1/*
2 *  Copyright (c) 2012 The WebM project authors. All Rights Reserved.
3 *
4 *  Use of this source code is governed by a BSD-style license
5 *  that can be found in the LICENSE file in the root of the source
6 *  tree. An additional intellectual property rights grant can be found
7 *  in the file PATENTS.  All contributing project authors may
8 *  be found in the AUTHORS file in the root of the source tree.
9 */
10
11
12#include <limits.h>
13
14#include "vpx_mem/vpx_mem.h"
15
16#include "vp9/common/vp9_pred_common.h"
17#include "vp9/common/vp9_tile_common.h"
18
19#include "vp9/encoder/vp9_cost.h"
20#include "vp9/encoder/vp9_segmentation.h"
21
22void vp9_enable_segmentation(struct segmentation *seg) {
23  seg->enabled = 1;
24  seg->update_map = 1;
25  seg->update_data = 1;
26}
27
28void vp9_disable_segmentation(struct segmentation *seg) {
29  seg->enabled = 0;
30  seg->update_map = 0;
31  seg->update_data = 0;
32}
33
34void vp9_set_segment_data(struct segmentation *seg,
35                          signed char *feature_data,
36                          unsigned char abs_delta) {
37  seg->abs_delta = abs_delta;
38
39  vpx_memcpy(seg->feature_data, feature_data, sizeof(seg->feature_data));
40
41  // TBD ?? Set the feature mask
42  // vpx_memcpy(cpi->mb.e_mbd.segment_feature_mask, 0,
43  //            sizeof(cpi->mb.e_mbd.segment_feature_mask));
44}
45void vp9_disable_segfeature(struct segmentation *seg, int segment_id,
46                            SEG_LVL_FEATURES feature_id) {
47  seg->feature_mask[segment_id] &= ~(1 << feature_id);
48}
49
50void vp9_clear_segdata(struct segmentation *seg, int segment_id,
51                       SEG_LVL_FEATURES feature_id) {
52  seg->feature_data[segment_id][feature_id] = 0;
53}
54
55// Based on set of segment counts calculate a probability tree
56static void calc_segtree_probs(int *segcounts, vp9_prob *segment_tree_probs) {
57  // Work out probabilities of each segment
58  const int c01 = segcounts[0] + segcounts[1];
59  const int c23 = segcounts[2] + segcounts[3];
60  const int c45 = segcounts[4] + segcounts[5];
61  const int c67 = segcounts[6] + segcounts[7];
62
63  segment_tree_probs[0] = get_binary_prob(c01 + c23, c45 + c67);
64  segment_tree_probs[1] = get_binary_prob(c01, c23);
65  segment_tree_probs[2] = get_binary_prob(c45, c67);
66  segment_tree_probs[3] = get_binary_prob(segcounts[0], segcounts[1]);
67  segment_tree_probs[4] = get_binary_prob(segcounts[2], segcounts[3]);
68  segment_tree_probs[5] = get_binary_prob(segcounts[4], segcounts[5]);
69  segment_tree_probs[6] = get_binary_prob(segcounts[6], segcounts[7]);
70}
71
72// Based on set of segment counts and probabilities calculate a cost estimate
73static int cost_segmap(int *segcounts, vp9_prob *probs) {
74  const int c01 = segcounts[0] + segcounts[1];
75  const int c23 = segcounts[2] + segcounts[3];
76  const int c45 = segcounts[4] + segcounts[5];
77  const int c67 = segcounts[6] + segcounts[7];
78  const int c0123 = c01 + c23;
79  const int c4567 = c45 + c67;
80
81  // Cost the top node of the tree
82  int cost = c0123 * vp9_cost_zero(probs[0]) +
83             c4567 * vp9_cost_one(probs[0]);
84
85  // Cost subsequent levels
86  if (c0123 > 0) {
87    cost += c01 * vp9_cost_zero(probs[1]) +
88            c23 * vp9_cost_one(probs[1]);
89
90    if (c01 > 0)
91      cost += segcounts[0] * vp9_cost_zero(probs[3]) +
92              segcounts[1] * vp9_cost_one(probs[3]);
93    if (c23 > 0)
94      cost += segcounts[2] * vp9_cost_zero(probs[4]) +
95              segcounts[3] * vp9_cost_one(probs[4]);
96  }
97
98  if (c4567 > 0) {
99    cost += c45 * vp9_cost_zero(probs[2]) +
100            c67 * vp9_cost_one(probs[2]);
