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// Copyright (c) 2011 The Chromium Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include "SkConvolver.h"
#include "SkTArray.h"
namespace {
// Converts the argument to an 8-bit unsigned value by clamping to the range
// 0-255.
inline unsigned char ClampTo8(int a) {
if (static_cast<unsigned>(a) < 256) {
return a; // Avoid the extra check in the common case.
}
if (a < 0) {
return 0;
}
return 255;
}
// Stores a list of rows in a circular buffer. The usage is you write into it
// by calling AdvanceRow. It will keep track of which row in the buffer it
// should use next, and the total number of rows added.
class CircularRowBuffer {
public:
// The number of pixels in each row is given in |sourceRowPixelWidth|.
// The maximum number of rows needed in the buffer is |maxYFilterSize|
// (we only need to store enough rows for the biggest filter).
//
// We use the |firstInputRow| to compute the coordinates of all of the
// following rows returned by Advance().
CircularRowBuffer(int destRowPixelWidth, int maxYFilterSize,
int firstInputRow)
: fRowByteWidth(destRowPixelWidth * 4),
fNumRows(maxYFilterSize),
fNextRow(0),
fNextRowCoordinate(firstInputRow) {
fBuffer.reset(fRowByteWidth * maxYFilterSize);
fRowAddresses.reset(fNumRows);
}
// Moves to the next row in the buffer, returning a pointer to the beginning
// of it.
unsigned char* advanceRow() {
unsigned char* row = &fBuffer[fNextRow * fRowByteWidth];
fNextRowCoordinate++;
// Set the pointer to the next row to use, wrapping around if necessary.
fNextRow++;
if (fNextRow == fNumRows) {
fNextRow = 0;
}
return row;
}
// Returns a pointer to an "unrolled" array of rows. These rows will start
// at the y coordinate placed into |*firstRowIndex| and will continue in
// order for the maximum number of rows in this circular buffer.
//
// The |firstRowIndex_| may be negative. This means the circular buffer
// starts before the top of the image (it hasn't been filled yet).
unsigned char* const* GetRowAddresses(int* firstRowIndex) {
// Example for a 4-element circular buffer holding coords 6-9.
// Row 0 Coord 8
// Row 1 Coord 9
// Row 2 Coord 6 <- fNextRow = 2, fNextRowCoordinate = 10.
// Row 3 Coord 7
//
// The "next" row is also the first (lowest) coordinate. This computation
// may yield a negative value, but that's OK, the math will work out
// since the user of this buffer will compute the offset relative
// to the firstRowIndex and the negative rows will never be used.
*firstRowIndex = fNextRowCoordinate - fNumRows;
int curRow = fNextRow;
for (int i = 0; i < fNumRows; i++) {
fRowAddresses[i] = &fBuffer[curRow * fRowByteWidth];
// Advance to the next row, wrapping if necessary.
curRow++;
if (curRow == fNumRows) {
curRow = 0;
}
}
return &fRowAddresses[0];
}
private:
// The buffer storing the rows. They are packed, each one fRowByteWidth.
SkTArray<unsigned char> fBuffer;
// Number of bytes per row in the |buffer|.
int fRowByteWidth;
// The number of rows available in the buffer.
int fNumRows;
// The next row index we should write into. This wraps around as the
// circular buffer is used.
int fNextRow;
// The y coordinate of the |fNextRow|. This is incremented each time a
// new row is appended and does not wrap.
int fNextRowCoordinate;
// Buffer used by GetRowAddresses().
SkTArray<unsigned char*> fRowAddresses;
};
// Convolves horizontally along a single row. The row data is given in
// |srcData| and continues for the numValues() of the filter.
template<bool hasAlpha>
void ConvolveHorizontally(const unsigned char* srcData,
const SkConvolutionFilter1D& filter,
unsigned char* outRow) {
// Loop over each pixel on this row in the output image.
int numValues = filter.numValues();
for (int outX = 0; outX < numValues; outX++) {
// Get the filter that determines the current output pixel.
int filterOffset, filterLength;
const SkConvolutionFilter1D::ConvolutionFixed* filterValues =
filter.FilterForValue(outX, &filterOffset, &filterLength);
// Compute the first pixel in this row that the filter affects. It will
// touch |filterLength| pixels (4 bytes each) after this.
const unsigned char* rowToFilter = &srcData[filterOffset * 4];
// Apply the filter to the row to get the destination pixel in |accum|.
