mirror of
https://repo.dactyloidae.xyz/Dactyloidae/UXP.git
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Update aom to v1.0.0
Update aom to commit id d14c5bb4f336ef1842046089849dee4a301fbbf0.
This commit is contained in:
trav90
Roy Tam
parent
bb61121b44
commit
48f6d2e034
1087 changed files with 154333 additions and 265310 deletions
277
third_party/aom/av1/encoder/segmentation.c
vendored
277
third_party/aom/av1/encoder/segmentation.c
vendored
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@ -18,26 +18,21 @@
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#include "av1/encoder/cost.h"
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#include "av1/encoder/segmentation.h"
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#include "av1/encoder/subexp.h"
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void av1_enable_segmentation(struct segmentation *seg) {
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seg->enabled = 1;
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seg->update_map = 1;
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seg->update_data = 1;
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seg->temporal_update = 0;
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}
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void av1_disable_segmentation(struct segmentation *seg) {
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seg->enabled = 0;
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seg->update_map = 0;
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seg->update_data = 0;
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seg->temporal_update = 0;
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}
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void av1_set_segment_data(struct segmentation *seg, int8_t *feature_data,
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unsigned char abs_delta) {
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seg->abs_delta = abs_delta;
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memcpy(seg->feature_data, feature_data, sizeof(seg->feature_data));
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}
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void av1_disable_segfeature(struct segmentation *seg, int segment_id,
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SEG_LVL_FEATURES feature_id) {
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seg->feature_mask[segment_id] &= ~(1 << feature_id);
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@ -48,76 +43,8 @@ void av1_clear_segdata(struct segmentation *seg, int segment_id,
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seg->feature_data[segment_id][feature_id] = 0;
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}
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// Based on set of segment counts calculate a probability tree
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static void calc_segtree_probs(unsigned *segcounts,
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aom_prob *segment_tree_probs,
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const aom_prob *cur_tree_probs,
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const int probwt) {
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// Work out probabilities of each segment
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const unsigned cc[4] = { segcounts[0] + segcounts[1],
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segcounts[2] + segcounts[3],
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segcounts[4] + segcounts[5],
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segcounts[6] + segcounts[7] };
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const unsigned ccc[2] = { cc[0] + cc[1], cc[2] + cc[3] };
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int i;
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segment_tree_probs[0] = get_binary_prob(ccc[0], ccc[1]);
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segment_tree_probs[1] = get_binary_prob(cc[0], cc[1]);
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segment_tree_probs[2] = get_binary_prob(cc[2], cc[3]);
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segment_tree_probs[3] = get_binary_prob(segcounts[0], segcounts[1]);
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segment_tree_probs[4] = get_binary_prob(segcounts[2], segcounts[3]);
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segment_tree_probs[5] = get_binary_prob(segcounts[4], segcounts[5]);
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segment_tree_probs[6] = get_binary_prob(segcounts[6], segcounts[7]);
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for (i = 0; i < 7; i++) {
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const unsigned *ct =
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i == 0 ? ccc : i < 3 ? cc + (i & 2) : segcounts + (i - 3) * 2;
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av1_prob_diff_update_savings_search(ct, cur_tree_probs[i],
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&segment_tree_probs[i],
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DIFF_UPDATE_PROB, probwt);
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}
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}
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// Based on set of segment counts and probabilities calculate a cost estimate
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static int cost_segmap(unsigned *segcounts, aom_prob *probs) {
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const int c01 = segcounts[0] + segcounts[1];
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const int c23 = segcounts[2] + segcounts[3];
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const int c45 = segcounts[4] + segcounts[5];
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const int c67 = segcounts[6] + segcounts[7];
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const int c0123 = c01 + c23;
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const int c4567 = c45 + c67;
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// Cost the top node of the tree
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int cost = c0123 * av1_cost_zero(probs[0]) + c4567 * av1_cost_one(probs[0]);
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// Cost subsequent levels
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if (c0123 > 0) {
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cost += c01 * av1_cost_zero(probs[1]) + c23 * av1_cost_one(probs[1]);
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if (c01 > 0)
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cost += segcounts[0] * av1_cost_zero(probs[3]) +
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segcounts[1] * av1_cost_one(probs[3]);
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if (c23 > 0)
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cost += segcounts[2] * av1_cost_zero(probs[4]) +
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segcounts[3] * av1_cost_one(probs[4]);
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}
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if (c4567 > 0) {
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cost += c45 * av1_cost_zero(probs[2]) + c67 * av1_cost_one(probs[2]);
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if (c45 > 0)
