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560 lines
22 KiB
C++
560 lines
22 KiB
C++
/* -*- Mode: C++; tab-width: 8; indent-tabs-mode: nil; c-basic-offset: 2 -*- */
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/* vim: set ts=8 sts=2 et sw=2 tw=80: */
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// Copyright (c) 2011-2016 Google Inc.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the gfx/skia/LICENSE file.
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#include "SkConvolver.h"
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#include "mozilla/Vector.h"
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#ifdef USE_SSE2
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# include "mozilla/SSE.h"
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#endif
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#ifdef USE_NEON
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# include "mozilla/arm.h"
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#endif
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namespace skia {
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// Converts the argument to an 8-bit unsigned value by clamping to the range
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// 0-255.
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static inline unsigned char ClampTo8(int a) {
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if (static_cast<unsigned>(a) < 256) {
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return a; // Avoid the extra check in the common case.
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}
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if (a < 0) {
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return 0;
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}
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return 255;
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}
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// Convolves horizontally along a single row. The row data is given in
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// |srcData| and continues for the numValues() of the filter.
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template <bool hasAlpha>
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void ConvolveHorizontally(const unsigned char* srcData,
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const SkConvolutionFilter1D& filter,
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unsigned char* outRow) {
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// Loop over each pixel on this row in the output image.
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int numValues = filter.numValues();
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for (int outX = 0; outX < numValues; outX++) {
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// Get the filter that determines the current output pixel.
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int filterOffset, filterLength;
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const SkConvolutionFilter1D::ConvolutionFixed* filterValues =
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filter.FilterForValue(outX, &filterOffset, &filterLength);
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// Compute the first pixel in this row that the filter affects. It will
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// touch |filterLength| pixels (4 bytes each) after this.
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const unsigned char* rowToFilter = &srcData[filterOffset * 4];
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// Apply the filter to the row to get the destination pixel in |accum|.
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int accum[4] = {0};
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for (int filterX = 0; filterX < filterLength; filterX++) {
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SkConvolutionFilter1D::ConvolutionFixed curFilter = filterValues[filterX];
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accum[0] += curFilter * rowToFilter[filterX * 4 + 0];
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accum[1] += curFilter * rowToFilter[filterX * 4 + 1];
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accum[2] += curFilter * rowToFilter[filterX * 4 + 2];
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if (hasAlpha) {
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accum[3] += curFilter * rowToFilter[filterX * 4 + 3];
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}
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}
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// Bring this value back in range. All of the filter scaling factors
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// are in fixed point with kShiftBits bits of fractional part.
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accum[0] >>= SkConvolutionFilter1D::kShiftBits;
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accum[1] >>= SkConvolutionFilter1D::kShiftBits;
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accum[2] >>= SkConvolutionFilter1D::kShiftBits;
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if (hasAlpha) {
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accum[3] >>= SkConvolutionFilter1D::kShiftBits;
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}
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// Store the new pixel.
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outRow[outX * 4 + 0] = ClampTo8(accum[0]);
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outRow[outX * 4 + 1] = ClampTo8(accum[1]);
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outRow[outX * 4 + 2] = ClampTo8(accum[2]);
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if (hasAlpha) {
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outRow[outX * 4 + 3] = ClampTo8(accum[3]);
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}
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}
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}
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// Does vertical convolution to produce one output row. The filter values and
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// length are given in the first two parameters. These are applied to each
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// of the rows pointed to in the |sourceDataRows| array, with each row
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// being |pixelWidth| wide.
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//
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// The output must have room for |pixelWidth * 4| bytes.
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template <bool hasAlpha>
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void ConvolveVertically(
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const SkConvolutionFilter1D::ConvolutionFixed* filterValues,
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int filterLength, unsigned char* const* sourceDataRows, int pixelWidth,
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unsigned char* outRow) {
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// We go through each column in the output and do a vertical convolution,
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// generating one output pixel each time.
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for (int outX = 0; outX < pixelWidth; outX++) {
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// Compute the number of bytes over in each row that the current column
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// we're convolving starts at. The pixel will cover the next 4 bytes.
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int byteOffset = outX * 4;
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// Apply the filter to one column of pixels.
