OLD | NEW |
---|---|
1 // Copyright (c) 2011 The Chromium Authors. All rights reserved. | 1 // Copyright (c) 2011 The Chromium Authors. All rights reserved. |
2 // Use of this source code is governed by a BSD-style license that can be | 2 // Use of this source code is governed by a BSD-style license that can be |
3 // found in the LICENSE file. | 3 // found in the LICENSE file. |
4 | 4 |
5 #include <algorithm> | 5 #include <algorithm> |
6 | 6 |
7 #include "skia/ext/convolver.h" | 7 #include "skia/ext/convolver.h" |
8 #include "skia/ext/convolver_SSE2.h" | |
8 #include "third_party/skia/include/core/SkTypes.h" | 9 #include "third_party/skia/include/core/SkTypes.h" |
9 | 10 |
10 #if defined(SIMD_SSE2) | |
11 #include <emmintrin.h> // ARCH_CPU_X86_FAMILY was defined in build/config.h | 11 #include <emmintrin.h> // ARCH_CPU_X86_FAMILY was defined in build/config.h |
12 #endif | |
13 | 12 |
14 namespace skia { | 13 namespace skia { |
15 | 14 |
16 namespace { | |
17 | |
18 // Converts the argument to an 8-bit unsigned value by clamping to the range | |
19 // 0-255. | |
20 inline unsigned char ClampTo8(int a) { | |
21 if (static_cast<unsigned>(a) < 256) | |
22 return a; // Avoid the extra check in the common case. | |
23 if (a < 0) | |
24 return 0; | |
25 return 255; | |
26 } | |
27 | |
28 // Stores a list of rows in a circular buffer. The usage is you write into it | |
29 // by calling AdvanceRow. It will keep track of which row in the buffer it | |
30 // should use next, and the total number of rows added. | |
31 class CircularRowBuffer { | |
32 public: | |
33 // The number of pixels in each row is given in |source_row_pixel_width|. | |
34 // The maximum number of rows needed in the buffer is |max_y_filter_size| | |
35 // (we only need to store enough rows for the biggest filter). | |
36 // | |
37 // We use the |first_input_row| to compute the coordinates of all of the | |
38 // following rows returned by Advance(). | |
39 CircularRowBuffer(int dest_row_pixel_width, int max_y_filter_size, | |
40 int first_input_row) | |
41 : row_byte_width_(dest_row_pixel_width * 4), | |
42 num_rows_(max_y_filter_size), | |
43 next_row_(0), | |
44 next_row_coordinate_(first_input_row) { | |
45 buffer_.resize(row_byte_width_ * max_y_filter_size); | |
46 row_addresses_.resize(num_rows_); | |
47 } | |
48 | |
49 // Moves to the next row in the buffer, returning a pointer to the beginning | |
50 // of it. | |
51 unsigned char* AdvanceRow() { | |
52 unsigned char* row = &buffer_[next_row_ * row_byte_width_]; | |
53 next_row_coordinate_++; | |
54 | |
55 // Set the pointer to the next row to use, wrapping around if necessary. | |
56 next_row_++; | |
57 if (next_row_ == num_rows_) | |
58 next_row_ = 0; | |
59 return row; | |
60 } | |
61 | |
62 // Returns a pointer to an "unrolled" array of rows. These rows will start | |
63 // at the y coordinate placed into |*first_row_index| and will continue in | |
64 // order for the maximum number of rows in this circular buffer. | |
65 // | |
66 // The |first_row_index_| may be negative. This means the circular buffer | |
67 // starts before the top of the image (it hasn't been filled yet). | |
68 unsigned char* const* GetRowAddresses(int* first_row_index) { | |
69 // Example for a 4-element circular buffer holding coords 6-9. | |
70 // Row 0 Coord 8 | |
71 // Row 1 Coord 9 | |
72 // Row 2 Coord 6 <- next_row_ = 2, next_row_coordinate_ = 10. | |
73 // Row 3 Coord 7 | |
74 // | |
75 // The "next" row is also the first (lowest) coordinate. This computation | |
