vpx/vp9/encoder/vp9_segmentation.c
Ronald S. Bultje 4d0ec7aacd Consistently use get_prob(), clip_prob() and newly added clip_pixel().
Add a function clip_pixel() to clip a pixel value to the [0,255] range
of allowed values, and use this where-ever appropriate (e.g. prediction,
reconstruction). Likewise, consistently use the recently added function
clip_prob(), which calculates a binary probability in the [1,255] range.
If possible, try to use get_prob() or its sister get_binary_prob() to
calculate binary probabilities, for consistency.

Since in some places, this means that binary probability calculations
are changed (we use {255,256}*count0/(total) in a range of places,
and all of these are now changed to use 256*count0+(total>>1)/total),
this changes the encoding result, so this patch warrants some extensive
testing.

Change-Id: Ibeeff8d886496839b8e0c0ace9ccc552351f7628
2012-12-12 10:01:19 -08:00

307 lines
10 KiB
C

/*
* 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 "vpx_mem/vpx_mem.h"
#include "vp9/encoder/vp9_segmentation.h"
#include "vp9/common/vp9_pred_common.h"
void vp9_update_gf_useage_maps(VP9_COMP *cpi, VP9_COMMON *cm, MACROBLOCK *x) {
int mb_row, mb_col;
MODE_INFO *this_mb_mode_info = cm->mi;
x->gf_active_ptr = (signed char *)cpi->gf_active_flags;
if ((cm->frame_type == KEY_FRAME) || (cm->refresh_golden_frame)) {
// Reset Gf useage monitors
vpx_memset(cpi->gf_active_flags, 1, (cm->mb_rows * cm->mb_cols));
cpi->gf_active_count = cm->mb_rows * cm->mb_cols;
} else {
// for each macroblock row in image
for (mb_row = 0; mb_row < cm->mb_rows; mb_row++) {
// for each macroblock col in image
for (mb_col = 0; mb_col < cm->mb_cols; mb_col++) {
// If using golden then set GF active flag if not already set.
// If using last frame 0,0 mode then leave flag as it is
// else if using non 0,0 motion or intra modes then clear
// flag if it is currently set
if ((this_mb_mode_info->mbmi.ref_frame == GOLDEN_FRAME) ||
(this_mb_mode_info->mbmi.ref_frame == ALTREF_FRAME)) {
if (*(x->gf_active_ptr) == 0) {
*(x->gf_active_ptr) = 1;
cpi->gf_active_count++;
}
} else if ((this_mb_mode_info->mbmi.mode != ZEROMV) &&
*(x->gf_active_ptr)) {
*(x->gf_active_ptr) = 0;
cpi->gf_active_count--;
}
x->gf_active_ptr++; // Step onto next entry
this_mb_mode_info++; // skip to next mb
}
// this is to account for the border
this_mb_mode_info++;
}
}
}
void vp9_enable_segmentation(VP9_PTR ptr) {
VP9_COMP *cpi = (VP9_COMP *)(ptr);
// Set the appropriate feature bit
cpi->mb.e_mbd.segmentation_enabled = 1;
cpi->mb.e_mbd.update_mb_segmentation_map = 1;
cpi->mb.e_mbd.update_mb_segmentation_data = 1;
}
void vp9_disable_segmentation(VP9_PTR ptr) {
VP9_COMP *cpi = (VP9_COMP *)(ptr);
// Clear the appropriate feature bit
cpi->mb.e_mbd.segmentation_enabled = 0;
}
void vp9_set_segmentation_map(VP9_PTR ptr,
unsigned char *segmentation_map) {
VP9_COMP *cpi = (VP9_COMP *)(ptr);
// Copy in the new segmentation map
vpx_memcpy(cpi->segmentation_map, segmentation_map,
(cpi->common.mb_rows * cpi->common.mb_cols));
// Signal that the map should be updated.
