31ee193a9c
Also some further simplification following removal of top node code. There is an issue in regards to the shared file vp8cx.h in regard to the roi_map as this interface assumes that there are only 4 segments. I have left the value here as 4 for now meaning that the roi_map interface is broken for VP9. Note that this change would have been easier if I hadn't had to search for hard wire instances of the number 4 and <= 3. Change-Id: Ia8b6deea4be4dbd20deb1656e689dd43a5f190e8
322 lines
12 KiB
C
322 lines
12 KiB
C
/*
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* Copyright (c) 2012 The WebM project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include <limits.h>
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#include "vpx_mem/vpx_mem.h"
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#include "vp9/encoder/vp9_segmentation.h"
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#include "vp9/common/vp9_pred_common.h"
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#include "vp9/common/vp9_tile_common.h"
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void vp9_enable_segmentation(VP9_PTR ptr) {
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VP9_COMP *cpi = (VP9_COMP *)(ptr);
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// Set the appropriate feature bit
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cpi->mb.e_mbd.segmentation_enabled = 1;
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cpi->mb.e_mbd.update_mb_segmentation_map = 1;
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cpi->mb.e_mbd.update_mb_segmentation_data = 1;
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}
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void vp9_disable_segmentation(VP9_PTR ptr) {
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VP9_COMP *cpi = (VP9_COMP *)(ptr);
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// Clear the appropriate feature bit
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cpi->mb.e_mbd.segmentation_enabled = 0;
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}
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void vp9_set_segmentation_map(VP9_PTR ptr,
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unsigned char *segmentation_map) {
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VP9_COMP *cpi = (VP9_COMP *)(ptr);
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// Copy in the new segmentation map
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vpx_memcpy(cpi->segmentation_map, segmentation_map,
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(cpi->common.mb_rows * cpi->common.mb_cols));
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// Signal that the map should be updated.
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cpi->mb.e_mbd.update_mb_segmentation_map = 1;
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cpi->mb.e_mbd.update_mb_segmentation_data = 1;
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}
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void vp9_set_segment_data(VP9_PTR ptr,
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signed char *feature_data,
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unsigned char abs_delta) {
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VP9_COMP *cpi = (VP9_COMP *)(ptr);
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cpi->mb.e_mbd.mb_segment_abs_delta = abs_delta;
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vpx_memcpy(cpi->mb.e_mbd.segment_feature_data, feature_data,
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sizeof(cpi->mb.e_mbd.segment_feature_data));
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// TBD ?? Set the feature mask
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// vpx_memcpy(cpi->mb.e_mbd.segment_feature_mask, 0,
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// sizeof(cpi->mb.e_mbd.segment_feature_mask));
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}
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// Based on set of segment counts calculate a probability tree
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static void calc_segtree_probs(MACROBLOCKD *xd,
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int *segcounts,
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vp9_prob *segment_tree_probs) {
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// Work out probabilities of each segment
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segment_tree_probs[0] =
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get_binary_prob(segcounts[0] + segcounts[1] + segcounts[2] + segcounts[3],
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segcounts[4] + segcounts[5] + segcounts[6] + segcounts[7]);
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segment_tree_probs[1] =
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get_binary_prob(segcounts[0] + segcounts[1], segcounts[2] + segcounts[3]);
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segment_tree_probs[2] = get_binary_prob(segcounts[0], segcounts[1]);
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segment_tree_probs[3] = get_binary_prob(segcounts[2], segcounts[3]);
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segment_tree_probs[4] =
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get_binary_prob(segcounts[4] + segcounts[5], segcounts[6] + segcounts[7]);
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segment_tree_probs[5] = get_binary_prob(segcounts[4], segcounts[5]);
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segment_tree_probs[6] = get_binary_prob(segcounts[6], segcounts[7]);
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}
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// Based on set of segment counts and probabilities calculate a cost estimate
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static int cost_segmap(MACROBLOCKD *xd,
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int *segcounts,
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vp9_prob *probs) {
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int cost;
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int count1, count2;
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// Cost the top node of the tree
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count1 = segcounts[0] + segcounts[1] + segcounts[2] + segcounts[3];
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count2 = segcounts[3] + segcounts[4] + segcounts[5] + segcounts[6];
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cost = count1 * vp9_cost_zero(probs[0]) +
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count2 * vp9_cost_one(probs[0]);
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// Cost subsequent levels
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if (count1 > 0) {
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count1 = segcounts[0] + segcounts[1];
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count2 = segcounts[2] + segcounts[3];
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cost += count1 * vp9_cost_zero(probs[1]) +
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count2 * vp9_cost_one(probs[1]);
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if (count1 > 0)
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cost += segcounts[0] * vp9_cost_zero(probs[2]) +
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segcounts[1] * vp9_cost_one(probs[2]);
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if (count2 > 0)
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cost += segcounts[2] * vp9_cost_zero(probs[3]) +
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segcounts[3] * vp9_cost_one(probs[3]);
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}
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if (count2 > 0) {
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count1 = segcounts[4] + segcounts[5];
