libvpx: Pull from upstream

source/libvpx/vp9/encoder/vp9_segmentation.c

 /*
  *  Copyright (c) 2012 The WebM project authors. All Rights Reserved.
  *
  *  Use of this source code is governed by a BSD-style license
  *  that can be found in the LICENSE file in the root of the source
  *  tree. An additional intellectual property rights grant can be found
  *  in the file PATENTS.  All contributing project authors may
  *  be found in the AUTHORS file in the root of the source tree.
  */
 
@@ skipping 99 matching lines @@
       cost += segcounts[4] * vp9_cost_zero(probs[5]) +
               segcounts[5] * vp9_cost_one(probs[5]);
     if (c67 > 0)
       cost += segcounts[6] * vp9_cost_zero(probs[6]) +
               segcounts[7] * vp9_cost_one(probs[6]);
   }
 
   return cost;
 }
 
-static void count_segs(VP9_COMP *cpi, MODE_INFO **mi_8x8,
+static void count_segs(VP9_COMP *cpi, const TileInfo *const tile,
+                       MODE_INFO **mi_8x8,
                        int *no_pred_segcounts,
                        int (*temporal_predictor_count)[2],
                        int *t_unpred_seg_counts,
                        int bw, int bh, int mi_row, int mi_col) {
   VP9_COMMON *const cm = &cpi->common;
   MACROBLOCKD *const xd = &cpi->mb.e_mbd;
   int segment_id;
 
   if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols)
     return;
 
-  segment_id = mi_8x8[0]->mbmi.segment_id;
+  xd->mi_8x8 = mi_8x8;
+  segment_id = xd->mi_8x8[0]->mbmi.segment_id;
 
-  set_mi_row_col(cm, xd, mi_row, bh, mi_col, bw);
+  set_mi_row_col(xd, tile, mi_row, bh, mi_col, bw, cm->mi_rows, cm->mi_cols);
 
   // Count the number of hits on each segment with no prediction
   no_pred_segcounts[segment_id]++;
 
   // Temporal prediction not allowed on key frames
   if (cm->frame_type != KEY_FRAME) {
     const BLOCK_SIZE bsize = mi_8x8[0]->mbmi.sb_type;
     // Test to see if the segment id matches the predicted value.
     const int pred_segment_id = vp9_get_segment_id(cm, cm->last_frame_seg_map,
                                                    bsize, mi_row, mi_col);
     const int pred_flag = pred_segment_id == segment_id;
     const int pred_context = vp9_get_pred_context_seg_id(xd);
 
     // Store the prediction status for this mb and update counts
     // as appropriate
     vp9_set_pred_flag_seg_id(xd, pred_flag);
     temporal_predictor_count[pred_context][pred_flag]++;
 
     if (!pred_flag)
       // Update the "unpredicted" segment count
       t_unpred_seg_counts[segment_id]++;
   }
 }
 
-static void count_segs_sb(VP9_COMP *cpi, MODE_INFO **mi_8x8,
+static void count_segs_sb(VP9_COMP *cpi, const TileInfo *const tile,
+                          MODE_INFO **mi_8x8,
                           int *no_pred_segcounts,
                           int (*temporal_predictor_count)[2],
                           int *t_unpred_seg_counts,
                           int mi_row, int mi_col,
                           BLOCK_SIZE bsize) {
   const VP9_COMMON *const cm = &cpi->common;
   const int mis = cm->mode_info_stride;
   int bw, bh;
   const int bs = num_8x8_blocks_wide_lookup[bsize], hbs = bs / 2;
 
   if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols)
     return;
 
   bw = num_8x8_blocks_wide_lookup[mi_8x8[0]->mbmi.sb_type];
   bh = num_8x8_blocks_high_lookup[mi_8x8[0]->mbmi.sb_type];
 
   if (bw == bs && bh == bs) {
-    count_segs(cpi, mi_8x8, no_pred_segcounts, temporal_predictor_count,
+    count_segs(cpi, tile, mi_8x8, no_pred_segcounts, temporal_predictor_count,
                t_unpred_seg_counts, bs, bs, mi_row, mi_col);
   } else if (bw == bs && bh < bs) {
-    count_segs(cpi, mi_8x8, no_pred_segcounts, temporal_predictor_count,
+    count_segs(cpi, tile, mi_8x8, no_pred_segcounts, temporal_predictor_count,
                t_unpred_seg_counts, bs, hbs, mi_row, mi_col);
-    count_segs(cpi, mi_8x8 + hbs * mis, no_pred_segcounts,
+    count_segs(cpi, tile, mi_8x8 + hbs * mis, no_pred_segcounts,
                temporal_predictor_count, t_unpred_seg_counts, bs, hbs,
                mi_row + hbs, mi_col);
   } else if (bw < bs && bh == bs) {
-    count_segs(cpi, mi_8x8, no_pred_segcounts, temporal_predictor_count,
+    count_segs(cpi, tile, mi_8x8, no_pred_segcounts, temporal_predictor_count,
                t_unpred_seg_counts, hbs, bs, mi_row, mi_col);
-    count_segs(cpi, mi_8x8 + hbs, no_pred_segcounts, temporal_predictor_count,
-               t_unpred_seg_counts, hbs, bs, mi_row, mi_col + hbs);
+    count_segs(cpi, tile, mi_8x8 + hbs,
+               no_pred_segcounts, temporal_predictor_count, t_unpred_seg_counts,
+               hbs, bs, mi_row, mi_col + hbs);
   } else {
     const BLOCK_SIZE subsize = subsize_lookup[PARTITION_SPLIT][bsize];
     int n;
 
