Line data Source code
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 :
21 0 : void vp9_enable_segmentation(struct segmentation *seg) {
22 0 : seg->enabled = 1;
23 0 : seg->update_map = 1;
24 0 : seg->update_data = 1;
25 0 : }
26 :
27 0 : void vp9_disable_segmentation(struct segmentation *seg) {
28 0 : seg->enabled = 0;
29 0 : seg->update_map = 0;
30 0 : seg->update_data = 0;
31 0 : }
32 :
33 0 : void vp9_set_segment_data(struct segmentation *seg, signed char *feature_data,
34 : unsigned char abs_delta) {
35 0 : seg->abs_delta = abs_delta;
36 :
37 0 : memcpy(seg->feature_data, feature_data, sizeof(seg->feature_data));
38 0 : }
39 0 : void vp9_disable_segfeature(struct segmentation *seg, int segment_id,
40 : SEG_LVL_FEATURES feature_id) {
41 0 : seg->feature_mask[segment_id] &= ~(1 << feature_id);
42 0 : }
43 :
44 0 : void vp9_clear_segdata(struct segmentation *seg, int segment_id,
45 : SEG_LVL_FEATURES feature_id) {
46 0 : seg->feature_data[segment_id][feature_id] = 0;
47 0 : }
48 :
49 : // Based on set of segment counts calculate a probability tree
50 0 : static void calc_segtree_probs(int *segcounts, vpx_prob *segment_tree_probs) {
51 : // Work out probabilities of each segment
52 0 : const int c01 = segcounts[0] + segcounts[1];
53 0 : const int c23 = segcounts[2] + segcounts[3];
54 0 : const int c45 = segcounts[4] + segcounts[5];
55 0 : const int c67 = segcounts[6] + segcounts[7];
56 :
57 0 : segment_tree_probs[0] = get_binary_prob(c01 + c23, c45 + c67);
58 0 : segment_tree_probs[1] = get_binary_prob(c01, c23);
59 0 : segment_tree_probs[2] = get_binary_prob(c45, c67);
60 0 : segment_tree_probs[3] = get_binary_prob(segcounts[0], segcounts[1]);
61 0 : segment_tree_probs[4] = get_binary_prob(segcounts[2], segcounts[3]);
62 0 : segment_tree_probs[5] = get_binary_prob(segcounts[4], segcounts[5]);
63 0 : segment_tree_probs[6] = get_binary_prob(segcounts[6], segcounts[7]);
64 0 : }
65 :
66 : // Based on set of segment counts and probabilities calculate a cost estimate
67 0 : static int cost_segmap(int *segcounts, vpx_prob *probs) {
68 0 : const int c01 = segcounts[0] + segcounts[1];
69 0 : const int c23 = segcounts[2] + segcounts[3];
70 0 : const int c45 = segcounts[4] + segcounts[5];
71 0 : const int c67 = segcounts[6] + segcounts[7];
72 0 : const int c0123 = c01 + c23;
73 0 : const int c4567 = c45 + c67;
74 :
75 : // Cost the top node of the tree
76 0 : int cost = c0123 * vp9_cost_zero(probs[0]) + c4567 * vp9_cost_one(probs[0]);
77 :
78 : // Cost subsequent levels
79 0 : if (c0123 > 0) {
80 0 : cost += c01 * vp9_cost_zero(probs[1]) + c23 * vp9_cost_one(probs[1]);
81 :
82 0 : if (c01 > 0)
83 0 : cost += segcounts[0] * vp9_cost_zero(probs[3]) +
84 0 : segcounts[1] * vp9_cost_one(probs[3]);
85 0 : if (c23 > 0)
86 0 : cost += segcounts[2] * vp9_cost_zero(probs[4]) +
87 0 : segcounts[3] * vp9_cost_one(probs[4]);
88 : }
89 :
90 0 : if (c4567 > 0) {
91 0 : cost += c45 * vp9_cost_zero(probs[2]) + c67 * vp9_cost_one(probs[2]);
92 :
93 0 : if (c45 > 0)
94 0 : cost += segcounts[4] * vp9_cost_zero(probs[5]) +
95 0 : segcounts[5] * vp9_cost_one(probs[5]);
96 0 : if (c67 > 0)
97 0 : cost += segcounts[6] * vp9_cost_zero(probs[6]) +
98 0 : segcounts[7] * vp9_cost_one(probs[6]);
99 : }
100 :
101 0 : return cost;
102 : }
103 :
104 0 : 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 0 : if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return;
113 :
114 0 : xd->mi = mi;
115 0 : segment_id = xd->mi[0]->segment_id;
116 :
117 0 : 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 0 : no_pred_segcounts[segment_id]++;
121 :
122 : // Temporal prediction not allowed on key frames
123 0 : if (cm->frame_type != KEY_FRAME) {
124 0 : const BLOCK_SIZE bsize = xd->mi[0]->sb_type;
125 : // Test to see if the segment id matches the predicted value.
