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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 #include "vpx_mem/vpx_mem.h" |
| 14 #include "vp9/encoder/vp9_segmentation.h" |
| 15 #include "vp9/common/vp9_pred_common.h" |
| 16 |
| 17 void vp9_update_gf_useage_maps(VP9_COMP *cpi, VP9_COMMON *cm, MACROBLOCK *x) { |
| 18 int mb_row, mb_col; |
| 19 |
| 20 MODE_INFO *this_mb_mode_info = cm->mi; |
| 21 |
| 22 x->gf_active_ptr = (signed char *)cpi->gf_active_flags; |
| 23 |
| 24 if ((cm->frame_type == KEY_FRAME) || (cm->refresh_golden_frame)) { |
| 25 // Reset Gf useage monitors |
| 26 vpx_memset(cpi->gf_active_flags, 1, (cm->mb_rows * cm->mb_cols)); |
| 27 cpi->gf_active_count = cm->mb_rows * cm->mb_cols; |
| 28 } else { |
| 29 // for each macroblock row in image |
| 30 for (mb_row = 0; mb_row < cm->mb_rows; mb_row++) { |
| 31 // for each macroblock col in image |
| 32 for (mb_col = 0; mb_col < cm->mb_cols; mb_col++) { |
| 33 |
| 34 // If using golden then set GF active flag if not already set. |
| 35 // If using last frame 0,0 mode then leave flag as it is |
| 36 // else if using non 0,0 motion or intra modes then clear |
| 37 // flag if it is currently set |
| 38 if ((this_mb_mode_info->mbmi.ref_frame == GOLDEN_FRAME) || |
| 39 (this_mb_mode_info->mbmi.ref_frame == ALTREF_FRAME)) { |
| 40 if (*(x->gf_active_ptr) == 0) { |
| 41 *(x->gf_active_ptr) = 1; |
| 42 cpi->gf_active_count++; |
| 43 } |
| 44 } else if ((this_mb_mode_info->mbmi.mode != ZEROMV) && |
| 45 *(x->gf_active_ptr)) { |
| 46 *(x->gf_active_ptr) = 0; |
| 47 cpi->gf_active_count--; |
| 48 } |
| 49 |
| 50 x->gf_active_ptr++; // Step onto next entry |
| 51 this_mb_mode_info++; // skip to next mb |
| 52 |
| 53 } |
| 54 |
| 55 // this is to account for the border |
| 56 this_mb_mode_info++; |
| 57 } |
| 58 } |
| 59 } |
| 60 |
| 61 void vp9_enable_segmentation(VP9_PTR ptr) { |
| 62 VP9_COMP *cpi = (VP9_COMP *)(ptr); |
| 63 |
| 64 // Set the appropriate feature bit |
| 65 cpi->mb.e_mbd.segmentation_enabled = 1; |
| 66 cpi->mb.e_mbd.update_mb_segmentation_map = 1; |
| 67 cpi->mb.e_mbd.update_mb_segmentation_data = 1; |
| 68 } |
| 69 |
| 70 void vp9_disable_segmentation(VP9_PTR ptr) { |
| 71 VP9_COMP *cpi = (VP9_COMP *)(ptr); |
| 72 |
| 73 // Clear the appropriate feature bit |
| 74 cpi->mb.e_mbd.segmentation_enabled = 0; |
| 75 } |
| 76 |
| 77 void vp9_set_segmentation_map(VP9_PTR ptr, |
| 78 unsigned char *segmentation_map) { |
| 79 VP9_COMP *cpi = (VP9_COMP *)(ptr); |
| 80 |
| 81 // Copy in the new segmentation map |
| 82 vpx_memcpy(cpi->segmentation_map, segmentation_map, |
| 83 (cpi->common.mb_rows * cpi->common.mb_cols)); |
| 84 |
| 85 // Signal that the map should be updated. |
| 86 cpi->mb.e_mbd.update_mb_segmentation_map = 1; |
| 87 cpi->mb.e_mbd.update_mb_segmentation_data = 1; |
| 88 } |
| 89 |
| 90 void vp9_set_segment_data(VP9_PTR ptr, |
| 91 signed char *feature_data, |
| 92 unsigned char abs_delta) { |
| 93 VP9_COMP *cpi = (VP9_COMP *)(ptr); |
