зеркало из https://github.com/mozilla/gecko-dev.git
554 строки
22 KiB
C++
554 строки
22 KiB
C++
// Copyright (c) 2006-2012 The Chromium Authors. All rights reserved.
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions
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// are met:
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// * Redistributions of source code must retain the above copyright
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// notice, this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright
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// notice, this list of conditions and the following disclaimer in
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// the documentation and/or other materials provided with the
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// distribution.
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// * Neither the name of Google, Inc. nor the names of its contributors
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// may be used to endorse or promote products derived from this
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// software without specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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// FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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// COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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// BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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// OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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// AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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// OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
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// OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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// SUCH DAMAGE.
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#include "base/basictypes.h"
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#define _USE_MATH_DEFINES
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#include <algorithm>
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#include <cmath>
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#include <limits>
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#include "image_operations.h"
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#include "nsAlgorithm.h"
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#include "base/stack_container.h"
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#include "convolver.h"
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#include "skia/SkColorPriv.h"
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#include "skia/SkBitmap.h"
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#include "skia/SkRect.h"
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#include "skia/SkFontHost.h"
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namespace skia {
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namespace {
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// Returns the ceiling/floor as an integer.
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inline int CeilInt(float val) {
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return static_cast<int>(ceil(val));
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}
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inline int FloorInt(float val) {
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return static_cast<int>(floor(val));
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}
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// Filter function computation -------------------------------------------------
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// Evaluates the box filter, which goes from -0.5 to +0.5.
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float EvalBox(float x) {
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return (x >= -0.5f && x < 0.5f) ? 1.0f : 0.0f;
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}
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// Evaluates the Lanczos filter of the given filter size window for the given
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// position.
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//
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// |filter_size| is the width of the filter (the "window"), outside of which
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// the value of the function is 0. Inside of the window, the value is the
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// normalized sinc function:
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// lanczos(x) = sinc(x) * sinc(x / filter_size);
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// where
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// sinc(x) = sin(pi*x) / (pi*x);
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float EvalLanczos(int filter_size, float x) {
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if (x <= -filter_size || x >= filter_size)
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return 0.0f; // Outside of the window.
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if (x > -std::numeric_limits<float>::epsilon() &&
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x < std::numeric_limits<float>::epsilon())
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return 1.0f; // Special case the discontinuity at the origin.
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float xpi = x * static_cast<float>(M_PI);
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return (sin(xpi) / xpi) * // sinc(x)
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sin(xpi / filter_size) / (xpi / filter_size); // sinc(x/filter_size)
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}
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// Evaluates the Hamming filter of the given filter size window for the given
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// 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
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// 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:
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// hamming(n) = 0.54 - 0.46 * cos(2 * pi * n / (N-1)))
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// In our case we want the function centered for x == 0 and at its minimum
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// on both ends of the window (x == +/- filter_size), hence the adjusted
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// formula:
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// hamming(x) = (0.54 -
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// 0.46 * cos(2 * pi * (x - filter_size)/ (2 * filter_size)))
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// = 0.54 - 0.46 * cos(pi * x / filter_size - pi)
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// = 0.54 + 0.46 * cos(pi * x / filter_size)
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float EvalHamming(int filter_size, float x) {
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if (x <= -filter_size || x >= filter_size)
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return 0.0f; // Outside of the window.
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if (x > -std::numeric_limits<float>::epsilon() &&
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x < std::numeric_limits<float>::epsilon())
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return 1.0f; // Special case the sinc discontinuity at the origin.
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const float xpi = x * static_cast<float>(M_PI);
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return ((sin(xpi) / xpi) * // sinc(x)
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(0.54f + 0.46f * cos(xpi / filter_size))); // hamming(x)
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}
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// ResizeFilter ----------------------------------------------------------------
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// Encapsulates computation and storage of the filters required for one complete
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// resize operation.
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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_; }
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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.
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return 0.5f; // Only want one side of the filter = /2.
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case ImageOperations::RESIZE_HAMMING1:
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// The Hamming filter takes as much space in the source image in
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// 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
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// each direction as the size of the window = 2 for Lanczos2.
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return 2.0f;
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case ImageOperations::RESIZE_LANCZOS3:
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// The Lanczos filter takes as much space in the source image in
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// each direction as the size of the window = 3 for Lanczos3.
