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Diffstat (limited to 'media/libvpx/vp9/encoder/vp9_segmentation.c')
| -rw-r--r-- | media/libvpx/vp9/encoder/vp9_segmentation.c | 281 |
1 files changed, 281 insertions, 0 deletions
diff --git a/media/libvpx/vp9/encoder/vp9_segmentation.c b/media/libvpx/vp9/encoder/vp9_segmentation.c new file mode 100644 index 000000000..9b15072e9 --- /dev/null +++ b/media/libvpx/vp9/encoder/vp9_segmentation.c @@ -0,0 +1,281 @@ +/* + * 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, vp9_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, vp9_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]->mbmi.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]->mbmi.sb_type; + // Test to see if the segment id matches the predicted value. + const int pred_segment_id = vp9_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]->mbmi.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]->mbmi.sb_type]; + bh = num_8x8_blocks_high_lookup[mi[0]->mbmi.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 }; + + 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)); + } +} + +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); +} |