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int accum[4] = {0};
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for (int filterY = 0; filterY < filterLength; filterY++) {
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SkConvolutionFilter1D::ConvolutionFixed curFilter = filterValues[filterY];
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accum[0] += curFilter * sourceDataRows[filterY][byteOffset + 0];
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accum[1] += curFilter * sourceDataRows[filterY][byteOffset + 1];
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accum[2] += curFilter * sourceDataRows[filterY][byteOffset + 2];
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if (hasAlpha) {
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accum[3] += curFilter * sourceDataRows[filterY][byteOffset + 3];
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}
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}
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// Bring this value back in range. All of the filter scaling factors
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// are in fixed point with kShiftBits bits of precision.
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accum[0] >>= SkConvolutionFilter1D::kShiftBits;
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accum[1] >>= SkConvolutionFilter1D::kShiftBits;
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accum[2] >>= SkConvolutionFilter1D::kShiftBits;
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if (hasAlpha) {
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accum[3] >>= SkConvolutionFilter1D::kShiftBits;
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}
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// Store the new pixel.
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outRow[byteOffset + 0] = ClampTo8(accum[0]);
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outRow[byteOffset + 1] = ClampTo8(accum[1]);
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outRow[byteOffset + 2] = ClampTo8(accum[2]);
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if (hasAlpha) {
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unsigned char alpha = ClampTo8(accum[3]);
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// Make sure the alpha channel doesn't come out smaller than any of the
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// color channels. We use premultipled alpha channels, so this should
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// never happen, but rounding errors will cause this from time to time.
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// These "impossible" colors will cause overflows (and hence random pixel
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// values) when the resulting bitmap is drawn to the screen.
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//
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// We only need to do this when generating the final output row (here).
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int maxColorChannel =
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std::max(outRow[byteOffset + 0],
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std::max(outRow[byteOffset + 1], outRow[byteOffset + 2]));
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if (alpha < maxColorChannel) {
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outRow[byteOffset + 3] = maxColorChannel;
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} else {
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outRow[byteOffset + 3] = alpha;
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}
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} else {
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// No alpha channel, the image is opaque.
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outRow[byteOffset + 3] = 0xff;
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}
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}
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}
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#ifdef USE_SSE2
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void convolve_vertically_avx2(const int16_t* filter, int filterLen,
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uint8_t* const* srcRows, int width, uint8_t* out,
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bool hasAlpha);
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void convolve_horizontally_sse2(const unsigned char* srcData,
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const SkConvolutionFilter1D& filter,
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unsigned char* outRow, bool hasAlpha);
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void convolve_vertically_sse2(const int16_t* filter, int filterLen,
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uint8_t* const* srcRows, int width, uint8_t* out,
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bool hasAlpha);
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#elif defined(USE_NEON)
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void convolve_horizontally_neon(const unsigned char* srcData,
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const SkConvolutionFilter1D& filter,
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unsigned char* outRow, bool hasAlpha);
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void convolve_vertically_neon(const int16_t* filter, int filterLen,
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uint8_t* const* srcRows, int width, uint8_t* out,
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bool hasAlpha);
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#endif
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void convolve_horizontally(const unsigned char* srcData,
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const SkConvolutionFilter1D& filter,
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unsigned char* outRow, bool hasAlpha) {
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#ifdef USE_SSE2
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if (mozilla::supports_sse2()) {
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convolve_horizontally_sse2(srcData, filter, outRow, hasAlpha);
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return;
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}
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#elif defined(USE_NEON)
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if (mozilla::supports_neon()) {
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convolve_horizontally_neon(srcData, filter, outRow, hasAlpha);
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return;
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}
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#endif
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if (hasAlpha) {
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ConvolveHorizontally<true>(srcData, filter, outRow);
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} else {
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ConvolveHorizontally<false>(srcData, filter, outRow);
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}
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}
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void convolve_vertically(
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const SkConvolutionFilter1D::ConvolutionFixed* filterValues,
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int filterLength, unsigned char* const* sourceDataRows, int pixelWidth,
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unsigned char* outRow, bool hasAlpha) {
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#ifdef USE_SSE2
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if (mozilla::supports_avx2()) {
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convolve_vertically_avx2(filterValues, filterLength, sourceDataRows,
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pixelWidth, outRow, hasAlpha);
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return;
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}
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if (mozilla::supports_sse2()) {
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convolve_vertically_sse2(filterValues, filterLength, sourceDataRows,
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pixelWidth, outRow, hasAlpha);
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return;
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}
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#elif defined(USE_NEON)
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if (mozilla::supports_neon()) {
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convolve_vertically_neon(filterValues, filterLength, sourceDataRows,
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pixelWidth, outRow, hasAlpha);
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return;
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}
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#endif
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if (hasAlpha) {
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ConvolveVertically<true>(filterValues, filterLength, sourceDataRows,
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pixelWidth, outRow);
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} else {
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ConvolveVertically<false>(filterValues, filterLength, sourceDataRows,
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pixelWidth, outRow);
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}
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}
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// Stores a list of rows in a circular buffer. The usage is you write into it
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// by calling AdvanceRow. It will keep track of which row in the buffer it
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// should use next, and the total number of rows added.