     assert(bw < bs && bh < bs);
 
     for (n = 0; n < 4; n++) {
       const int mi_dc = hbs * (n & 1);
       const int mi_dr = hbs * (n >> 1);
 
-      count_segs_sb(cpi, &mi_8x8[mi_dr * mis + mi_dc],
+      count_segs_sb(cpi, tile, &mi_8x8[mi_dr * mis + mi_dc],
                     no_pred_segcounts, temporal_predictor_count,
                     t_unpred_seg_counts,
                     mi_row + mi_dr, mi_col + mi_dc, subsize);
     }
   }
 }
 
 void vp9_choose_segmap_coding_method(VP9_COMP *cpi) {
   VP9_COMMON *const cm = &cpi->common;
   struct segmentation *seg = &cm->seg;
@@ skipping 15 matching lines @@
   MODE_INFO **mi_ptr, **mi;
 
   // Set default state for the segment tree probabilities and the
   // temporal coding probabilities
   vpx_memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
   vpx_memset(seg->pred_probs, 255, sizeof(seg->pred_probs));
 
   // First of all generate stats regarding how well the last segment map
   // predicts this one
   for (tile_col = 0; tile_col < 1 << cm->log2_tile_cols; tile_col++) {
-    vp9_get_tile_col_offsets(cm, tile_col);
-    mi_ptr = cm->mi_grid_visible + cm->cur_tile_mi_col_start;
+    TileInfo tile;
+
+    vp9_tile_init(&tile, cm, 0, tile_col);
+    mi_ptr = cm->mi_grid_visible + tile.mi_col_start;
     for (mi_row = 0; mi_row < cm->mi_rows;
          mi_row += 8, mi_ptr += 8 * mis) {
       mi = mi_ptr;
-      for (mi_col = cm->cur_tile_mi_col_start; mi_col < cm->cur_tile_mi_col_end;
+      for (mi_col = tile.mi_col_start; mi_col < tile.mi_col_end;
            mi_col += 8, mi += 8)
-        count_segs_sb(cpi, mi, no_pred_segcounts, temporal_predictor_count,
-                      t_unpred_seg_counts, mi_row, mi_col, BLOCK_64X64);
+        count_segs_sb(cpi, &tile, mi, no_pred_segcounts,
+                      temporal_predictor_count, t_unpred_seg_counts,
+                      mi_row, mi_col, BLOCK_64X64);
     }
   }
 
   // Work out probability tree for coding segments without prediction
   // and the cost.
   calc_segtree_probs(no_pred_segcounts, no_pred_tree);
   no_pred_cost = cost_segmap(no_pred_segcounts, no_pred_tree);
 
   // Key frames cannot use temporal prediction
-  if (cm->frame_type != KEY_FRAME) {
+  if (!frame_is_intra_only(cm)) {
     // Work out probability tree for coding those segments not
     // predicted using the temporal method and the cost.
     calc_segtree_probs(t_unpred_seg_counts, t_pred_tree);
     t_pred_cost = cost_segmap(t_unpred_seg_counts, t_pred_tree);
 
-    // Add in the cost of the signalling for each prediction context
+    // Add in the cost of the signaling for each prediction context.
     for (i = 0; i < PREDICTION_PROBS; i++) {
       const int count0 = temporal_predictor_count[i][0];
       const int count1 = temporal_predictor_count[i][1];
 
       t_nopred_prob[i] = get_binary_prob(count0, count1);
 
       // Add in the predictor signaling cost
       t_pred_cost += count0 * vp9_cost_zero(t_nopred_prob[i]) +
                      count1 * vp9_cost_one(t_nopred_prob[i]);
     }
   }
 
   // Now choose which coding method to use.
   if (t_pred_cost < no_pred_cost) {
     seg->temporal_update = 1;
     vpx_memcpy(seg->tree_probs, t_pred_tree, sizeof(t_pred_tree));
     vpx_memcpy(seg->pred_probs, t_nopred_prob, sizeof(t_nopred_prob));
   } else {
     seg->temporal_update = 0;
     vpx_memcpy(seg->tree_probs, no_pred_tree, sizeof(no_pred_tree));
   }
 }