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Bug 1120050 - Expose Skia scaler internals for use by downscale-during-decode. r=tn

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This commit is contained in:
Seth Fowler 2015-01-20 03:06:37 -08:00
parent 2722ba972e
commit 7b3eb49cc5
4 changed files with 219 additions and 194 deletions
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78
gfx/2d/convolver.cpp
View File

@ -153,6 +153,8 @@ class CircularRowBuffer {
std::vector<unsigned char*> row_addresses_;
};
} // namespace
// Convolves horizontally along a single row. The row data is given in
// |src_data| and continues for the [begin, end) of the filter.
template<bool has_alpha>
@ -267,7 +269,60 @@ void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
}
}
} // namespace
void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
int filter_length,
unsigned char* const* source_data_rows,
int width, unsigned char* out_row,
bool has_alpha, bool use_sse2) {
int processed = 0;
#if defined(USE_SSE2)
// If the binary was not built with SSE2 support, we had to fallback to C version.
int simd_width = width & ~3;
if (use_sse2 && simd_width) {
ConvolveVertically_SSE2(filter_values, filter_length,
source_data_rows, 0, simd_width,
out_row, has_alpha);
processed = simd_width;
}
#endif
if (width > processed) {
if (has_alpha) {
ConvolveVertically<true>(filter_values, filter_length, source_data_rows,
processed, width, out_row);
} else {
ConvolveVertically<false>(filter_values, filter_length, source_data_rows,
processed, width, out_row);
}
}
}
void ConvolveHorizontally(const unsigned char* src_data,
const ConvolutionFilter1D& filter,
unsigned char* out_row,
bool has_alpha, bool use_sse2) {
int width = filter.num_values();
int processed = 0;
#if defined(USE_SSE2)
int simd_width = width & ~3;
if (use_sse2 && simd_width) {
// SIMD implementation works with 4 pixels at a time.
// Therefore we process as much as we can using SSE and then use
// C implementation for leftovers
ConvolveHorizontally_SSE2(src_data, 0, simd_width, filter, out_row);
processed = simd_width;
}
#endif
if (width > processed) {
if (has_alpha) {
ConvolveHorizontally<true>(src_data, processed, width, filter, out_row);
} else {
ConvolveHorizontally<false>(src_data, processed, width, filter, out_row);
}
}
}
// ConvolutionFilter1D ---------------------------------------------------------
@ -462,24 +517,9 @@ void BGRAConvolve2D(const unsigned char* source_data,
unsigned char* const* first_row_for_filter =
&rows_to_convolve[filter_offset - first_row_in_circular_buffer];
int processed = 0;
#if defined(USE_SSE2)
int simd_width = pixel_width & ~3;
if (use_sse2 && simd_width) {
ConvolveVertically_SSE2(filter_values, filter_length, first_row_for_filter,
0, simd_width, cur_output_row, source_has_alpha);
processed = simd_width;
}
#endif
if (source_has_alpha) {
ConvolveVertically<true>(filter_values, filter_length,
first_row_for_filter,
processed, pixel_width, cur_output_row);
} else {
ConvolveVertically<false>(filter_values, filter_length,
first_row_for_filter,
processed, pixel_width, cur_output_row);
}
ConvolveVertically(filter_values, filter_length,
first_row_for_filter, pixel_width,
cur_output_row, source_has_alpha, use_sse2);
}
}

11
gfx/2d/convolver.h
View File

@ -186,6 +186,17 @@ void BGRAConvolve2D(const unsigned char* source_data,
int output_byte_row_stride,
unsigned char* output);
void ConvolveHorizontally(const unsigned char* src_data,
const ConvolutionFilter1D& filter,
unsigned char* out_row,
bool has_alpha, bool use_sse2);
void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values,
int filter_length,
unsigned char* const* source_data_rows,
int pixel_width, unsigned char* out_row,
bool has_alpha, bool use_sse2);
} // namespace skia
#endif // SKIA_EXT_CONVOLVER_H_

