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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 
vp9_enable_segmentation(struct segmentation * seg)22 void vp9_enable_segmentation(struct segmentation *seg) {
23   seg->enabled = 1;
24   seg->update_map = 1;
25   seg->update_data = 1;
26 }
27 
vp9_disable_segmentation(struct segmentation * seg)28 void vp9_disable_segmentation(struct segmentation *seg) {
29   seg->enabled = 0;
30   seg->update_map = 0;
31   seg->update_data = 0;
32 }
33 
vp9_set_segment_data(struct segmentation * seg,signed char * feature_data,unsigned char abs_delta)34 void 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 }
vp9_disable_segfeature(struct segmentation * seg,int segment_id,SEG_LVL_FEATURES feature_id)41 void 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 
vp9_clear_segdata(struct segmentation * seg,int segment_id,SEG_LVL_FEATURES feature_id)46 void 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
calc_segtree_probs(int * segcounts,vpx_prob * segment_tree_probs)52 static 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
cost_segmap(int * segcounts,vpx_prob * probs)69 static 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 
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)109 static 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 
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)148 static 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 
vp9_choose_segmap_coding_method(VP9_COMMON * cm,MACROBLOCKD * xd)198 void 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 
vp9_reset_segment_features(struct segmentation * seg)274 void 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