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