| 94 |
| 95 cpi->mb.e_mbd.mb_segment_abs_delta = abs_delta; |
| 96 |
| 97 vpx_memcpy(cpi->mb.e_mbd.segment_feature_data, feature_data, |
| 98 sizeof(cpi->mb.e_mbd.segment_feature_data)); |
| 99 |
| 100 // TBD ?? Set the feature mask |
| 101 // vpx_memcpy(cpi->mb.e_mbd.segment_feature_mask, 0, |
| 102 // sizeof(cpi->mb.e_mbd.segment_feature_mask)); |
| 103 } |
| 104 |
| 105 // Based on set of segment counts calculate a probability tree |
| 106 static void calc_segtree_probs(MACROBLOCKD *xd, |
| 107 int *segcounts, |
| 108 vp9_prob *segment_tree_probs) { |
| 109 int count1, count2; |
| 110 int tot_count; |
| 111 int i; |
| 112 |
| 113 // Blank the strtucture to start with |
| 114 vpx_memset(segment_tree_probs, 0, |
| 115 MB_FEATURE_TREE_PROBS * sizeof(*segment_tree_probs)); |
| 116 |
| 117 // Total count for all segments |
| 118 count1 = segcounts[0] + segcounts[1]; |
| 119 count2 = segcounts[2] + segcounts[3]; |
| 120 tot_count = count1 + count2; |
| 121 |
| 122 // Work out probabilities of each segment |
| 123 if (tot_count) |
| 124 segment_tree_probs[0] = (count1 * 255) / tot_count; |
| 125 if (count1 > 0) |
| 126 segment_tree_probs[1] = (segcounts[0] * 255) / count1; |
| 127 if (count2 > 0) |
| 128 segment_tree_probs[2] = (segcounts[2] * 255) / count2; |
| 129 |
| 130 // Clamp probabilities to minimum allowed value |
| 131 for (i = 0; i < MB_FEATURE_TREE_PROBS; i++) { |
| 132 if (segment_tree_probs[i] == 0) |
| 133 segment_tree_probs[i] = 1; |
| 134 } |
| 135 } |
| 136 |
| 137 // Based on set of segment counts and probabilities calculate a cost estimate |
| 138 static int cost_segmap(MACROBLOCKD *xd, |
| 139 int *segcounts, |
| 140 vp9_prob *probs) { |
| 141 int cost; |
| 142 int count1, count2; |
| 143 |
| 144 // Cost the top node of the tree |
| 145 count1 = segcounts[0] + segcounts[1]; |
| 146 count2 = segcounts[2] + segcounts[3]; |
| 147 cost = count1 * vp9_cost_zero(probs[0]) + |
| 148 count2 * vp9_cost_one(probs[0]); |
| 149 |
| 150 // Now add the cost of each individual segment branch |
| 151 if (count1 > 0) |
| 152 cost += segcounts[0] * vp9_cost_zero(probs[1]) + |
| 153 segcounts[1] * vp9_cost_one(probs[1]); |
| 154 |
| 155 if (count2 > 0) |
| 156 cost += segcounts[2] * vp9_cost_zero(probs[2]) + |
| 157 segcounts[3] * vp9_cost_one(probs[2]); |
| 158 |
| 159 return cost; |
| 160 |
| 161 } |
| 162 |
| 163 void vp9_choose_segmap_coding_method(VP9_COMP *cpi) { |
| 164 VP9_COMMON *const cm = &cpi->common; |
| 165 MACROBLOCKD *const xd = &cpi->mb.e_mbd; |
| 166 |
| 167 int i; |
| 168 int tot_count; |
| 169 int no_pred_cost; |
| 170 int t_pred_cost = INT_MAX; |
| 171 int pred_context; |
| 172 |
| 173 int mb_row, mb_col; |
| 174 int segmap_index = 0; |
| 175 unsigned char segment_id; |
| 176 |
| 177 int temporal_predictor_count[PREDICTION_PROBS][2]; |
| 178 int no_pred_segcounts[MAX_MB_SEGMENTS]; |
| 179 int t_unpred_seg_counts[MAX_MB_SEGMENTS]; |
| 180 |
| 181 vp9_prob no_pred_tree[MB_FEATURE_TREE_PROBS]; |