cpi->mb.e_mbd.update_mb_segmentation_map = 1;
cpi->mb.e_mbd.update_mb_segmentation_data = 1;
}
void vp9_set_segment_data(VP9_PTR ptr,
signed char *feature_data,
unsigned char abs_delta) {
VP9_COMP *cpi = (VP9_COMP *)(ptr);
cpi->mb.e_mbd.mb_segment_abs_delta = abs_delta;
vpx_memcpy(cpi->mb.e_mbd.segment_feature_data, feature_data,
sizeof(cpi->mb.e_mbd.segment_feature_data));
// TBD ?? Set the feature mask
// vpx_memcpy(cpi->mb.e_mbd.segment_feature_mask, 0,
// sizeof(cpi->mb.e_mbd.segment_feature_mask));
}
// Based on set of segment counts calculate a probability tree
static void calc_segtree_probs(MACROBLOCKD *xd,
int *segcounts,
vp9_prob *segment_tree_probs) {
int count1, count2;
// Total count for all segments
count1 = segcounts[0] + segcounts[1];
count2 = segcounts[2] + segcounts[3];
// Work out probabilities of each segment
segment_tree_probs[0] = get_binary_prob(count1, count2);
segment_tree_probs[1] = get_prob(segcounts[0], count1);
segment_tree_probs[2] = get_prob(segcounts[2], count2);
}
// Based on set of segment counts and probabilities calculate a cost estimate
static int cost_segmap(MACROBLOCKD *xd,
int *segcounts,
vp9_prob *probs) {
int cost;
int count1, count2;
// Cost the top node of the tree
count1 = segcounts[0] + segcounts[1];
count2 = segcounts[2] + segcounts[3];
cost = count1 * vp9_cost_zero(probs[0]) +
count2 * vp9_cost_one(probs[0]);
// Now add the cost of each individual segment branch
if (count1 > 0)
cost += segcounts[0] * vp9_cost_zero(probs[1]) +
segcounts[1] * vp9_cost_one(probs[1]);
if (count2 > 0)
cost += segcounts[2] * vp9_cost_zero(probs[2]) +
segcounts[3] * vp9_cost_one(probs[2]);
return cost;
}
void vp9_choose_segmap_coding_method(VP9_COMP *cpi) {
VP9_COMMON *const cm = &cpi->common;
MACROBLOCKD *const xd = &cpi->mb.e_mbd;
int i;
int no_pred_cost;
int t_pred_cost = INT_MAX;
int pred_context;
int mb_row, mb_col;
int segmap_index = 0;
unsigned char segment_id;
int temporal_predictor_count[PREDICTION_PROBS][2];
int no_pred_segcounts[MAX_MB_SEGMENTS];
int t_unpred_seg_counts[MAX_MB_SEGMENTS];
vp9_prob no_pred_tree[MB_FEATURE_TREE_PROBS];
vp9_prob t_pred_tree[MB_FEATURE_TREE_PROBS];
vp9_prob t_nopred_prob[PREDICTION_PROBS];
#if CONFIG_SUPERBLOCKS
const int mis = cm->mode_info_stride;
#endif
// Set default state for the segment tree probabilities and the
// temporal coding probabilities
vpx_memset(xd->mb_segment_tree_probs, 255,
sizeof(xd->mb_segment_tree_probs));
vpx_memset(cm->segment_pred_probs, 255,
sizeof(cm->segment_pred_probs));
vpx_memset(no_pred_segcounts, 0, sizeof(no_pred_segcounts));
vpx_memset(t_unpred_seg_counts, 0, sizeof(t_unpred_seg_counts));
vpx_memset(temporal_predictor_count, 0, sizeof(temporal_predictor_count));
// First of all generate stats regarding how well the last segment map
// predicts this one
// Initialize macroblock decoder mode info context for the first mb
// in the frame
xd->mode_info_context = cm->mi;
for (mb_row = 0; mb_row < cm->mb_rows; mb_row += 2) {
for (mb_col = 0; mb_col < cm->mb_cols; mb_col += 2) {
for (i = 0; i < 4; i++) {
static const int dx[4] = { +1, -1, +1, +1 };
static const int dy[4] = { 0, +1, 0, -1 };
int x_idx = i & 1, y_idx = i >> 1;