76 // may yield a negative value, but that's OK, the math will work out | |
77 // since the user of this buffer will compute the offset relative | |
78 // to the first_row_index and the negative rows will never be used. | |
79 *first_row_index = next_row_coordinate_ - num_rows_; | |
80 | |
81 int cur_row = next_row_; | |
82 for (int i = 0; i < num_rows_; i++) { | |
83 row_addresses_[i] = &buffer_[cur_row * row_byte_width_]; | |
84 | |
85 // Advance to the next row, wrapping if necessary. | |
86 cur_row++; | |
87 if (cur_row == num_rows_) | |
88 cur_row = 0; | |
89 } | |
90 return &row_addresses_[0]; | |
91 } | |
92 | |
93 private: | |
94 // The buffer storing the rows. They are packed, each one row_byte_width_. | |
95 std::vector<unsigned char> buffer_; | |
96 | |
97 // Number of bytes per row in the |buffer_|. | |
98 int row_byte_width_; | |
99 | |
100 // The number of rows available in the buffer. | |
101 int num_rows_; | |
102 | |
103 // The next row index we should write into. This wraps around as the | |
104 // circular buffer is used. | |
105 int next_row_; | |
106 | |
107 // The y coordinate of the |next_row_|. This is incremented each time a | |
108 // new row is appended and does not wrap. | |
109 int next_row_coordinate_; | |
110 | |
111 // Buffer used by GetRowAddresses(). | |
112 std::vector<unsigned char*> row_addresses_; | |
113 }; | |
114 | |
115 // Convolves horizontally along a single row. The row data is given in | |
116 // |src_data| and continues for the num_values() of the filter. | |
117 template<bool has_alpha> | |
118 void ConvolveHorizontally(const unsigned char* src_data, | |
119 const ConvolutionFilter1D& filter, | |
120 unsigned char* out_row) { | |
121 // Loop over each pixel on this row in the output image. | |
122 int num_values = filter.num_values(); | |
123 for (int out_x = 0; out_x < num_values; out_x++) { | |
124 // Get the filter that determines the current output pixel. | |
125 int filter_offset, filter_length; | |
126 const ConvolutionFilter1D::Fixed* filter_values = | |
127 filter.FilterForValue(out_x, &filter_offset, &filter_length); | |
128 | |
129 // Compute the first pixel in this row that the filter affects. It will | |
130 // touch |filter_length| pixels (4 bytes each) after this. | |
131 const unsigned char* row_to_filter = &src_data[filter_offset * 4]; | |
132 | |
133 // Apply the filter to the row to get the destination pixel in |accum|. | |
134 int accum[4] = {0}; | |
135 for (int filter_x = 0; filter_x < filter_length; filter_x++) { | |
136 ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_x]; | |
137 accum[0] += cur_filter * row_to_filter[filter_x * 4 + 0]; | |
138 accum[1] += cur_filter * row_to_filter[filter_x * 4 + 1]; | |
139 accum[2] += cur_filter * row_to_filter[filter_x * 4 + 2]; | |
140 if (has_alpha) | |
141 accum[3] += cur_filter * row_to_filter[filter_x * 4 + 3]; | |
142 } | |
143 | |
144 // Bring this value back in range. All of the filter scaling factors | |
145 // are in fixed point with kShiftBits bits of fractional part. | |
146 accum[0] >>= ConvolutionFilter1D::kShiftBits; | |
147 accum[1] >>= ConvolutionFilter1D::kShiftBits; | |
148 accum[2] >>= ConvolutionFilter1D::kShiftBits; | |
149 if (has_alpha) | |
150 accum[3] >>= ConvolutionFilter1D::kShiftBits; | |
151 | |
152 // Store the new pixel. | |
153 out_row[out_x * 4 + 0] = ClampTo8(accum[0]); | |
154 out_row[out_x * 4 + 1] = ClampTo8(accum[1]); | |
155 out_row[out_x * 4 + 2] = ClampTo8(accum[2]); | |
156 if (has_alpha) | |