int accum[4] = {0};
for (int filterX = 0; filterX < filterLength; filterX++) {
SkConvolutionFilter1D::ConvolutionFixed curFilter = filterValues[filterX];
accum[0] += curFilter * rowToFilter[filterX * 4 + 0];
accum[1] += curFilter * rowToFilter[filterX * 4 + 1];
accum[2] += curFilter * rowToFilter[filterX * 4 + 2];
if (hasAlpha) {
accum[3] += curFilter * rowToFilter[filterX * 4 + 3];
}
}
// Bring this value back in range. All of the filter scaling factors
// are in fixed point with kShiftBits bits of fractional part.
accum[0] >>= SkConvolutionFilter1D::kShiftBits;
accum[1] >>= SkConvolutionFilter1D::kShiftBits;
accum[2] >>= SkConvolutionFilter1D::kShiftBits;
if (hasAlpha) {
accum[3] >>= SkConvolutionFilter1D::kShiftBits;
}
// Store the new pixel.
outRow[outX * 4 + 0] = ClampTo8(accum[0]);
outRow[outX * 4 + 1] = ClampTo8(accum[1]);
outRow[outX * 4 + 2] = ClampTo8(accum[2]);
if (hasAlpha) {
outRow[outX * 4 + 3] = ClampTo8(accum[3]);
}
}
}
// There's a bug somewhere here with GCC autovectorization (-ftree-vectorize). We originally
// thought this was 32 bit only, but subsequent tests show that some 64 bit gcc compiles
// suffer here too.
//
// Dropping to -O2 disables -ftree-vectorize. GCC 4.6 needs noinline. https://bug.skia.org/2575
#if SK_HAS_ATTRIBUTE(optimize) && defined(SK_RELEASE)
#define SK_MAYBE_DISABLE_VECTORIZATION __attribute__((optimize("O2"), noinline))
#else
#define SK_MAYBE_DISABLE_VECTORIZATION
#endif
SK_MAYBE_DISABLE_VECTORIZATION
static void ConvolveHorizontallyAlpha(const unsigned char* srcData,
const SkConvolutionFilter1D& filter,
unsigned char* outRow) {
return ConvolveHorizontally<true>(srcData, filter, outRow);
}
SK_MAYBE_DISABLE_VECTORIZATION
static void ConvolveHorizontallyNoAlpha(const unsigned char* srcData,
const SkConvolutionFilter1D& filter,
unsigned char* outRow) {
return ConvolveHorizontally<false>(srcData, filter, outRow);
}
#undef SK_MAYBE_DISABLE_VECTORIZATION
// Does vertical convolution to produce one output row. The filter values and
// length are given in the first two parameters. These are applied to each
// of the rows pointed to in the |sourceDataRows| array, with each row
// being |pixelWidth| wide.
//
// The output must have room for |pixelWidth * 4| bytes.
template<bool hasAlpha>
void ConvolveVertically(const SkConvolutionFilter1D::ConvolutionFixed* filterValues,
int filterLength,
unsigned char* const* sourceDataRows,
int pixelWidth,
unsigned char* outRow) {
// We go through each column in the output and do a vertical convolution,
// generating one output pixel each time.
for (int outX = 0; outX < pixelWidth; outX++) {
// Compute the number of bytes over in each row that the current column
// we're convolving starts at. The pixel will cover the next 4 bytes.
int byteOffset = outX * 4;
// Apply the filter to one column of pixels.
int accum[4] = {0};
for (int filterY = 0; filterY < filterLength; filterY++) {
SkConvolutionFilter1D::ConvolutionFixed curFilter = filterValues[filterY];
accum[0] += curFilter * sourceDataRows[filterY][byteOffset + 0];
accum[1] += curFilter * sourceDataRows[filterY][byteOffset + 1];
accum[2] += curFilter * sourceDataRows[filterY][byteOffset + 2];
if (hasAlpha) {
accum[3] += curFilter * sourceDataRows[filterY][byteOffset + 3];
}
}
// Bring this value back in range. All of the filter scaling factors
// are in fixed point with kShiftBits bits of precision.
accum[0] >>= SkConvolutionFilter1D::kShiftBits;
accum[1] >>= SkConvolutionFilter1D::kShiftBits;
accum[2] >>= SkConvolutionFilter1D::kShiftBits;
if (hasAlpha) {
accum[3] >>= SkConvolutionFilter1D::kShiftBits;
}
// Store the new pixel.
outRow[byteOffset + 0] = ClampTo8(accum[0]);
outRow[byteOffset + 1] = ClampTo8(accum[1]);
outRow[byteOffset + 2] = ClampTo8(accum[2]);
if (hasAlpha) {
unsigned char alpha = ClampTo8(accum[3]);
// Make sure the alpha channel doesn't come out smaller than any of the
// color channels. We use premultipled alpha channels, so this should
// never happen, but rounding errors will cause this from time to time.
