src/third_party/libvpx/vp9/encoder/vp9_segmentation.c - cobalt - Git at Google

 /*
  *  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.
  */

 #include <limits.h>
 #include <math.h>

 #include "vpx_mem/vpx_mem.h"

 #include "vp9/common/vp9_pred_common.h"
 #include "vp9/common/vp9_tile_common.h"

 #include "vp9/encoder/vp9_cost.h"
 #include "vp9/encoder/vp9_segmentation.h"

 void vp9_enable_segmentation(struct segmentation *seg) {
   seg->enabled = 1;
   seg->update_map = 1;
   seg->update_data = 1;
 }

 void vp9_disable_segmentation(struct segmentation *seg) {
   seg->enabled = 0;
   seg->update_map = 0;
   seg->update_data = 0;
 }

 void vp9_set_segment_data(struct segmentation *seg, signed char *feature_data,
                           unsigned char abs_delta) {
   seg->abs_delta = abs_delta;

   memcpy(seg->feature_data, feature_data, sizeof(seg->feature_data));
 }
 void vp9_disable_segfeature(struct segmentation *seg, int segment_id,
                             SEG_LVL_FEATURES feature_id) {
   seg->feature_mask[segment_id] &= ~(1 << feature_id);
 }

 void vp9_clear_segdata(struct segmentation *seg, int segment_id,
                        SEG_LVL_FEATURES feature_id) {
   seg->feature_data[segment_id][feature_id] = 0;
 }

 void vp9_psnr_aq_mode_setup(struct segmentation *seg) {
   int i;

   vp9_enable_segmentation(seg);
   vp9_clearall_segfeatures(seg);
   seg->abs_delta = SEGMENT_DELTADATA;

   for (i = 0; i < MAX_SEGMENTS; ++i) {
     vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, 2 * (i - (MAX_SEGMENTS / 2)));
     vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
   }
 }

 void vp9_perceptual_aq_mode_setup(struct VP9_COMP *cpi,
                                   struct segmentation *seg) {
   const VP9_COMMON *cm = &cpi->common;
   const int seg_counts = cpi->kmeans_ctr_num;
   const int base_qindex = cm->base_qindex;
   const double base_qstep = vp9_convert_qindex_to_q(base_qindex, cm->bit_depth);
   const double mid_ctr = cpi->kmeans_ctr_ls[seg_counts / 2];
   const double var_diff_scale = 4.0;
   int i;

   assert(seg_counts <= MAX_SEGMENTS);

   vp9_enable_segmentation(seg);
   vp9_clearall_segfeatures(seg);
   seg->abs_delta = SEGMENT_DELTADATA;

   for (i = 0; i < seg_counts / 2; ++i) {
     double wiener_var_diff = mid_ctr - cpi->kmeans_ctr_ls[i];
     double target_qstep = base_qstep / (1.0 + wiener_var_diff / var_diff_scale);
     int target_qindex = vp9_convert_q_to_qindex(target_qstep, cm->bit_depth);
     assert(wiener_var_diff >= 0.0);

     vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, target_qindex - base_qindex);
     vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
   }

   vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, 0);
   vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);

   for (; i < seg_counts; ++i) {
     double wiener_var_diff = cpi->kmeans_ctr_ls[i] - mid_ctr;
     double target_qstep = base_qstep * (1.0 + wiener_var_diff / var_diff_scale);
     int target_qindex = vp9_convert_q_to_qindex(target_qstep, cm->bit_depth);
     assert(wiener_var_diff >= 0.0);

     vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, target_qindex - base_qindex);
     vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
   }
 }

 // Based on set of segment counts calculate a probability tree
 static void calc_segtree_probs(int *segcounts, vpx_prob *segment_tree_probs) {
   // Work out probabilities of each segment
   const int c01 = segcounts[0] + segcounts[1];
   const int c23 = segcounts[2] + segcounts[3];
   const int c45 = segcounts[4] + segcounts[5];
   const int c67 = segcounts[6] + segcounts[7];

   segment_tree_probs[0] = get_binary_prob(c01 + c23, c45 + c67);
   segment_tree_probs[1] = get_binary_prob(c01, c23);
   segment_tree_probs[2] = get_binary_prob(c45, c67);
   segment_tree_probs[3] = get_binary_prob(segcounts[0], segcounts[1]);
   segment_tree_probs[4] = get_binary_prob(segcounts[2], segcounts[3]);
   segment_tree_probs[5] = get_binary_prob(segcounts[4], segcounts[5]);
   segment_tree_probs[6] = get_binary_prob(segcounts[6], segcounts[7]);
 }