157 out_row[out_x * 4 + 3] = ClampTo8(accum[3]); | |
158 } | |
159 } | |
160 | |
161 // Does vertical convolution to produce one output row. The filter values and | |
162 // length are given in the first two parameters. These are applied to each | |
163 // of the rows pointed to in the |source_data_rows| array, with each row | |
164 // being |pixel_width| wide. | |
165 // | |
166 // The output must have room for |pixel_width * 4| bytes. | |
167 template<bool has_alpha> | |
168 void ConvolveVertically(const ConvolutionFilter1D::Fixed* filter_values, | |
169 int filter_length, | |
170 unsigned char* const* source_data_rows, | |
171 int pixel_width, | |
172 unsigned char* out_row) { | |
173 // We go through each column in the output and do a vertical convolution, | |
174 // generating one output pixel each time. | |
175 for (int out_x = 0; out_x < pixel_width; out_x++) { | |
176 // Compute the number of bytes over in each row that the current column | |
177 // we're convolving starts at. The pixel will cover the next 4 bytes. | |
178 int byte_offset = out_x * 4; | |
179 | |
180 // Apply the filter to one column of pixels. | |
181 int accum[4] = {0}; | |
182 for (int filter_y = 0; filter_y < filter_length; filter_y++) { | |
183 ConvolutionFilter1D::Fixed cur_filter = filter_values[filter_y]; | |
184 accum[0] += cur_filter * source_data_rows[filter_y][byte_offset + 0]; | |
185 accum[1] += cur_filter * source_data_rows[filter_y][byte_offset + 1]; | |
186 accum[2] += cur_filter * source_data_rows[filter_y][byte_offset + 2]; | |
187 if (has_alpha) | |
188 accum[3] += cur_filter * source_data_rows[filter_y][byte_offset + 3]; | |
189 } | |
190 | |
191 // Bring this value back in range. All of the filter scaling factors | |
192 // are in fixed point with kShiftBits bits of precision. | |
193 accum[0] >>= ConvolutionFilter1D::kShiftBits; | |
194 accum[1] >>= ConvolutionFilter1D::kShiftBits; | |
195 accum[2] >>= ConvolutionFilter1D::kShiftBits; | |
196 if (has_alpha) | |
197 accum[3] >>= ConvolutionFilter1D::kShiftBits; | |
198 | |
199 // Store the new pixel. | |
200 out_row[byte_offset + 0] = ClampTo8(accum[0]); | |
201 out_row[byte_offset + 1] = ClampTo8(accum[1]); | |
202 out_row[byte_offset + 2] = ClampTo8(accum[2]); | |
203 if (has_alpha) { | |
204 unsigned char alpha = ClampTo8(accum[3]); | |
205 | |
206 // Make sure the alpha channel doesn't come out smaller than any of the | |
207 // color channels. We use premultipled alpha channels, so this should | |
208 // never happen, but rounding errors will cause this from time to time. | |
209 // These "impossible" colors will cause overflows (and hence random pixel | |
210 // values) when the resulting bitmap is drawn to the screen. | |
211 // | |
212 // We only need to do this when generating the final output row (here). | |
213 int max_color_channel = std::max(out_row[byte_offset + 0], | |
214 std::max(out_row[byte_offset + 1], out_row[byte_offset + 2])); | |
215 if (alpha < max_color_channel) | |
216 out_row[byte_offset + 3] = max_color_channel; | |
217 else | |
218 out_row[byte_offset + 3] = alpha; | |
219 } else { | |
220 // No alpha channel, the image is opaque. | |
221 out_row[byte_offset + 3] = 0xff; | |
222 } | |
223 } | |
224 } | |
225 | |
226 | |
227 // Convolves horizontally along a single row. The row data is given in | 15 // Convolves horizontally along a single row. The row data is given in |
228 // |src_data| and continues for the num_values() of the filter. | 16 // |src_data| and continues for the num_values() of the filter. |