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return 3.0f;
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default:
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return 1.0f;
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}
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}
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// Computes one set of filters either horizontally or vertically. The caller
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// 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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//
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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
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// -- 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
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// for the transform is also specified.
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void ComputeFilters(int src_size,
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int dest_subset_lo, int dest_subset_size,
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float scale, float src_support,
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ConvolutionFilter1D* output);
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// Computes the filter value given the coordinate in filter space.
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inline float ComputeFilter(float pos) {
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switch (method_) {
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case ImageOperations::RESIZE_BOX:
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return EvalBox(pos);
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case ImageOperations::RESIZE_HAMMING1:
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return EvalHamming(1, pos);
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case ImageOperations::RESIZE_LANCZOS2:
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return EvalLanczos(2, pos);
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case ImageOperations::RESIZE_LANCZOS3:
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return EvalLanczos(3, pos);
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default:
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return 0;
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}
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}
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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_;
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ConvolutionFilter1D x_filter_;
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ConvolutionFilter1D y_filter_;
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DISALLOW_COPY_AND_ASSIGN(ResizeFilter);
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};
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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) &&
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(method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD));
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float scale_x = static_cast<float>(dest_width) /
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static_cast<float>(src_full_width);
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float scale_y = static_cast<float>(dest_height) /
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static_cast<float>(src_full_height);
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x_filter_support_ = GetFilterSupport(scale_x);
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y_filter_support_ = GetFilterSupport(scale_y);
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// Support of the filter in source space.
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float src_x_support = x_filter_support_ / scale_x;
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float src_y_support = y_filter_support_ / scale_y;
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ComputeFilters(src_full_width, dest_subset.fLeft, dest_subset.width(),
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scale_x, src_x_support, &x_filter_);
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ComputeFilters(src_full_height, dest_subset.fTop, dest_subset.height(),
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scale_y, src_y_support, &y_filter_);
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}
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// TODO(egouriou): Take advantage of periods in the convolution.
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// Practical resizing filters are periodic outside of the border area.
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// For Lanczos, a scaling by a (reduced) factor of p/q (q pixels in the
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// source become p pixels in the destination) will have a period of p.
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// A nice consequence is a period of 1 when downscaling by an integral
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// factor. Downscaling from typical display resolutions is also bound
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// to produce interesting periods as those are chosen to have multiple
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// small factors.
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// Small periods reduce computational load and improve cache usage if
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// the coefficients can be shared. For periods of 1 we can consider
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// loading the factors only once outside the borders.
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void ResizeFilter::ComputeFilters(int src_size,
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int dest_subset_lo, int dest_subset_size,
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float scale, float src_support,
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ConvolutionFilter1D* output) {
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int dest_subset_hi = dest_subset_lo + dest_subset_size; // [lo, hi)
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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 clamped_scale = std::min(1.0f, scale);
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// Speed up the divisions below by turning them into multiplies.
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float inv_scale = 1.0f / scale;
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StackVector<float, 64> filter_values;
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StackVector<int16_t, 64> fixed_filter_values;
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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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for (int dest_subset_i = dest_subset_lo; dest_subset_i < dest_subset_hi;
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dest_subset_i++) {
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// Reset the arrays. We don't declare them inside so they can re-use the
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// same malloc-ed buffer.
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filter_values->clear();
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fixed_filter_values->clear();
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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 src_pixel = (static_cast<float>(dest_subset_i) + 0.5f) * inv_scale;
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// Compute the (inclusive) range of source pixels the filter covers.
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int src_begin = std::max(0, FloorInt(src_pixel - src_support));
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int src_end = std::min(src_size - 1, CeilInt(src_pixel + src_support));
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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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float filter_sum = 0.0f; // Sub of the filter values for normalizing.
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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
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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 'src_pixel'. 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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float src_filter_dist =
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((static_cast<float>(cur_filter_pixel) + 0.5f) - src_pixel);
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// 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);
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filter_values->push_back(filter_value);
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filter_sum += filter_value;
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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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int16_t fixed_sum = 0;
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for (size_t i = 0; i < filter_values->size(); i++) {
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int16_t cur_fixed = output->FloatToFixed(filter_values[i] / filter_sum);
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fixed_sum += cur_fixed;
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fixed_filter_values->push_back(cur_fixed);
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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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int16_t leftovers = output->FloatToFixed(1.0f) - fixed_sum;
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fixed_filter_values[fixed_filter_values->size() / 2] += leftovers;
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// Now it's ready to go.
