290 строки
10 KiB
C
290 строки
10 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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cpi->mb.e_mbd.seg.enabled = 1;
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cpi->mb.e_mbd.seg.update_map = 1;
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cpi->mb.e_mbd.seg.update_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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cpi->mb.e_mbd.seg.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.mi_rows * cpi->common.mi_cols));
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// Signal that the map should be updated.
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cpi->mb.e_mbd.seg.update_map = 1;
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cpi->mb.e_mbd.seg.update_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.seg.abs_delta = abs_delta;
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vpx_memcpy(cpi->mb.e_mbd.seg.feature_data, feature_data,
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sizeof(cpi->mb.e_mbd.seg.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(int *segcounts, vp9_prob *segment_tree_probs) {
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// Work out probabilities of each segment
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const int c01 = segcounts[0] + segcounts[1];
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const int c23 = segcounts[2] + segcounts[3];
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const int c45 = segcounts[4] + segcounts[5];
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const int c67 = segcounts[6] + segcounts[7];
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segment_tree_probs[0] = get_binary_prob(c01 + c23, c45 + c67);
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segment_tree_probs[1] = get_binary_prob(c01, c23);
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segment_tree_probs[2] = get_binary_prob(c45, c67);
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segment_tree_probs[3] = get_binary_prob(segcounts[0], segcounts[1]);
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segment_tree_probs[4] = get_binary_prob(segcounts[2], segcounts[3]);
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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(int *segcounts, vp9_prob *probs) {
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const int c01 = segcounts[0] + segcounts[1];
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const int c23 = segcounts[2] + segcounts[3];
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const int c45 = segcounts[4] + segcounts[5];
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const int c67 = segcounts[6] + segcounts[7];
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const int c0123 = c01 + c23;
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const int c4567 = c45 + c67;
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// Cost the top node of the tree
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int cost = c0123 * vp9_cost_zero(probs[0]) +
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c4567 * vp9_cost_one(probs[0]);
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// Cost subsequent levels
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if (c0123 > 0) {
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cost += c01 * vp9_cost_zero(probs[1]) +
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c23 * vp9_cost_one(probs[1]);
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if (c01 > 0)
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cost += segcounts[0] * vp9_cost_zero(probs[3]) +
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segcounts[1] * vp9_cost_one(probs[3]);
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if (c23 > 0)
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cost += segcounts[2] * vp9_cost_zero(probs[4]) +
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segcounts[3] * vp9_cost_one(probs[4]);
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}
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if (c4567 > 0) {
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cost += c45 * vp9_cost_zero(probs[2]) +
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c67 * vp9_cost_one(probs[2]);
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if (c45 > 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 (c67 > 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, 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 mi_row, int mi_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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int segment_id;
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if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols)
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return;
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segment_id = mi->mbmi.segment_id;
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xd->mode_info_context = mi;
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set_mi_row_col(cm, xd, mi_row, bh, mi_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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const BLOCK_SIZE_TYPE bsize = mi->mbmi.sb_type;
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// Test to see if the segment id matches the predicted value.
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const int pred_segment_id = vp9_get_segment_id(cm, cm->last_frame_seg_map,
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bsize, mi_row, mi_col);
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const int pred_flag = pred_segment_id == segment_id;
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const int pred_context = vp9_get_pred_context_seg_id(xd);
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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_seg_id(cm, bsize, mi_row, mi_col, pred_flag);
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temporal_predictor_count[pred_context][pred_flag]++;
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if (!pred_flag)
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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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static void count_segs_sb(VP9_COMP *cpi, 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 mi_row, int mi_col,
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BLOCK_SIZE_TYPE bsize) {
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VP9_COMMON *const cm = &cpi->common;
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const int mis = cm->mode_info_stride;
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int bwl, bhl;
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const int bsl = mi_width_log2(bsize), bs = 1 << (bsl - 1);
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if (mi_row >= cm->mi_rows || mi_col >= cm->mi_cols)
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return;
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bwl = mi_width_log2(mi->mbmi.sb_type);
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bhl = mi_height_log2(mi->mbmi.sb_type);
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if (bwl == bsl && bhl == bsl) {
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count_segs(cpi, mi, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, 1 << bsl, 1 << bsl, mi_row, mi_col);
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} else if (bwl == bsl && bhl < bsl) {
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count_segs(cpi, mi, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, 1 << bsl, bs, mi_row, mi_col);
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count_segs(cpi, mi + bs * mis, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, 1 << bsl, bs, mi_row + bs, mi_col);
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} else if (bwl < bsl && bhl == bsl) {
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count_segs(cpi, mi, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, bs, 1 << bsl, mi_row, mi_col);
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count_segs(cpi, mi + bs, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, bs, 1 << bsl, mi_row, mi_col + bs);
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} else {
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BLOCK_SIZE_TYPE subsize;
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int n;
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assert(bwl < bsl && bhl < bsl);
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if (bsize == BLOCK_64X64) {
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subsize = BLOCK_32X32;
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} else if (bsize == BLOCK_32X32) {
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subsize = BLOCK_16X16;
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} else {
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assert(bsize == BLOCK_16X16);
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subsize = BLOCK_8X8;
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}
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for (n = 0; n < 4; n++) {
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const int y_idx = n >> 1, x_idx = n & 0x01;
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count_segs_sb(cpi, mi + y_idx * bs * mis + x_idx * bs,
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no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts,
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mi_row + y_idx * bs, mi_col + x_idx * bs, subsize);
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}
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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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struct segmentation *seg = &cpi->mb.e_mbd.seg;
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int no_pred_cost;
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int t_pred_cost = INT_MAX;
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int i, tile_col, mi_row, mi_col;
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int temporal_predictor_count[PREDICTION_PROBS][2];
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int no_pred_segcounts[MAX_SEGMENTS];
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int t_unpred_seg_counts[MAX_SEGMENTS];
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vp9_prob no_pred_tree[SEG_TREE_PROBS];
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vp9_prob t_pred_tree[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(seg->tree_probs, 255, sizeof(seg->tree_probs));
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vpx_memset(seg->pred_probs, 255, sizeof(seg->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 < 1 << cm->log2_tile_cols; 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_mi_col_start;
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for (mi_row = 0; mi_row < cm->mi_rows;
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mi_row += 8, mi_ptr += 8 * mis) {
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mi = mi_ptr;
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for (mi_col = cm->cur_tile_mi_col_start; mi_col < cm->cur_tile_mi_col_end;
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mi_col += 8, mi += 8)
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count_segs_sb(cpi, mi, no_pred_segcounts, temporal_predictor_count,
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t_unpred_seg_counts, mi_row, mi_col, BLOCK_64X64);
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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(no_pred_segcounts, no_pred_tree);
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no_pred_cost = cost_segmap(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(t_unpred_seg_counts, t_pred_tree);
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t_pred_cost = cost_segmap(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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const int count0 = temporal_predictor_count[i][0];
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const int count1 = temporal_predictor_count[i][1];
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t_nopred_prob[i] = get_binary_prob(count0, count1);
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// Add in the predictor signaling cost
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t_pred_cost += count0 * vp9_cost_zero(t_nopred_prob[i]) +
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count1 * 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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seg->temporal_update = 1;
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vpx_memcpy(seg->tree_probs, t_pred_tree, sizeof(t_pred_tree));
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vpx_memcpy(seg->pred_probs, t_nopred_prob, sizeof(t_nopred_prob));
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} else {
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seg->temporal_update = 0;
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vpx_memcpy(seg->tree_probs, no_pred_tree, sizeof(no_pred_tree));
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}
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}
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