| Index: skia/ext/image_operations.cc
|
| diff --git a/skia/ext/image_operations.cc b/skia/ext/image_operations.cc
|
| deleted file mode 100644
|
| index a14344d319ea0a098c7a03d57a54430a4c25595b..0000000000000000000000000000000000000000
|
| --- a/skia/ext/image_operations.cc
|
| +++ /dev/null
|
| @@ -1,413 +0,0 @@
|
| -// Copyright (c) 2012 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.
|
| -
|
| -#define _USE_MATH_DEFINES
|
| -#include <algorithm>
|
| -#include <cmath>
|
| -#include <limits>
|
| -
|
| -#include "skia/ext/image_operations.h"
|
| -
|
| -// TODO(pkasting): skia/ext should not depend on base/!
|
| -#include "base/containers/stack_container.h"
|
| -#include "base/logging.h"
|
| -#include "base/metrics/histogram.h"
|
| -#include "base/time/time.h"
|
| -#include "base/trace_event/trace_event.h"
|
| -#include "build/build_config.h"
|
| -#include "skia/ext/convolver.h"
|
| -#include "third_party/skia/include/core/SkColorPriv.h"
|
| -#include "third_party/skia/include/core/SkRect.h"
|
| -
|
| -namespace skia {
|
| -
|
| -namespace {
|
| -
|
| -// Returns the ceiling/floor as an integer.
|
| -inline int CeilInt(float val) {
|
| - return static_cast<int>(ceil(val));
|
| -}
|
| -inline int FloorInt(float val) {
|
| - return static_cast<int>(floor(val));
|
| -}
|
| -
|
| -// Filter function computation -------------------------------------------------
|
| -
|
| -// Evaluates the box filter, which goes from -0.5 to +0.5.
|
| -float EvalBox(float x) {
|
| - return (x >= -0.5f && x < 0.5f) ? 1.0f : 0.0f;
|
| -}
|
| -
|
| -// Evaluates the Lanczos filter of the given filter size window for the given
|
| -// position.
|
| -//
|
| -// |filter_size| is the width of the filter (the "window"), outside of which
|
| -// the value of the function is 0. Inside of the window, the value is the
|
| -// normalized sinc function:
|
| -// lanczos(x) = sinc(x) * sinc(x / filter_size);
|
| -// where
|
| -// sinc(x) = sin(pi*x) / (pi*x);
|
| -float EvalLanczos(int filter_size, float x) {
|
| - if (x <= -filter_size || x >= filter_size)
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| - return 0.0f; // Outside of the window.
|
| - if (x > -std::numeric_limits<float>::epsilon() &&
|
| - x < std::numeric_limits<float>::epsilon())
|
| - return 1.0f; // Special case the discontinuity at the origin.
|
| - float xpi = x * static_cast<float>(M_PI);
|
| - return (sin(xpi) / xpi) * // sinc(x)
|
| - sin(xpi / filter_size) / (xpi / filter_size); // sinc(x/filter_size)
|
| -}
|
| -
|
| -// Evaluates the Hamming filter of the given filter size window for the given
|
| -// position.
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| -//
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| -// The filter covers [-filter_size, +filter_size]. Outside of this window
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| -// the value of the function is 0. Inside of the window, the value is sinus
|
| -// cardinal multiplied by a recentered Hamming function. The traditional
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| -// Hamming formula for a window of size N and n ranging in [0, N-1] is:
|
| -// hamming(n) = 0.54 - 0.46 * cos(2 * pi * n / (N-1)))
|
| -// In our case we want the function centered for x == 0 and at its minimum
|
| -// on both ends of the window (x == +/- filter_size), hence the adjusted
|
| -// formula:
|
| -// hamming(x) = (0.54 -
|
| -// 0.46 * cos(2 * pi * (x - filter_size)/ (2 * filter_size)))
|
| -// = 0.54 - 0.46 * cos(pi * x / filter_size - pi)
|
| -// = 0.54 + 0.46 * cos(pi * x / filter_size)
|
| -float EvalHamming(int filter_size, float x) {
|
| - if (x <= -filter_size || x >= filter_size)
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| - return 0.0f; // Outside of the window.