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output->AddFilter(src_begin, &fixed_filter_values[0],
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static_cast<int>(fixed_filter_values->size()));
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}
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output->PaddingForSIMD(8);
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}
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ImageOperations::ResizeMethod ResizeMethodToAlgorithmMethod(
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ImageOperations::ResizeMethod method) {
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// Convert any "Quality Method" into an "Algorithm Method"
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if (method >= ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD &&
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method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD) {
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return method;
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}
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// The call to ImageOperationsGtv::Resize() above took care of
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// GPU-acceleration in the cases where it is possible. So now we just
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// pick the appropriate software method for each resize quality.
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switch (method) {
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// Users of RESIZE_GOOD are willing to trade a lot of quality to
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// get speed, allowing the use of linear resampling to get hardware
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// acceleration (SRB). Hence any of our "good" software filters
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// will be acceptable, and we use the fastest one, Hamming-1.
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case ImageOperations::RESIZE_GOOD:
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// Users of RESIZE_BETTER are willing to trade some quality in order
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// to improve performance, but are guaranteed not to devolve to a linear
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// resampling. In visual tests we see that Hamming-1 is not as good as
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// Lanczos-2, however it is about 40% faster and Lanczos-2 itself is
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// about 30% faster than Lanczos-3. The use of Hamming-1 has been deemed
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// an acceptable trade-off between quality and speed.
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case ImageOperations::RESIZE_BETTER:
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return ImageOperations::RESIZE_HAMMING1;
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default:
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return ImageOperations::RESIZE_LANCZOS3;
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}
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}
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} // namespace
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// Resize ----------------------------------------------------------------------
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// static
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SkBitmap ImageOperations::Resize(const SkBitmap& source,
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ResizeMethod method,
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int dest_width, int dest_height,
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const SkIRect& dest_subset,
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void* dest_pixels /* = nullptr */) {
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if (method == ImageOperations::RESIZE_SUBPIXEL)
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return ResizeSubpixel(source, dest_width, dest_height, dest_subset);
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else
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return ResizeBasic(source, method, dest_width, dest_height, dest_subset,
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dest_pixels);
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}
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// static
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SkBitmap ImageOperations::ResizeSubpixel(const SkBitmap& source,
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int dest_width, int dest_height,
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const SkIRect& dest_subset) {
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// Currently only works on Linux/BSD because these are the only platforms
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// where SkFontHost::GetSubpixelOrder is defined.
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#if defined(XP_UNIX)
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// Understand the display.
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const SkFontHost::LCDOrder order = SkFontHost::GetSubpixelOrder();
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const SkFontHost::LCDOrientation orientation =
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SkFontHost::GetSubpixelOrientation();
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// Decide on which dimension, if any, to deploy subpixel rendering.
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int w = 1;
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int h = 1;
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switch (orientation) {
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case SkFontHost::kHorizontal_LCDOrientation:
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w = dest_width < source.width() ? 3 : 1;
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break;
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case SkFontHost::kVertical_LCDOrientation:
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h = dest_height < source.height() ? 3 : 1;
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break;
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}
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// Resize the image.
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const int width = dest_width * w;
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const int height = dest_height * h;
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SkIRect subset = { dest_subset.fLeft, dest_subset.fTop,
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dest_subset.fLeft + dest_subset.width() * w,
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dest_subset.fTop + dest_subset.height() * h };
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SkBitmap img = ResizeBasic(source, ImageOperations::RESIZE_LANCZOS3, width,
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height, subset);
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const int row_words = img.rowBytes() / 4;
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if (w == 1 && h == 1)
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return img;
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// Render into subpixels.