229 void ConvolveHorizontally_SSE2(const unsigned char* src_data, | 17 void ConvolveHorizontally_SSE2(const unsigned char* src_data, |
230 const ConvolutionFilter1D& filter, | 18 const ConvolutionFilter1D& filter, |
231 unsigned char* out_row) { | 19 unsigned char* out_row) { |
232 #if defined(SIMD_SSE2) | |
233 int num_values = filter.num_values(); | 20 int num_values = filter.num_values(); |
234 | 21 |
235 int filter_offset, filter_length; | 22 int filter_offset, filter_length; |
236 __m128i zero = _mm_setzero_si128(); | 23 __m128i zero = _mm_setzero_si128(); |
237 __m128i mask[4]; | 24 __m128i mask[4]; |
238 // |mask| will be used to decimate all extra filter coefficients that are | 25 // |mask| will be used to decimate all extra filter coefficients that are |
239 // loaded by SIMD when |filter_length| is not divisible by 4. | 26 // loaded by SIMD when |filter_length| is not divisible by 4. |
240 // mask[0] is not used in following algorithm. | 27 // mask[0] is not used in following algorithm. |
241 mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1); | 28 mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1); |
242 mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1); | 29 mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1); |
(...skipping 100 matching lines...) Expand 10 before | Expand all | Expand 10 after Loading... | |
343 | 130 |
344 // Packing 32 bits |accum| to 16 bits per channel (signed saturation). | 131 // Packing 32 bits |accum| to 16 bits per channel (signed saturation). |
345 accum = _mm_packs_epi32(accum, zero); | 132 accum = _mm_packs_epi32(accum, zero); |
346 // Packing 16 bits |accum| to 8 bits per channel (unsigned saturation). | 133 // Packing 16 bits |accum| to 8 bits per channel (unsigned saturation). |
347 accum = _mm_packus_epi16(accum, zero); | 134 accum = _mm_packus_epi16(accum, zero); |
348 | 135 |
349 // Store the pixel value of 32 bits. | 136 // Store the pixel value of 32 bits. |
350 *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum); | 137 *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum); |
351 out_row += 4; | 138 out_row += 4; |
352 } | 139 } |
353 #endif | |
354 } | 140 } |
355 | 141 |
356 // Convolves horizontally along four rows. The row data is given in | 142 // Convolves horizontally along four rows. The row data is given in |
357 // |src_data| and continues for the num_values() of the filter. | 143 // |src_data| and continues for the num_values() of the filter. |
358 // The algorithm is almost same as |ConvolveHorizontally_SSE2|. Please | 144 // The algorithm is almost same as |ConvolveHorizontally_SSE2|. Please |
359 // refer to that function for detailed comments. | 145 // refer to that function for detailed comments. |
360 void ConvolveHorizontally4_SSE2(const unsigned char* src_data[4], | 146 void Convolve4RowsHorizontally_SSE2(const unsigned char* src_data[4], |
361 const ConvolutionFilter1D& filter, | 147 const ConvolutionFilter1D& filter, |
362 unsigned char* out_row[4]) { | 148 unsigned char* out_row[4]) { |
363 #if defined(SIMD_SSE2) | |
364 int num_values = filter.num_values(); | 149 int num_values = filter.num_values(); |
365 | 150 |
366 int filter_offset, filter_length; | 151 int filter_offset, filter_length; |
367 __m128i zero = _mm_setzero_si128(); | 152 __m128i zero = _mm_setzero_si128(); |
368 __m128i mask[4]; | 153 __m128i mask[4]; |
369 // |mask| will be used to decimate all extra filter coefficients that are | 154 // |mask| will be used to decimate all extra filter coefficients that are |
