// 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 #include #include #include "build/build_config.h" #include "third_party/skia/include/core/SkSize.h" #include "third_party/skia/include/core/SkTypes.h" // We can build SSE2 optimized versions for all x86 CPUs // except when building for the IOS emulator. #if defined(ARCH_CPU_X86_FAMILY) && !defined(OS_IOS) #define SIMD_SSE2 1 #define SIMD_PADDING 8 // 8 * int16_t #endif #if defined (ARCH_CPU_MIPS_FAMILY) && \ defined(__mips_dsp) && (__mips_dsp_rev >= 2) #define SIMD_MIPS_DSPR2 1 #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(f * (1 << kShiftBits)); } static unsigned char FixedToChar(Fixed x) { return static_cast(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. static_assert(sizeof(Fixed) == 2, "fixed type should fit in float mantissa"); float raw = static_cast(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(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.trimmed_length; if (filter.trimmed_length == 0) { return NULL; } return &filter_values_[filter.data_location]; } // Retrieves the filter for the offset 0, presumed to be the one and only. // The offset and length of the filter values are put into the corresponding // out arguments (see AddFilter). Note that |filter_legth| and // |specified_filter_length| may be different if leading/trailing zeros of the // original floating point form were clipped. // There will be |filter_length| values in the return array. // Returns NULL if the filter is 0-length (for instance when all floating // point values passed to AddFilter were clipped to 0). SK_API const Fixed* GetSingleFilter(int* specified_filter_length, int* filter_offset, int* filter_length) const; inline void PaddingForSIMD() { // 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 implementation. // This has to be done after all |AddFilter| calls. #ifdef SIMD_PADDING for (int i = 0; i < SIMD_PADDING; ++i) filter_values_.push_back(static_cast(0)); #endif } 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 trimmed_length; // Filter length as specified. Note that this may be different from // 'trimmed_length' if leading/trailing zeros of the original floating // point form were clipped differently on each tail. int length; }; // Stores the information for each filter added to this class. std::vector 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 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_simd_if_possible); // Does a 1D convolution of the given source image along the X dimension on // a single channel of the bitmap. // // The function uses the same convolution kernel for each pixel. That kernel // must be added to |filter| at offset 0. This is a most straightforward // implementation of convolution, intended chiefly for development purposes. SK_API void SingleChannelConvolveX1D(const unsigned char* source_data, int source_byte_row_stride, int input_channel_index, int input_channel_count, const ConvolutionFilter1D& filter, const SkISize& image_size, unsigned char* output, int output_byte_row_stride, int output_channel_index, int output_channel_count, bool absolute_values); // Does a 1D convolution of the given source image along the Y dimension on // a single channel of the bitmap. SK_API void SingleChannelConvolveY1D(const unsigned char* source_data, int source_byte_row_stride, int input_channel_index, int input_channel_count, const ConvolutionFilter1D& filter, const SkISize& image_size, unsigned char* output, int output_byte_row_stride, int output_channel_index, int output_channel_count, bool absolute_values); // Set up the |filter| instance with a gaussian kernel. |kernel_sigma| is the // parameter of gaussian. If |derivative| is true, the kernel will be that of // the first derivative. Intended for use with the two routines above. SK_API void SetUpGaussianConvolutionKernel(ConvolutionFilter1D* filter, float kernel_sigma, bool derivative); } // namespace skia #endif // SKIA_EXT_CONVOLVER_H_