/*

 *  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] &= ~(1u << 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);

}