101
102    if (c45 > 0)
103      cost += segcounts[4] * vp9_cost_zero(probs[5]) +
104              segcounts[5] * vp9_cost_one(probs[5]);
105    if (c67 > 0)
106      cost += segcounts[6] * vp9_cost_zero(probs[6]) +
107              segcounts[7] * vp9_cost_one(probs[6]);
108  }
109
110  return cost;
111}
112
113static void count_segs(const VP9_COMMON *cm, MACROBLOCKD *xd,
114                       const TileInfo *tile, MODE_INFO *mi,
115                       int *no_pred_segcounts,
116                       int (*temporal_predictor_count)[2],
117                       int *t_unpred_seg_counts,
118                       int bw, int bh, int mi_row, int mi_col) {
119  int segment_id;
120
121  if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols)
122    return;
123
124  xd->mi = mi;
125  segment_id = xd->mi[0].src_mi->mbmi.segment_id;
126
127  set_mi_row_col(xd, tile, mi_row, bh, mi_col, bw, cm->mi_rows, cm->mi_cols);
128
129  // Count the number of hits on each segment with no prediction
130  no_pred_segcounts[segment_id]++;
131
132  // Temporal prediction not allowed on key frames
133  if (cm->frame_type != KEY_FRAME) {
134    const BLOCK_SIZE bsize = xd->mi[0].src_mi->mbmi.sb_type;
135    // Test to see if the segment id matches the predicted value.
136    const int pred_segment_id = vp9_get_segment_id(cm, cm->last_frame_seg_map,
137                                                   bsize, mi_row, mi_col);
138    const int pred_flag = pred_segment_id == segment_id;
139    const int pred_context = vp9_get_pred_context_seg_id(xd);
140
141    // Store the prediction status for this mb and update counts
142    // as appropriate
143    xd->mi[0].src_mi->mbmi.seg_id_predicted = pred_flag;
144    temporal_predictor_count[pred_context][pred_flag]++;
145
146    // Update the "unpredicted" segment count
147    if (!pred_flag)
148      t_unpred_seg_counts[segment_id]++;
149  }
150}
151
152static void count_segs_sb(const VP9_COMMON *cm, MACROBLOCKD *xd,
153                          const TileInfo *tile, MODE_INFO *mi,
154                          int *no_pred_segcounts,
155                          int (*temporal_predictor_count)[2],
156                          int *t_unpred_seg_counts,
157                          int mi_row, int mi_col,
158                          BLOCK_SIZE bsize) {
159  const int mis = cm->mi_stride;
160  int bw, bh;
161  const int bs = num_8x8_blocks_wide_lookup[bsize], hbs = bs / 2;
162
163  if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols)
164    return;
165
166  bw = num_8x8_blocks_wide_lookup[mi[0].src_mi->mbmi.sb_type];
167  bh = num_8x8_blocks_high_lookup[mi[0].src_mi->mbmi.sb_type];
168
169  if (bw == bs && bh == bs) {
170    count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
171               t_unpred_seg_counts, bs, bs, mi_row, mi_col);
172  } else if (bw == bs && bh < bs) {
173    count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
174               t_unpred_seg_counts, bs, hbs, mi_row, mi_col);
175    count_segs(cm, xd, tile, mi + hbs * mis, no_pred_segcounts,
176               temporal_predictor_count, t_unpred_seg_counts, bs, hbs,
177               mi_row + hbs, mi_col);
178  } else if (bw < bs && bh == bs) {
179    count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
180               t_unpred_seg_counts, hbs, bs, mi_row, mi_col);
181    count_segs(cm, xd, tile, mi + hbs,
182               no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts,
183               hbs, bs, mi_row, mi_col + hbs);
184  } else {
185    const BLOCK_SIZE subsize = subsize_lookup[PARTITION_SPLIT][bsize];
186    int n;
187
188    assert(bw < bs && bh < bs);
189
190    for (n = 0; n < 4; n++) {