if (mb_col + x_idx >= cm->mb_cols ||
mb_row + y_idx >= cm->mb_rows) {
goto end;
}
xd->mb_to_top_edge = -((mb_row * 16) << 3);
xd->mb_to_left_edge = -((mb_col * 16) << 3);
segmap_index = (mb_row + y_idx) * cm->mb_cols + mb_col + x_idx;
segment_id = xd->mode_info_context->mbmi.segment_id;
#if CONFIG_SUPERBLOCKS
if (xd->mode_info_context->mbmi.encoded_as_sb) {
if (mb_col + 1 < cm->mb_cols)
segment_id = segment_id &&
xd->mode_info_context[1].mbmi.segment_id;
if (mb_row + 1 < cm->mb_rows) {
segment_id = segment_id &&
xd->mode_info_context[mis].mbmi.segment_id;
if (mb_col + 1 < cm->mb_cols)
segment_id = segment_id &&
xd->mode_info_context[mis + 1].mbmi.segment_id;
}
xd->mb_to_bottom_edge = ((cm->mb_rows - 2 - mb_row) * 16) << 3;
xd->mb_to_right_edge = ((cm->mb_cols - 2 - mb_col) * 16) << 3;
} else {
#endif
xd->mb_to_bottom_edge = ((cm->mb_rows - 1 - mb_row) * 16) << 3;
xd->mb_to_right_edge = ((cm->mb_cols - 1 - mb_col) * 16) << 3;
#if CONFIG_SUPERBLOCKS
}
#endif
// 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) {
// Test to see if the segment id matches the predicted value.
int seg_predicted =
(segment_id == vp9_get_pred_mb_segid(cm, xd, segmap_index));
// Get the segment id prediction context
pred_context =
vp9_get_pred_context(cm, xd, PRED_SEG_ID);
// Store the prediction status for this mb and update counts
// as appropriate
vp9_set_pred_flag(xd, PRED_SEG_ID, seg_predicted);
temporal_predictor_count[pred_context][seg_predicted]++;
if (!seg_predicted)
// Update the "unpredicted" segment count
t_unpred_seg_counts[segment_id]++;
}
#if CONFIG_SUPERBLOCKS
if (xd->mode_info_context->mbmi.encoded_as_sb) {
assert(!i);
xd->mode_info_context += 2;
break;
}
#endif
end:
xd->mode_info_context += dx[i] + dy[i] * cm->mode_info_stride;
}
}
// this is to account for the border in mode_info_context
xd->mode_info_context -= mb_col;
xd->mode_info_context += cm->mode_info_stride * 2;
}
// Work out probability tree for coding segments without prediction
// and the cost.
calc_segtree_probs(xd, no_pred_segcounts, no_pred_tree);
no_pred_cost = cost_segmap(xd, no_pred_segcounts, no_pred_tree);
// Key frames cannot use temporal prediction
if (cm->frame_type != KEY_FRAME) {
// Work out probability tree for coding those segments not
// predicted using the temporal method and the cost.
calc_segtree_probs(xd, t_unpred_seg_counts, t_pred_tree);
t_pred_cost = cost_segmap(xd, t_unpred_seg_counts, t_pred_tree);
// Add in the cost of the signalling for each prediction context
for (i = 0; i < PREDICTION_PROBS; i++) {
t_nopred_prob[i] = get_binary_prob(temporal_predictor_count[i][0],
temporal_predictor_count[i][1]);
// Add in the predictor signaling cost
t_pred_cost += (temporal_predictor_count[i][0] *
vp9_cost_zero(t_nopred_prob[i])) +
(temporal_predictor_count[i][1] *
vp9_cost_one(t_nopred_prob[i]));
}
}
// Now choose which coding method to use.
if (t_pred_cost < no_pred_cost) {
cm->temporal_update = 1;
vpx_memcpy(xd->mb_segment_tree_probs,
t_pred_tree, sizeof(t_pred_tree));
vpx_memcpy(&cm->segment_pred_probs,
t_nopred_prob, sizeof(t_nopred_prob));
} else {
cm->temporal_update = 0;
vpx_memcpy(xd->mb_segment_tree_probs,
no_pred_tree, sizeof(no_pred_tree));
}
}