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class CircularRowBuffer {
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public:
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// The number of pixels in each row is given in |sourceRowPixelWidth|.
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// The maximum number of rows needed in the buffer is |maxYFilterSize|
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// (we only need to store enough rows for the biggest filter).
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//
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// We use the |firstInputRow| to compute the coordinates of all of the
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// following rows returned by Advance().
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CircularRowBuffer(int destRowPixelWidth, int maxYFilterSize,
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int firstInputRow)
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: fRowByteWidth(destRowPixelWidth * 4),
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fNumRows(maxYFilterSize),
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fNextRow(0),
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fNextRowCoordinate(firstInputRow) {
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fBuffer.resize(fRowByteWidth * maxYFilterSize);
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fRowAddresses.resize(fNumRows);
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}
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// Moves to the next row in the buffer, returning a pointer to the beginning
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// of it.
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unsigned char* advanceRow() {
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unsigned char* row = &fBuffer[fNextRow * fRowByteWidth];
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fNextRowCoordinate++;
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// Set the pointer to the next row to use, wrapping around if necessary.
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fNextRow++;
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if (fNextRow == fNumRows) {
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fNextRow = 0;
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}
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return row;
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}
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// Returns a pointer to an "unrolled" array of rows. These rows will start
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// at the y coordinate placed into |*firstRowIndex| and will continue in
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// order for the maximum number of rows in this circular buffer.
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//
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// The |firstRowIndex_| may be negative. This means the circular buffer
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// starts before the top of the image (it hasn't been filled yet).
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unsigned char* const* GetRowAddresses(int* firstRowIndex) {
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// Example for a 4-element circular buffer holding coords 6-9.
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// Row 0 Coord 8
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// Row 1 Coord 9
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// Row 2 Coord 6 <- fNextRow = 2, fNextRowCoordinate = 10.
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// Row 3 Coord 7
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//
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// The "next" row is also the first (lowest) coordinate. This computation
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// may yield a negative value, but that's OK, the math will work out
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// since the user of this buffer will compute the offset relative
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// to the firstRowIndex and the negative rows will never be used.
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*firstRowIndex = fNextRowCoordinate - fNumRows;
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int curRow = fNextRow;
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for (int i = 0; i < fNumRows; i++) {
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fRowAddresses[i] = &fBuffer[curRow * fRowByteWidth];
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// Advance to the next row, wrapping if necessary.
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curRow++;
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if (curRow == fNumRows) {
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curRow = 0;
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}
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}
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return &fRowAddresses[0];
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}
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private:
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// The buffer storing the rows. They are packed, each one fRowByteWidth.
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std::vector<unsigned char> fBuffer;
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// Number of bytes per row in the |buffer|.
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int fRowByteWidth;
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// The number of rows available in the buffer.
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int fNumRows;
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// The next row index we should write into. This wraps around as the
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// circular buffer is used.
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int fNextRow;
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// The y coordinate of the |fNextRow|. This is incremented each time a
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// new row is appended and does not wrap.
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int fNextRowCoordinate;
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// Buffer used by GetRowAddresses().
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std::vector<unsigned char*> fRowAddresses;
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};
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SkConvolutionFilter1D::SkConvolutionFilter1D() : fMaxFilter(0) {}
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SkConvolutionFilter1D::~SkConvolutionFilter1D() = default;
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void SkConvolutionFilter1D::AddFilter(int filterOffset,
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const ConvolutionFixed* filterValues,
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int filterLength) {
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// It is common for leading/trailing filter values to be zeros. In such
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// cases it is beneficial to only store the central factors.