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cost += segcounts[4] * av1_cost_zero(probs[5]) +
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segcounts[5] * av1_cost_one(probs[5]);
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if (c67 > 0)
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cost += segcounts[6] * av1_cost_zero(probs[6]) +
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segcounts[7] * av1_cost_one(probs[6]);
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}
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return cost;
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}
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static void count_segs(const AV1_COMMON *cm, MACROBLOCKD *xd,
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const TileInfo *tile, MODE_INFO **mi,
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const TileInfo *tile, MB_MODE_INFO **mi,
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unsigned *no_pred_segcounts,
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unsigned (*temporal_predictor_count)[2],
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unsigned *t_unpred_seg_counts, int bw, int bh,
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@ -127,29 +54,27 @@ static void count_segs(const AV1_COMMON *cm, MACROBLOCKD *xd,
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if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return;
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xd->mi = mi;
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segment_id = xd->mi[0]->mbmi.segment_id;
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segment_id = xd->mi[0]->segment_id;
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set_mi_row_col(xd, tile, mi_row, bh, mi_col, bw,
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#if CONFIG_DEPENDENT_HORZTILES
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cm->dependent_horz_tiles,
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#endif // CONFIG_DEPENDENT_HORZTILES
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cm->mi_rows, cm->mi_cols);
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set_mi_row_col(xd, tile, mi_row, bh, mi_col, bw, cm->mi_rows, cm->mi_cols);
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// Count the number of hits on each segment with no prediction
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no_pred_segcounts[segment_id]++;
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// Temporal prediction not allowed on key frames
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if (cm->frame_type != KEY_FRAME) {
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const BLOCK_SIZE bsize = xd->mi[0]->mbmi.sb_type;
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const BLOCK_SIZE bsize = xd->mi[0]->sb_type;
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// Test to see if the segment id matches the predicted value.
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const int pred_segment_id =
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get_segment_id(cm, cm->last_frame_seg_map, bsize, mi_row, mi_col);
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cm->last_frame_seg_map
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? get_segment_id(cm, cm->last_frame_seg_map, bsize, mi_row, mi_col)
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: 0;
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const int pred_flag = pred_segment_id == segment_id;
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const int pred_context = av1_get_pred_context_seg_id(xd);
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// Store the prediction status for this mb and update counts
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// as appropriate
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xd->mi[0]->mbmi.seg_id_predicted = pred_flag;
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xd->mi[0]->seg_id_predicted = pred_flag;
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temporal_predictor_count[pred_context][pred_flag]++;
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// Update the "unpredicted" segment count
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@ -158,21 +83,15 @@ static void count_segs(const AV1_COMMON *cm, MACROBLOCKD *xd,
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}
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static void count_segs_sb(const AV1_COMMON *cm, MACROBLOCKD *xd,
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const TileInfo *tile, MODE_INFO **mi,
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const TileInfo *tile, MB_MODE_INFO **mi,
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unsigned *no_pred_segcounts,
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unsigned (*temporal_predictor_count)[2],
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unsigned *t_unpred_seg_counts, int mi_row, int mi_col,
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BLOCK_SIZE bsize) {
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const int mis = cm->mi_stride;
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const int bs = mi_size_wide[bsize], hbs = bs / 2;
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#if CONFIG_EXT_PARTITION_TYPES
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PARTITION_TYPE partition;
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#if CONFIG_EXT_PARTITION_TYPES_AB
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const int qbs = bs / 4;
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#endif // CONFIG_EXT_PARTITION_TYPES_AB
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#else
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int bw, bh;
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#endif // CONFIG_EXT_PARTITION_TYPES
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if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return;
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@ -181,7 +100,6 @@ static void count_segs_sb(const AV1_COMMON *cm, MACROBLOCKD *xd,
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no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts, \
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(cs_bw), (cs_bh), mi_row + (cs_rowoff), mi_col + (cs_coloff));
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#if CONFIG_EXT_PARTITION_TYPES
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if (bsize == BLOCK_8X8)
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partition = PARTITION_NONE;
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else
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@ -196,55 +114,43 @@ static void count_segs_sb(const AV1_COMMON *cm, MACROBLOCKD *xd,
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CSEGS(hbs, bs, 0, 0);
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CSEGS(hbs, bs, 0, hbs);
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break;
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#if CONFIG_EXT_PARTITION_TYPES_AB
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case PARTITION_HORZ_A:
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CSEGS(hbs, hbs, 0, 0);
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CSEGS(hbs, hbs, 0, hbs);
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CSEGS(bs, hbs, hbs, 0);
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break;