|
| - if (x > -std::numeric_limits<float>::epsilon() &&
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| - x < std::numeric_limits<float>::epsilon())
|
| - return 1.0f; // Special case the sinc discontinuity at the origin.
|
| - const float xpi = x * static_cast<float>(M_PI);
|
| -
|
| - return ((sin(xpi) / xpi) * // sinc(x)
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| - (0.54f + 0.46f * cos(xpi / filter_size))); // hamming(x)
|
| -}
|
| -
|
| -// ResizeFilter ----------------------------------------------------------------
|
| -
|
| -// Encapsulates computation and storage of the filters required for one complete
|
| -// resize operation.
|
| -class ResizeFilter {
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| - public:
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| - ResizeFilter(ImageOperations::ResizeMethod method,
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| - int src_full_width, int src_full_height,
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| - int dest_width, int dest_height,
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| - const SkIRect& dest_subset);
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| -
|
| - // Returns the filled filter values.
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| - const ConvolutionFilter1D& x_filter() { return x_filter_; }
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| - const ConvolutionFilter1D& y_filter() { return y_filter_; }
|
| -
|
| - private:
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| - // Returns the number of pixels that the filer spans, in filter space (the
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| - // destination image).
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| - float GetFilterSupport(float scale) {
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| - switch (method_) {
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| - case ImageOperations::RESIZE_BOX:
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| - // The box filter just scales with the image scaling.
|
| - return 0.5f; // Only want one side of the filter = /2.
|
| - case ImageOperations::RESIZE_HAMMING1:
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| - // The Hamming filter takes as much space in the source image in
|
| - // each direction as the size of the window = 1 for Hamming1.
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| - return 1.0f;
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| - case ImageOperations::RESIZE_LANCZOS2:
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| - // The Lanczos filter takes as much space in the source image in
|
| - // each direction as the size of the window = 2 for Lanczos2.
|
| - return 2.0f;
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| - case ImageOperations::RESIZE_LANCZOS3:
|
| - // The Lanczos filter takes as much space in the source image in
|
| - // each direction as the size of the window = 3 for Lanczos3.
|
| - return 3.0f;
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| - default:
|
| - NOTREACHED();
|
| - return 1.0f;
|
| - }
|
| - }
|
| -
|
| - // Computes one set of filters either horizontally or vertically. The caller
|
| - // will specify the "min" and "max" rather than the bottom/top and
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| - // right/bottom so that the same code can be re-used in each dimension.
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| - //
|
| - // |src_depend_lo| and |src_depend_size| gives the range for the source
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| - // depend rectangle (horizontally or vertically at the caller's discretion
|
| - // -- see above for what this means).
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| - //
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| - // Likewise, the range of destination values to compute and the scale factor
|
| - // for the transform is also specified.
|
| - void ComputeFilters(int src_size,
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| - int dest_subset_lo, int dest_subset_size,
|
| - float scale,
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| - ConvolutionFilter1D* output);
|
| -
|
| - // Computes the filter value given the coordinate in filter space.
|
| - inline float ComputeFilter(float pos) {
|
| - switch (method_) {
|
| - case ImageOperations::RESIZE_BOX:
|
| - return EvalBox(pos);
|
| - case ImageOperations::RESIZE_HAMMING1:
|
| - return EvalHamming(1, pos);
|
| - case ImageOperations::RESIZE_LANCZOS2:
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| - return EvalLanczos(2, pos);
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| - case ImageOperations::RESIZE_LANCZOS3:
|
| - return EvalLanczos(3, pos);
|
| - default:
|
| - NOTREACHED();
|
| - return 0;
|
| - }
|
| - }
|
| -
|
| - ImageOperations::ResizeMethod method_;
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| -
|
| - // Size of the filter support on one side only in the destination space.
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| - // See GetFilterSupport.
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| - float x_filter_support_;
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| - float y_filter_support_;
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| -
|
| - // Subset of scaled destination bitmap to compute.
