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; 33af51b94a435132e9014c324e25fb686b3d07a8c8Vikas 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 } 66af51b94a435132e9014c324e25fb686b3d07a8c8Vikas 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]) { 1447c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int nb = enc->segment_hdr_.num_segments_; 1457c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int centers[NUM_MB_SEGMENTS]; 146a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora int weighted_average = 0; 1471e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int map[MAX_ALPHA + 1]; 1487c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int a, n, k; 1491e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int min_a = 0, max_a = MAX_ALPHA, range_a; 1507c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // 'int' type is ok for histo, and won't overflow 1517c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int accum[NUM_MB_SEGMENTS], dist_accum[NUM_MB_SEGMENTS]; 1527c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1538b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora assert(nb >= 1); 154af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora assert(nb <= NUM_MB_SEGMENTS); 1558b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 1567c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // bracket the input 1571e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora for (n = 0; n <= MAX_ALPHA && alphas[n] == 0; ++n) {} 1587c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora min_a = n; 1591e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora for (n = MAX_ALPHA; n > min_a && alphas[n] == 0; --n) {} 1607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora max_a = n; 1617c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora range_a = max_a - min_a; 1627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1637c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Spread initial centers evenly 1648b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora for (k = 0, n = 1; k < nb; ++k, n += 2) { 1658b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora assert(n < 2 * nb); 1668b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora centers[k] = min_a + (n * range_a) / (2 * nb); 1677c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1687c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 1697c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (k = 0; k < MAX_ITERS_K_MEANS; ++k) { // few iters are enough 1707c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int total_weight; 1717c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int displaced; 1727c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Reset stats 1737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 1747c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora accum[n] = 0; 1757c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora dist_accum[n] = 0; 1767c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1777c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Assign nearest center for each 'a' 1787c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora n = 0; // track the nearest center for current 'a' 1797c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (a = min_a; a <= max_a; ++a) { 1807c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (alphas[a]) { 1818b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora while (n + 1 < nb && abs(a - centers[n + 1]) < abs(a - centers[n])) { 1827c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora n++; 1837c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1847c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora map[a] = n; 1857c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // accumulate contribution into best centroid 1867c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora dist_accum[n] += a * alphas[a]; 1877c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora accum[n] += alphas[a]; 1887c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1897c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 1907c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // All point are classified. Move the centroids to the 1917c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // center of their respective cloud. 1927c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora displaced = 0; 1937c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average = 0; 1947c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora total_weight = 0; 1957c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < nb; ++n) { 1967c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (accum[n]) { 1977c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int new_center = (dist_accum[n] + accum[n] / 2) / accum[n]; 1987c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora displaced += abs(centers[n] - new_center); 1997c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora centers[n] = new_center; 2007c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average += new_center * accum[n]; 2017c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora total_weight += accum[n]; 2027c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2037c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2047c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora weighted_average = (weighted_average + total_weight / 2) / total_weight; 2057c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (displaced < 5) break; // no need to keep on looping... 2067c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2077c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2087c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Map each original value to the closest centroid 2097c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (n = 0; n < enc->mb_w_ * enc->mb_h_; ++n) { 2107c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MBInfo* const mb = &enc->mb_info_[n]; 211a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora const int alpha = mb->alpha_; 212a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora mb->segment_ = map[alpha]; 2131e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->alpha_ = centers[map[alpha]]; // for the record. 2147c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2157c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2167c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (nb > 1) { 2177c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const int smooth = (enc->config_->preprocessing & 1); 2187c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora if (smooth) SmoothSegmentMap(enc); 2197c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2207c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora SetSegmentAlphas(enc, centers, weighted_average); // pick some alphas. 2227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 2237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 224a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora//------------------------------------------------------------------------------ 2257c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Macroblock analysis: collect histogram for each mode, deduce the maximal 2267c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// susceptibility and set best modes for this macroblock. 2277c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Segment assignment is done later. 