skia/ext/convolver.h - chromium - Git at Google

 // 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.

 #ifndef SKIA_EXT_CONVOLVER_H_
 #define SKIA_EXT_CONVOLVER_H_

 #include <cmath>
 #include <vector>

 #include "base/basictypes.h"
 #include "base/cpu.h"
 #include "third_party/skia/include/core/SkTypes.h"

 #if defined(ARCH_CPU_X86_FAMILY)
 #if defined(__x86_64__) || defined(_M_X64) || defined(__SSE2__) || _M_IX86_FP==2
 // This is where we had compiler support for SSE2 instructions.
 // FIXME: Known buggy, so disabling for M22.
 // #define SIMD_SSE2 1
 #endif
 #endif

 // avoid confusion with Mac OS X's math library (Carbon)
 #if defined(__APPLE__)
 #undef FloatToFixed
 #undef FixedToFloat
 #endif

 namespace skia {

 // Represents a filter in one dimension. Each output pixel has one entry in this
 // object for the filter values contributing to it. You build up the filter
 // list by calling AddFilter for each output pixel (in order).
 //
 // We do 2-dimensional convolution by first convolving each row by one
 // ConvolutionFilter1D, then convolving each column by another one.
 //
 // Entries are stored in fixed point, shifted left by kShiftBits.
 class ConvolutionFilter1D {
  public:
   typedef short Fixed;

   // The number of bits that fixed point values are shifted by.
   enum { kShiftBits = 14 };

   SK_API ConvolutionFilter1D();
   SK_API ~ConvolutionFilter1D();

   // Convert between floating point and our fixed point representation.
   static Fixed FloatToFixed(float f) {
     return static_cast<Fixed>(f * (1 << kShiftBits));
   }
   static unsigned char FixedToChar(Fixed x) {
     return static_cast<unsigned char>(x >> kShiftBits);
   }
   static float FixedToFloat(Fixed x) {
     // The cast relies on Fixed being a short, implying that on
     // the platforms we care about all (16) bits will fit into
     // the mantissa of a (32-bit) float.
     COMPILE_ASSERT(sizeof(Fixed) == 2, fixed_type_should_fit_in_float_mantissa);
     float raw = static_cast<float>(x);
     return ldexpf(raw, -kShiftBits);
   }

   // Returns the maximum pixel span of a filter.
   int max_filter() const { return max_filter_; }

   // Returns the number of filters in this filter. This is the dimension of the
   // output image.
   int num_values() const { return static_cast<int>(filters_.size()); }

   // Appends the given list of scaling values for generating a given output
   // pixel. |filter_offset| is the distance from the edge of the image to where
   // the scaling factors start. The scaling factors apply to the source pixels
   // starting from this position, and going for the next |filter_length| pixels.
   //
   // You will probably want to make sure your input is normalized (that is,
   // all entries in |filter_values| sub to one) to prevent affecting the overall
   // brighness of the image.
   //
   // The filter_length must be > 0.
   //
   // This version will automatically convert your input to fixed point.
   SK_API void AddFilter(int filter_offset,
                         const float* filter_values,
                         int filter_length);

   // Same as the above version, but the input is already fixed point.
   void AddFilter(int filter_offset,
                  const Fixed* filter_values,
                  int filter_length);

   // Retrieves a filter for the given |value_offset|, a position in the output
   // image in the direction we're convolving. The offset and length of the
   // filter values are put into the corresponding out arguments (see AddFilter
   // above for what these mean), and a pointer to the first scaling factor is
   // returned. There will be |filter_length| values in this array.
   inline const Fixed* FilterForValue(int value_offset,
                                      int* filter_offset,
                                      int* filter_length) const {
     const FilterInstance& filter = filters_[value_offset];
     *filter_offset = filter.offset;
     *filter_length = filter.length;
     if (filter.length == 0) {
       return NULL;
     }
     return &filter_values_[filter.data_location];
   }


   inline void PaddingForSIMD(int padding_count) {
     // Padding |padding_count| of more dummy coefficients after the coefficients
     // of last filter to prevent SIMD instructions which load 8 or 16 bytes
     // together to access invalid memory areas. We are not trying to align the
     // coefficients right now due to the opaqueness of <vector> implementation.
     // This has to be done after all |AddFilter| calls.
     for (int i = 0; i < padding_count; ++i)
       filter_values_.push_back(static_cast<Fixed>(0));
   }

  private:
   struct FilterInstance {
     // Offset within filter_values for this instance of the filter.
     int data_location;

