static void count_segs(VP9_COMP *cpi,
                       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) {
  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->mbmi.segment_id;
  xd->mode_info_context = mi;
  set_mi_row_col(cm, xd, mi_row, bh, mi_col, bw);

  // 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) {
    // Test to see if the segment id matches the predicted value.
    const int pred_seg_id = vp9_get_pred_mi_segid(cm, mi->mbmi.sb_type,
                                                  mi_row, mi_col);
    const int seg_predicted = (segment_id == pred_seg_id);

    // Get the segment id prediction context
    const int pred_context = vp9_get_pred_context(cm, xd, PRED_SEG_ID);

    // Store the prediction status for this mb and update counts
    // as appropriate
    vp9_set_pred_flag(xd, PRED_SEG_ID, seg_predicted);
    temporal_predictor_count[pred_context][seg_predicted]++;

    if (!seg_predicted)
      // Update the "unpredicted" segment count
      t_unpred_seg_counts[segment_id]++;
  }
}
Example #2
0
void vp9_choose_segmap_coding_method(VP9_COMP *cpi) {
  VP9_COMMON *const cm = &cpi->common;
  MACROBLOCKD *const xd = &cpi->mb.e_mbd;

  int i;
  int tot_count;
  int no_pred_cost;
  int t_pred_cost = INT_MAX;
  int pred_context;

  int mb_row, mb_col;
  int segmap_index = 0;
  unsigned char segment_id;

  int temporal_predictor_count[PREDICTION_PROBS][2];
  int no_pred_segcounts[MAX_MB_SEGMENTS];
  int t_unpred_seg_counts[MAX_MB_SEGMENTS];

  vp9_prob no_pred_tree[MB_FEATURE_TREE_PROBS];
  vp9_prob t_pred_tree[MB_FEATURE_TREE_PROBS];
  vp9_prob t_nopred_prob[PREDICTION_PROBS];

#if CONFIG_SUPERBLOCKS
  const int mis = cm->mode_info_stride;
#endif

  // Set default state for the segment tree probabilities and the
  // temporal coding probabilities
  vpx_memset(xd->mb_segment_tree_probs, 255,
             sizeof(xd->mb_segment_tree_probs));
  vpx_memset(cm->segment_pred_probs, 255,
             sizeof(cm->segment_pred_probs));

  vpx_memset(no_pred_segcounts, 0, sizeof(no_pred_segcounts));
  vpx_memset(t_unpred_seg_counts, 0, sizeof(t_unpred_seg_counts));
  vpx_memset(temporal_predictor_count, 0, sizeof(temporal_predictor_count));

  // First of all generate stats regarding how well the last segment map
  // predicts this one

  // Initialize macroblock decoder mode info context for the first mb
  // in the frame
  xd->mode_info_context = cm->mi;

  for (mb_row = 0; mb_row < cm->mb_rows; mb_row += 2) {
    for (mb_col = 0; mb_col < cm->mb_cols; mb_col += 2) {
      for (i = 0; i < 4; i++) {
        static const int dx[4] = { +1, -1, +1, +1 };
        static const int dy[4] = {  0, +1,  0, -1 };
        int x_idx = i & 1, y_idx = i >> 1;

        if (mb_col + x_idx >= cm->mb_cols ||
            mb_row + y_idx >= cm->mb_rows) {
          goto end;
        }

        xd->mb_to_top_edge = -((mb_row * 16) << 3);
        xd->mb_to_left_edge = -((mb_col * 16) << 3);