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| - SkIRect out_bounds_;
|
| -
|
| - ConvolutionFilter1D x_filter_;
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| - ConvolutionFilter1D y_filter_;
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| -
|
| - DISALLOW_COPY_AND_ASSIGN(ResizeFilter);
|
| -};
|
| -
|
| -ResizeFilter::ResizeFilter(ImageOperations::ResizeMethod method,
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| - int src_full_width, int src_full_height,
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| - int dest_width, int dest_height,
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| - const SkIRect& dest_subset)
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| - : method_(method),
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| - out_bounds_(dest_subset) {
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| - // method_ will only ever refer to an "algorithm method".
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| - SkASSERT((ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD <= method) &&
|
| - (method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD));
|
| -
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| - float scale_x = static_cast<float>(dest_width) /
|
| - static_cast<float>(src_full_width);
|
| - float scale_y = static_cast<float>(dest_height) /
|
| - static_cast<float>(src_full_height);
|
| -
|
| - ComputeFilters(src_full_width, dest_subset.fLeft, dest_subset.width(),
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| - scale_x, &x_filter_);
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| - ComputeFilters(src_full_height, dest_subset.fTop, dest_subset.height(),
|
| - scale_y, &y_filter_);
|
| -}
|
| -
|
| -// TODO(egouriou): Take advantage of periods in the convolution.
|
| -// Practical resizing filters are periodic outside of the border area.
|
| -// For Lanczos, a scaling by a (reduced) factor of p/q (q pixels in the
|
| -// source become p pixels in the destination) will have a period of p.
|
| -// A nice consequence is a period of 1 when downscaling by an integral
|
| -// factor. Downscaling from typical display resolutions is also bound
|
| -// to produce interesting periods as those are chosen to have multiple
|
| -// small factors.
|
| -// Small periods reduce computational load and improve cache usage if
|
| -// the coefficients can be shared. For periods of 1 we can consider
|
| -// loading the factors only once outside the borders.
|
| -void ResizeFilter::ComputeFilters(int src_size,
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| - int dest_subset_lo, int dest_subset_size,
|
| - float scale,
|
| - ConvolutionFilter1D* output) {
|
| - int dest_subset_hi = dest_subset_lo + dest_subset_size; // [lo, hi)
|
| -
|
| - // When we're doing a magnification, the scale will be larger than one. This
|
| - // means the destination pixels are much smaller than the source pixels, and
|
| - // that the range covered by the filter won't necessarily cover any source
|
| - // pixel boundaries. Therefore, we use these clamped values (max of 1) for
|
| - // some computations.
|
| - float clamped_scale = std::min(1.0f, scale);
|
| -
|
| - // This is how many source pixels from the center we need to count
|
| - // to support the filtering function.
|
| - float src_support = GetFilterSupport(clamped_scale) / clamped_scale;
|
| -
|
| - // Speed up the divisions below by turning them into multiplies.
|
| - float inv_scale = 1.0f / scale;
|
| -
|
| - base::StackVector<float, 64> filter_values;
|
| - base::StackVector<int16, 64> fixed_filter_values;
|
| -
|
| - // Loop over all pixels in the output range. We will generate one set of
|
| - // filter values for each one. Those values will tell us how to blend the
|
| - // source pixels to compute the destination pixel.
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| - for (int dest_subset_i = dest_subset_lo; dest_subset_i < dest_subset_hi;
|
| - dest_subset_i++) {
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| - // Reset the arrays. We don't declare them inside so they can re-use the
|
| - // same malloc-ed buffer.
|
| - filter_values->clear();
|
| - fixed_filter_values->clear();
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| -
|
| - // This is the pixel in the source directly under the pixel in the dest.
|
| - // Note that we base computations on the "center" of the pixels. To see
|
| - // why, observe that the destination pixel at coordinates (0, 0) in a 5.0x
|
| - // 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).
|
| - // Hence we need to scale coordinates (0.5, 0.5), not (0, 0).
|
| - float src_pixel = (static_cast<float>(dest_subset_i) + 0.5f) * inv_scale;
|
| -
|
| - // Compute the (inclusive) range of source pixels the filter covers.