196
gfx/2d/image_operations.cpp
View File

@ -44,171 +44,7 @@
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)
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.
//
// The filter covers [-filter_size, +filter_size]. Outside of this window
// the value of the function is 0. Inside of the window, the value is sinus
// cardinal multiplied by a recentered Hamming function. The traditional
// 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)
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 sinc discontinuity at the origin.
const float xpi = x * static_cast<float>(M_PI);
return ((sin(xpi) / xpi) * // sinc(x)
(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 {
public:
ResizeFilter(ImageOperations::ResizeMethod method,
int src_full_width, int src_full_height,
int dest_width, int dest_height,
const SkIRect& dest_subset);
// Returns the filled filter values.
const ConvolutionFilter1D& x_filter() { return x_filter_; }
const ConvolutionFilter1D& y_filter() { return y_filter_; }
private:
// Returns the number of pixels that the filer spans, in filter space (the
// destination image).
float GetFilterSupport(float scale) {
switch (method_) {
case ImageOperations::RESIZE_BOX:
// The box filter just scales with the image scaling.
return 0.5f; // Only want one side of the filter = /2.
case ImageOperations::RESIZE_HAMMING1:
// The Hamming filter takes as much space in the source image in
// each direction as the size of the window = 1 for Hamming1.
return 1.0f;
case ImageOperations::RESIZE_LANCZOS2:
// 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;
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;
default:
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
// right/bottom so that the same code can be re-used in each dimension.
//
// |src_depend_lo| and |src_depend_size| gives the range for the source
// depend rectangle (horizontally or vertically at the caller's discretion
// -- see above for what this means).
//
// Likewise, the range of destination values to compute and the scale factor
// for the transform is also specified.
void ComputeFilters(int src_size,
int dest_subset_lo, int dest_subset_size,
float scale, 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:
return EvalLanczos(2, pos);
case ImageOperations::RESIZE_LANCZOS3:
return EvalLanczos(3, pos);
default:
return 0;
}
}
ImageOperations::ResizeMethod method_;
// Subset of scaled destination bitmap to compute.
SkIRect out_bounds_;
ConvolutionFilter1D x_filter_;
ConvolutionFilter1D y_filter_;
DISALLOW_COPY_AND_ASSIGN(ResizeFilter);
};
ResizeFilter::ResizeFilter(ImageOperations::ResizeMethod method,
int src_full_width, int src_full_height,
int dest_width, int dest_height,
const SkIRect& dest_subset)
: method_(method),
out_bounds_(dest_subset) {
// method_ will only ever refer to an "algorithm method".
SkASSERT((ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD <= method) &&
(method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD));
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(),
scale_x, &x_filter_);
ComputeFilters(src_full_height, dest_subset.fTop, dest_subset.height(),
scale_y, &y_filter_);
}
namespace resize {
// TODO(egouriou): Take advantage of periods in the convolution.
// Practical resizing filters are periodic outside of the border area.
@ -221,9 +57,16 @@ ResizeFilter::ResizeFilter(ImageOperations::ResizeMethod method,
// 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,
int dest_subset_lo, int dest_subset_size,
float scale, ConvolutionFilter1D* output) {
void ComputeFilters(ImageOperations::ResizeMethod method,
int src_size, int dst_size,
int dest_subset_lo, int dest_subset_size,
ConvolutionFilter1D* output) {
// method_ will only ever refer to an "algorithm method".
SkASSERT((ImageOperations::RESIZE_FIRST_ALGORITHM_METHOD <= method) &&
(method <= ImageOperations::RESIZE_LAST_ALGORITHM_METHOD));
float scale = static_cast<float>(dst_size) / static_cast<float>(src_size);
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
@ -233,7 +76,7 @@ void ResizeFilter::ComputeFilters(int src_size,
// some computations.
float clamped_scale = std::min(1.0f, scale);
float src_support = GetFilterSupport(clamped_scale) / clamped_scale;
float src_support = GetFilterSupport(method, clamped_scale) / clamped_scale;
// Speed up the divisions below by turning them into multiplies.
float inv_scale = 1.0f / scale;
@ -281,7 +124,7 @@ void ResizeFilter::ComputeFilters(int src_size,
float dest_filter_dist = src_filter_dist * clamped_scale;
// Compute the filter value at that location.
float filter_value = ComputeFilter(dest_filter_dist);
float filter_value = ComputeFilter(method, dest_filter_dist);
filter_values->push_back(filter_value);
filter_sum += filter_value;
@ -312,6 +155,8 @@ void ResizeFilter::ComputeFilters(int src_size,
output->PaddingForSIMD(8);
}
}
ImageOperations::ResizeMethod ResizeMethodToAlgorithmMethod(
ImageOperations::ResizeMethod method) {
// Convert any "Quality Method" into an "Algorithm Method"
@ -341,8 +186,6 @@ ImageOperations::ResizeMethod ResizeMethodToAlgorithmMethod(
}
}
} // namespace
// Resize ----------------------------------------------------------------------
// static
@ -496,8 +339,11 @@ SkBitmap ImageOperations::ResizeBasic(const SkBitmap& source,
if (!source.readyToDraw())
return SkBitmap();
ResizeFilter filter(method, source.width(), source.height(),
dest_width, dest_height, dest_subset);
ConvolutionFilter1D x_filter;
ConvolutionFilter1D y_filter;
resize::ComputeFilters(method, source.width(), dest_width, dest_subset.fLeft, dest_subset.width(), &x_filter);
resize::ComputeFilters(method, source.height(), dest_height, dest_subset.fTop, dest_subset.height(), &y_filter);
// Get a source bitmap encompassing this touched area. We construct the
// offsets and row strides such that it looks like a new bitmap, while
@ -522,7 +368,7 @@ SkBitmap ImageOperations::ResizeBasic(const SkBitmap& source,
return SkBitmap();
BGRAConvolve2D(source_subset, static_cast<int>(source.rowBytes()),
!source.isOpaque(), filter.x_filter(), filter.y_filter(),
!source.isOpaque(), x_filter, y_filter,
static_cast<int>(result.rowBytes()),
static_cast<unsigned char*>(result.getPixels()));