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count2 = segcounts[6] + segcounts[7];
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cost += count1 * vp9_cost_zero(probs[4]) +
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count2 * vp9_cost_one(probs[4]);
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if (count1 > 0)
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cost += segcounts[4] * vp9_cost_zero(probs[5]) +
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segcounts[5] * vp9_cost_one(probs[5]);
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if (count2 > 0)
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cost += segcounts[6] * vp9_cost_zero(probs[6]) +
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segcounts[7] * vp9_cost_one(probs[6]);
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}
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return cost;
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}
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static void count_segs(VP9_COMP *cpi,
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MODE_INFO *mi,
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int *no_pred_segcounts,
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int (*temporal_predictor_count)[2],
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int *t_unpred_seg_counts,
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int bw, int bh, int mb_row, int mb_col) {
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VP9_COMMON *const cm = &cpi->common;
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MACROBLOCKD *const xd = &cpi->mb.e_mbd;
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const int segment_id = mi->mbmi.segment_id;
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xd->mode_info_context = mi;
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set_mb_row(cm, xd, mb_row, bh);
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set_mb_col(cm, xd, mb_col, bw);
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// Count the number of hits on each segment with no prediction
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no_pred_segcounts[segment_id]++;
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// Temporal prediction not allowed on key frames
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if (cm->frame_type != KEY_FRAME) {
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// Test to see if the segment id matches the predicted value.
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const int pred_seg_id = vp9_get_pred_mb_segid(cm, mi->mbmi.sb_type,
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mb_row, mb_col);
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const int seg_predicted = (segment_id == pred_seg_id);
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// Get the segment id prediction context
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const int pred_context = vp9_get_pred_context(cm, xd, PRED_SEG_ID);
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// Store the prediction status for this mb and update counts
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// as appropriate
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vp9_set_pred_flag(xd, PRED_SEG_ID, seg_predicted);
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temporal_predictor_count[pred_context][seg_predicted]++;
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if (!seg_predicted)
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// Update the "unpredicted" segment count
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t_unpred_seg_counts[segment_id]++;
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}
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}
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void vp9_choose_segmap_coding_method(VP9_COMP *cpi) {
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VP9_COMMON *const cm = &cpi->common;
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MACROBLOCKD *const xd = &cpi->mb.e_mbd;
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int no_pred_cost;
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int t_pred_cost = INT_MAX;
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int i;
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int tile_col, mb_row, mb_col;
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int temporal_predictor_count[PREDICTION_PROBS][2];
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int no_pred_segcounts[MAX_MB_SEGMENTS];
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int t_unpred_seg_counts[MAX_MB_SEGMENTS];
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vp9_prob no_pred_tree[MB_SEG_TREE_PROBS];
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vp9_prob t_pred_tree[MB_SEG_TREE_PROBS];
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vp9_prob t_nopred_prob[PREDICTION_PROBS];
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const int mis = cm->mode_info_stride;
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MODE_INFO *mi_ptr, *mi;
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// Set default state for the segment tree probabilities and the
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// temporal coding probabilities
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vpx_memset(xd->mb_segment_tree_probs, 255,
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sizeof(xd->mb_segment_tree_probs));
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vpx_memset(cm->segment_pred_probs, 255,
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sizeof(cm->segment_pred_probs));
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vpx_memset(no_pred_segcounts, 0, sizeof(no_pred_segcounts));
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vpx_memset(t_unpred_seg_counts, 0, sizeof(t_unpred_seg_counts));
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vpx_memset(temporal_predictor_count, 0, sizeof(temporal_predictor_count));
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// First of all generate stats regarding how well the last segment map
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// predicts this one
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for (tile_col = 0; tile_col < cm->tile_columns; tile_col++) {
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vp9_get_tile_col_offsets(cm, tile_col);
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mi_ptr = cm->mi + cm->cur_tile_mb_col_start;
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for (mb_row = 0; mb_row < cm->mb_rows; mb_row += 4, mi_ptr += 4 * mis) {
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mi = mi_ptr;
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for (mb_col = cm->cur_tile_mb_col_start;
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mb_col < cm->cur_tile_mb_col_end; mb_col += 4, mi += 4) {
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if (mi->mbmi.sb_type == BLOCK_SIZE_SB64X64) {
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count_segs(cpi, mi, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, 4, 4, mb_row, mb_col);
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#if CONFIG_SBSEGMENT
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} else if (mi->mbmi.sb_type == BLOCK_SIZE_SB64X32) {
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count_segs(cpi, mi, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, 4, 2, mb_row, mb_col);
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if (mb_row + 2 != cm->mb_rows)
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count_segs(cpi, mi + 2 * mis, no_pred_segcounts,
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temporal_predictor_count,
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t_unpred_seg_counts, 4, 2, mb_row + 2, mb_col);
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} else if (mi->mbmi.sb_type == BLOCK_SIZE_SB32X64) {