|
| - int src_begin = std::max(0, FloorInt(src_pixel - src_support));
|
| - int src_end = std::min(src_size - 1, CeilInt(src_pixel + src_support));
|
| -
|
| - // Compute the unnormalized filter value at each location of the source
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| - // it covers.
|
| - float filter_sum = 0.0f; // Sub of the filter values for normalizing.
|
| - for (int cur_filter_pixel = src_begin; cur_filter_pixel <= src_end;
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| - cur_filter_pixel++) {
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| - // Distance from the center of the filter, this is the filter coordinate
|
| - // in source space. We also need to consider the center of the pixel
|
| - // when comparing distance against 'src_pixel'. In the 5x downscale
|
| - // example used above the distance from the center of the filter to
|
| - // the pixel with coordinates (2, 2) should be 0, because its center
|
| - // is at (2.5, 2.5).
|
| - float src_filter_dist =
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| - ((static_cast<float>(cur_filter_pixel) + 0.5f) - src_pixel);
|
| -
|
| - // Since the filter really exists in dest space, map it there.
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| - float dest_filter_dist = src_filter_dist * clamped_scale;
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| -
|
| - // Compute the filter value at that location.
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| - float filter_value = ComputeFilter(dest_filter_dist);
|
| - filter_values->push_back(filter_value);
|
| -
|
| - filter_sum += filter_value;
|
| - }
|
| - DCHECK(!filter_values->empty()) << "We should always get a filter!";
|
| -
|
| - // The filter must be normalized so that we don't affect the brightness of
|
| - // the image. Convert to normalized fixed point.
|
| - int16 fixed_sum = 0;
|
| - for (size_t i = 0; i < filter_values->size(); i++) {
|
| - int16 cur_fixed = output->FloatToFixed(filter_values[i] / filter_sum);
|
| - fixed_sum += cur_fixed;
|
| - fixed_filter_values->push_back(cur_fixed);
|
| - }
|
| -
|
| - // The conversion to fixed point will leave some rounding errors, which
|
| - // we add back in to avoid affecting the brightness of the image. We
|
| - // arbitrarily add this to the center of the filter array (this won't always
|
| - // be the center of the filter function since it could get clipped on the
|
| - // edges, but it doesn't matter enough to worry about that case).
|
| - int16 leftovers = output->FloatToFixed(1.0f) - fixed_sum;
|
| - fixed_filter_values[fixed_filter_values->size() / 2] += leftovers;
|
| -
|
| - // Now it's ready to go.
|
| - output->AddFilter(src_begin, &fixed_filter_values[0],
|
| - static_cast<int>(fixed_filter_values->size()));
|
| - }
|
| -
|
| - output->PaddingForSIMD();
|
| -}
|
| -
|
| -ImageOperations::ResizeMethod ResizeMethodToAlgorithmMethod(
|
| - ImageOperations::ResizeMethod method) {
|
| - // Convert any "Quality Method" into an "Algorithm Method"
|
| - if (method >= ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD &&
|
| - method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD) {
|
| - return method;
|
| - }
|
| - // The call to ImageOperationsGtv::Resize() above took care of
|
| - // GPU-acceleration in the cases where it is possible. So now we just
|
| - // pick the appropriate software method for each resize quality.
|
| - switch (method) {
|
| - // Users of RESIZE_GOOD are willing to trade a lot of quality to
|
| - // get speed, allowing the use of linear resampling to get hardware
|
| - // acceleration (SRB). Hence any of our "good" software filters
|
| - // will be acceptable, and we use the fastest one, Hamming-1.
|
| - case ImageOperations::RESIZE_GOOD:
|
| - // Users of RESIZE_BETTER are willing to trade some quality in order
|
| - // to improve performance, but are guaranteed not to devolve to a linear
|
| - // resampling. In visual tests we see that Hamming-1 is not as good as
|
| - // Lanczos-2, however it is about 40% faster and Lanczos-2 itself is
|
| - // about 30% faster than Lanczos-3. The use of Hamming-1 has been deemed
|
| - // an acceptable trade-off between quality and speed.