2287c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 229af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora// Number of modes to inspect for alpha_ evaluation. We don't need to test all 230af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora// the possible modes during the analysis phase: we risk falling into a local 231af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora// optimum, or be subject to boundary effect 2327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_INTRA16_MODE 2 2337c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_INTRA4_MODE 2 2347c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora#define MAX_UV_MODE 2 2357c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2367c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestIntra16Mode(VP8EncIterator* const it) { 237af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora const int max_mode = MAX_INTRA16_MODE; 2387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 2391e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int best_alpha = DEFAULT_ALPHA; 2407c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_mode = 0; 2417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeLuma16Preds(it); 2437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 2441e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram histo = { { 0 } }; 2451e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alpha; 2461e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 2471e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8CollectHistogram(it->yuv_in_ + Y_OFF, 2481e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora it->yuv_p_ + VP8I16ModeOffsets[mode], 2491e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 0, 16, &histo); 2501e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora alpha = GetAlpha(&histo); 2511e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (IS_BETTER_ALPHA(alpha, best_alpha)) { 2527c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = alpha; 2537c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode = mode; 2547c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2557c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2567c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra16Mode(it, best_mode); 2577c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 2587c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 2597c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2607c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestIntra4Mode(VP8EncIterator* const it, 2617c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_alpha) { 262a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora uint8_t modes[16]; 263af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora const int max_mode = MAX_INTRA4_MODE; 2641e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int i4_alpha; 2651e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram total_histo = { { 0 } }; 2661e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int cur_histo = 0; 2671e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 2687c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8IteratorStartI4(it); 2697c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora do { 2707c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 2711e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int best_mode_alpha = DEFAULT_ALPHA; 2721e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram histos[2]; 2737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const uint8_t* const src = it->yuv_in_ + Y_OFF + VP8Scan[it->i4_]; 2747c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2757c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeIntra4Preds(it); 2767c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 2771e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alpha; 2781e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 2791e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora memset(&histos[cur_histo], 0, sizeof(histos[cur_histo])); 2801e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8CollectHistogram(src, it->yuv_p_ + VP8I4ModeOffsets[mode], 2811e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 0, 1, &histos[cur_histo]); 2821e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora alpha = GetAlpha(&histos[cur_histo]); 2831e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (IS_BETTER_ALPHA(alpha, best_mode_alpha)) { 2847c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode_alpha = alpha; 2857c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora modes[it->i4_] = mode; 2861e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora cur_histo ^= 1; // keep track of best histo so far. 2877c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2887c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2891e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // accumulate best histogram 2901e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora MergeHistograms(&histos[cur_histo ^ 1], &total_histo); 2917c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Note: we reuse the original samples for predictors 2927c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } while (VP8IteratorRotateI4(it, it->yuv_in_ + Y_OFF)); 2937c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 2941e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora i4_alpha = GetAlpha(&total_histo); 2951e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (IS_BETTER_ALPHA(i4_alpha, best_alpha)) { 2967c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra4Mode(it, modes); 2971e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora best_alpha = i4_alpha; 2987c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 2997c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 3007c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3017c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3027c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic int MBAnalyzeBestUVMode(VP8EncIterator* const it) { 3031e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int best_alpha = DEFAULT_ALPHA; 3047c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_mode = 0; 305af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora const int max_mode = MAX_UV_MODE; 3067c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int mode; 307af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora 3087c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8MakeChroma8Preds(it); 3097c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora for (mode = 0; mode < max_mode; ++mode) { 3101e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8Histogram histo = { { 0 } }; 3111e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alpha; 3121e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora VP8CollectHistogram(it->yuv_in_ + U_OFF, 3131e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora it->yuv_p_ + VP8UVModeOffsets[mode], 3141e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 16, 16 + 4 + 4, &histo); 3151e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora alpha = GetAlpha(&histo); 3161e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (IS_BETTER_ALPHA(alpha, best_alpha)) { 3177c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = alpha; 3187c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_mode = mode; 3197c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3207c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3217c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntraUVMode(it, best_mode); 3227c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora return best_alpha; 3237c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3247c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3257c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arorastatic void MBAnalyze(VP8EncIterator* const it, 3261e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int alphas[MAX_ALPHA + 1], 3271e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int* const alpha, int* const uv_alpha) { 3287c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora const VP8Encoder* const enc = it->enc_; 3297c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora int best_alpha, best_uv_alpha; 3307c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3317c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetIntra16Mode(it, 0); // default: Intra16, DC_PRED 3327c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetSkip(it, 0); // not skipped 3337c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora VP8SetSegment(it, 0); // default segment, spec-wise. 3347c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3357c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = MBAnalyzeBestIntra16Mode(it); 3361e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (enc->method_ >= 5) { 3377c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // We go and make a fast decision for intra4/intra16. 