128
gfx/2d/image_operations.h
View File

@ -31,6 +31,8 @@
#include "skia/SkTypes.h"
#include "Types.h"
#include "convolver.h"
#include "skia/SkRect.h"
class SkBitmap;
struct SkIRect;
@ -152,6 +154,132 @@ class ImageOperations {
const SkIRect& dest_subset);
};
// 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.
inline 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);
inline float EvalLanczos(int filter_size, float x) {
if (x <= -filter_size || x >= filter_size)
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.
//
// The filter covers [-filter_size, +filter_size]. Outside of this window
// the value of the function is 0. Inside of the window, the value is sinus
// cardinal multiplied by a recentered Hamming function. The traditional
// 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)
inline float EvalHamming(int filter_size, float x) {
if (x <= -filter_size || x >= filter_size)
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 sinc discontinuity at the origin.
const float xpi = x * static_cast<float>(M_PI);
return ((sin(xpi) / xpi) * // sinc(x)
(0.54f + 0.46f * cos(xpi / filter_size))); // hamming(x)
}
// ResizeFilter ----------------------------------------------------------------
// Encapsulates computation and storage of the filters required for one complete
// resize operation.
namespace resize {
// Returns the number of pixels that the filer spans, in filter space (the
// destination image).
inline float GetFilterSupport(ImageOperations::ResizeMethod method,
float scale) {
switch (method) {
case ImageOperations::RESIZE_BOX:
// The box filter just scales with the image scaling.
return 0.5f; // Only want one side of the filter = /2.
case ImageOperations::RESIZE_HAMMING1:
// The Hamming filter takes as much space in the source image in
// each direction as the size of the window = 1 for Hamming1.
return 1.0f;
case ImageOperations::RESIZE_LANCZOS2:
// 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;
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;
default:
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
// right/bottom so that the same code can be re-used in each dimension.
//
// |src_depend_lo| and |src_depend_size| gives the range for the source
// depend rectangle (horizontally or vertically at the caller's discretion
// -- see above for what this means).
//
// Likewise, the range of destination values to compute and the scale factor
// for the transform is also specified.
void ComputeFilters(ImageOperations::ResizeMethod method,
int src_size, int dst_size,
int dest_subset_lo, int dest_subset_size,
ConvolutionFilter1D* output);
// Computes the filter value given the coordinate in filter space.
inline float ComputeFilter(ImageOperations::ResizeMethod method, float pos) {
switch (method) {
case ImageOperations::RESIZE_BOX:
return EvalBox(pos);
case ImageOperations::RESIZE_HAMMING1:
return EvalHamming(1, pos);
case ImageOperations::RESIZE_LANCZOS2:
return EvalLanczos(2, pos);
case ImageOperations::RESIZE_LANCZOS3:
return EvalLanczos(3, pos);
default:
return 0;
}
}
}
} // namespace skia
#endif // SKIA_EXT_IMAGE_OPERATIONS_H_