// Allocate storage for each tile column.
// TODO(jzern): when max_threads <= 1 the same storage could be used for each
// tile.
static void alloc_tile_storage(VP9D_COMP *pbi, int tile_cols) {
VP9_COMMON *const cm = &pbi->common;
const int aligned_mi_cols = mi_cols_aligned_to_sb(cm->mi_cols);
int i, tile_col;
CHECK_MEM_ERROR(cm, pbi->mi_streams,
vpx_realloc(pbi->mi_streams, tile_cols *
sizeof(*pbi->mi_streams)));
for (tile_col = 0; tile_col < tile_cols; ++tile_col) {
TileInfo tile;
vp9_tile_init(&tile, cm, 0, tile_col);
pbi->mi_streams[tile_col] =
&cm->mi[cm->mi_rows * tile.mi_col_start];
}
// 2 contexts per 'mi unit', so that we have one context per 4x4 txfm
// block where mi unit size is 8x8.
CHECK_MEM_ERROR(cm, pbi->above_context[0],
vpx_realloc(pbi->above_context[0],
sizeof(*pbi->above_context[0]) * MAX_MB_PLANE *
2 * aligned_mi_cols));
for (i = 1; i < MAX_MB_PLANE; ++i) {
pbi->above_context[i] = pbi->above_context[0] +
i * sizeof(*pbi->above_context[0]) *
2 * aligned_mi_cols;
}
// This is sized based on the entire frame. Each tile operates within its
// column bounds.
CHECK_MEM_ERROR(cm, pbi->above_seg_context,
vpx_realloc(pbi->above_seg_context,
sizeof(*pbi->above_seg_context) *
aligned_mi_cols));
}
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 };
vp9_prob no_pred_tree[SEG_TREE_PROBS];
vp9_prob t_pred_tree[SEG_TREE_PROBS];
vp9_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));
}
}