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SkBitmap result;
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result.setConfig(SkBitmap::kARGB_8888_Config, dest_subset.width(),
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dest_subset.height());
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result.allocPixels();
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if (!result.readyToDraw())
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return img;
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SkAutoLockPixels locker(img);
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if (!img.readyToDraw())
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return img;
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uint32_t* src_row = img.getAddr32(0, 0);
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uint32_t* dst_row = result.getAddr32(0, 0);
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for (int y = 0; y < dest_subset.height(); y++) {
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uint32_t* src = src_row;
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uint32_t* dst = dst_row;
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for (int x = 0; x < dest_subset.width(); x++, src += w, dst++) {
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uint8_t r = 0, g = 0, b = 0, a = 0;
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switch (order) {
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case SkFontHost::kRGB_LCDOrder:
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switch (orientation) {
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case SkFontHost::kHorizontal_LCDOrientation:
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r = SkGetPackedR32(src[0]);
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g = SkGetPackedG32(src[1]);
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b = SkGetPackedB32(src[2]);
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a = SkGetPackedA32(src[1]);
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break;
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case SkFontHost::kVertical_LCDOrientation:
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r = SkGetPackedR32(src[0 * row_words]);
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g = SkGetPackedG32(src[1 * row_words]);
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b = SkGetPackedB32(src[2 * row_words]);
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a = SkGetPackedA32(src[1 * row_words]);
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break;
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}
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break;
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case SkFontHost::kBGR_LCDOrder:
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switch (orientation) {
|
|
case SkFontHost::kHorizontal_LCDOrientation:
|
|
b = SkGetPackedB32(src[0]);
|
|
g = SkGetPackedG32(src[1]);
|
|
r = SkGetPackedR32(src[2]);
|
|
a = SkGetPackedA32(src[1]);
|
|
break;
|
|
case SkFontHost::kVertical_LCDOrientation:
|
|
b = SkGetPackedB32(src[0 * row_words]);
|
|
g = SkGetPackedG32(src[1 * row_words]);
|
|
r = SkGetPackedR32(src[2 * row_words]);
|
|
a = SkGetPackedA32(src[1 * row_words]);
|
|
break;
|
|
}
|
|
break;
|
|
case SkFontHost::kNONE_LCDOrder:
|
|
break;
|
|
}
|
|
// Premultiplied alpha is very fragile.
|
|
a = a > r ? a : r;
|
|
a = a > g ? a : g;
|
|
a = a > b ? a : b;
|
|
*dst = SkPackARGB32(a, r, g, b);
|
|
}
|
|
src_row += h * row_words;
|
|
dst_row += result.rowBytes() / 4;
|
|
}
|
|
result.setIsOpaque(img.isOpaque());
|
|
return result;
|
|
#else
|
|
return SkBitmap();
|
|
#endif // OS_POSIX && !OS_MACOSX && !defined(OS_ANDROID)
|
|
}
|
|
|
|
// static
|
|
SkBitmap ImageOperations::ResizeBasic(const SkBitmap& source,
|
|
ResizeMethod method,
|
|
int dest_width, int dest_height,
|
|
const SkIRect& dest_subset,
|
|
void* dest_pixels /* = nullptr */) {
|
|
// 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)));
|
|
|
|
// 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())
|
|
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_t* source_subset =
|
|
reinterpret_cast<const uint8_t*>(source.getPixels());
|
|
|
|
// Convolve into the result.
|
|
SkBitmap result;
|
|
result.setConfig(SkBitmap::kARGB_8888_Config,
|
|
dest_subset.width(), dest_subset.height());
|
|
|
|
if (dest_pixels) {
|
|
result.setPixels(dest_pixels);
|
|
} else {
|
|
result.allocPixels();
|
|
}
|
|
|
|
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()),
|
|
/* sse = */ false);
|
|
|
|
// Preserve the "opaque" flag for use as an optimization later.
|
|
result.setIsOpaque(source.isOpaque());
|
|
|
|
return result;
|
|
}
|
|
|
|
// static
|
|
SkBitmap ImageOperations::Resize(const SkBitmap& source,
|
|
ResizeMethod method,
|
|
int dest_width, int dest_height,
|
|
void* dest_pixels /* = nullptr */) {
|
|
SkIRect dest_subset = { 0, 0, dest_width, dest_height };
|
|
return Resize(source, method, dest_width, dest_height, dest_subset,
|
|
dest_pixels);
|
|
}
|
|
|
|
} // namespace skia
|