1a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora// Copyright 2011 Google Inc. All Rights Reserved. 27c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// 30406ce1417f76f2034833414dcecc9f56253640cVikas Arora// Use of this source code is governed by a BSD-style license 40406ce1417f76f2034833414dcecc9f56253640cVikas Arora// that can be found in the COPYING file in the root of the source 50406ce1417f76f2034833414dcecc9f56253640cVikas Arora// tree. An additional intellectual property rights grant can be found 60406ce1417f76f2034833414dcecc9f56253640cVikas Arora// in the file PATENTS. All contributing project authors may 70406ce1417f76f2034833414dcecc9f56253640cVikas Arora// be found in the AUTHORS file in the root of the source tree. 87c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// ----------------------------------------------------------------------------- 97c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// 107c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Macroblock analysis 117c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// 127c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Author: Skal (pascal.massimino@gmail.com) 137c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 147c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#include <stdlib.h> 157c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#include <string.h> 167c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#include <assert.h> 177c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 18a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora#include "./vp8enci.h" 19a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora#include "./cost.h" 20a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora#include "../utils/utils.h" 217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_ITERS_K_MEANS 6 237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 24a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora//------------------------------------------------------------------------------ 257c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Smooth the segment map by replacing isolated block by the majority of its 267c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// neighbours. 277c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 287c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void SmoothSegmentMap(VP8Encoder* const enc) { 297c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int n, x, y; 307c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int w = enc->mb_w_; 317c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int h = enc->mb_h_; 327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int majority_cnt_3_x_3_grid = 5; 3333f74dabbc7920a65ed435d7417987589febdc16Vikas Arora uint8_t* const tmp = (uint8_t*)WebPSafeMalloc(w * h, sizeof(*tmp)); 34a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora assert((uint64_t)(w * h) == (uint64_t)w * h); // no overflow, as per spec 357c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 367c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (tmp == NULL) return; 377c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (y = 1; y < h - 1; ++y) { 387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (x = 1; x < w - 1; ++x) { 397c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int cnt[NUM_MB_SEGMENTS] = { 0 }; 407c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const VP8MBInfo* const mb = &enc->mb_info_[x + w * y]; 417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int majority_seg = mb->segment_; 427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Check the 8 neighbouring segment values. 437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora cnt[mb[-w - 1].segment_]++; // top-left 447c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora cnt[mb[-w + 0].segment_]++; // top 457c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora cnt[mb[-w + 1].segment_]++; // top-right 46466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ - 1].segment_]++; // left 47466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ + 1].segment_]++; // right 48466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ w - 1].segment_]++; // bottom-left 49466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ w + 0].segment_]++; // bottom 50466727975bcc57c0c5597bcd0747a2fe4777b303Vikas Arora cnt[mb[ w + 1].segment_]++; // bottom-right 517c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < NUM_MB_SEGMENTS; ++n) { 527c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (cnt[n] >= majority_cnt_3_x_3_grid) { 537c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora majority_seg = n; 548b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora break; 557c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 567c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 577c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora tmp[x + y * w] = majority_seg; 587c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 597c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (y = 1; y < h - 1; ++y) { 617c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (x = 1; x < w - 1; ++x) { 627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MBInfo* const mb = &enc->mb_info_[x + w * y]; 637c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora mb->segment_ = tmp[x + y * w]; 647c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 657c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 6633f74dabbc7920a65ed435d7417987589febdc16Vikas Arora WebPSafeFree(tmp); 677c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 687c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 69a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora//------------------------------------------------------------------------------ 701e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora// set segment susceptibility alpha_ / beta_ 717c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 72a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arorastatic WEBP_INLINE int clip(int v, int m, int M) { 731e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora return (v < m) ? m : (v > M) ? M : v; 747c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 757c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 767c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void SetSegmentAlphas(VP8Encoder* const enc, 777c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int centers[NUM_MB_SEGMENTS], 787c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mid) { 797c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int nb = enc->segment_hdr_.num_segments_; 807c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int min = centers[0], max = centers[0]; 817c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int n; 827c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 837c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (nb > 1) { 847c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 857c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (min > centers[n]) min = centers[n]; 867c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (max < centers[n]) max = centers[n]; 877c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 887c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 897c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (max == min) max = min + 1; 907c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora assert(mid <= max && mid >= min); 917c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 927c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int alpha = 255 * (centers[n] - mid) / (max - min); 937c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int beta = 255 * (centers[n] - min) / (max - min); 947c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->dqm_[n].alpha_ = clip(alpha, -127, 127); 957c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora enc->dqm_[n].beta_ = clip(beta, 0, 255); 967c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 977c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 987c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 99a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora//------------------------------------------------------------------------------ 1001e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora// Compute susceptibility based on DCT-coeff histograms: 1011e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora// the higher, the "easier" the macroblock is to compress. 1021e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 1031e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora#define MAX_ALPHA 255 // 8b of precision for susceptibilities. 1041e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora#define ALPHA_SCALE (2 * MAX_ALPHA) // scaling factor for alpha. 1051e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora#define DEFAULT_ALPHA (-1) 1061e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora#define IS_BETTER_ALPHA(alpha, best_alpha) ((alpha) > (best_alpha)) 1071e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 1081e7bf8805bd030c19924a5306837ecd72c295751Vikas Arorastatic int FinalAlphaValue(int alpha) { 1091e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora alpha = MAX_ALPHA - alpha; 1101e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora return clip(alpha, 0, MAX_ALPHA); 1111e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora} 1121e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 1131e7bf8805bd030c19924a5306837ecd72c295751Vikas Arorastatic int GetAlpha(const VP8Histogram* const histo) { 1141e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int max_value = 0, last_non_zero = 1; 1151e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int k; 1161e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alpha; 1171e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora for (k = 0; k <= MAX_COEFF_THRESH; ++k) { 1181e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora const int value = histo->distribution[k]; 1191e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (value > 0) { 1201e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (value > max_value) max_value = value; 1211e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora last_non_zero = k; 1221e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } 1231e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } 1241e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // 'alpha' will later be clipped to [0..MAX_ALPHA] range, clamping outer 1251e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // values which happen to be mostly noise. This leaves the maximum precision 1261e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // for handling the useful small values which contribute most. 1271e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora alpha = (max_value > 1) ? ALPHA_SCALE * last_non_zero / max_value : 0; 1281e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora return alpha; 1291e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora} 1301e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 1311e7bf8805bd030c19924a5306837ecd72c295751Vikas Arorastatic void MergeHistograms(const VP8Histogram* const in, 1321e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram* const out) { 1331e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int i; 1341e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora for (i = 0; i <= MAX_COEFF_THRESH; ++i) { 1351e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora out->distribution[i] += in->distribution[i]; 1361e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } 1371e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora} 1381e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 1391e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora//------------------------------------------------------------------------------ 1407c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Simplified k-Means, to assign Nb segments based on alpha-histogram 1417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1421e7bf8805bd030c19924a5306837ecd72c295751Vikas Arorastatic void AssignSegments(VP8Encoder* const enc, 1431e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora const int alphas[MAX_ALPHA + 1]) { 1448c098653157979e397d3954fc2ea0ee43bae6ab2Vikas Arora // 'num_segments_' is previously validated and <= NUM_MB_SEGMENTS, but an 1458c098653157979e397d3954fc2ea0ee43bae6ab2Vikas Arora // explicit check is needed to avoid spurious warning about 'n + 1' exceeding 1468c098653157979e397d3954fc2ea0ee43bae6ab2Vikas Arora // array bounds of 'centers' with some compilers (noticed with gcc-4.9). 1478c098653157979e397d3954fc2ea0ee43bae6ab2Vikas Arora const int nb = (enc->segment_hdr_.num_segments_ < NUM_MB_SEGMENTS) ? 1488c098653157979e397d3954fc2ea0ee43bae6ab2Vikas Arora enc->segment_hdr_.num_segments_ : NUM_MB_SEGMENTS; 1497c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int centers[NUM_MB_SEGMENTS]; 150a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora int weighted_average = 0; 1511e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int map[MAX_ALPHA + 1]; 1527c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int a, n, k; 1531e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int min_a = 0, max_a = MAX_ALPHA, range_a; 1547c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // 'int' type is ok for histo, and won't overflow 1557c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int accum[NUM_MB_SEGMENTS], dist_accum[NUM_MB_SEGMENTS]; 1567c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1578b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora assert(nb >= 1); 15833f74dabbc7920a65ed435d7417987589febdc16Vikas Arora assert(nb <= NUM_MB_SEGMENTS); 1598b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 1607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // bracket the input 1611e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora for (n = 0; n <= MAX_ALPHA && alphas[n] == 0; ++n) {} 1627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora min_a = n; 1631e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora for (n = MAX_ALPHA; n > min_a && alphas[n] == 0; --n) {} 1647c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora max_a = n; 