| 182 vp9_prob t_pred_tree[MB_FEATURE_TREE_PROBS]; |
| 183 vp9_prob t_nopred_prob[PREDICTION_PROBS]; |
| 184 |
| 185 #if CONFIG_SUPERBLOCKS |
| 186 const int mis = cm->mode_info_stride; |
| 187 #endif |
| 188 |
| 189 // Set default state for the segment tree probabilities and the |
| 190 // temporal coding probabilities |
| 191 vpx_memset(xd->mb_segment_tree_probs, 255, |
| 192 sizeof(xd->mb_segment_tree_probs)); |
| 193 vpx_memset(cm->segment_pred_probs, 255, |
| 194 sizeof(cm->segment_pred_probs)); |
| 195 |
| 196 vpx_memset(no_pred_segcounts, 0, sizeof(no_pred_segcounts)); |
| 197 vpx_memset(t_unpred_seg_counts, 0, sizeof(t_unpred_seg_counts)); |
| 198 vpx_memset(temporal_predictor_count, 0, sizeof(temporal_predictor_count)); |
| 199 |
| 200 // First of all generate stats regarding how well the last segment map |
| 201 // predicts this one |
| 202 |
| 203 // Initialize macroblock decoder mode info context for the first mb |
| 204 // in the frame |
| 205 xd->mode_info_context = cm->mi; |
| 206 |
| 207 for (mb_row = 0; mb_row < cm->mb_rows; mb_row += 2) { |
| 208 for (mb_col = 0; mb_col < cm->mb_cols; mb_col += 2) { |
| 209 for (i = 0; i < 4; i++) { |
| 210 static const int dx[4] = { +1, -1, +1, +1 }; |
| 211 static const int dy[4] = { 0, +1, 0, -1 }; |
| 212 int x_idx = i & 1, y_idx = i >> 1; |
| 213 |
| 214 if (mb_col + x_idx >= cm->mb_cols || |
| 215 mb_row + y_idx >= cm->mb_rows) { |
| 216 goto end; |
| 217 } |
| 218 |
| 219 xd->mb_to_top_edge = -((mb_row * 16) << 3); |
| 220 xd->mb_to_left_edge = -((mb_col * 16) << 3); |
| 221 |
| 222 segmap_index = (mb_row + y_idx) * cm->mb_cols + mb_col + x_idx; |
| 223 segment_id = xd->mode_info_context->mbmi.segment_id; |
| 224 #if CONFIG_SUPERBLOCKS |
| 225 if (xd->mode_info_context->mbmi.encoded_as_sb) { |
| 226 if (mb_col + 1 < cm->mb_cols) |
| 227 segment_id = segment_id && |
| 228 xd->mode_info_context[1].mbmi.segment_id; |
| 229 if (mb_row + 1 < cm->mb_rows) { |
| 230 segment_id = segment_id && |
| 231 xd->mode_info_context[mis].mbmi.segment_id; |
| 232 if (mb_col + 1 < cm->mb_cols) |
| 233 segment_id = segment_id && |
| 234 xd->mode_info_context[mis + 1].mbmi.segment_id; |
| 235 } |
| 236 xd->mb_to_bottom_edge = ((cm->mb_rows - 2 - mb_row) * 16) << 3; |
| 237 xd->mb_to_right_edge = ((cm->mb_cols - 2 - mb_col) * 16) << 3; |
| 238 } else { |
| 239 #endif |
| 240 xd->mb_to_bottom_edge = ((cm->mb_rows - 1 - mb_row) * 16) << 3; |
| 241 xd->mb_to_right_edge = ((cm->mb_cols - 1 - mb_col) * 16) << 3; |
| 242 #if CONFIG_SUPERBLOCKS |
| 243 } |
| 244 #endif |
| 245 |
| 246 // Count the number of hits on each segment with no prediction |
| 247 no_pred_segcounts[segment_id]++; |
| 248 |
| 249 // Temporal prediction not allowed on key frames |
| 250 if (cm->frame_type != KEY_FRAME) { |
| 251 // Test to see if the segment id matches the predicted value. |
| 252 int seg_predicted = |
| 253 (segment_id == vp9_get_pred_mb_segid(cm, xd, segmap_index)); |
| 254 |