 // Based on set of segment counts and probabilities calculate a cost estimate
 static int cost_segmap(int *segcounts, vpx_prob *probs) {
   const int c01 = segcounts[0] + segcounts[1];
   const int c23 = segcounts[2] + segcounts[3];
   const int c45 = segcounts[4] + segcounts[5];
   const int c67 = segcounts[6] + segcounts[7];
   const int c0123 = c01 + c23;
   const int c4567 = c45 + c67;

   // Cost the top node of the tree
   int cost = c0123 * vp9_cost_zero(probs[0]) + c4567 * vp9_cost_one(probs[0]);

   // Cost subsequent levels
   if (c0123 > 0) {
     cost += c01 * vp9_cost_zero(probs[1]) + c23 * vp9_cost_one(probs[1]);

     if (c01 > 0)
       cost += segcounts[0] * vp9_cost_zero(probs[3]) +
               segcounts[1] * vp9_cost_one(probs[3]);
     if (c23 > 0)
       cost += segcounts[2] * vp9_cost_zero(probs[4]) +
               segcounts[3] * vp9_cost_one(probs[4]);
   }

   if (c4567 > 0) {
     cost += c45 * vp9_cost_zero(probs[2]) + c67 * vp9_cost_one(probs[2]);

     if (c45 > 0)
       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(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) {
   int segment_id;

   if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols) return;

   xd->mi = mi;
   segment_id = xd->mi[0]->segment_id;

   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 = xd->mi[0]->sb_type;
     // Test to see if the segment id matches the predicted value.
     const int pred_segment_id =
         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
     xd->mi[0]->seg_id_predicted = pred_flag;
     temporal_predictor_count[pred_context][pred_flag]++;

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

 static void 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) {
   const int mis = cm->mi_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[0]->sb_type];
   bh = num_8x8_blocks_high_lookup[mi[0]->sb_type];

   if (bw == bs && bh == bs) {
     count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
                t_unpred_seg_counts, bs, bs, mi_row, mi_col);
   } else if (bw == bs && bh < bs) {
     count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
                t_unpred_seg_counts, bs, hbs, mi_row, mi_col);
     count_segs(cm, xd, tile, mi + 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(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
                t_unpred_seg_counts, hbs, bs, mi_row, mi_col);
     count_segs(cm, xd, tile, mi + 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(cm, xd, tile, &mi[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_COMMON *cm, MACROBLOCKD *xd) {
   struct segmentation *seg = &cm->seg;

   int no_pred_cost;
   int t_pred_cost = INT_MAX;

   int i, tile_col, mi_row, mi_col;

   int temporal_predictor_count[PREDICTION_PROBS][2] = { { 0 } };
   int no_pred_segcounts[MAX_SEGMENTS] = { 0 };
   int t_unpred_seg_counts[MAX_SEGMENTS] = { 0 };

   vpx_prob no_pred_tree[SEG_TREE_PROBS];
   vpx_prob t_pred_tree[SEG_TREE_PROBS];
   vpx_prob t_nopred_prob[PREDICTION_PROBS];

   // Set default state for the segment tree probabilities and the
   // temporal coding probabilities
   memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
   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++) {
     TileInfo tile;
     MODE_INFO **mi_ptr;
     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 * cm->mi_stride) {
       MODE_INFO **mi = mi_ptr;
       for (mi_col = tile.mi_col_start; mi_col < tile.mi_col_end;
            mi_col += 8, mi += 8)
         count_segs_sb(cm, xd, &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 (!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 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;
     memcpy(seg->tree_probs, t_pred_tree, sizeof(t_pred_tree));
     memcpy(seg->pred_probs, t_nopred_prob, sizeof(t_nopred_prob));
   } else {
     seg->temporal_update = 0;
     memcpy(seg->tree_probs, no_pred_tree, sizeof(no_pred_tree));
   }
 }

 void vp9_reset_segment_features(struct segmentation *seg) {
   // Set up default state for MB feature flags
   seg->enabled = 0;
   seg->update_map = 0;
   seg->update_data = 0;
   memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
   vp9_clearall_segfeatures(seg);
 }
	/*
	* 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.
	*/

	#include <limits.h>
	#include <math.h>

	#include "vpx_mem/vpx_mem.h"

