, d34{kHalf},
d45{kHalf}, d56{kHalf}, d67{kHalf}, d78{kHalf};
auto flush = [&](uint8_t* to, const Sk8h& v0, const Sk8h& v1) {
store(to, v0, width);
to += dstStride;
store(to, v1, width);
return to + dstStride;
};
for (int y = 0; y < srcH; y += 1) {
auto s = load(src, width);
auto b = blur(s,
g0, g1, g2, g3, g4,
&d01, &d12, &d23, &d34, &d45, &d56, &d67, &d78);
store(dst, b, width);
src += srcStride;
dst += dstStride;
}
if (radius >= 1) {
dst = flush(dst, d01, d12);
}
if (radius >= 2) {
dst = flush(dst, d23, d34);
}
if (radius >= 3) {
dst = flush(dst, d45, d56);
}
if (radius >= 4) {
flush(dst, d67, d78);
}
}
// BlurY will be one of blur_y_radius_(1|2|3|4).
static SK_ALWAYS_INLINE void blur_y_rect(
BlurY blur, int radius, uint16_t *gauss,
const uint8_t *src, size_t srcStride, int srcW, int srcH,
uint8_t *dst, size_t dstStride) {
Sk8h g0{gauss[0]},
g1{gauss[1]},
g2{gauss[2]},
g3{gauss[3]},
g4{gauss[4]};
int x = 0;
for (; x <= srcW - 8; x += 8) {
blur_column(blur, radius, 8,
g0, g1, g2, g3, g4,
src, srcStride, srcH,
dst, dstStride);
src += 8;
dst += 8;
}
int xTail = srcW - x;
if (xTail > 0) {
blur_column(blur, radius, xTail,
g0, g1, g2, g3, g4,
src, srcStride, srcH,
dst, dstStride);
}
}
SK_ATTRIBUTE(noinline) static void direct_blur_y(
int radius, uint16_t* gauss,
const uint8_t* src, size_t srcStride, int srcW, int srcH,
uint8_t* dst, size_t dstStride) {
switch (radius) {
case 1:
blur_y_rect(blur_y_radius_1, 1, gauss,
src, srcStride, srcW, srcH,
dst, dstStride);
break;
case 2:
blur_y_rect(blur_y_radius_2, 2, gauss,
src, srcStride, srcW, srcH,
dst, dstStride);
break;
case 3:
blur_y_rect(blur_y_radius_3, 3, gauss,
src, srcStride, srcW, srcH,
dst, dstStride);
break;
case 4:
blur_y_rect(blur_y_radius_4, 4, gauss,
src, srcStride, srcW, srcH,
dst, dstStride);
break;
default:
SkASSERTF(false, "The radius %d is not handled\n", radius);
}
}
static SkIPoint small_blur(double sigmaX, double sigmaY, const SkMask& src, SkMask* dst) {
SkASSERT(0 <= sigmaX && sigmaX < 2);
SkASSERT(0 <= sigmaY && sigmaY < 2);
SkGaussFilter filterX{sigmaX, SkGaussFilter::Type::Bessel},
filterY{sigmaY, SkGaussFilter::Type::Bessel};
int radiusX = filterX.radius(),
radiusY = filterY.radius();
SkASSERT(radiusX <= 4 && radiusY <= 4);
auto prepareGauss = [](const SkGaussFilter& filter, uint16_t* factors) {
int i = 0;
for (double d : filter) {
factors[i++] = static_cast<uint16_t>(round(d * (1 << 16)));
}
};
uint16_t gaussFactorsX[5],
gaussFactorsY[5];
prepareGauss(filterX, gaussFactorsX);
prepareGauss(filterY, gaussFactorsY);
*dst = prepare_destination(radiusX, radiusY, src);
if (src.fImage == nullptr) {
return {SkTo<int32_t>(radiusX), SkTo<int32_t>(radiusY)};
}
if (dst->fImage == nullptr) {
dst->fBounds.setEmpty();
return {0, 0};
}
int srcW = src.fBounds.width(),
srcH = src.fBounds.height();
int dstW = dst->fBounds.width(),
dstH = dst->fBounds.height();
size_t srcStride = src.fRowBytes,
dstStride = dst->fRowBytes;
//TODO: handle bluring in only one direction.
// Blur vertically and copy to destination.
direct_blur_y(radiusY, gaussFactorsY,
src.fImage, srcStride, srcW, srcH,
dst->fImage + radiusX, dstStride);
// Blur horizontally in place.
direct_blur_x(radiusX, gaussFactorsX,
dst->fImage + radiusX, dstStride, srcW,
dst->fImage, dstStride, dstW, dstH);
return {radiusX, radiusY};
}
#endif // SK_USE_LEGACY_INTERP_BLUR
SkIPoint SkMaskBlurFilter::blur(const SkMask& src, SkMask* dst) const {
#if !defined(SK_USE_LEGACY_INTERP_BLUR)
if (fSigmaW < 2.0 && fSigmaH < 2.0) {
return small_blur(fSigmaW, fSigmaH, src, dst);
}
#endif
// 1024 is a place holder guess until more analysis can be done.
SkSTArenaAlloc<1024> alloc;
@ -1260,6 +623,7 @@ SkIPoint SkMaskBlurFilter::blur(const SkMask& src, SkMask* dst) const {
tmpStart, tmpW, tmpStart + tmpW * tmpH);
}
// Blur vertically (scan in memory order because of the transposition),
// and transpose back to the original orientation.
auto scanH = planH->makeBlurScan(&alloc, tmpW, buffer);
@ -1314,3 +678,5 @@ SkIPoint SkMaskBlurFilter::blur(const SkMask& src, SkMask* dst) const {
return {SkTo<int32_t>(borderW), SkTo<int32_t>(borderH)};
}