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/*
* 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 <limits.h>
#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);
}
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