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