3387c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // It's usually not a good and definitive pick, but helps seeding the stats 3397c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // about level bit-cost. 3407c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // TODO(skal): improve criterion. 3417c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_alpha = MBAnalyzeBestIntra4Mode(it, best_alpha); 3427c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora } 3437c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora best_uv_alpha = MBAnalyzeBestUVMode(it); 3447c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3457c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora // Final susceptibility mix 3461e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora best_alpha = (3 * best_alpha + best_uv_alpha + 2) >> 2; 3471e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora best_alpha = FinalAlphaValue(best_alpha); 3487c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora alphas[best_alpha]++; 3491e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora it->mb_->alpha_ = best_alpha; // for later remapping. 3501e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 3511e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // Accumulate for later complexity analysis. 3521e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora *alpha += best_alpha; // mixed susceptibility (not just luma) 3537c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora *uv_alpha += best_uv_alpha; 3541e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora} 3551e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 3561e7bf8805bd030c19924a5306837ecd72c295751Vikas Arorastatic void DefaultMBInfo(VP8MBInfo* const mb) { 3571e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->type_ = 1; // I16x16 3581e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->uv_mode_ = 0; 3591e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->skip_ = 0; // not skipped 3601e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->segment_ = 0; // default segment 3611e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora mb->alpha_ = 0; 3627c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 3637c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 364a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora//------------------------------------------------------------------------------ 3657c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Main analysis loop: 3667c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// Collect all susceptibilities for each macroblock and record their 3677c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// distribution in alphas[]. Segments is assigned a-posteriori, based on 3687c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// this histogram. 3697c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// We also pick an intra16 prediction mode, which shouldn't be considered 3707c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// final except for fast-encode settings. We can also pick some intra4 modes 3717c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// and decide intra4/intra16, but that's usually almost always a bad choice at 3727c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora// this stage. 3737c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 3741e7bf8805bd030c19924a5306837ecd72c295751Vikas Arorastatic void ResetAllMBInfo(VP8Encoder* const enc) { 3751e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora int n; 3761e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora for (n = 0; n < enc->mb_w_ * enc->mb_h_; ++n) { 3771e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora DefaultMBInfo(&enc->mb_info_[n]); 3781e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } 3791e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora // Default susceptibilities. 3801e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora enc->dqm_[0].alpha_ = 0; 3811e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora enc->dqm_[0].beta_ = 0; 3828b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // Note: we can't compute this alpha_ / uv_alpha_ -> set to default value. 3838b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora enc->alpha_ = 0; 3848b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora enc->uv_alpha_ = 0; 3851e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora WebPReportProgress(enc->pic_, enc->percent_ + 20, &enc->percent_); 3861e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora} 3871e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora 3888b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora// struct used to collect job result 3898b720228d581a84fd173b6dcb2fa295b59db489aVikas Aroratypedef struct { 3908b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora WebPWorker worker; 3918b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int alphas[MAX_ALPHA + 1]; 3928b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int alpha, uv_alpha; 3938b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8EncIterator it; 3948b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int delta_progress; 3958b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora} SegmentJob; 3968b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 3978b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora// main work call 3988b720228d581a84fd173b6dcb2fa295b59db489aVikas Arorastatic int DoSegmentsJob(SegmentJob* const job, VP8EncIterator* const it) { 3998b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int ok = 1; 4008b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (!VP8IteratorIsDone(it)) { 4018b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora uint8_t tmp[32 + ALIGN_CST]; 4028b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora uint8_t* const scratch = (uint8_t*)DO_ALIGN(tmp); 4038b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora do { 4048b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // Let's pretend we have perfect lossless reconstruction. 