191      const int mi_dc = hbs * (n & 1);
192      const int mi_dr = hbs * (n >> 1);
193
194      count_segs_sb(cm, xd, tile, &mi[mi_dr * mis + mi_dc],
195                    no_pred_segcounts, temporal_predictor_count,
196                    t_unpred_seg_counts,
197                    mi_row + mi_dr, mi_col + mi_dc, subsize);
198    }
199  }
200}
201
202void vp9_choose_segmap_coding_method(VP9_COMMON *cm, MACROBLOCKD *xd) {
203  struct segmentation *seg = &cm->seg;
204
205  int no_pred_cost;
206  int t_pred_cost = INT_MAX;
207
208  int i, tile_col, mi_row, mi_col;
209
210  int temporal_predictor_count[PREDICTION_PROBS][2] = { { 0 } };
211  int no_pred_segcounts[MAX_SEGMENTS] = { 0 };
212  int t_unpred_seg_counts[MAX_SEGMENTS] = { 0 };
213
214  vp9_prob no_pred_tree[SEG_TREE_PROBS];
215  vp9_prob t_pred_tree[SEG_TREE_PROBS];
216  vp9_prob t_nopred_prob[PREDICTION_PROBS];
217
218  // Set default state for the segment tree probabilities and the
219  // temporal coding probabilities
220  vpx_memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
221  vpx_memset(seg->pred_probs, 255, sizeof(seg->pred_probs));
222
223  // First of all generate stats regarding how well the last segment map
224  // predicts this one
225  for (tile_col = 0; tile_col < 1 << cm->log2_tile_cols; tile_col++) {
226    TileInfo tile;
227    MODE_INFO *mi_ptr;
228    vp9_tile_init(&tile, cm, 0, tile_col);
229
230    mi_ptr = cm->mi + tile.mi_col_start;
231    for (mi_row = 0; mi_row < cm->mi_rows;
232         mi_row += 8, mi_ptr += 8 * cm->mi_stride) {
233      MODE_INFO *mi = mi_ptr;
234      for (mi_col = tile.mi_col_start; mi_col < tile.mi_col_end;
235           mi_col += 8, mi += 8)
236        count_segs_sb(cm, xd, &tile, mi, no_pred_segcounts,
237                      temporal_predictor_count, t_unpred_seg_counts,
238                      mi_row, mi_col, BLOCK_64X64);
239    }
240  }
241
242  // Work out probability tree for coding segments without prediction
243  // and the cost.
244  calc_segtree_probs(no_pred_segcounts, no_pred_tree);
245  no_pred_cost = cost_segmap(no_pred_segcounts, no_pred_tree);
246
247  // Key frames cannot use temporal prediction
248  if (!frame_is_intra_only(cm)) {
249    // Work out probability tree for coding those segments not
250    // predicted using the temporal method and the cost.
251    calc_segtree_probs(t_unpred_seg_counts, t_pred_tree);
252    t_pred_cost = cost_segmap(t_unpred_seg_counts, t_pred_tree);
253
254    // Add in the cost of the signaling for each prediction context.
255    for (i = 0; i < PREDICTION_PROBS; i++) {
256      const int count0 = temporal_predictor_count[i][0];
257      const int count1 = temporal_predictor_count[i][1];
258
259      t_nopred_prob[i] = get_binary_prob(count0, count1);
260
261      // Add in the predictor signaling cost
262      t_pred_cost += count0 * vp9_cost_zero(t_nopred_prob[i]) +
263                     count1 * vp9_cost_one(t_nopred_prob[i]);
264    }
265  }
266
267  // Now choose which coding method to use.
268  if (t_pred_cost < no_pred_cost) {
269    seg->temporal_update = 1;
270    vpx_memcpy(seg->tree_probs, t_pred_tree, sizeof(t_pred_tree));
271    vpx_memcpy(seg->pred_probs, t_nopred_prob, sizeof(t_nopred_prob));
272  } else {
273    seg->temporal_update = 0;
274    vpx_memcpy(seg->tree_probs, no_pred_tree, sizeof(no_pred_tree));
275  }
276}
277
278void vp9_reset_segment_features(struct segmentation *seg) {
279  // Set up default state for MB feature flags
280  seg->enabled = 0;
281  seg->update_map = 0;
282  seg->update_data = 0;
283  vpx_memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
284  vp9_clearall_segfeatures(seg);
285}
286