        segmap_index = (mb_row + y_idx) * cm->mb_cols + mb_col + x_idx;
        segment_id = xd->mode_info_context->mbmi.segment_id;
#if CONFIG_SUPERBLOCKS
        if (xd->mode_info_context->mbmi.encoded_as_sb) {
          if (mb_col + 1 < cm->mb_cols)
            segment_id = segment_id &&
                         xd->mode_info_context[1].mbmi.segment_id;
          if (mb_row + 1 < cm->mb_rows) {
            segment_id = segment_id &&
                         xd->mode_info_context[mis].mbmi.segment_id;
            if (mb_col + 1 < cm->mb_cols)
              segment_id = segment_id &&
                           xd->mode_info_context[mis + 1].mbmi.segment_id;
          }
          xd->mb_to_bottom_edge = ((cm->mb_rows - 2 - mb_row) * 16) << 3;
          xd->mb_to_right_edge  = ((cm->mb_cols - 2 - mb_col) * 16) << 3;
        } else {
#endif
          xd->mb_to_bottom_edge = ((cm->mb_rows - 1 - mb_row) * 16) << 3;
          xd->mb_to_right_edge  = ((cm->mb_cols - 1 - mb_col) * 16) << 3;
#if CONFIG_SUPERBLOCKS
        }
#endif

        // 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) {
          // Test to see if the segment id matches the predicted value.
          int seg_predicted =
            (segment_id == vp9_get_pred_mb_segid(cm, xd, segmap_index));

          // Get the segment id prediction context
          pred_context =
            vp9_get_pred_context(cm, xd, PRED_SEG_ID);

          // Store the prediction status for this mb and update counts
          // as appropriate
          vp9_set_pred_flag(xd, PRED_SEG_ID, seg_predicted);
          temporal_predictor_count[pred_context][seg_predicted]++;

          if (!seg_predicted)
            // Update the "unpredicted" segment count
            t_unpred_seg_counts[segment_id]++;
        }

#if CONFIG_SUPERBLOCKS
        if (xd->mode_info_context->mbmi.encoded_as_sb) {
          assert(!i);
          xd->mode_info_context += 2;
          break;
        }
#endif
      end:
        xd->mode_info_context += dx[i] + dy[i] * cm->mode_info_stride;
      }
    }

    // this is to account for the border in mode_info_context
    xd->mode_info_context -= mb_col;
    xd->mode_info_context += cm->mode_info_stride * 2;
  }

  // Work out probability tree for coding segments without prediction
  // and the cost.
  calc_segtree_probs(xd, no_pred_segcounts, no_pred_tree);
  no_pred_cost = cost_segmap(xd, no_pred_segcounts, no_pred_tree);

  // Key frames cannot use temporal prediction
  if (cm->frame_type != KEY_FRAME) {
    // Work out probability tree for coding those segments not
    // predicted using the temporal method and the cost.
    calc_segtree_probs(xd, t_unpred_seg_counts, t_pred_tree);
    t_pred_cost = cost_segmap(xd, t_unpred_seg_counts, t_pred_tree);

    // Add in the cost of the signalling for each prediction context
    for (i = 0; i < PREDICTION_PROBS; i++) {
      tot_count = temporal_predictor_count[i][0] +
                  temporal_predictor_count[i][1];

      // Work out the context probabilities for the segment
      // prediction flag
      if (tot_count) {
        t_nopred_prob[i] = (temporal_predictor_count[i][0] * 255) /
                           tot_count;

        // Clamp to minimum allowed value
        if (t_nopred_prob[i] < 1)
          t_nopred_prob[i] = 1;
      } else
        t_nopred_prob[i] = 1;

      // Add in the predictor signaling cost
      t_pred_cost += (temporal_predictor_count[i][0] *
                      vp9_cost_zero(t_nopred_prob[i])) +
                     (temporal_predictor_count[i][1] *
                      vp9_cost_one(t_nopred_prob[i]));
    }
  }

  // Now choose which coding method to use.
  if (t_pred_cost < no_pred_cost) {
    cm->temporal_update = 1;
    vpx_memcpy(xd->mb_segment_tree_probs,
               t_pred_tree, sizeof(t_pred_tree));
    vpx_memcpy(&cm->segment_pred_probs,
               t_nopred_prob, sizeof(t_nopred_prob));
  } else {
    cm->temporal_update = 0;
    vpx_memcpy(xd->mb_segment_tree_probs,
               no_pred_tree, sizeof(no_pred_tree));
  }
}