1657c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora range_a = max_a - min_a; 1667c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1677c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Spread initial centers evenly 1688b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora for (k = 0, n = 1; k < nb; ++k, n += 2) { 1698b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora assert(n < 2 * nb); 1708b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora centers[k] = min_a + (n * range_a) / (2 * nb); 1717c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1727c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (k = 0; k < MAX_ITERS_K_MEANS; ++k) { // few iters are enough 1747c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int total_weight; 1757c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int displaced; 1767c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Reset stats 1777c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 1787c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora accum[n] = 0; 1797c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora dist_accum[n] = 0; 1807c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1817c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Assign nearest center for each 'a' 1827c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora n = 0; // track the nearest center for current 'a' 1837c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (a = min_a; a <= max_a; ++a) { 1847c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (alphas[a]) { 1858b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora while (n + 1 < nb && abs(a - centers[n + 1]) < abs(a - centers[n])) { 1867c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora n++; 1877c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1887c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora map[a] = n; 1897c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // accumulate contribution into best centroid 1907c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora dist_accum[n] += a * alphas[a]; 1917c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora accum[n] += alphas[a]; 1927c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1937c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1947c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // All point are classified. Move the centroids to the 1957c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // center of their respective cloud. 1967c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora displaced = 0; 1977c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average = 0; 1987c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora total_weight = 0; 1997c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 2007c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (accum[n]) { 2017c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int new_center = (dist_accum[n] + accum[n] / 2) / accum[n]; 2027c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora displaced += abs(centers[n] - new_center); 2037c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora centers[n] = new_center; 2047c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average += new_center * accum[n]; 2057c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora total_weight += accum[n]; 2067c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2077c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2087c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average = (weighted_average + total_weight / 2) / total_weight; 2097c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (displaced < 5) break; // no need to keep on looping... 2107c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2117c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2127c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Map each original value to the closest centroid 2137c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < enc->mb_w_ * enc->mb_h_; ++n) { 2147c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MBInfo* const mb = &enc->mb_info_[n]; 215a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora const int alpha = mb->alpha_; 216a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora mb->segment_ = map[alpha]; 2171e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->alpha_ = centers[map[alpha]]; // for the record. 2187c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2197c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2207c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (nb > 1) { 2217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int smooth = (enc->config_->preprocessing & 1); 2227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (smooth) SmoothSegmentMap(enc); 2237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2247c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2257c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora SetSegmentAlphas(enc, centers, weighted_average); // pick some alphas. 2267c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 2277c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 228a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora//------------------------------------------------------------------------------ 2297c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Macroblock analysis: collect histogram for each mode, deduce the maximal 2307c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// susceptibility and set best modes for this macroblock. 2317c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Segment assignment is done later. 2327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 23333f74dabbc7920a65ed435d7417987589febdc16Vikas Arora// Number of modes to inspect for alpha_ evaluation. We don't need to test all 23433f74dabbc7920a65ed435d7417987589febdc16Vikas Arora// the possible modes during the analysis phase: we risk falling into a local 23533f74dabbc7920a65ed435d7417987589febdc16Vikas Arora// optimum, or be subject to boundary effect 2367c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_INTRA16_MODE 2 2377c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_INTRA4_MODE 2 2387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_UV_MODE 2 2397c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2407c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestIntra16Mode(VP8EncIterator* const it) { 24133f74dabbc7920a65ed435d7417987589febdc16Vikas Arora const int max_mode = MAX_INTRA16_MODE; 2427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 2431e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int best_alpha = DEFAULT_ALPHA; 2447c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_mode = 0; 2457c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2467c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeLuma16Preds(it); 2477c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 2481e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram histo = { { 0 } }; 2491e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alpha; 2501e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 