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// For a scaling to 1/4th in each dimension using a Lanczos-2 filter on
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// a 1080p image this optimization gives a ~10% speed improvement.
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int filterSize = filterLength;
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int firstNonZero = 0;
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while (firstNonZero < filterLength && filterValues[firstNonZero] == 0) {
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firstNonZero++;
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}
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if (firstNonZero < filterLength) {
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// Here we have at least one non-zero factor.
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int lastNonZero = filterLength - 1;
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while (lastNonZero >= 0 && filterValues[lastNonZero] == 0) {
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lastNonZero--;
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}
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filterOffset += firstNonZero;
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filterLength = lastNonZero + 1 - firstNonZero;
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MOZ_ASSERT(filterLength > 0);
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fFilterValues.insert(fFilterValues.end(), &filterValues[firstNonZero],
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&filterValues[lastNonZero + 1]);
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} else {
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// Here all the factors were zeroes.
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filterLength = 0;
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}
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FilterInstance instance = {
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// We pushed filterLength elements onto fFilterValues
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int(fFilterValues.size()) - filterLength, filterOffset, filterLength,
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filterSize};
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fFilters.push_back(instance);
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fMaxFilter = std::max(fMaxFilter, filterLength);
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}
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bool SkConvolutionFilter1D::ComputeFilterValues(
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const SkBitmapFilter& aBitmapFilter, int32_t aSrcSize, int32_t aDstSize) {
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// When we're doing a magnification, the scale will be larger than one. This
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// means the destination pixels are much smaller than the source pixels, and
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// that the range covered by the filter won't necessarily cover any source
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// pixel boundaries. Therefore, we use these clamped values (max of 1) for
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// some computations.
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float scale = float(aDstSize) / float(aSrcSize);
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float clampedScale = std::min(1.0f, scale);
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// This is how many source pixels from the center we need to count
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// to support the filtering function.
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float srcSupport = aBitmapFilter.width() / clampedScale;
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float invScale = 1.0f / scale;
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mozilla::Vector<float, 64> filterValues;
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mozilla::Vector<ConvolutionFixed, 64> fixedFilterValues;
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// Loop over all pixels in the output range. We will generate one set of
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// filter values for each one. Those values will tell us how to blend the
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// source pixels to compute the destination pixel.
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// This value is computed based on how SkTDArray::resizeStorageToAtLeast works
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// in order to ensure that it does not overflow or assert. That functions
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// computes
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// n+4 + (n+4)/4
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// and we want to to fit in a 32 bit signed int. Equating that to 2^31-1 and
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// solving n gives n = (2^31-6)*4/5 = 1717986913.6
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const int32_t maxToPassToReserveAdditional = 1717986913;
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int32_t filterValueCount = int32_t(ceilf(aDstSize * srcSupport * 2));
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if (aDstSize > maxToPassToReserveAdditional || filterValueCount < 0 ||
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filterValueCount > maxToPassToReserveAdditional) {
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return false;
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}
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reserveAdditional(aDstSize, filterValueCount);
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for (int32_t destI = 0; destI < aDstSize; destI++) {
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// This is the pixel in the source directly under the pixel in the dest.
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// Note that we base computations on the "center" of the pixels. To see
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// why, observe that the destination pixel at coordinates (0, 0) in a 5.0x
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// downscale should "cover" the pixels around the pixel with *its center*
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// at coordinates (2.5, 2.5) in the source, not those around (0, 0).
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// Hence we need to scale coordinates (0.5, 0.5), not (0, 0).
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float srcPixel = (static_cast<float>(destI) + 0.5f) * invScale;
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// Compute the (inclusive) range of source pixels the filter covers.
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float srcBegin = std::max(0.0f, floorf(srcPixel - srcSupport));
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float srcEnd = std::min(aSrcSize - 1.0f, ceilf(srcPixel + srcSupport));
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// Compute the unnormalized filter value at each location of the source
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// it covers.
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// Sum of the filter values for normalizing.
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// Distance from the center of the filter, this is the filter coordinate
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// in source space. We also need to consider the center of the pixel
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// when comparing distance against 'srcPixel'. In the 5x downscale
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// example used above the distance from the center of the filter to
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// the pixel with coordinates (2, 2) should be 0, because its center
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// is at (2.5, 2.5).