126 0 : const int pred_segment_id =
127 0 : get_segment_id(cm, cm->last_frame_seg_map, bsize, mi_row, mi_col);
128 0 : const int pred_flag = pred_segment_id == segment_id;
129 0 : 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 0 : xd->mi[0]->seg_id_predicted = pred_flag;
134 0 : temporal_predictor_count[pred_context][pred_flag]++;
135 :
136 : // Update the "unpredicted" segment count
137 0 : if (!pred_flag) t_unpred_seg_counts[segment_id]++;
138 : }
139 : }
140 :
141 0 : 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 0 : const int mis = cm->mi_stride;
148 : int bw, bh;
149 0 : const int bs = num_8x8_blocks_wide_lookup[bsize], hbs = bs / 2;
150 :
151 0 : if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return;
152 :
153 0 : bw = num_8x8_blocks_wide_lookup[mi[0]->sb_type];
154 0 : bh = num_8x8_blocks_high_lookup[mi[0]->sb_type];
155 :
156 0 : if (bw == bs && bh == bs) {
157 0 : count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
158 : t_unpred_seg_counts, bs, bs, mi_row, mi_col);
159 0 : } else if (bw == bs && bh < bs) {
160 0 : count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
161 : t_unpred_seg_counts, bs, hbs, mi_row, mi_col);
162 0 : 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 0 : } else if (bw < bs && bh == bs) {
166 0 : count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
167 : t_unpred_seg_counts, hbs, bs, mi_row, mi_col);
168 0 : 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 0 : const BLOCK_SIZE subsize = subsize_lookup[PARTITION_SPLIT][bsize];
173 : int n;
174 :
175 0 : assert(bw < bs && bh < bs);
176 :
177 0 : for (n = 0; n < 4; n++) {
178 0 : const int mi_dc = hbs * (n & 1);
179 0 : const int mi_dr = hbs * (n >> 1);
180 :
181 0 : 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 :
188 0 : void vp9_choose_segmap_coding_method(VP9_COMMON *cm, MACROBLOCKD *xd) {
189 0 : struct segmentation *seg = &cm->seg;
190 :
191 : int no_pred_cost;
192 0 : int t_pred_cost = INT_MAX;
193 :
194 : int i, tile_col, mi_row, mi_col;
195 :
196 0 : int temporal_predictor_count[PREDICTION_PROBS][2] = { { 0 } };
197 0 : int no_pred_segcounts[MAX_SEGMENTS] = { 0 };
198 0 : 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 0 : memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
207 0 : 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 0 : for (tile_col = 0; tile_col < 1 << cm->log2_tile_cols; tile_col++) {
212 : TileInfo tile;
213 : MODE_INFO **mi_ptr;
214 0 : vp9_tile_init(&tile, cm, 0, tile_col);
215 :
216 0 : mi_ptr = cm->mi_grid_visible + tile.mi_col_start;
217 0 : for (mi_row = 0; mi_row < cm->mi_rows;
218 0 : mi_row += 8, mi_ptr += 8 * cm->mi_stride) {
219 0 : MODE_INFO **mi = mi_ptr;
220 0 : for (mi_col = tile.mi_col_start; mi_col < tile.mi_col_end;
221 0 : mi_col += 8, mi += 8)
222 0 : 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 0 : calc_segtree_probs(no_pred_segcounts, no_pred_tree);
231 0 : no_pred_cost = cost_segmap(no_pred_segcounts, no_pred_tree);
232 :
233 : // Key frames cannot use temporal prediction
234 0 : 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 0 : calc_segtree_probs(t_unpred_seg_counts, t_pred_tree);
238 0 : 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 0 : for (i = 0; i < PREDICTION_PROBS; i++) {
242 0 : const int count0 = temporal_predictor_count[i][0];
243 0 : const int count1 = temporal_predictor_count[i][1];
244 :
245 0 : t_nopred_prob[i] = get_binary_prob(count0, count1);
246 :
247 : // Add in the predictor signaling cost
248 0 : t_pred_cost += count0 * vp9_cost_zero(t_nopred_prob[i]) +
249 0 : count1 * vp9_cost_one(t_nopred_prob[i]);
250 : }
251 : }
252 :
253 : // Now choose which coding method to use.
254 0 : if (t_pred_cost < no_pred_cost) {
255 0 : seg->temporal_update = 1;
256 0 : memcpy(seg->tree_probs, t_pred_tree, sizeof(t_pred_tree));
257 0 : memcpy(seg->pred_probs, t_nopred_prob, sizeof(t_nopred_prob));
258 : } else {
259 0 : seg->temporal_update = 0;
260 0 : memcpy(seg->tree_probs, no_pred_tree, sizeof(no_pred_tree));
261 : }
262 0 : }
263 :
264 0 : void vp9_reset_segment_features(struct segmentation *seg) {
265 : // Set up default state for MB feature flags
266 0 : seg->enabled = 0;
267 0 : seg->update_map = 0;
268 0 : seg->update_data = 0;
269 0 : memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
270 0 : vp9_clearall_segfeatures(seg);
271 0 : }
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