370 // loaded by SIMD when |filter_length| is not divisible by 4. | 155 // loaded by SIMD when |filter_length| is not divisible by 4. |
371 // mask[0] is not used in following algorithm. | 156 // mask[0] is not used in following algorithm. |
372 mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1); | 157 mask[1] = _mm_set_epi16(0, 0, 0, 0, 0, 0, 0, -1); |
373 mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1); | 158 mask[2] = _mm_set_epi16(0, 0, 0, 0, 0, 0, -1, -1); |
(...skipping 90 matching lines...) Expand 10 before | Expand all | Expand 10 after Loading... | |
464 *(reinterpret_cast<int*>(out_row[0])) = _mm_cvtsi128_si32(accum0); | 249 *(reinterpret_cast<int*>(out_row[0])) = _mm_cvtsi128_si32(accum0); |
465 *(reinterpret_cast<int*>(out_row[1])) = _mm_cvtsi128_si32(accum1); | 250 *(reinterpret_cast<int*>(out_row[1])) = _mm_cvtsi128_si32(accum1); |
466 *(reinterpret_cast<int*>(out_row[2])) = _mm_cvtsi128_si32(accum2); | 251 *(reinterpret_cast<int*>(out_row[2])) = _mm_cvtsi128_si32(accum2); |
467 *(reinterpret_cast<int*>(out_row[3])) = _mm_cvtsi128_si32(accum3); | 252 *(reinterpret_cast<int*>(out_row[3])) = _mm_cvtsi128_si32(accum3); |
468 | 253 |
469 out_row[0] += 4; | 254 out_row[0] += 4; |
470 out_row[1] += 4; | 255 out_row[1] += 4; |
471 out_row[2] += 4; | 256 out_row[2] += 4; |
472 out_row[3] += 4; | 257 out_row[3] += 4; |
473 } | 258 } |
474 #endif | |
475 } | 259 } |
476 | 260 |
477 // Does vertical convolution to produce one output row. The filter values and | 261 // Does vertical convolution to produce one output row. The filter values and |
478 // length are given in the first two parameters. These are applied to each | 262 // length are given in the first two parameters. These are applied to each |
479 // of the rows pointed to in the |source_data_rows| array, with each row | 263 // of the rows pointed to in the |source_data_rows| array, with each row |
480 // being |pixel_width| wide. | 264 // being |pixel_width| wide. |
481 // | 265 // |
482 // The output must have room for |pixel_width * 4| bytes. | 266 // The output must have room for |pixel_width * 4| bytes. |
483 template<bool has_alpha> | 267 template<bool has_alpha> |
484 void ConvolveVertically_SSE2(const ConvolutionFilter1D::Fixed* filter_values, | 268 void ConvolveVertically_SSE2(const ConvolutionFilter1D::Fixed* filter_values, |
485 int filter_length, | 269 int filter_length, |
486 unsigned char* const* source_data_rows, | 270 unsigned char* const* source_data_rows, |
487 int pixel_width, | 271 int pixel_width, |
488 unsigned char* out_row) { | 272 unsigned char* out_row) { |
489 #if defined(SIMD_SSE2) | |
490 int width = pixel_width & ~3; | 273 int width = pixel_width & ~3; |
491 | 274 |
492 __m128i zero = _mm_setzero_si128(); | 275 __m128i zero = _mm_setzero_si128(); |
493 __m128i accum0, accum1, accum2, accum3, coeff16; | 276 __m128i accum0, accum1, accum2, accum3, coeff16; |
494 const __m128i* src; | 277 const __m128i* src; |
495 // Output four pixels per iteration (16 bytes). | 278 // Output four pixels per iteration (16 bytes). |
496 for (int out_x = 0; out_x < width; out_x += 4) { | 279 for (int out_x = 0; out_x < width; out_x += 4) { |
497 | 280 |
498 // Accumulated result for each pixel. 32 bits per RGBA channel. | 281 // Accumulated result for each pixel. 32 bits per RGBA channel. |
499 accum0 = _mm_setzero_si128(); | 282 accum0 = _mm_setzero_si128(); |
(...skipping 140 matching lines...) Expand 10 before | Expand all | Expand 10 after Loading... | |