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case PARTITION_HORZ_B:
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CSEGS(bs, hbs, 0, 0);
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CSEGS(hbs, hbs, hbs, 0);
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CSEGS(hbs, hbs, hbs, hbs);
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break;
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case PARTITION_VERT_A:
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CSEGS(hbs, hbs, 0, 0);
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CSEGS(hbs, hbs, hbs, 0);
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CSEGS(hbs, bs, 0, hbs);
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break;
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case PARTITION_VERT_B:
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CSEGS(hbs, bs, 0, 0);
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CSEGS(hbs, hbs, 0, hbs);
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CSEGS(hbs, hbs, hbs, hbs);
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break;
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case PARTITION_HORZ_4:
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CSEGS(bs, qbs, 0, 0);
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CSEGS(bs, qbs, qbs, 0);
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CSEGS(bs, hbs, hbs, 0);
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break;
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case PARTITION_HORZ_B:
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CSEGS(bs, hbs, 0, 0);
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CSEGS(bs, qbs, hbs, 0);
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CSEGS(bs, qbs, 2 * qbs, 0);
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if (mi_row + 3 * qbs < cm->mi_rows) CSEGS(bs, qbs, 3 * qbs, 0);
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break;
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case PARTITION_VERT_A:
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case PARTITION_VERT_4:
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CSEGS(qbs, bs, 0, 0);
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CSEGS(qbs, bs, 0, qbs);
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CSEGS(hbs, bs, 0, hbs);
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break;
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case PARTITION_VERT_B:
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CSEGS(hbs, bs, 0, 0);
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CSEGS(qbs, bs, 0, hbs);
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CSEGS(qbs, bs, 0, 2 * qbs);
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if (mi_col + 3 * qbs < cm->mi_cols) CSEGS(qbs, bs, 0, 3 * qbs);
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break;
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#else
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case PARTITION_HORZ_A:
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CSEGS(hbs, hbs, 0, 0);
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CSEGS(hbs, hbs, 0, hbs);
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CSEGS(bs, hbs, hbs, 0);
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break;
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case PARTITION_HORZ_B:
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CSEGS(bs, hbs, 0, 0);
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CSEGS(hbs, hbs, hbs, 0);
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CSEGS(hbs, hbs, hbs, hbs);
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break;
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case PARTITION_VERT_A:
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CSEGS(hbs, hbs, 0, 0);
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CSEGS(hbs, hbs, hbs, 0);
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CSEGS(hbs, bs, 0, hbs);
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break;
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case PARTITION_VERT_B:
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CSEGS(hbs, bs, 0, 0);
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CSEGS(hbs, hbs, 0, hbs);
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CSEGS(hbs, hbs, hbs, hbs);
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break;
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#endif
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case PARTITION_SPLIT: {
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const BLOCK_SIZE subsize = subsize_lookup[PARTITION_SPLIT][bsize];
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int n;
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assert(num_8x8_blocks_wide_lookup[mi[0]->mbmi.sb_type] < bs &&
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num_8x8_blocks_high_lookup[mi[0]->mbmi.sb_type] < bs);
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case PARTITION_SPLIT: {
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const BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_SPLIT);
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int n;
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for (n = 0; n < 4; n++) {
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const int mi_dc = hbs * (n & 1);
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@ -257,34 +163,6 @@ static void count_segs_sb(const AV1_COMMON *cm, MACROBLOCKD *xd,
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} break;
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default: assert(0);
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}
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#else
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bw = mi_size_wide[mi[0]->mbmi.sb_type];
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bh = mi_size_high[mi[0]->mbmi.sb_type];
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if (bw == bs && bh == bs) {
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CSEGS(bs, bs, 0, 0);
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} else if (bw == bs && bh < bs) {
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CSEGS(bs, hbs, 0, 0);
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CSEGS(bs, hbs, hbs, 0);
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} else if (bw < bs && bh == bs) {
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CSEGS(hbs, bs, 0, 0);
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CSEGS(hbs, bs, 0, hbs);
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} else {
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const BLOCK_SIZE subsize = subsize_lookup[PARTITION_SPLIT][bsize];
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int n;
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assert(bw < bs && bh < bs);
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for (n = 0; n < 4; n++) {
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const int mi_dc = hbs * (n & 1);
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const int mi_dr = hbs * (n >> 1);
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count_segs_sb(cm, xd, tile, &mi[mi_dr * mis + mi_dc], no_pred_segcounts,
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temporal_predictor_count, t_unpred_seg_counts,
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mi_row + mi_dr, mi_col + mi_dc, subsize);