// These "impossible" colors will cause overflows (and hence random pixel
// values) when the resulting bitmap is drawn to the screen.
//
// We only need to do this when generating the final output row (here).
int maxColorChannel = SkTMax(outRow[byteOffset + 0],
SkTMax(outRow[byteOffset + 1],
outRow[byteOffset + 2]));
if (alpha < maxColorChannel) {
outRow[byteOffset + 3] = maxColorChannel;
} else {
outRow[byteOffset + 3] = alpha;
}
} else {
// No alpha channel, the image is opaque.
outRow[byteOffset + 3] = 0xff;
}
}
}
void ConvolveVertically(const SkConvolutionFilter1D::ConvolutionFixed* filterValues,
int filterLength,
unsigned char* const* sourceDataRows,
int pixelWidth,
unsigned char* outRow,
bool sourceHasAlpha) {
if (sourceHasAlpha) {
ConvolveVertically<true>(filterValues, filterLength,
sourceDataRows, pixelWidth,
outRow);
} else {
ConvolveVertically<false>(filterValues, filterLength,
sourceDataRows, pixelWidth,
outRow);
}
}
} // namespace
// SkConvolutionFilter1D ---------------------------------------------------------
SkConvolutionFilter1D::SkConvolutionFilter1D()
: fMaxFilter(0) {
}
SkConvolutionFilter1D::~SkConvolutionFilter1D() {
}
void SkConvolutionFilter1D::AddFilter(int filterOffset,
const ConvolutionFixed* filterValues,
int filterLength) {
// It is common for leading/trailing filter values to be zeros. In such
// cases it is beneficial to only store the central factors.
// For a scaling to 1/4th in each dimension using a Lanczos-2 filter on
// a 1080p image this optimization gives a ~10% speed improvement.
int filterSize = filterLength;
int firstNonZero = 0;
while (firstNonZero < filterLength && filterValues[firstNonZero] == 0) {
firstNonZero++;
}
if (firstNonZero < filterLength) {
// Here we have at least one non-zero factor.
int lastNonZero = filterLength - 1;
while (lastNonZero >= 0 && filterValues[lastNonZero] == 0) {
lastNonZero--;
}
filterOffset += firstNonZero;
filterLength = lastNonZero + 1 - firstNonZero;
SkASSERT(filterLength > 0);
fFilterValues.append(filterLength, &filterValues[firstNonZero]);
} else {
// Here all the factors were zeroes.
filterLength = 0;
}
FilterInstance instance;
// We pushed filterLength elements onto fFilterValues
instance.fDataLocation = (static_cast<int>(fFilterValues.count()) -
filterLength);
instance.fOffset = filterOffset;
instance.fTrimmedLength = filterLength;
instance.fLength = filterSize;
fFilters.push(instance);
fMaxFilter = SkTMax(fMaxFilter, filterLength);
}
const SkConvolutionFilter1D::ConvolutionFixed* SkConvolutionFilter1D::GetSingleFilter(
int* specifiedFilterlength,
int* filterOffset,
int* filterLength) const {
const FilterInstance& filter = fFilters[0];
*filterOffset = filter.fOffset;
*filterLength = filter.fTrimmedLength;
*specifiedFilterlength = filter.fLength;
if (filter.fTrimmedLength == 0) {
return nullptr;
}
return &fFilterValues[filter.fDataLocation];
}
bool BGRAConvolve2D(const unsigned char* sourceData,
int sourceByteRowStride,
bool sourceHasAlpha,
const SkConvolutionFilter1D& filterX,
const SkConvolutionFilter1D& filterY,
int outputByteRowStride,
unsigned char* output,
const SkConvolutionProcs& convolveProcs,
bool useSimdIfPossible) {
int maxYFilterSize = filterY.maxFilter();
// The next row in the input that we will generate a horizontally
// convolved row for. If the filter doesn't start at the beginning of the
// image (this is the case when we are only resizing a subset), then we
// don't want to generate any output rows before that. Compute the starting
// row for convolution as the first pixel for the first vertical filter.
int filterOffset, filterLength;
const SkConvolutionFilter1D::ConvolutionFixed* filterValues =
filterY.FilterForValue(0, &filterOffset, &filterLength);
int nextXRow = filterOffset;
// We loop over each row in the input doing a horizontal convolution. This
// will result in a horizontally convolved image. We write the results into
// a circular buffer of convolved rows and do vertical convolution as rows
// are available. This prevents us from having to store the entire
// intermediate image and helps cache coherency.
// We will need four extra rows to allow horizontal convolution could be done
// simultaneously. We also pad each row in row buffer to be aligned-up to
// 16 bytes.