| 255 // Get the segment id prediction context |
| 256 pred_context = |
| 257 vp9_get_pred_context(cm, xd, PRED_SEG_ID); |
| 258 |
| 259 // Store the prediction status for this mb and update counts |
| 260 // as appropriate |
| 261 vp9_set_pred_flag(xd, PRED_SEG_ID, seg_predicted); |
| 262 temporal_predictor_count[pred_context][seg_predicted]++; |
| 263 |
| 264 if (!seg_predicted) |
| 265 // Update the "unpredicted" segment count |
| 266 t_unpred_seg_counts[segment_id]++; |
| 267 } |
| 268 |
| 269 #if CONFIG_SUPERBLOCKS |
| 270 if (xd->mode_info_context->mbmi.encoded_as_sb) { |
| 271 assert(!i); |
| 272 xd->mode_info_context += 2; |
| 273 break; |
| 274 } |
| 275 #endif |
| 276 end: |
| 277 xd->mode_info_context += dx[i] + dy[i] * cm->mode_info_stride; |
| 278 } |
| 279 } |
| 280 |
| 281 // this is to account for the border in mode_info_context |
| 282 xd->mode_info_context -= mb_col; |
| 283 xd->mode_info_context += cm->mode_info_stride * 2; |
| 284 } |
| 285 |
| 286 // Work out probability tree for coding segments without prediction |
| 287 // and the cost. |
| 288 calc_segtree_probs(xd, no_pred_segcounts, no_pred_tree); |
| 289 no_pred_cost = cost_segmap(xd, no_pred_segcounts, no_pred_tree); |
| 290 |
| 291 // Key frames cannot use temporal prediction |
| 292 if (cm->frame_type != KEY_FRAME) { |
| 293 // Work out probability tree for coding those segments not |
| 294 // predicted using the temporal method and the cost. |
| 295 calc_segtree_probs(xd, t_unpred_seg_counts, t_pred_tree); |
| 296 t_pred_cost = cost_segmap(xd, t_unpred_seg_counts, t_pred_tree); |
| 297 |
| 298 // Add in the cost of the signalling for each prediction context |
| 299 for (i = 0; i < PREDICTION_PROBS; i++) { |
| 300 tot_count = temporal_predictor_count[i][0] + |
| 301 temporal_predictor_count[i][1]; |
| 302 |
| 303 // Work out the context probabilities for the segment |
| 304 // prediction flag |
| 305 if (tot_count) { |
| 306 t_nopred_prob[i] = (temporal_predictor_count[i][0] * 255) / |
| 307 tot_count; |
| 308 |
| 309 // Clamp to minimum allowed value |
| 310 if (t_nopred_prob[i] < 1) |
| 311 t_nopred_prob[i] = 1; |
| 312 } else |
| 313 t_nopred_prob[i] = 1; |
| 314 |
| 315 // Add in the predictor signaling cost |
| 316 t_pred_cost += (temporal_predictor_count[i][0] * |
| 317 vp9_cost_zero(t_nopred_prob[i])) + |
| 318 (temporal_predictor_count[i][1] * |
| 319 vp9_cost_one(t_nopred_prob[i])); |
| 320 } |
| 321 } |
| 322 |
| 323 // Now choose which coding method to use. |
| 324 if (t_pred_cost < no_pred_cost) { |
| 325 cm->temporal_update = 1; |
| 326 vpx_memcpy(xd->mb_segment_tree_probs, |
| 327 t_pred_tree, sizeof(t_pred_tree)); |
| 328 vpx_memcpy(&cm->segment_pred_probs, |
| 329 t_nopred_prob, sizeof(t_nopred_prob)); |
| 330 } else { |
| 331 cm->temporal_update = 0; |
| 332 vpx_memcpy(xd->mb_segment_tree_probs, |
| 333 no_pred_tree, sizeof(no_pred_tree)); |
| 334 } |
| 335 } |
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