640 __m128i mask = _mm_set1_epi32(0xff000000); | 423 __m128i mask = _mm_set1_epi32(0xff000000); |
641 accum0 = _mm_or_si128(accum0, mask); | 424 accum0 = _mm_or_si128(accum0, mask); |
642 } | 425 } |
643 | 426 |
644 for (int out_x = width; out_x < pixel_width; out_x++) { | 427 for (int out_x = width; out_x < pixel_width; out_x++) { |
645 *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum0); | 428 *(reinterpret_cast<int*>(out_row)) = _mm_cvtsi128_si32(accum0); |
646 accum0 = _mm_srli_si128(accum0, 4); | 429 accum0 = _mm_srli_si128(accum0, 4); |
647 out_row += 4; | 430 out_row += 4; |
648 } | 431 } |
649 } | 432 } |
650 #endif | |
651 } | |
652 | |
653 } // namespace | |
654 | |
655 // ConvolutionFilter1D --------------------------------------------------------- | |
656 | |
657 ConvolutionFilter1D::ConvolutionFilter1D() | |
658 : max_filter_(0) { | |
659 } | |
660 | |
661 ConvolutionFilter1D::~ConvolutionFilter1D() { | |
662 } | |
663 | |
664 void ConvolutionFilter1D::AddFilter(int filter_offset, | |
665 const float* filter_values, | |
666 int filter_length) { | |
667 SkASSERT(filter_length > 0); | |
668 | |
669 std::vector<Fixed> fixed_values; | |
670 fixed_values.reserve(filter_length); | |
671 | |
672 for (int i = 0; i < filter_length; ++i) | |
673 fixed_values.push_back(FloatToFixed(filter_values[i])); | |
674 | |
675 AddFilter(filter_offset, &fixed_values[0], filter_length); | |
676 } | |
677 | |
678 void ConvolutionFilter1D::AddFilter(int filter_offset, | |
679 const Fixed* filter_values, | |
680 int filter_length) { | |
681 // It is common for leading/trailing filter values to be zeros. In such | |
682 // cases it is beneficial to only store the central factors. | |
683 // For a scaling to 1/4th in each dimension using a Lanczos-2 filter on | |
684 // a 1080p image this optimization gives a ~10% speed improvement. | |
685 int first_non_zero = 0; | |
686 while (first_non_zero < filter_length && filter_values[first_non_zero] == 0) | |
687 first_non_zero++; | |
688 | |
689 if (first_non_zero < filter_length) { | |
690 // Here we have at least one non-zero factor. | |
691 int last_non_zero = filter_length - 1; | |
692 while (last_non_zero >= 0 && filter_values[last_non_zero] == 0) | |
693 last_non_zero--; | |
694 | |
695 filter_offset += first_non_zero; | |
696 filter_length = last_non_zero + 1 - first_non_zero; | |
697 SkASSERT(filter_length > 0); | |
698 | |
699 for (int i = first_non_zero; i <= last_non_zero; i++) | |
700 filter_values_.push_back(filter_values[i]); | |
701 } else { | |
702 // Here all the factors were zeroes. | |
703 filter_length = 0; | |
704 } | |
705 | |
706 FilterInstance instance; | |
707 | |
708 // We pushed filter_length elements onto filter_values_ | |
709 instance.data_location = (static_cast<int>(filter_values_.size()) - | |
710 filter_length); | |
711 instance.offset = filter_offset; | |
712 instance.length = filter_length; | |
713 filters_.push_back(instance); | |
714 | |
715 max_filter_ = std::max(max_filter_, filter_length); | |
716 } | |
717 | |
718 void BGRAConvolve2D(const unsigned char* source_data, | |
719 int source_byte_row_stride, | |
720 bool source_has_alpha, | |
721 const ConvolutionFilter1D& filter_x, | |
722 const ConvolutionFilter1D& filter_y, | |
723 int output_byte_row_stride, | |
724 unsigned char* output, | |
725 bool use_sse2) { | |
726 #if !defined(SIMD_SSE2) | |
727 // Even we have runtime support for SSE2 instructions, since the binary | |
728 // was not built with SSE2 support, we had to fallback to C version. | |
