/* * Copyright (c) 2016, Alliance for Open Media. All rights reserved * * This source code is subject to the terms of the BSD 2 Clause License and * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License * was not distributed with this source code in the LICENSE file, you can * obtain it at www.aomedia.org/license/software. If the Alliance for Open * Media Patent License 1.0 was not distributed with this source code in the * PATENTS file, you can obtain it at www.aomedia.org/license/patent. */ #include #include "aom_mem/aom_mem.h" #include "av1/common/pred_common.h" #include "av1/common/tile_common.h" #include "av1/encoder/cost.h" #include "av1/encoder/segmentation.h" void av1_enable_segmentation(struct segmentation *seg) { seg->enabled = 1; seg->update_map = 1; seg->update_data = 1; seg->temporal_update = 0; } void av1_disable_segmentation(struct segmentation *seg) { seg->enabled = 0; seg->update_map = 0; seg->update_data = 0; seg->temporal_update = 0; } void av1_disable_segfeature(struct segmentation *seg, int segment_id, SEG_LVL_FEATURES feature_id) { seg->feature_mask[segment_id] &= ~(1 << feature_id); } void av1_clear_segdata(struct segmentation *seg, int segment_id, SEG_LVL_FEATURES feature_id) { seg->feature_data[segment_id][feature_id] = 0; } static void count_segs(const AV1_COMMON *cm, MACROBLOCKD *xd, const TileInfo *tile, MB_MODE_INFO **mi, unsigned *no_pred_segcounts, unsigned (*temporal_predictor_count)[2], unsigned *t_unpred_seg_counts, int bw, int bh, int mi_row, int mi_col) { int segment_id; if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return; xd->mi = mi; segment_id = xd->mi[0]->segment_id; set_mi_row_col(xd, tile, mi_row, bh, mi_col, bw, cm->mi_rows, cm->mi_cols); // Count the number of hits on each segment with no prediction no_pred_segcounts[segment_id]++; // Temporal prediction not allowed on key frames if (cm->frame_type != KEY_FRAME) { const BLOCK_SIZE bsize = xd->mi[0]->sb_type; // Test to see if the segment id matches the predicted value. const int pred_segment_id = cm->last_frame_seg_map ? get_segment_id(cm, cm->last_frame_seg_map, bsize, mi_row, mi_col) : 0; const int pred_flag = pred_segment_id == segment_id; const int pred_context = av1_get_pred_context_seg_id(xd); // Store the prediction status for this mb and update counts // as appropriate xd->mi[0]->seg_id_predicted = pred_flag; temporal_predictor_count[pred_context][pred_flag]++; // Update the "unpredicted" segment count if (!pred_flag) t_unpred_seg_counts[segment_id]++; } } static void count_segs_sb(const AV1_COMMON *cm, MACROBLOCKD *xd, const TileInfo *tile, MB_MODE_INFO **mi, unsigned *no_pred_segcounts, unsigned (*temporal_predictor_count)[2], unsigned *t_unpred_seg_counts, int mi_row, int mi_col, BLOCK_SIZE bsize) { const int mis = cm->mi_stride; const int bs = mi_size_wide[bsize], hbs = bs / 2; PARTITION_TYPE partition; const int qbs = bs / 4; if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return; #define CSEGS(cs_bw, cs_bh, cs_rowoff, cs_coloff) \ count_segs(cm, xd, tile, mi + mis * (cs_rowoff) + (cs_coloff), \ no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, \ (cs_bw), (cs_bh), mi_row + (cs_rowoff), mi_col + (cs_coloff)); if (bsize == BLOCK_8X8) partition = PARTITION_NONE; else partition = get_partition(cm, mi_row, mi_col, bsize); switch (partition) { case PARTITION_NONE: CSEGS(bs, bs, 0, 0); break; case PARTITION_HORZ: CSEGS(bs, hbs, 0, 0); CSEGS(bs, hbs, hbs, 0); break; case PARTITION_VERT: CSEGS(hbs, bs, 0, 0); CSEGS(hbs, bs, 0, hbs); break; case PARTITION_HORZ_A: CSEGS(hbs, hbs, 0, 0); CSEGS(hbs, hbs, 0, hbs); CSEGS(bs, hbs, hbs, 0); break; case PARTITION_HORZ_B: CSEGS(bs, hbs, 0, 0); CSEGS(hbs, hbs, hbs, 0); CSEGS(hbs, hbs, hbs, hbs); break; case PARTITION_VERT_A: CSEGS(hbs, hbs, 0, 0); CSEGS(hbs, hbs, hbs, 0); CSEGS(hbs, bs, 0, hbs); break; case PARTITION_VERT_B: CSEGS(hbs, bs, 0, 0); CSEGS(hbs, hbs, 0, hbs); CSEGS(hbs, hbs, hbs, hbs); break; case PARTITION_HORZ_4: CSEGS(bs, qbs, 0, 0); CSEGS(bs, qbs, qbs, 0); CSEGS(bs, qbs, 2 * qbs, 0); if (mi_row + 3 * qbs < cm->mi_rows) CSEGS(bs, qbs, 3 * qbs, 0); break; case PARTITION_VERT_4: CSEGS(qbs, bs, 0, 0); CSEGS(qbs, bs, 0, qbs); CSEGS(qbs, bs, 0, 2 * qbs); if (mi_col + 3 * qbs < cm->mi_cols) CSEGS(qbs, bs, 0, 3 * qbs); break; case PARTITION_SPLIT: { const BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_SPLIT); int n; for (n = 0; n < 4; n++) { const int mi_dc = hbs * (n & 1); const int mi_dr = hbs * (n >> 1); count_segs_sb(cm, xd, tile, &mi[mi_dr * mis + mi_dc], no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, mi_row + mi_dr, mi_col + mi_dc, subsize); } } break; default: assert(0); } #undef CSEGS } void av1_choose_segmap_coding_method(AV1_COMMON *cm, MACROBLOCKD *xd) { struct segmentation *seg = &cm->seg; struct segmentation_probs *segp = &cm->fc->seg; int no_pred_cost; int t_pred_cost = INT_MAX; int tile_col, tile_row, mi_row, mi_col; unsigned temporal_predictor_count[SEG_TEMPORAL_PRED_CTXS][2] = { { 0 } }; unsigned no_pred_segcounts[MAX_SEGMENTS] = { 0 }; unsigned t_unpred_seg_counts[MAX_SEGMENTS] = { 0 }; (void)xd; // First of all generate stats regarding how well the last segment map // predicts this one for (tile_row = 0; tile_row < cm->tile_rows; tile_row++) { TileInfo tile_info; av1_tile_set_row(&tile_info, cm, tile_row); for (tile_col = 0; tile_col < cm->tile_cols; tile_col++) { MB_MODE_INFO **mi_ptr; av1_tile_set_col(&tile_info, cm, tile_col); mi_ptr = cm->mi_grid_visible + tile_info.mi_row_start * cm->mi_stride + tile_info.mi_col_start; for (mi_row = tile_info.mi_row_start; mi_row < tile_info.mi_row_end; mi_row += cm->seq_params.mib_size, mi_ptr += cm->seq_params.mib_size * cm->mi_stride) { MB_MODE_INFO **mi = mi_ptr; for (mi_col = tile_info.mi_col_start; mi_col < tile_info.mi_col_end; mi_col += cm->seq_params.mib_size, mi += cm->seq_params.mib_size) { count_segs_sb(cm, xd, &tile_info, mi, no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, mi_row, mi_col, cm->seq_params.sb_size); } } } } int seg_id_cost[MAX_SEGMENTS]; av1_cost_tokens_from_cdf(seg_id_cost, segp->tree_cdf, NULL); no_pred_cost = 0; for (int i = 0; i < MAX_SEGMENTS; ++i) no_pred_cost += no_pred_segcounts[i] * seg_id_cost[i]; // Frames without past dependency cannot use temporal prediction if (cm->primary_ref_frame != PRIMARY_REF_NONE) { int pred_flag_cost[SEG_TEMPORAL_PRED_CTXS][2]; for (int i = 0; i < SEG_TEMPORAL_PRED_CTXS; ++i) av1_cost_tokens_from_cdf(pred_flag_cost[i], segp->pred_cdf[i], NULL); t_pred_cost = 0; // Cost for signaling the prediction flag. for (int i = 0; i < SEG_TEMPORAL_PRED_CTXS; ++i) { for (int j = 0; j < 2; ++j) t_pred_cost += temporal_predictor_count[i][j] * pred_flag_cost[i][j]; } // Cost for signaling the unpredicted segment id. for (int i = 0; i < MAX_SEGMENTS; ++i) t_pred_cost += t_unpred_seg_counts[i] * seg_id_cost[i]; } // Now choose which coding method to use. if (t_pred_cost < no_pred_cost) { assert(!cm->error_resilient_mode); seg->temporal_update = 1; } else { seg->temporal_update = 0; } } void av1_reset_segment_features(AV1_COMMON *cm) { struct segmentation *seg = &cm->seg; // Set up default state for MB feature flags seg->enabled = 0; seg->update_map = 0; seg->update_data = 0; av1_clearall_segfeatures(seg); }