2511e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8CollectHistogram(it->yuv_in_ + Y_OFF, 2521e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora it->yuv_p_ + VP8I16ModeOffsets[mode], 2531e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 0, 16, &histo); 2541e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora alpha = GetAlpha(&histo); 2551e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (IS_BETTER_ALPHA(alpha, best_alpha)) { 2567c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = alpha; 2577c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode = mode; 2587c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2597c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra16Mode(it, best_mode); 2617c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 2627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 2637c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2647c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestIntra4Mode(VP8EncIterator* const it, 2657c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_alpha) { 266a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora uint8_t modes[16]; 26733f74dabbc7920a65ed435d7417987589febdc16Vikas Arora const int max_mode = MAX_INTRA4_MODE; 2681e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int i4_alpha; 2691e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram total_histo = { { 0 } }; 2701e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int cur_histo = 0; 2711e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 2727c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8IteratorStartI4(it); 2737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora do { 2747c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 2751e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int best_mode_alpha = DEFAULT_ALPHA; 2761e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram histos[2]; 2777c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const uint8_t* const src = it->yuv_in_ + Y_OFF + VP8Scan[it->i4_]; 2787c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2797c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeIntra4Preds(it); 2807c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 2811e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alpha; 2821e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 2831e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora memset(&histos[cur_histo], 0, sizeof(histos[cur_histo])); 2841e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8CollectHistogram(src, it->yuv_p_ + VP8I4ModeOffsets[mode], 2851e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 0, 1, &histos[cur_histo]); 2861e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora alpha = GetAlpha(&histos[cur_histo]); 2871e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (IS_BETTER_ALPHA(alpha, best_mode_alpha)) { 2887c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode_alpha = alpha; 2897c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora modes[it->i4_] = mode; 2901e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora cur_histo ^= 1; // keep track of best histo so far. 2917c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2927c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2931e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // accumulate best histogram 2941e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora MergeHistograms(&histos[cur_histo ^ 1], &total_histo); 2957c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Note: we reuse the original samples for predictors 2967c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } while (VP8IteratorRotateI4(it, it->yuv_in_ + Y_OFF)); 2977c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2981e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora i4_alpha = GetAlpha(&total_histo); 2991e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (IS_BETTER_ALPHA(i4_alpha, best_alpha)) { 3007c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra4Mode(it, modes); 3011e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora best_alpha = i4_alpha; 3027c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3037c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 3047c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3057c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3067c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestUVMode(VP8EncIterator* const it) { 3071e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int best_alpha = DEFAULT_ALPHA; 3087c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_mode = 0; 30933f74dabbc7920a65ed435d7417987589febdc16Vikas Arora const int max_mode = MAX_UV_MODE; 3107c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 31133f74dabbc7920a65ed435d7417987589febdc16Vikas Arora 3127c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeChroma8Preds(it); 3137c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 3141e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram histo = { { 0 } }; 3151e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alpha; 3161e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8CollectHistogram(it->yuv_in_ + U_OFF, 3171e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora it->yuv_p_ + VP8UVModeOffsets[mode], 3181e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 16, 16 + 4 + 4, &histo); 3191e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora alpha = GetAlpha(&histo); 3201e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (IS_BETTER_ALPHA(alpha, best_alpha)) { 3217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = alpha; 3227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode = mode; 3237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3247c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3257c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntraUVMode(it, best_mode); 3267c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 3277c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3287c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3297c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void MBAnalyze(VP8EncIterator* const it, 3301e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alphas[MAX_ALPHA + 1], 3311e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int* const alpha, int* const uv_alpha) { 3327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const VP8Encoder* const enc = it->enc_; 3337c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_alpha, best_uv_alpha; 3347c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3357c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra16Mode(it, 0); // default: Intra16, DC_PRED 3367c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetSkip(it, 0); // not skipped 3377c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetSegment(it, 0); // default segment, spec-wise. 3387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3397c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = MBAnalyzeBestIntra16Mode(it); 3401e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (enc->method_ >= 5) { 3417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // We go and make a fast decision for intra4/intra16. 