729 use_sse2 = false; | |
730 #endif | |
731 | |
732 int max_y_filter_size = filter_y.max_filter(); | |
733 | |
734 // The next row in the input that we will generate a horizontally | |
735 // convolved row for. If the filter doesn't start at the beginning of the | |
736 // image (this is the case when we are only resizing a subset), then we | |
737 // don't want to generate any output rows before that. Compute the starting | |
738 // row for convolution as the first pixel for the first vertical filter. | |
739 int filter_offset, filter_length; | |
740 const ConvolutionFilter1D::Fixed* filter_values = | |
741 filter_y.FilterForValue(0, &filter_offset, &filter_length); | |
742 int next_x_row = filter_offset; | |
743 | |
744 // We loop over each row in the input doing a horizontal convolution. This | |
745 // will result in a horizontally convolved image. We write the results into | |
746 // a circular buffer of convolved rows and do vertical convolution as rows | |
747 // are available. This prevents us from having to store the entire | |
748 // intermediate image and helps cache coherency. | |
749 // We will need four extra rows to allow horizontal convolution could be done | |
750 // simultaneously. We also padding each row in row buffer to be aligned-up to | |
751 // 16 bytes. | |
752 // TODO(jiesun): We do not use aligned load from row buffer in vertical | |
753 // convolution pass yet. Somehow Windows does not like it. | |
754 int row_buffer_width = (filter_x.num_values() + 15) & ~0xF; | |
755 int row_buffer_height = max_y_filter_size + (use_sse2 ? 4 : 0); | |
756 CircularRowBuffer row_buffer(row_buffer_width, | |
757 row_buffer_height, | |
758 filter_offset); | |
759 | |
760 // Loop over every possible output row, processing just enough horizontal | |
761 // convolutions to run each subsequent vertical convolution. | |
762 SkASSERT(output_byte_row_stride >= filter_x.num_values() * 4); | |
763 int num_output_rows = filter_y.num_values(); | |
764 | |
765 // We need to check which is the last line to convolve before we advance 4 | |
766 // lines in one iteration. | |
767 int last_filter_offset, last_filter_length; | |
768 | |
769 // SSE2 can access up to 3 extra pixels past the end of the | |
770 // buffer. At the bottom of the image, we have to be careful | |
771 // not to access data past the end of the buffer. Normally | |
772 // we fall back to the C++ implementation for the last row. | |
773 // If the last row is less than 3 pixels wide, we may have to fall | |
774 // back to the C++ version for more rows. Compute how many | |
775 // rows we need to avoid the SSE implementation for here. | |
776 filter_x.FilterForValue(filter_x.num_values() - 1, &last_filter_offset, | |
777 &last_filter_length); | |
778 int avoid_sse_rows = 1 + 3/(last_filter_offset + last_filter_length); | |
779 | |
780 filter_y.FilterForValue(num_output_rows - 1, &last_filter_offset, | |
781 &last_filter_length); | |
782 | |
783 for (int out_y = 0; out_y < num_output_rows; out_y++) { | |
784 filter_values = filter_y.FilterForValue(out_y, | |
785 &filter_offset, &filter_length); | |
786 | |
787 // Generate output rows until we have enough to run the current filter. | |
788 if (use_sse2) { | |
789 while (next_x_row < filter_offset + filter_length) { | |
790 if (next_x_row + 3 < last_filter_offset + last_filter_length - | |
791 avoid_sse_rows) { | |
792 const unsigned char* src[4]; | |
793 unsigned char* out_row[4]; | |
794 for (int i = 0; i < 4; ++i) { | |
795 src[i] = &source_data[(next_x_row + i) * source_byte_row_stride]; | |