// TODO(jiesun): We do not use aligned load from row buffer in vertical
// convolution pass yet. Somehow Windows does not like it.
int rowBufferWidth = (filterX.numValues() + 15) & ~0xF;
int rowBufferHeight = maxYFilterSize +
(convolveProcs.fConvolve4RowsHorizontally ? 4 : 0);
// check for too-big allocation requests : crbug.com/528628
{
int64_t size = sk_64_mul(rowBufferWidth, rowBufferHeight);
// need some limit, to avoid over-committing success from malloc, but then
// crashing when we try to actually use the memory.
// 100meg seems big enough to allow "normal" zoom factors and image sizes through
// while avoiding the crash seen by the bug (crbug.com/528628)
if (size > 100 * 1024 * 1024) {
// SkDebugf("BGRAConvolve2D: tmp allocation [%lld] too big\n", size);
return false;
}
}
CircularRowBuffer rowBuffer(rowBufferWidth,
rowBufferHeight,
filterOffset);
// Loop over every possible output row, processing just enough horizontal
// convolutions to run each subsequent vertical convolution.
SkASSERT(outputByteRowStride >= filterX.numValues() * 4);
int numOutputRows = filterY.numValues();
// We need to check which is the last line to convolve before we advance 4
// lines in one iteration.
int lastFilterOffset, lastFilterLength;
// SSE2 can access up to 3 extra pixels past the end of the
// buffer. At the bottom of the image, we have to be careful
// not to access data past the end of the buffer. Normally
// we fall back to the C++ implementation for the last row.
// If the last row is less than 3 pixels wide, we may have to fall
// back to the C++ version for more rows. Compute how many
// rows we need to avoid the SSE implementation for here.
filterX.FilterForValue(filterX.numValues() - 1, &lastFilterOffset,
&lastFilterLength);
int avoidSimdRows = 1 + convolveProcs.fExtraHorizontalReads /
(lastFilterOffset + lastFilterLength);
filterY.FilterForValue(numOutputRows - 1, &lastFilterOffset,
&lastFilterLength);
for (int outY = 0; outY < numOutputRows; outY++) {
filterValues = filterY.FilterForValue(outY,
&filterOffset, &filterLength);
// Generate output rows until we have enough to run the current filter.
while (nextXRow < filterOffset + filterLength) {
if (convolveProcs.fConvolve4RowsHorizontally &&
nextXRow + 3 < lastFilterOffset + lastFilterLength -
avoidSimdRows) {
const unsigned char* src[4];
unsigned char* outRow[4];
for (int i = 0; i < 4; ++i) {
src[i] = &sourceData[(uint64_t)(nextXRow + i) * sourceByteRowStride];
outRow[i] = rowBuffer.advanceRow();
}
convolveProcs.fConvolve4RowsHorizontally(src, filterX, outRow, 4*rowBufferWidth);
nextXRow += 4;
} else {
// Check if we need to avoid SSE2 for this row.
if (convolveProcs.fConvolveHorizontally &&
nextXRow < lastFilterOffset + lastFilterLength -
avoidSimdRows) {
convolveProcs.fConvolveHorizontally(
&sourceData[(uint64_t)nextXRow * sourceByteRowStride],
filterX, rowBuffer.advanceRow(), sourceHasAlpha);
} else {
if (sourceHasAlpha) {
ConvolveHorizontallyAlpha(
&sourceData[(uint64_t)nextXRow * sourceByteRowStride],
filterX, rowBuffer.advanceRow());
} else {
ConvolveHorizontallyNoAlpha(
&sourceData[(uint64_t)nextXRow * sourceByteRowStride],
filterX, rowBuffer.advanceRow());
}
}
nextXRow++;
}
}
// Compute where in the output image this row of final data will go.
unsigned char* curOutputRow = &output[(uint64_t)outY * outputByteRowStride];
// Get the list of rows that the circular buffer has, in order.
int firstRowInCircularBuffer;
unsigned char* const* rowsToConvolve =
rowBuffer.GetRowAddresses(&firstRowInCircularBuffer);
// Now compute the start of the subset of those rows that the filter
// needs.
unsigned char* const* firstRowForFilter =
&rowsToConvolve[filterOffset - firstRowInCircularBuffer];
if (convolveProcs.fConvolveVertically) {
convolveProcs.fConvolveVertically(filterValues, filterLength,
firstRowForFilter,
filterX.numValues(), curOutputRow,
sourceHasAlpha);
} else {
ConvolveVertically(filterValues, filterLength,
firstRowForFilter,
filterX.numValues(), curOutputRow,
sourceHasAlpha);
}
}
return true;
}
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