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count_segs(cpi, mi, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, 2, 4, mb_row, mb_col);
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if (mb_col + 2 != cm->mb_cols)
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count_segs(cpi, mi + 2, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, 2, 4, mb_row, mb_col + 2);
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#endif
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} else {
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for (i = 0; i < 4; i++) {
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int x_idx = (i & 1) << 1, y_idx = i & 2;
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MODE_INFO *sb_mi = mi + y_idx * mis + x_idx;
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if (mb_col + x_idx >= cm->mb_cols ||
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mb_row + y_idx >= cm->mb_rows) {
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continue;
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}
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if (sb_mi->mbmi.sb_type == BLOCK_SIZE_SB32X32) {
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count_segs(cpi, sb_mi, no_pred_segcounts,
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temporal_predictor_count, t_unpred_seg_counts, 2, 2,
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mb_row + y_idx, mb_col + x_idx);
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#if CONFIG_SBSEGMENT
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} else if (sb_mi->mbmi.sb_type == BLOCK_SIZE_SB32X16) {
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count_segs(cpi, sb_mi, no_pred_segcounts,
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temporal_predictor_count,
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t_unpred_seg_counts, 2, 1,
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mb_row + y_idx, mb_col + x_idx);
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if (mb_row + y_idx + 1 != cm->mb_rows)
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count_segs(cpi, sb_mi + mis, no_pred_segcounts,
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temporal_predictor_count,
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t_unpred_seg_counts, 2, 1,
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mb_row + y_idx + 1, mb_col + x_idx);
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} else if (sb_mi->mbmi.sb_type == BLOCK_SIZE_SB16X32) {
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count_segs(cpi, sb_mi, no_pred_segcounts,
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temporal_predictor_count,
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t_unpred_seg_counts, 1, 2,
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mb_row + y_idx, mb_col + x_idx);
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if (mb_col + x_idx + 1 != cm->mb_cols)
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count_segs(cpi, sb_mi + 1, no_pred_segcounts,
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temporal_predictor_count,
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t_unpred_seg_counts, 1, 2,
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mb_row + y_idx, mb_col + x_idx + 1);
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#endif
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} else {
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int j;
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for (j = 0; j < 4; j++) {
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const int x_idx_mb = x_idx + (j & 1);
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const int y_idx_mb = y_idx + (j >> 1);
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MODE_INFO *mb_mi = mi + x_idx_mb + y_idx_mb * mis;
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if (mb_col + x_idx_mb >= cm->mb_cols ||
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mb_row + y_idx_mb >= cm->mb_rows) {
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continue;
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}
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assert(mb_mi->mbmi.sb_type == BLOCK_SIZE_MB16X16);
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count_segs(cpi, mb_mi, no_pred_segcounts,
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temporal_predictor_count, t_unpred_seg_counts,
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1, 1, mb_row + y_idx_mb, mb_col + x_idx_mb);
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}
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}
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}
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}
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}
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}
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}
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// Work out probability tree for coding segments without prediction
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// and the cost.
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calc_segtree_probs(xd, no_pred_segcounts, no_pred_tree);
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no_pred_cost = cost_segmap(xd, no_pred_segcounts, no_pred_tree);
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// Key frames cannot use temporal prediction
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if (cm->frame_type != KEY_FRAME) {
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// Work out probability tree for coding those segments not
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// predicted using the temporal method and the cost.
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calc_segtree_probs(xd, t_unpred_seg_counts, t_pred_tree);
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t_pred_cost = cost_segmap(xd, t_unpred_seg_counts, t_pred_tree);
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// Add in the cost of the signalling for each prediction context
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for (i = 0; i < PREDICTION_PROBS; i++) {
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t_nopred_prob[i] = get_binary_prob(temporal_predictor_count[i][0],
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temporal_predictor_count[i][1]);
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// Add in the predictor signaling cost
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t_pred_cost += (temporal_predictor_count[i][0] *
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vp9_cost_zero(t_nopred_prob[i])) +
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(temporal_predictor_count[i][1] *
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vp9_cost_one(t_nopred_prob[i]));
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}
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}
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// Now choose which coding method to use.
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if (t_pred_cost < no_pred_cost) {
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cm->temporal_update = 1;
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vpx_memcpy(xd->mb_segment_tree_probs,
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t_pred_tree, sizeof(t_pred_tree));
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vpx_memcpy(&cm->segment_pred_probs,
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t_nopred_prob, sizeof(t_nopred_prob));
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} else {
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cm->temporal_update = 0;
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vpx_memcpy(xd->mb_segment_tree_probs,
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no_pred_tree, sizeof(no_pred_tree));
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}
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}
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