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 i, tile_col, tile_row, mi_row, mi_col;
#if CONFIG_TILE_GROUPS
const int probwt = cm->num_tg;
#else
const int probwt = 1;
#endif
unsigned(*temporal_predictor_count)[2] = cm->counts.seg.pred;
unsigned *no_pred_segcounts = cm->counts.seg.tree_total;
unsigned *t_unpred_seg_counts = cm->counts.seg.tree_mispred;
aom_prob no_pred_tree[SEG_TREE_PROBS];
aom_prob t_pred_tree[SEG_TREE_PROBS];
aom_prob t_nopred_prob[PREDICTION_PROBS];
(void)xd;
// We are about to recompute all the segment counts, so zero the accumulators.
av1_zero(cm->counts.seg);
// 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++) {
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->mib_size, mi_ptr += cm->mib_size * cm->mi_stride) {
MODE_INFO **mi = mi_ptr;
for (mi_col = tile_info.mi_col_start; mi_col < tile_info.mi_col_end;
mi_col += cm->mib_size, mi += cm->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->sb_size);
}
}
}
}
// Work out probability tree for coding segments without prediction
// and the cost.
calc_segtree_probs(no_pred_segcounts, no_pred_tree, segp->tree_probs, probwt);
no_pred_cost = cost_segmap(no_pred_segcounts, no_pred_tree);
// Key frames cannot use temporal prediction
if (!frame_is_intra_only(cm) && !cm->error_resilient_mode) {
// 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, segp->tree_probs,
probwt);
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);
av1_prob_diff_update_savings_search(
temporal_predictor_count[i], segp->pred_probs[i], &t_nopred_prob[i],
DIFF_UPDATE_PROB, probwt);
// Add in the predictor signaling cost
t_pred_cost += count0 * av1_cost_zero(t_nopred_prob[i]) +
count1 * av1_cost_one(t_nopred_prob[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;
}
}
/* TODO(negge) This function may be called by more than one thread when using
a multi-threaded decoder and this may cause a data race. */
int ifd_inspect(insp_frame_data *fd, void *decoder) {
struct AV1Decoder *pbi = (struct AV1Decoder *)decoder;
AV1_COMMON *const cm = &pbi->common;
if (fd->mi_rows != cm->mi_rows || fd->mi_cols != cm->mi_cols) {
ifd_clear(fd);
ifd_init_mi_rc(fd, cm->mi_rows, cm->mi_cols);
}
fd->show_frame = cm->show_frame;
fd->frame_type = cm->frame_type;
fd->base_qindex = cm->base_qindex;
// Set width and height of the first tile until generic support can be added
TileInfo tile_info;
av1_tile_set_row(&tile_info, cm, 0);
av1_tile_set_col(&tile_info, cm, 0);
fd->tile_mi_cols = tile_info.mi_col_end - tile_info.mi_col_start;
fd->tile_mi_rows = tile_info.mi_row_end - tile_info.mi_row_start;
fd->delta_q_present_flag = cm->delta_q_present_flag;
fd->delta_q_res = cm->delta_q_res;
#if CONFIG_ACCOUNTING
fd->accounting = &pbi->accounting;
#endif
// TODO(negge): copy per frame CDEF data
int i, j;
for (i = 0; i < MAX_SEGMENTS; i++) {
for (j = 0; j < 2; j++) {
fd->y_dequant[i][j] = cm->y_dequant_QTX[i][j];
fd->u_dequant[i][j] = cm->u_dequant_QTX[i][j];
fd->v_dequant[i][j] = cm->v_dequant_QTX[i][j];
}
}
for (j = 0; j < cm->mi_rows; j++) {
for (i = 0; i < cm->mi_cols; i++) {
const MB_MODE_INFO *mbmi = cm->mi_grid_visible[j * cm->mi_stride + i];
insp_mi_data *mi = &fd->mi_grid[j * cm->mi_cols + i];
// Segment
mi->segment_id = mbmi->segment_id;
// Motion Vectors
mi->mv[0].row = mbmi->mv[0].as_mv.row;
mi->mv[0].col = mbmi->mv[0].as_mv.col;
mi->mv[1].row = mbmi->mv[1].as_mv.row;
mi->mv[1].col = mbmi->mv[1].as_mv.col;
// Reference Frames
mi->ref_frame[0] = mbmi->ref_frame[0];
mi->ref_frame[1] = mbmi->ref_frame[1];
// Prediction Mode
mi->mode = mbmi->mode;
// Prediction Mode for Chromatic planes
if (mi->mode < INTRA_MODES) {
mi->uv_mode = mbmi->uv_mode;
} else {
mi->uv_mode = UV_MODE_INVALID;
}
// Block Size
mi->sb_type = mbmi->sb_type;
// Skip Flag
mi->skip = mbmi->skip;
mi->filter[0] = av1_extract_interp_filter(mbmi->interp_filters, 0);
mi->filter[1] = av1_extract_interp_filter(mbmi->interp_filters, 1);
mi->dual_filter_type = mi->filter[0] * 3 + mi->filter[1];
// Transform
// TODO(anyone): extract tx type info from mbmi->txk_type[].
mi->tx_type = DCT_DCT;
mi->tx_size = mbmi->tx_size;
mi->cdef_level =
cm->cdef_strengths[mbmi->cdef_strength] / CDEF_SEC_STRENGTHS;
mi->cdef_strength =
cm->cdef_strengths[mbmi->cdef_strength] % CDEF_SEC_STRENGTHS;
mi->cdef_strength += mi->cdef_strength == 3;
if (mbmi->uv_mode == UV_CFL_PRED) {
mi->cfl_alpha_idx = mbmi->cfl_alpha_idx;
mi->cfl_alpha_sign = mbmi->cfl_alpha_signs;
} else {
mi->cfl_alpha_idx = 0;
mi->cfl_alpha_sign = 0;
}
// delta_q
mi->current_qindex = mbmi->current_qindex;
}
}
return 1;
}