3427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // It's usually not a good and definitive pick, but helps seeding the stats 3437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // about level bit-cost. 3447c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // TODO(skal): improve criterion. 3457c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = MBAnalyzeBestIntra4Mode(it, best_alpha); 3467c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3477c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_uv_alpha = MBAnalyzeBestUVMode(it); 3487c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3497c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Final susceptibility mix 3501e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora best_alpha = (3 * best_alpha + best_uv_alpha + 2) >> 2; 3511e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora best_alpha = FinalAlphaValue(best_alpha); 3527c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora alphas[best_alpha]++; 3531e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora it->mb_->alpha_ = best_alpha; // for later remapping. 3541e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 3551e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // Accumulate for later complexity analysis. 3561e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora *alpha += best_alpha; // mixed susceptibility (not just luma) 3577c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora *uv_alpha += best_uv_alpha; 3581e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora} 3591e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 3601e7bf8805bd030c19924a5306837ecd72c295751Vikas Arorastatic void DefaultMBInfo(VP8MBInfo* const mb) { 3611e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->type_ = 1; // I16x16 3621e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->uv_mode_ = 0; 3631e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->skip_ = 0; // not skipped 3641e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->segment_ = 0; // default segment 3651e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->alpha_ = 0; 3667c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3677c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 368a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora//------------------------------------------------------------------------------ 3697c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Main analysis loop: 3707c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Collect all susceptibilities for each macroblock and record their 3717c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// distribution in alphas[]. Segments is assigned a-posteriori, based on 3727c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// this histogram. 3737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// We also pick an intra16 prediction mode, which shouldn't be considered 3747c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// final except for fast-encode settings. We can also pick some intra4 modes 3757c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// and decide intra4/intra16, but that's usually almost always a bad choice at 3767c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// this stage. 3777c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3781e7bf8805bd030c19924a5306837ecd72c295751Vikas Arorastatic void ResetAllMBInfo(VP8Encoder* const enc) { 3791e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int n; 3801e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora for (n = 0; n < enc->mb_w_ * enc->mb_h_; ++n) { 3811e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora DefaultMBInfo(&enc->mb_info_[n]); 3821e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } 3831e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // Default susceptibilities. 3841e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora enc->dqm_[0].alpha_ = 0; 3851e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora enc->dqm_[0].beta_ = 0; 3868b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // Note: we can't compute this alpha_ / uv_alpha_ -> set to default value. 3878b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora enc->alpha_ = 0; 3888b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora enc->uv_alpha_ = 0; 3891e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora WebPReportProgress(enc->pic_, enc->percent_ + 20, &enc->percent_); 3901e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora} 3911e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 3928b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora// struct used to collect job result 3938b720228d581a84fd173b6dcb2fa295b59db489aVikas Aroratypedef struct { 3948b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora WebPWorker worker; 3958b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int alphas[MAX_ALPHA + 1]; 3968b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int alpha, uv_alpha; 3978b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8EncIterator it; 3988b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int delta_progress; 3998b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora} SegmentJob; 4008b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 4018b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora// main work call 4028b720228d581a84fd173b6dcb2fa295b59db489aVikas Arorastatic int DoSegmentsJob(SegmentJob* const job, VP8EncIterator* const it) { 4038b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int ok = 1; 4048b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (!VP8IteratorIsDone(it)) { 4058b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora uint8_t tmp[32 + ALIGN_CST]; 4068b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora uint8_t* const scratch = (uint8_t*)DO_ALIGN(tmp); 4078b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora do { 4088b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // Let's pretend we have perfect lossless reconstruction. 4098b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8IteratorImport(it, scratch); 4108b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora MBAnalyze(it, job->alphas, &job->alpha, &job->uv_alpha); 4118b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora ok = VP8IteratorProgress(it, job->delta_progress); 4128b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } while (ok && VP8IteratorNext(it)); 4138b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } 4148b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora return ok; 4158b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora} 4168b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 4178b720228d581a84fd173b6dcb2fa295b59db489aVikas Arorastatic void MergeJobs(const SegmentJob* const src, SegmentJob* const dst) { 4188b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int i; 4198b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora for (i = 0; i <= MAX_ALPHA; ++i) dst->alphas[i] += src->alphas[i]; 4208b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora dst->alpha += src->alpha; 4218b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora dst->uv_alpha += src->uv_alpha; 4228b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora} 4238b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 4248b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora// initialize the job struct with some TODOs 4258b720228d581a84fd173b6dcb2fa295b59db489aVikas Arorastatic void InitSegmentJob(VP8Encoder* const enc, SegmentJob* const job, 4268b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int start_row, int end_row) { 42733f74dabbc7920a65ed435d7417987589febdc16Vikas Arora WebPGetWorkerInterface()->Init(&job->worker); 4288b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->worker.data1 = job; 4298b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->worker.data2 = &job->it; 4308b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->worker.hook = (WebPWorkerHook)DoSegmentsJob; 4318b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8IteratorInit(enc, &job->it); 4328b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8IteratorSetRow(&job->it, start_row); 4338b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8IteratorSetCountDown(&job->it, (end_row - start_row) * enc->mb_w_); 4348b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora memset(job->alphas, 0, sizeof(job->alphas)); 4358b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->alpha = 0; 4368b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->uv_alpha = 0; 4378b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // only one of both jobs can record the progress, since we don't 4388b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // expect the user's hook to be multi-thread safe 4398b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->delta_progress = (start_row == 0) ? 20 : 0; 4408b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora} 4418b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 4428b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora// main entry point 4437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Aroraint VP8EncAnalyze(VP8Encoder* const enc) { 444a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora int ok = 1; 4451e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora const int do_segments = 4461e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora enc->config_->emulate_jpeg_size || // We need the complexity evaluation. 4471e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora (enc->segment_hdr_.num_segments_ > 1) || 4481e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora (enc->method_ == 0); // for method 0, we need preds_[] to be filled. 4491e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (do_segments) { 4508b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int last_row = enc->mb_h_; 4518b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // We give a little more than a half work to the main thread. 4528b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int split_row = (9 * last_row + 15) >> 4; 4538b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int total_mb = last_row * enc->mb_w_; 4548b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora#ifdef WEBP_USE_THREAD 4558b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int kMinSplitRow = 2; // minimal rows needed for mt to be worth it 4568b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int do_mt = (enc->thread_level_ > 0) && (split_row >= kMinSplitRow); 4578b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora#else 4588b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int do_mt = 0; 4598b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora#endif 46033f74dabbc7920a65ed435d7417987589febdc16Vikas Arora const WebPWorkerInterface* const worker_interface = 46133f74dabbc7920a65ed435d7417987589febdc16Vikas Arora WebPGetWorkerInterface(); 4628b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora SegmentJob main_job; 4638b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (do_mt) { 4648b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora SegmentJob side_job; 4658b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // Note the use of '&' instead of '&&' because we must call the functions 4668b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // no matter what. 4678b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora InitSegmentJob(enc, &main_job, 0, split_row); 4688b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora InitSegmentJob(enc, &side_job, split_row, last_row); 4698b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // we don't need to call Reset() on main_job.worker, since we're calling 4708b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // WebPWorkerExecute() on it 47133f74dabbc7920a65ed435d7417987589febdc16Vikas Arora ok &= worker_interface->Reset(&side_job.worker); 4728b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // launch the two jobs in parallel 4738b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (ok) { 47433f74dabbc7920a65ed435d7417987589febdc16Vikas Arora worker_interface->Launch(&side_job.worker); 47533f74dabbc7920a65ed435d7417987589febdc16Vikas Arora worker_interface->Execute(&main_job.worker); 47633f74dabbc7920a65ed435d7417987589febdc16Vikas Arora ok &= worker_interface->Sync(&side_job.worker); 47733f74dabbc7920a65ed435d7417987589febdc16Vikas Arora ok &= worker_interface->Sync(&main_job.worker); 4788b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } 47933f74dabbc7920a65ed435d7417987589febdc16Vikas Arora worker_interface->End(&side_job.worker); 4808b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (ok) MergeJobs(&side_job, &main_job); // merge results together 4818b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } else { 4828b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // Even for single-thread case, we use the generic Worker tools. 4838b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora InitSegmentJob(enc, &main_job, 0, last_row); 48433f74dabbc7920a65ed435d7417987589febdc16Vikas Arora worker_interface->Execute(&main_job.worker); 48533f74dabbc7920a65ed435d7417987589febdc16Vikas Arora ok &= worker_interface->Sync(&main_job.worker); 4868b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } 48733f74dabbc7920a65ed435d7417987589febdc16Vikas Arora worker_interface->End(&main_job.worker); 4888b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (ok) { 4898b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora enc->alpha_ = main_job.alpha / total_mb; 4908b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora enc->uv_alpha_ = main_job.uv_alpha / total_mb; 4918b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora AssignSegments(enc, main_job.alphas); 4928b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } 4931e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } else { // Use only one default segment. 4941e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora ResetAllMBInfo(enc); 4951e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } 496a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora return ok; 4977c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 4987c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 499