|
| - case ImageOperations::RESIZE_BETTER:
|
| - return ImageOperations::RESIZE_HAMMING1;
|
| - default:
|
| - return ImageOperations::RESIZE_LANCZOS3;
|
| - }
|
| -}
|
| -
|
| -} // namespace
|
| -
|
| -// Resize ----------------------------------------------------------------------
|
| -
|
| -// static
|
| -SkBitmap ImageOperations::Resize(const SkBitmap& source,
|
| - ResizeMethod method,
|
| - int dest_width, int dest_height,
|
| - const SkIRect& dest_subset,
|
| - SkBitmap::Allocator* allocator) {
|
| - TRACE_EVENT2("disabled-by-default-skia", "ImageOperations::Resize",
|
| - "src_pixels", source.width() * source.height(), "dst_pixels",
|
| - dest_width * dest_height);
|
| - // Ensure that the ResizeMethod enumeration is sound.
|
| - SkASSERT(((RESIZE_FIRST_QUALITY_METHOD <= method) &&
|
| - (method <= RESIZE_LAST_QUALITY_METHOD)) ||
|
| - ((RESIZE_FIRST_ALGORITHM_METHOD <= method) &&
|
| - (method <= RESIZE_LAST_ALGORITHM_METHOD)));
|
| -
|
| - // Time how long this takes to see if it's a problem for users.
|
| - base::TimeTicks resize_start = base::TimeTicks::Now();
|
| -
|
| - SkIRect dest = { 0, 0, dest_width, dest_height };
|
| - DCHECK(dest.contains(dest_subset)) <<
|
| - "The supplied subset does not fall within the destination image.";
|
| -
|
| - // If the size of source or destination is 0, i.e. 0x0, 0xN or Nx0, just
|
| - // return empty.
|
| - if (source.width() < 1 || source.height() < 1 ||
|
| - dest_width < 1 || dest_height < 1)
|
| - return SkBitmap();
|
| -
|
| - method = ResizeMethodToAlgorithmMethod(method);
|
| - // Check that we deal with an "algorithm methods" from this point onward.
|
| - SkASSERT((ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD <= method) &&
|
| - (method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD));
|
| -
|
| - SkAutoLockPixels locker(source);
|
| - if (!source.readyToDraw() || source.colorType() != kN32_SkColorType)
|
| - return SkBitmap();
|
| -
|
| - ResizeFilter filter(method, source.width(), source.height(),
|
| - dest_width, dest_height, dest_subset);
|
| -
|
| - // Get a source bitmap encompassing this touched area. We construct the
|
| - // offsets and row strides such that it looks like a new bitmap, while
|
| - // referring to the old data.
|
| - const uint8* source_subset =
|
| - reinterpret_cast<const uint8*>(source.getPixels());
|
| -
|
| - // Convolve into the result.
|
| - SkBitmap result;
|
| - result.setInfo(SkImageInfo::MakeN32(dest_subset.width(), dest_subset.height(), source.alphaType()));
|
| - result.allocPixels(allocator, NULL);
|
| - if (!result.readyToDraw())
|
| - return SkBitmap();
|
| -
|
| - BGRAConvolve2D(source_subset, static_cast<int>(source.rowBytes()),
|
| - !source.isOpaque(), filter.x_filter(), filter.y_filter(),
|
| - static_cast<int>(result.rowBytes()),
|
| - static_cast<unsigned char*>(result.getPixels()),
|
| - true);
|
| -
|
| - base::TimeDelta delta = base::TimeTicks::Now() - resize_start;
|
| - UMA_HISTOGRAM_TIMES("Image.ResampleMS", delta);
|
| -
|
| - return result;
|
| -}
|
| -
|
| -// static
|
| -SkBitmap ImageOperations::Resize(const SkBitmap& source,
|
| - ResizeMethod method,
|
| - int dest_width, int dest_height,
|
| - SkBitmap::Allocator* allocator) {
|
| - SkIRect dest_subset = { 0, 0, dest_width, dest_height };
|
| - return Resize(source, method, dest_width, dest_height, dest_subset,
|
| - allocator);
|
| -}
|
| -
|
| -} // namespace skia
|
|
|