	#include "vp9/common/vp9_pred_common.h"
	#include "vp9/common/vp9_tile_common.h"

	#include "vp9/encoder/vp9_cost.h"
	#include "vp9/encoder/vp9_segmentation.h"

	void vp9_enable_segmentation(struct segmentation *seg) {
	seg->enabled = 1;
	seg->update_map = 1;
	seg->update_data = 1;
	}

	void vp9_disable_segmentation(struct segmentation *seg) {
	seg->enabled = 0;
	seg->update_map = 0;
	seg->update_data = 0;
	}

	void vp9_set_segment_data(struct segmentation seg, signed char feature_data,
	unsigned char abs_delta) {
	seg->abs_delta = abs_delta;

	memcpy(seg->feature_data, feature_data, sizeof(seg->feature_data));
	}
	void vp9_disable_segfeature(struct segmentation *seg, int segment_id,
	SEG_LVL_FEATURES feature_id) {
	seg->feature_mask[segment_id] &= ~(1 << feature_id);
	}

	void vp9_clear_segdata(struct segmentation *seg, int segment_id,
	SEG_LVL_FEATURES feature_id) {
	seg->feature_data[segment_id][feature_id] = 0;
	}

	void vp9_psnr_aq_mode_setup(struct segmentation *seg) {
	int i;

	vp9_enable_segmentation(seg);
	vp9_clearall_segfeatures(seg);
	seg->abs_delta = SEGMENT_DELTADATA;

	for (i = 0; i < MAX_SEGMENTS; ++i) {
	vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, 2 * (i - (MAX_SEGMENTS / 2)));
	vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
	}
	}

	void vp9_perceptual_aq_mode_setup(struct VP9_COMP *cpi,
	struct segmentation *seg) {
	const VP9_COMMON *cm = &cpi->common;
	const int seg_counts = cpi->kmeans_ctr_num;
	const int base_qindex = cm->base_qindex;
	const double base_qstep = vp9_convert_qindex_to_q(base_qindex, cm->bit_depth);
	const double mid_ctr = cpi->kmeans_ctr_ls[seg_counts / 2];
	const double var_diff_scale = 4.0;
	int i;

	assert(seg_counts <= MAX_SEGMENTS);

	vp9_enable_segmentation(seg);
	vp9_clearall_segfeatures(seg);
	seg->abs_delta = SEGMENT_DELTADATA;

	for (i = 0; i < seg_counts / 2; ++i) {
	double wiener_var_diff = mid_ctr - cpi->kmeans_ctr_ls[i];
	double target_qstep = base_qstep / (1.0 + wiener_var_diff / var_diff_scale);
	int target_qindex = vp9_convert_q_to_qindex(target_qstep, cm->bit_depth);
	assert(wiener_var_diff >= 0.0);

	vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, target_qindex - base_qindex);
	vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
	}

	vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, 0);
	vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);

	for (; i < seg_counts; ++i) {
	double wiener_var_diff = cpi->kmeans_ctr_ls[i] - mid_ctr;
	double target_qstep = base_qstep * (1.0 + wiener_var_diff / var_diff_scale);
	int target_qindex = vp9_convert_q_to_qindex(target_qstep, cm->bit_depth);
	assert(wiener_var_diff >= 0.0);

	vp9_set_segdata(seg, i, SEG_LVL_ALT_Q, target_qindex - base_qindex);
	vp9_enable_segfeature(seg, i, SEG_LVL_ALT_Q);
	}
	}

	// Based on set of segment counts calculate a probability tree
	static void calc_segtree_probs(int segcounts, vpx_prob segment_tree_probs) {
	// Work out probabilities of each segment
	const int c01 = segcounts[0] + segcounts[1];
	const int c23 = segcounts[2] + segcounts[3];
	const int c45 = segcounts[4] + segcounts[5];
	const int c67 = segcounts[6] + segcounts[7];

	segment_tree_probs[0] = get_binary_prob(c01 + c23, c45 + c67);
	segment_tree_probs[1] = get_binary_prob(c01, c23);
	segment_tree_probs[2] = get_binary_prob(c45, c67);
	segment_tree_probs[3] = get_binary_prob(segcounts[0], segcounts[1]);
	segment_tree_probs[4] = get_binary_prob(segcounts[2], segcounts[3]);
	segment_tree_probs[5] = get_binary_prob(segcounts[4], segcounts[5]);
	segment_tree_probs[6] = get_binary_prob(segcounts[6], segcounts[7]);
	}