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int32_t filterCount = int32_t(srcEnd - srcBegin) + 1;
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if (filterCount <= 0 || !filterValues.resize(filterCount) ||
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!fixedFilterValues.resize(filterCount)) {
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return false;
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}
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float destFilterDist = (srcBegin + 0.5f - srcPixel) * clampedScale;
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float filterSum = 0.0f;
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for (int32_t index = 0; index < filterCount; index++) {
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float filterValue = aBitmapFilter.evaluate(destFilterDist);
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filterValues[index] = filterValue;
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filterSum += filterValue;
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destFilterDist += clampedScale;
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}
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// The filter must be normalized so that we don't affect the brightness of
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// the image. Convert to normalized fixed point.
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ConvolutionFixed fixedSum = 0;
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float invFilterSum = 1.0f / filterSum;
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for (int32_t fixedI = 0; fixedI < filterCount; fixedI++) {
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ConvolutionFixed curFixed = ToFixed(filterValues[fixedI] * invFilterSum);
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fixedSum += curFixed;
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fixedFilterValues[fixedI] = curFixed;
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}
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// The conversion to fixed point will leave some rounding errors, which
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// we add back in to avoid affecting the brightness of the image. We
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// arbitrarily add this to the center of the filter array (this won't always
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// be the center of the filter function since it could get clipped on the
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// edges, but it doesn't matter enough to worry about that case).
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ConvolutionFixed leftovers = ToFixed(1) - fixedSum;
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fixedFilterValues[filterCount / 2] += leftovers;
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AddFilter(int32_t(srcBegin), fixedFilterValues.begin(), filterCount);
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}
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return maxFilter() > 0 && numValues() == aDstSize;
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}
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// Does a two-dimensional convolution on the given source image.
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//
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// It is assumed the source pixel offsets referenced in the input filters
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// reference only valid pixels, so the source image size is not required. Each
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// row of the source image starts |sourceByteRowStride| after the previous
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// one (this allows you to have rows with some padding at the end).
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//
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// The result will be put into the given output buffer. The destination image
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// size will be xfilter.numValues() * yfilter.numValues() pixels. It will be
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// in rows of exactly xfilter.numValues() * 4 bytes.
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//
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// |sourceHasAlpha| is a hint that allows us to avoid doing computations on
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// the alpha channel if the image is opaque. If you don't know, set this to
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// true and it will work properly, but setting this to false will be a few
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|
// percent faster if you know the image is opaque.
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|
//
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|
// The layout in memory is assumed to be 4-bytes per pixel in B-G-R-A order
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|
// (this is ARGB when loaded into 32-bit words on a little-endian machine).
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|
/**
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|
* Returns false if it was unable to perform the convolution/rescale. in which
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|
* case the output buffer is assumed to be undefined.
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|
*/
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|
bool BGRAConvolve2D(const unsigned char* sourceData, int sourceByteRowStride,
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|
bool sourceHasAlpha, const SkConvolutionFilter1D& filterX,
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const SkConvolutionFilter1D& filterY,
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|
int outputByteRowStride, unsigned char* output) {
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|
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 = 0, filterLength = 0;
|
|
const SkConvolutionFilter1D::ConvolutionFixed* filterValues =
|
|
filterY.FilterForValue(0, &filterOffset, &filterLength);
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|
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
|
|
// 32 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() + 31) & ~0x1F;
|
|
int rowBufferHeight = maxYFilterSize;
|
|
|
|
// check for too-big allocation requests : crbug.com/528628
|
|
{
|
|
int64_t size = int64_t(rowBufferWidth) * int64_t(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) {
|
|
// printf_stderr("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.
|
|
MOZ_ASSERT(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;
|
|
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) {
|
|
convolve_horizontally(
|
|
&sourceData[(uint64_t)nextXRow * sourceByteRowStride], filterX,
|
|
rowBuffer.advanceRow(), sourceHasAlpha);
|
|
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];
|
|
|
|
convolve_vertically(filterValues, filterLength, firstRowForFilter,
|
|
filterX.numValues(), curOutputRow, sourceHasAlpha);
|
|
}
|
|
return true;
|
|
}
|
|
|
|
} // namespace skia
|