     // Distance from the left of the filter to the center. IN PIXELS
     int offset;

     // Number of values in this filter instance.
     int length;
   };

   // Stores the information for each filter added to this class.
   std::vector<FilterInstance> filters_;

   // We store all the filter values in this flat list, indexed by
   // |FilterInstance.data_location| to avoid the mallocs required for storing
   // each one separately.
   std::vector<Fixed> filter_values_;

   // The maximum size of any filter we've added.
   int max_filter_;
 };

 // Does a two-dimensional convolution on the given source image.
 //
 // It is assumed the source pixel offsets referenced in the input filters
 // reference only valid pixels, so the source image size is not required. Each
 // row of the source image starts |source_byte_row_stride| after the previous
 // one (this allows you to have rows with some padding at the end).
 //
 // The result will be put into the given output buffer. The destination image
 // size will be xfilter.num_values() * yfilter.num_values() pixels. It will be
 // in rows of exactly xfilter.num_values() * 4 bytes.
 //
 // |source_has_alpha| is a hint that allows us to avoid doing computations on
 // the alpha channel if the image is opaque. If you don't know, set this to
 // true and it will work properly, but setting this to false will be a few
 // percent faster if you know the image is opaque.
 //
 // The layout in memory is assumed to be 4-bytes per pixel in B-G-R-A order
 // (this is ARGB when loaded into 32-bit words on a little-endian machine).
 SK_API void BGRAConvolve2D(const unsigned char* source_data,
                            int source_byte_row_stride,
                            bool source_has_alpha,
                            const ConvolutionFilter1D& xfilter,
                            const ConvolutionFilter1D& yfilter,
                            int output_byte_row_stride,
                            unsigned char* output,
                            bool use_sse2);
 }  // namespace skia

 #endif  // SKIA_EXT_CONVOLVER_H_
	// 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.

	#ifndef SKIA_EXT_CONVOLVER_H_
	#define SKIA_EXT_CONVOLVER_H_

	#include <cmath>
	#include <vector>

	#include "base/basictypes.h"
	#include "base/cpu.h"
	#include "third_party/skia/include/core/SkTypes.h"

	#if defined(ARCH_CPU_X86_FAMILY)
	#if defined(__x86_64__) \|\| defined(_M_X64) \|\| defined(__SSE2__) \|\| _M_IX86_FP==2
	// This is where we had compiler support for SSE2 instructions.
	// FIXME: Known buggy, so disabling for M22.
	// #define SIMD_SSE2 1
	#endif
	#endif

	// avoid confusion with Mac OS X's math library (Carbon)
	#if defined(__APPLE__)
	#undef FloatToFixed
	#undef FixedToFloat
	#endif

	namespace skia {

	// Represents a filter in one dimension. Each output pixel has one entry in this
	// object for the filter values contributing to it. You build up the filter
	// list by calling AddFilter for each output pixel (in order).
	//
	// We do 2-dimensional convolution by first convolving each row by one
	// ConvolutionFilter1D, then convolving each column by another one.
	//
	// Entries are stored in fixed point, shifted left by kShiftBits.
	class ConvolutionFilter1D {
	public:
	typedef short Fixed;

	// The number of bits that fixed point values are shifted by.
	enum { kShiftBits = 14 };

	SK_API ConvolutionFilter1D();
	SK_API ~ConvolutionFilter1D();

	// Convert between floating point and our fixed point representation.
	static Fixed FloatToFixed(float f) {
	return static_cast<Fixed>(f * (1 << kShiftBits));
	}
	static unsigned char FixedToChar(Fixed x) {
	return static_cast<unsigned char>(x >> kShiftBits);
	}
	static float FixedToFloat(Fixed x) {
	// The cast relies on Fixed being a short, implying that on
	// the platforms we care about all (16) bits will fit into
	// the mantissa of a (32-bit) float.
	COMPILE_ASSERT(sizeof(Fixed) == 2, fixed_type_should_fit_in_float_mantissa);
	float raw = static_cast<float>(x);
	return ldexpf(raw, -kShiftBits);
	}