	// Based on set of segment counts and probabilities calculate a cost estimate
	static int cost_segmap(int segcounts, vpx_prob probs) {
	const int c01 = segcounts[0] + segcounts[1];
	const int c23 = segcounts[2] + segcounts[3];
	const int c45 = segcounts[4] + segcounts[5];
	const int c67 = segcounts[6] + segcounts[7];
	const int c0123 = c01 + c23;
	const int c4567 = c45 + c67;

	// Cost the top node of the tree
	int cost = c0123 * vp9_cost_zero(probs[0]) + c4567 * vp9_cost_one(probs[0]);

	// Cost subsequent levels
	if (c0123 > 0) {
	cost += c01 * vp9_cost_zero(probs[1]) + c23 * vp9_cost_one(probs[1]);

	if (c01 > 0)
	cost += segcounts[0] * vp9_cost_zero(probs[3]) +
	segcounts[1] * vp9_cost_one(probs[3]);
	if (c23 > 0)
	cost += segcounts[2] * vp9_cost_zero(probs[4]) +
	segcounts[3] * vp9_cost_one(probs[4]);
	}

	if (c4567 > 0) {
	cost += c45 * vp9_cost_zero(probs[2]) + c67 * vp9_cost_one(probs[2]);

	if (c45 > 0)
	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(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) {
	int segment_id;

	if (mi_row >= cm->mi_rows \|\| mi_col >= cm->mi_cols) return;

	xd->mi = mi;
	segment_id = xd->mi[0]->segment_id;

	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 = xd->mi[0]->sb_type;
	// Test to see if the segment id matches the predicted value.
	const int pred_segment_id =
	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
	xd->mi[0]->seg_id_predicted = pred_flag;
	temporal_predictor_count[pred_context][pred_flag]++;

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

	static void 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) {
	const int mis = cm->mi_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[0]->sb_type];
	bh = num_8x8_blocks_high_lookup[mi[0]->sb_type];

	if (bw == bs && bh == bs) {
	count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
	t_unpred_seg_counts, bs, bs, mi_row, mi_col);
	} else if (bw == bs && bh < bs) {
	count_segs(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
	t_unpred_seg_counts, bs, hbs, mi_row, mi_col);
	count_segs(cm, xd, tile, mi + 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(cm, xd, tile, mi, no_pred_segcounts, temporal_predictor_count,
	t_unpred_seg_counts, hbs, bs, mi_row, mi_col);
	count_segs(cm, xd, tile, mi + 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(cm, xd, tile, &mi[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_COMMON cm, MACROBLOCKD xd) {
	struct segmentation *seg = &cm->seg;

	int no_pred_cost;
	int t_pred_cost = INT_MAX;

	int i, tile_col, mi_row, mi_col;

	int temporal_predictor_count[PREDICTION_PROBS][2] = { { 0 } };
	int no_pred_segcounts[MAX_SEGMENTS] = { 0 };
	int t_unpred_seg_counts[MAX_SEGMENTS] = { 0 };

	vpx_prob no_pred_tree[SEG_TREE_PROBS];
	vpx_prob t_pred_tree[SEG_TREE_PROBS];
	vpx_prob t_nopred_prob[PREDICTION_PROBS];

	// Set default state for the segment tree probabilities and the
	// temporal coding probabilities
	memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
	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++) {
	TileInfo tile;
	MODE_INFO **mi_ptr;
	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 * cm->mi_stride) {
	MODE_INFO **mi = mi_ptr;
	for (mi_col = tile.mi_col_start; mi_col < tile.mi_col_end;
	mi_col += 8, mi += 8)
	count_segs_sb(cm, xd, &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 (!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 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;
	memcpy(seg->tree_probs, t_pred_tree, sizeof(t_pred_tree));
	memcpy(seg->pred_probs, t_nopred_prob, sizeof(t_nopred_prob));
	} else {
	seg->temporal_update = 0;
	memcpy(seg->tree_probs, no_pred_tree, sizeof(no_pred_tree));
	}
	}

	void vp9_reset_segment_features(struct segmentation *seg) {
	// Set up default state for MB feature flags
	seg->enabled = 0;
	seg->update_map = 0;
	seg->update_data = 0;
	memset(seg->tree_probs, 255, sizeof(seg->tree_probs));
	vp9_clearall_segfeatures(seg);
	}