5d4cffb35f
This commit adds a pick_sb_mode() function which selects the best 32x32 superblock coding mode. Then it selects the best per-MB modes, compares the two and encodes that in the bitstream. The bitstream coding is rather simplistic right now. At the SB level, we code a bit to indicate whether this block uses SB-coding (32x32 prediction) or MB-coding (anything else), and then we follow with the actual modes. This could and should be modified in the future, but is omitted from this commit because it will likely involve reorganizing much more code rather than just adding SB coding, so it's better to let that be judged on its own merits. Gains on derf: about even, YT/HD: +0.75%, STD/HD: +1.5%. Change-Id: Iae313a7cbd8f75b3c66d04a68b991cb096eaaba6
308 lines
10 KiB
C
308 lines
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 "segmentation.h"
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#include "vp8/common/pred_common.h"
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void vp8_update_gf_useage_maps(VP8_COMP *cpi, VP8_COMMON *cm, MACROBLOCK *x) {
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int mb_row, mb_col;
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MODE_INFO *this_mb_mode_info = cm->mi;
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x->gf_active_ptr = (signed char *)cpi->gf_active_flags;
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if ((cm->frame_type == KEY_FRAME) || (cm->refresh_golden_frame)) {
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// Reset Gf useage monitors
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vpx_memset(cpi->gf_active_flags, 1, (cm->mb_rows * cm->mb_cols));
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cpi->gf_active_count = cm->mb_rows * cm->mb_cols;
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} else {
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// for each macroblock row in image
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for (mb_row = 0; mb_row < cm->mb_rows; mb_row++) {
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// for each macroblock col in image
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for (mb_col = 0; mb_col < cm->mb_cols; mb_col++) {
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// If using golden then set GF active flag if not already set.
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// If using last frame 0,0 mode then leave flag as it is
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// else if using non 0,0 motion or intra modes then clear
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// flag if it is currently set
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if ((this_mb_mode_info->mbmi.ref_frame == GOLDEN_FRAME) ||
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(this_mb_mode_info->mbmi.ref_frame == ALTREF_FRAME)) {
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if (*(x->gf_active_ptr) == 0) {
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*(x->gf_active_ptr) = 1;
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cpi->gf_active_count++;
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}
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} else if ((this_mb_mode_info->mbmi.mode != ZEROMV) &&
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*(x->gf_active_ptr)) {
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*(x->gf_active_ptr) = 0;
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cpi->gf_active_count--;
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}
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x->gf_active_ptr++; // Step onto next entry
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this_mb_mode_info++; // skip to next mb
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}
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// this is to account for the border
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this_mb_mode_info++;
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}
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}
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}
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void vp8_enable_segmentation(VP8_PTR ptr) {
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VP8_COMP *cpi = (VP8_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 vp8_disable_segmentation(VP8_PTR ptr) {
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VP8_COMP *cpi = (VP8_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 vp8_set_segmentation_map(VP8_PTR ptr,
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unsigned char *segmentation_map) {
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VP8_COMP *cpi = (VP8_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 vp8_set_segment_data(VP8_PTR ptr,
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signed char *feature_data,
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unsigned char abs_delta) {
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VP8_COMP *cpi = (VP8_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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vp8_prob *segment_tree_probs) {
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int count1, count2;
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int tot_count;
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int i;
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// Blank the strtucture to start with
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vpx_memset(segment_tree_probs, 0,
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MB_FEATURE_TREE_PROBS * sizeof(*segment_tree_probs));
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// Total count for all segments
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count1 = segcounts[0] + segcounts[1];
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count2 = segcounts[2] + segcounts[3];
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tot_count = count1 + count2;
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// Work out probabilities of each segment
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if (tot_count)
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segment_tree_probs[0] = (count1 * 255) / tot_count;
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if (count1 > 0)
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segment_tree_probs[1] = (segcounts[0] * 255) / count1;
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if (count2 > 0)
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segment_tree_probs[2] = (segcounts[2] * 255) / count2;
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// Clamp probabilities to minimum allowed value
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for (i = 0; i < MB_FEATURE_TREE_PROBS; i++) {
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if (segment_tree_probs[i] == 0)
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segment_tree_probs[i] = 1;
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}
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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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vp8_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];
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count2 = segcounts[2] + segcounts[3];
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cost = count1 * vp8_cost_zero(probs[0]) +
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count2 * vp8_cost_one(probs[0]);
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// Now add the cost of each individual segment branch
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if (count1 > 0)
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cost += segcounts[0] * vp8_cost_zero(probs[1]) +
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segcounts[1] * vp8_cost_one(probs[1]);
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if (count2 > 0)
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cost += segcounts[2] * vp8_cost_zero(probs[2]) +
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segcounts[3] * vp8_cost_one(probs[2]);
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return cost;
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}
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void choose_segmap_coding_method(VP8_COMP *cpi) {
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VP8_COMMON *const cm = & cpi->common;
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MACROBLOCKD *const xd = & cpi->mb.e_mbd;
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int i;
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int tot_count;
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int no_pred_cost;
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int t_pred_cost = INT_MAX;
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int pred_context;
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int mb_row, mb_col;
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int segmap_index = 0;
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unsigned char segment_id;
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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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vp8_prob no_pred_tree[MB_FEATURE_TREE_PROBS];
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vp8_prob t_pred_tree[MB_FEATURE_TREE_PROBS];
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vp8_prob t_nopred_prob[PREDICTION_PROBS];
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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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// Initialize macroblock decoder mode info context for the first mb
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// in the frame
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xd->mode_info_context = cm->mi;
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for (mb_row = 0; mb_row < cm->mb_rows; mb_row += 2) {
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for (mb_col = 0; mb_col < cm->mb_cols; mb_col += 2) {
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for (i = 0; i < 4; i++) {
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static const int dx[4] = { +1, -1, +1, +1 };
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static const int dy[4] = { 0, +1, 0, -1 };
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int x_idx = i & 1, y_idx = i >> 1;
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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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goto end;
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}
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segmap_index = (mb_row + y_idx) * cm->mb_cols + mb_col + x_idx;
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segment_id = xd->mode_info_context->mbmi.segment_id;
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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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int seg_predicted =
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(segment_id == get_pred_mb_segid(cm, segmap_index));
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// Get the segment id prediction context
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pred_context =
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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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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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#if CONFIG_SUPERBLOCKS
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if (xd->mode_info_context->mbmi.encoded_as_sb) {
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assert(!i);
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xd->mode_info_context += 2;
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break;
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}
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#endif
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end:
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xd->mode_info_context += dx[i] + dy[i] * cm->mode_info_stride;
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}
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}
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// this is to account for the border in mode_info_context
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xd->mode_info_context -= mb_col;
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xd->mode_info_context += cm->mode_info_stride * 2;
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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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tot_count = temporal_predictor_count[i][0] +
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temporal_predictor_count[i][1];
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// Work out the context probabilities for the segment
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// prediction flag
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if (tot_count) {
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t_nopred_prob[i] = (temporal_predictor_count[i][0] * 255) /
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tot_count;
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// Clamp to minimum allowed value
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if (t_nopred_prob[i] < 1)
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t_nopred_prob[i] = 1;
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} else
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t_nopred_prob[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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vp8_cost_zero(t_nopred_prob[i])) +
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(temporal_predictor_count[i][1] *
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vp8_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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