4058b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8IteratorImport(it, scratch); 4068b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora MBAnalyze(it, job->alphas, &job->alpha, &job->uv_alpha); 4078b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora ok = VP8IteratorProgress(it, job->delta_progress); 4088b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } while (ok && VP8IteratorNext(it)); 4098b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } 4108b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora return ok; 4118b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora} 4128b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 4138b720228d581a84fd173b6dcb2fa295b59db489aVikas Arorastatic void MergeJobs(const SegmentJob* const src, SegmentJob* const dst) { 4148b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int i; 4158b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora for (i = 0; i <= MAX_ALPHA; ++i) dst->alphas[i] += src->alphas[i]; 4168b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora dst->alpha += src->alpha; 4178b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora dst->uv_alpha += src->uv_alpha; 4188b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora} 4198b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 4208b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora// initialize the job struct with some TODOs 4218b720228d581a84fd173b6dcb2fa295b59db489aVikas Arorastatic void InitSegmentJob(VP8Encoder* const enc, SegmentJob* const job, 4228b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora int start_row, int end_row) { 423af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora WebPGetWorkerInterface()->Init(&job->worker); 4248b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->worker.data1 = job; 4258b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->worker.data2 = &job->it; 4268b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->worker.hook = (WebPWorkerHook)DoSegmentsJob; 4278b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8IteratorInit(enc, &job->it); 4288b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8IteratorSetRow(&job->it, start_row); 4298b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora VP8IteratorSetCountDown(&job->it, (end_row - start_row) * enc->mb_w_); 4308b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora memset(job->alphas, 0, sizeof(job->alphas)); 4318b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->alpha = 0; 4328b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->uv_alpha = 0; 4338b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // only one of both jobs can record the progress, since we don't 4348b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // expect the user's hook to be multi-thread safe 4358b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora job->delta_progress = (start_row == 0) ? 20 : 0; 4368b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora} 4378b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora 4388b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora// main entry point 4397c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Aroraint VP8EncAnalyze(VP8Encoder* const enc) { 440a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora int ok = 1; 4411e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora const int do_segments = 4421e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora enc->config_->emulate_jpeg_size || // We need the complexity evaluation. 4431e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora (enc->segment_hdr_.num_segments_ > 1) || 4441e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora (enc->method_ == 0); // for method 0, we need preds_[] to be filled. 4451e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora if (do_segments) { 4468b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int last_row = enc->mb_h_; 4478b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // We give a little more than a half work to the main thread. 4488b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int split_row = (9 * last_row + 15) >> 4; 4498b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int total_mb = last_row * enc->mb_w_; 4508b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora#ifdef WEBP_USE_THREAD 4518b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int kMinSplitRow = 2; // minimal rows needed for mt to be worth it 4528b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int do_mt = (enc->thread_level_ > 0) && (split_row >= kMinSplitRow); 4538b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora#else 4548b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora const int do_mt = 0; 4558b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora#endif 456af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora const WebPWorkerInterface* const worker_interface = 457af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora WebPGetWorkerInterface(); 4588b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora SegmentJob main_job; 4598b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (do_mt) { 4608b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora SegmentJob side_job; 4618b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // Note the use of '&' instead of '&&' because we must call the functions 4628b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // no matter what. 4638b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora InitSegmentJob(enc, &main_job, 0, split_row); 4648b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora InitSegmentJob(enc, &side_job, split_row, last_row); 4658b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // we don't need to call Reset() on main_job.worker, since we're calling 4668b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // WebPWorkerExecute() on it 467af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora ok &= worker_interface->Reset(&side_job.worker); 4688b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // launch the two jobs in parallel 4698b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (ok) { 470af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora worker_interface->Launch(&side_job.worker); 471af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora worker_interface->Execute(&main_job.worker); 472af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora ok &= worker_interface->Sync(&side_job.worker); 473af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora ok &= worker_interface->Sync(&main_job.worker); 4748b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } 475af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora worker_interface->End(&side_job.worker); 4768b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (ok) MergeJobs(&side_job, &main_job); // merge results together 4778b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } else { 4788b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora // Even for single-thread case, we use the generic Worker tools. 4798b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora InitSegmentJob(enc, &main_job, 0, last_row); 480af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora worker_interface->Execute(&main_job.worker); 481af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora ok &= worker_interface->Sync(&main_job.worker); 4828b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } 483af51b94a435132e9014c324e25fb686b3d07a8c8Vikas Arora worker_interface->End(&main_job.worker); 4848b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora if (ok) { 4858b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora enc->alpha_ = main_job.alpha / total_mb; 4868b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora enc->uv_alpha_ = main_job.uv_alpha / total_mb; 4878b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora AssignSegments(enc, main_job.alphas); 4888b720228d581a84fd173b6dcb2fa295b59db489aVikas Arora } 4891e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } else { // Use only one default segment. 4901e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora ResetAllMBInfo(enc); 4911e7bf8805bd030c19924a5306837ecd72c295751Vikas Arora } 492a2415724fb3466168b2af5b08bd94ba732c0e753Vikas Arora return ok; 4937c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora} 4947c970a0a679089e416c5887cf7fcece15a70bfa4Vikas Arora 495