796 out_row[i] = row_buffer.AdvanceRow(); | |
797 } | |
798 ConvolveHorizontally4_SSE2(src, filter_x, out_row); | |
799 next_x_row += 4; | |
800 } else { | |
801 // Check if we need to avoid SSE2 for this row. | |
802 if (next_x_row >= last_filter_offset + last_filter_length - | |
803 avoid_sse_rows) { | |
804 if (source_has_alpha) { | |
805 ConvolveHorizontally<true>( | |
806 &source_data[next_x_row * source_byte_row_stride], | |
807 filter_x, row_buffer.AdvanceRow()); | |
808 } else { | |
809 ConvolveHorizontally<false>( | |
810 &source_data[next_x_row * source_byte_row_stride], | |
811 filter_x, row_buffer.AdvanceRow()); | |
812 } | |
813 } else { | |
814 ConvolveHorizontally_SSE2( | |
815 &source_data[next_x_row * source_byte_row_stride], | |
816 filter_x, row_buffer.AdvanceRow()); | |
817 } | |
818 next_x_row++; | |
819 } | |
820 } | |
821 } else { | |
822 while (next_x_row < filter_offset + filter_length) { | |
823 if (source_has_alpha) { | |
824 ConvolveHorizontally<true>( | |
825 &source_data[next_x_row * source_byte_row_stride], | |
826 filter_x, row_buffer.AdvanceRow()); | |
827 } else { | |
828 ConvolveHorizontally<false>( | |
829 &source_data[next_x_row * source_byte_row_stride], | |
830 filter_x, row_buffer.AdvanceRow()); | |
831 } | |
832 next_x_row++; | |
833 } | |
834 } | |
835 | |
836 // Compute where in the output image this row of final data will go. | |
837 unsigned char* cur_output_row = &output[out_y * output_byte_row_stride]; | |
838 | |
839 // Get the list of rows that the circular buffer has, in order. | |
840 int first_row_in_circular_buffer; | |
841 unsigned char* const* rows_to_convolve = | |
842 row_buffer.GetRowAddresses(&first_row_in_circular_buffer); | |
843 | |
844 // Now compute the start of the subset of those rows that the filter | |
845 // needs. | |
846 unsigned char* const* first_row_for_filter = | |
847 &rows_to_convolve[filter_offset - first_row_in_circular_buffer]; | |
848 | |
849 if (source_has_alpha) { | |
850 if (use_sse2) { | |
851 ConvolveVertically_SSE2<true>(filter_values, filter_length, | |
852 first_row_for_filter, | |
853 filter_x.num_values(), cur_output_row); | |
854 } else { | |
855 ConvolveVertically<true>(filter_values, filter_length, | |
856 first_row_for_filter, | |
857 filter_x.num_values(), cur_output_row); | |
858 } | |
859 } else { | |
860 if (use_sse2) { | |
861 ConvolveVertically_SSE2<false>(filter_values, filter_length, | |
862 first_row_for_filter, | |
863 filter_x.num_values(), cur_output_row); | |
864 } else { | |
865 ConvolveVertically<false>(filter_values, filter_length, | |
866 first_row_for_filter, | |
867 filter_x.num_values(), cur_output_row); | |
868 } | |
869 } | |
870 } | |
871 } | 433 } |
872 | 434 |
435 void ConvolveVertically_SSE2(const ConvolutionFilter1D::Fixed* filter_values, | |
Stephen White
2013/04/05 08:40:47
It might be a good idea to add a similar wrapper f
hubbe
2013/04/06 20:45:46
Done.
| |
436 int filter_length, | |
437 unsigned char* const* source_data_rows, | |
438 int pixel_width, | |
439 unsigned char* out_row, | |
440 bool has_alpha) { | |
441 if (has_alpha) { | |
442 ConvolveVertically_SSE2<true>(filter_values, | |
443 filter_length, | |
444 source_data_rows, | |
445 pixel_width, | |
446 out_row); | |
447 } else { | |
448 ConvolveVertically_SSE2<false>(filter_values, | |
449 filter_length, | |
450 source_data_rows, | |
451 pixel_width, | |
452 out_row); | |
453 } | |
454 } | |
455 | |
873 } // namespace skia | 456 } // namespace skia |
OLD | NEW |