	// Returns the maximum pixel span of a filter.
	int max_filter() const { return max_filter_; }

	// Returns the number of filters in this filter. This is the dimension of the
	// output image.
	int num_values() const { return static_cast<int>(filters_.size()); }

	// Appends the given list of scaling values for generating a given output
	// pixel. \|filter_offset\| is the distance from the edge of the image to where
	// the scaling factors start. The scaling factors apply to the source pixels
	// starting from this position, and going for the next \|filter_length\| pixels.
	//
	// You will probably want to make sure your input is normalized (that is,
	// all entries in \|filter_values\| sub to one) to prevent affecting the overall
	// brighness of the image.
	//
	// The filter_length must be > 0.
	//
	// This version will automatically convert your input to fixed point.
	SK_API void AddFilter(int filter_offset,
	const float* filter_values,
	int filter_length);

	// Same as the above version, but the input is already fixed point.
	void AddFilter(int filter_offset,
	const Fixed* filter_values,
	int filter_length);

	// Retrieves a filter for the given \|value_offset\|, a position in the output
	// image in the direction we're convolving. The offset and length of the
	// filter values are put into the corresponding out arguments (see AddFilter
	// above for what these mean), and a pointer to the first scaling factor is
	// returned. There will be \|filter_length\| values in this array.
	inline const Fixed* FilterForValue(int value_offset,
	int* filter_offset,
	int* filter_length) const {
	const FilterInstance& filter = filters_[value_offset];
	*filter_offset = filter.offset;
	*filter_length = filter.length;
	if (filter.length == 0) {
	return NULL;
	}
	return &filter_values_[filter.data_location];
	}


	inline void PaddingForSIMD(int padding_count) {
	// Padding \|padding_count\| of more dummy coefficients after the coefficients
	// of last filter to prevent SIMD instructions which load 8 or 16 bytes
	// together to access invalid memory areas. We are not trying to align the
	// coefficients right now due to the opaqueness of <vector> implementation.
	// This has to be done after all \|AddFilter\| calls.
	for (int i = 0; i < padding_count; ++i)
	filter_values_.push_back(static_cast<Fixed>(0));
	}

	private:
	struct FilterInstance {
	// Offset within filter_values for this instance of the filter.
	int data_location;

	// Distance from the left of the filter to the center. IN PIXELS
	int offset;

	// Number of values in this filter instance.
	int length;
	};

	// Stores the information for each filter added to this class.
	std::vector<FilterInstance> filters_;

	// We store all the filter values in this flat list, indexed by
	// \|FilterInstance.data_location\| to avoid the mallocs required for storing
	// each one separately.
	std::vector<Fixed> filter_values_;

	// The maximum size of any filter we've added.
	int max_filter_;
	};

	// Does a two-dimensional convolution on the given source image.
	//
	// It is assumed the source pixel offsets referenced in the input filters
	// reference only valid pixels, so the source image size is not required. Each
	// row of the source image starts \|source_byte_row_stride\| after the previous
	// one (this allows you to have rows with some padding at the end).
	//
	// The result will be put into the given output buffer. The destination image
	// size will be xfilter.num_values() * yfilter.num_values() pixels. It will be
	// in rows of exactly xfilter.num_values() * 4 bytes.
	//
	// \|source_has_alpha\| is a hint that allows us to avoid doing computations on
	// the alpha channel if the image is opaque. If you don't know, set this to
	// true and it will work properly, but setting this to false will be a few
	// percent faster if you know the image is opaque.
	//
	// The layout in memory is assumed to be 4-bytes per pixel in B-G-R-A order
	// (this is ARGB when loaded into 32-bit words on a little-endian machine).
	SK_API void BGRAConvolve2D(const unsigned char* source_data,
	int source_byte_row_stride,
	bool source_has_alpha,
	const ConvolutionFilter1D& xfilter,
	const ConvolutionFilter1D& yfilter,
	int output_byte_row_stride,
	unsigned char* output,
	bool use_sse2);
	} // namespace skia

	#endif // SKIA_EXT_CONVOLVER_H_