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}
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}
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#endif // CONFIG_EXT_PARTITION_TYPES
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#undef CSEGS
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}
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@ -292,83 +170,58 @@ static void count_segs_sb(const AV1_COMMON *cm, MACROBLOCKD *xd,
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void av1_choose_segmap_coding_method(AV1_COMMON *cm, MACROBLOCKD *xd) {
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struct segmentation *seg = &cm->seg;
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struct segmentation_probs *segp = &cm->fc->seg;
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int no_pred_cost;
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int t_pred_cost = INT_MAX;
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int tile_col, tile_row, mi_row, mi_col;
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const int probwt = cm->num_tg;
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unsigned(*temporal_predictor_count)[2] = cm->counts.seg.pred;
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unsigned *no_pred_segcounts = cm->counts.seg.tree_total;
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unsigned *t_unpred_seg_counts = cm->counts.seg.tree_mispred;
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aom_prob no_pred_tree[SEG_TREE_PROBS];
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aom_prob t_pred_tree[SEG_TREE_PROBS];
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#if !CONFIG_NEW_MULTISYMBOL
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aom_prob t_nopred_prob[PREDICTION_PROBS];
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#endif
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unsigned temporal_predictor_count[SEG_TEMPORAL_PRED_CTXS][2] = { { 0 } };
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unsigned no_pred_segcounts[MAX_SEGMENTS] = { 0 };
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unsigned t_unpred_seg_counts[MAX_SEGMENTS] = { 0 };
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(void)xd;
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// We are about to recompute all the segment counts, so zero the accumulators.
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av1_zero(cm->counts.seg);
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// First of all generate stats regarding how well the last segment map
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// predicts this one
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for (tile_row = 0; tile_row < cm->tile_rows; tile_row++) {
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TileInfo tile_info;
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av1_tile_set_row(&tile_info, cm, tile_row);
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for (tile_col = 0; tile_col < cm->tile_cols; tile_col++) {
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MODE_INFO **mi_ptr;
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MB_MODE_INFO **mi_ptr;
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av1_tile_set_col(&tile_info, cm, tile_col);
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#if CONFIG_DEPENDENT_HORZTILES
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av1_tile_set_tg_boundary(&tile_info, cm, tile_row, tile_col);
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#endif
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mi_ptr = cm->mi_grid_visible + tile_info.mi_row_start * cm->mi_stride +
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tile_info.mi_col_start;
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for (mi_row = tile_info.mi_row_start; mi_row < tile_info.mi_row_end;
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mi_row += cm->mib_size, mi_ptr += cm->mib_size * cm->mi_stride) {
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MODE_INFO **mi = mi_ptr;
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mi_row += cm->seq_params.mib_size,
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mi_ptr += cm->seq_params.mib_size * cm->mi_stride) {
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MB_MODE_INFO **mi = mi_ptr;
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for (mi_col = tile_info.mi_col_start; mi_col < tile_info.mi_col_end;
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mi_col += cm->mib_size, mi += cm->mib_size) {
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mi_col += cm->seq_params.mib_size, mi += cm->seq_params.mib_size) {
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count_segs_sb(cm, xd, &tile_info, mi, no_pred_segcounts,
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temporal_predictor_count, t_unpred_seg_counts, mi_row,
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mi_col, cm->sb_size);
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mi_col, cm->seq_params.sb_size);
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}
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}
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}
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}
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// Work out probability tree for coding segments without prediction
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// and the cost.
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calc_segtree_probs(no_pred_segcounts, no_pred_tree, segp->tree_probs, probwt);
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no_pred_cost = cost_segmap(no_pred_segcounts, no_pred_tree);
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int seg_id_cost[MAX_SEGMENTS];
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av1_cost_tokens_from_cdf(seg_id_cost, segp->tree_cdf, NULL);
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no_pred_cost = 0;
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for (int i = 0; i < MAX_SEGMENTS; ++i)
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no_pred_cost += no_pred_segcounts[i] * seg_id_cost[i];
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// Key frames cannot use temporal prediction
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if (!frame_is_intra_only(cm) && !cm->error_resilient_mode) {
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// Work out probability tree for coding those segments not
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// predicted using the temporal method and the cost.
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calc_segtree_probs(t_unpred_seg_counts, t_pred_tree, segp->tree_probs,
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probwt);
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t_pred_cost = cost_segmap(t_unpred_seg_counts, t_pred_tree);
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#if !CONFIG_NEW_MULTISYMBOL
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// Add in the cost of the signaling for each prediction context.
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int i;
|
||||
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]);
|
||||
// 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];
|
||||
}
|
||||
#endif
|
||||
// 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.
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue