ref: c7072ae2f4f3478a2f62811979540a94b32ec431
dir: /vp9/encoder/vp9_segmentation.c/
/* * Copyright (c) 2012 The WebM project authors. All Rights Reserved. * * Use of this source code is governed by a BSD-style license * that can be found in the LICENSE file in the root of the source * tree. An additional intellectual property rights grant can be found * in the file PATENTS. All contributing project authors may * be found in the AUTHORS file in the root of the source tree. */ #include <limits.h> #include "vpx_mem/vpx_mem.h" #include "vp9/common/vp9_pred_common.h" #include "vp9/common/vp9_tile_common.h" #include "vp9/encoder/vp9_cost.h" #include "vp9/encoder/vp9_segmentation.h" void vp9_enable_segmentation(struct segmentation *seg) { seg->enabled = 1; seg->update_map = 1; seg->update_data = 1; } void vp9_disable_segmentation(struct segmentation *seg) { seg->enabled = 0; seg->update_map = 0; seg->update_data = 0; } void vp9_set_segment_data(struct segmentation *seg, signed char *feature_data, unsigned char abs_delta) { seg->abs_delta = abs_delta; memcpy(seg->feature_data, feature_data, sizeof(seg->feature_data)); } void vp9_disable_segfeature(struct segmentation *seg, int segment_id, SEG_LVL_FEATURES feature_id) { seg->feature_mask[segment_id] &= ~(1 << feature_id); } void vp9_clear_segdata(struct segmentation *seg, int segment_id, SEG_LVL_FEATURES feature_id) { seg->feature_data[segment_id][feature_id] = 0; } // Based on set of segment counts calculate a probability tree static void calc_segtree_probs(int *segcounts, vpx_prob *segment_tree_probs) { // Work out probabilities of each segment const int c01 = segcounts[0] + segcounts[1]; const int c23 = segcounts[2] + segcounts[3]; const int c45 = segcounts[4] + segcounts[5]; const int c67 = segcounts[6] + segcounts[7]; segment_tree_probs[0] = get_binary_prob(c01 + c23, c45 + c67); segment_tree_probs[1] = get_binary_prob(c01, c23); segment_tree_probs[2] = get_binary_prob(c45, c67); segment_tree_probs[3] = get_binary_prob(segcounts[0], segcounts[1]); segment_tree_probs[4] = get_binary_prob(segcounts[2], segcounts[3]); segment_tree_probs[5] = get_binary_prob(segcounts[4], segcounts[5]); segment_tree_probs[6] = get_binary_prob(segcounts[6], segcounts[7]); } // Based on set of segment counts and probabilities calculate a cost estimate static int cost_segmap(int *segcounts, vpx_prob *probs) { const int c01 = segcounts[0] + segcounts[1]; const int c23 = segcounts[2] + segcounts[3]; const int c45 = segcounts[4] + segcounts[5]; const int c67 = segcounts[6] + segcounts[7]; const int c0123 = c01 + c23; const int c4567 = c45 + c67; // Cost the top node of the tree int cost = c0123 * vp9_cost_zero(probs[0]) + c4567 * vp9_cost_one(probs[0]); // Cost subsequent levels if (c0123 > 0) { cost += c01 * vp9_cost_zero(probs[1]) + c23 * vp9_cost_one(probs[1]); if (c01 > 0) cost += segcounts[0] * vp9_cost_zero(probs[3]) + segcounts[1] * vp9_cost_one(probs[3]); if (c23 > 0) cost += segcounts[2] * vp9_cost_zero(probs[4]) + segcounts[3] * vp9_cost_one(probs[4]); } if (c4567 > 0) { cost += c45 * vp9_cost_zero(probs[2]) + c67 * vp9_cost_one(probs[2]); if (c45 > 0) cost += segcounts[4] * vp9_cost_zero(probs[5]) + segcounts[5] * vp9_cost_one(probs[5]); if (c67 > 0) cost += segcounts[6] * vp9_cost_zero(probs[6]) + segcounts[7] * vp9_cost_one(probs[6]); } return cost; } static void count_segs(const VP9_COMMON *cm, MACROBLOCKD *xd, const TileInfo *tile, MODE_INFO **mi, int *no_pred_segcounts, int (*temporal_predictor_count)[2], int *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 = get_segment_id(cm, cm->last_frame_seg_map, bsize, mi_row, mi_col); const int pred_flag = pred_segment_id == segment_id; const int pred_context = vp9_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 VP9_COMMON *cm, MACROBLOCKD *xd, const TileInfo *tile, MODE_INFO **mi, int *no_pred_segcounts, int (*temporal_predictor_count)[2], int *t_unpred_seg_counts, int mi_row, int mi_col, BLOCK_SIZE bsize) { const int mis = cm->mi_stride; int bw, bh; const int bs = num_8x8_blocks_wide_lookup[bsize], hbs = bs / 2; if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return; bw = num_8x8_blocks_wide_lookup[mi[0]->sb_type]; bh = num_8x8_blocks_high_lookup[mi[0]->sb_type]; if (bw == bs && bh == bs) { count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, bs, bs, mi_row, mi_col); } else if (bw == bs && bh < bs) { count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, bs, hbs, mi_row, mi_col); count_segs(cm, xd, tile, mi + hbs * mis, no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, bs, hbs, mi_row + hbs, mi_col); } else if (bw < bs && bh == bs) { count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, hbs, bs, mi_row, mi_col); count_segs(cm, xd, tile, mi + hbs, no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, hbs, bs, mi_row, mi_col + hbs); } else { const BLOCK_SIZE subsize = subsize_lookup[PARTITION_SPLIT][bsize]; int n; assert(bw < bs && bh < bs); 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); } } } void vp9_choose_segmap_coding_method(VP9_COMMON *cm, MACROBLOCKD *xd) { struct segmentation *seg = &cm->seg; int no_pred_cost; int t_pred_cost = INT_MAX; int i, tile_col, mi_row, mi_col; int temporal_predictor_count[PREDICTION_PROBS][2] = { { 0 } }; int no_pred_segcounts[MAX_SEGMENTS] = { 0 }; int t_unpred_seg_counts[MAX_SEGMENTS] = { 0 }; vpx_prob no_pred_tree[SEG_TREE_PROBS]; vpx_prob t_pred_tree[SEG_TREE_PROBS]; vpx_prob t_nopred_prob[PREDICTION_PROBS]; // Set default state for the segment tree probabilities and the // temporal coding probabilities memset(seg->tree_probs, 255, sizeof(seg->tree_probs)); memset(seg->pred_probs, 255, sizeof(seg->pred_probs)); // First of all generate stats regarding how well the last segment map // predicts this one for (tile_col = 0; tile_col < 1 << cm->log2_tile_cols; tile_col++) { TileInfo tile; MODE_INFO **mi_ptr; vp9_tile_init(&tile, cm, 0, tile_col); mi_ptr = cm->mi_grid_visible + tile.mi_col_start; for (mi_row = 0; mi_row < cm->mi_rows; mi_row += 8, mi_ptr += 8 * cm->mi_stride) { MODE_INFO **mi = mi_ptr; for (mi_col = tile.mi_col_start; mi_col < tile.mi_col_end; mi_col += 8, mi += 8) count_segs_sb(cm, xd, &tile, mi, no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, mi_row, mi_col, BLOCK_64X64); } } // Work out probability tree for coding segments without prediction // and the cost. calc_segtree_probs(no_pred_segcounts, no_pred_tree); no_pred_cost = cost_segmap(no_pred_segcounts, no_pred_tree); // Key frames cannot use temporal prediction if (!frame_is_intra_only(cm)) { // Work out probability tree for coding those segments not // predicted using the temporal method and the cost. calc_segtree_probs(t_unpred_seg_counts, t_pred_tree); t_pred_cost = cost_segmap(t_unpred_seg_counts, t_pred_tree); // Add in the cost of the signaling for each prediction context. for (i = 0; i < PREDICTION_PROBS; i++) { const int count0 = temporal_predictor_count[i][0]; const int count1 = temporal_predictor_count[i][1]; t_nopred_prob[i] = get_binary_prob(count0, count1); // Add in the predictor signaling cost t_pred_cost += count0 * vp9_cost_zero(t_nopred_prob[i]) + count1 * vp9_cost_one(t_nopred_prob[i]); } } // Now choose which coding method to use. if (t_pred_cost < no_pred_cost) { seg->temporal_update = 1; memcpy(seg->tree_probs, t_pred_tree, sizeof(t_pred_tree)); memcpy(seg->pred_probs, t_nopred_prob, sizeof(t_nopred_prob)); } else { seg->temporal_update = 0; memcpy(seg->tree_probs, no_pred_tree, sizeof(no_pred_tree)); } } void vp9_reset_segment_features(struct segmentation *seg) { // Set up default state for MB feature flags seg->enabled = 0; seg->update_map = 0; seg->update_data = 0; memset(seg->tree_probs, 255, sizeof(seg->tree_probs)); vp9_clearall_segfeatures(seg); }