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/*
* Copyright (c) 2019, Alliance for Open Media. All rights reserved
*
* This source code is subject to the terms of the BSD 2 Clause License and
* the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
* was not distributed with this source code in the LICENSE file, you can
* obtain it at www.aomedia.org/license/software. If the Alliance for Open
* Media Patent License 1.0 was not distributed with this source code in the
* PATENTS file, you can obtain it at www.aomedia.org/license/patent.
*/
#include <limits.h>
#include <math.h>
#include <stdbool.h>
#include <stdio.h>
#include "config/aom_config.h"
#include "config/aom_dsp_rtcd.h"
#include "config/av1_rtcd.h"
#include "aom_dsp/aom_dsp_common.h"
#include "aom_dsp/binary_codes_writer.h"
#include "aom_ports/mem.h"
#include "aom_ports/aom_timer.h"
#include "aom_ports/system_state.h"
#include "av1/common/reconinter.h"
#include "av1/common/blockd.h"
#include "av1/encoder/encodeframe.h"
#include "av1/encoder/var_based_part.h"
#include "av1/encoder/reconinter_enc.h"
extern const uint8_t AV1_VAR_OFFS[];
typedef struct {
// TODO(kyslov): consider changing to 64bit
// This struct is used for computing variance in choose_partitioning(), where
// the max number of samples within a superblock is 32x32 (with 4x4 avg).
// With 8bit bitdepth, uint32_t is enough for sum_square_error (2^8 * 2^8 * 32
// * 32 = 2^26). For high bitdepth we need to consider changing this to 64 bit
uint32_t sum_square_error;
int32_t sum_error;
int log2_count;
int variance;
} var;
typedef struct {
var none;
var horz[2];
var vert[2];
} partition_variance;
typedef struct {
partition_variance part_variances;
var split[4];
} v4x4;
typedef struct {
partition_variance part_variances;
v4x4 split[4];
} v8x8;
typedef struct {
partition_variance part_variances;
v8x8 split[4];
} v16x16;
typedef struct {
partition_variance part_variances;
v16x16 split[4];
} v32x32;
typedef struct {
partition_variance part_variances;
v32x32 split[4];
} v64x64;
typedef struct {
partition_variance part_variances;
v64x64 split[4];
} v128x128;
typedef struct {
partition_variance *part_variances;
var *split[4];
} variance_node;
static void tree_to_node(void *data, BLOCK_SIZE bsize, variance_node *node) {
int i;
node->part_variances = NULL;
switch (bsize) {
case BLOCK_128X128: {
v128x128 *vt = (v128x128 *)data;
node->part_variances = &vt->part_variances;
for (i = 0; i < 4; i++)
node->split[i] = &vt->split[i].part_variances.none;
break;
}
case BLOCK_64X64: {
v64x64 *vt = (v64x64 *)data;
node->part_variances = &vt->part_variances;
for (i = 0; i < 4; i++)
node->split[i] = &vt->split[i].part_variances.none;
break;
}
case BLOCK_32X32: {
v32x32 *vt = (v32x32 *)data;
node->part_variances = &vt->part_variances;
for (i = 0; i < 4; i++)
node->split[i] = &vt->split[i].part_variances.none;
break;
}
case BLOCK_16X16: {
v16x16 *vt = (v16x16 *)data;
node->part_variances = &vt->part_variances;
for (i = 0; i < 4; i++)
node->split[i] = &vt->split[i].part_variances.none;
break;
}
case BLOCK_8X8: {
v8x8 *vt = (v8x8 *)data;
node->part_variances = &vt->part_variances;
for (i = 0; i < 4; i++)
node->split[i] = &vt->split[i].part_variances.none;
break;
}
default: {
v4x4 *vt = (v4x4 *)data;
assert(bsize == BLOCK_4X4);
node->part_variances = &vt->part_variances;
for (i = 0; i < 4; i++) node->split[i] = &vt->split[i];
break;
}
}
}
// Set variance values given sum square error, sum error, count.
static void fill_variance(uint32_t s2, int32_t s, int c, var *v) {
v->sum_square_error = s2;
v->sum_error = s;
v->log2_count = c;
}
static void get_variance(var *v) {
v->variance =
(int)(256 * (v->sum_square_error -
(uint32_t)(((int64_t)v->sum_error * v->sum_error) >>
v->log2_count)) >>
v->log2_count);
}
static void sum_2_variances(const var *a, const var *b, var *r) {
assert(a->log2_count == b->log2_count);
fill_variance(a->sum_square_error + b->sum_square_error,
a->sum_error + b->sum_error, a->log2_count + 1, r);
}
static void fill_variance_tree(void *data, BLOCK_SIZE bsize) {
variance_node node;
memset(&node, 0, sizeof(node));
tree_to_node(data, bsize, &node);
sum_2_variances(node.split[0], node.split[1], &node.part_variances->horz[0]);
sum_2_variances(node.split[2], node.split[3], &node.part_variances->horz[1]);
sum_2_variances(node.split[0], node.split[2], &node.part_variances->vert[0]);
sum_2_variances(node.split[1], node.split[3], &node.part_variances->vert[1]);
sum_2_variances(&node.part_variances->vert[0], &node.part_variances->vert[1],
&node.part_variances->none);
}
static void set_block_size(AV1_COMP *const cpi, MACROBLOCK *const x,
MACROBLOCKD *const xd, int mi_row, int mi_col,
BLOCK_SIZE bsize) {
if (cpi->common.mi_cols > mi_col && cpi->common.mi_rows > mi_row) {
set_mode_info_offsets(cpi, x, xd, mi_row, mi_col);
xd->mi[0]->sb_type = bsize;
}
}
static int set_vt_partitioning(AV1_COMP *cpi, MACROBLOCK *const x,
MACROBLOCKD *const xd,
const TileInfo *const tile, void *data,
BLOCK_SIZE bsize, int mi_row, int mi_col,
int64_t threshold, BLOCK_SIZE bsize_min,
int force_split) {
AV1_COMMON *const cm = &cpi->common;
variance_node vt;
const int block_width = mi_size_wide[bsize];
const int block_height = mi_size_high[bsize];
assert(block_height == block_width);
tree_to_node(data, bsize, &vt);
if (force_split == 1) return 0;
// For bsize=bsize_min (16x16/8x8 for 8x8/4x4 downsampling), select if
// variance is below threshold, otherwise split will be selected.
// No check for vert/horiz split as too few samples for variance.
if (bsize == bsize_min) {
// Variance already computed to set the force_split.
if (frame_is_intra_only(cm)) get_variance(&vt.part_variances->none);
if (mi_col + block_width <= tile->mi_col_end &&
mi_row + block_height <= tile->mi_row_end &&
vt.part_variances->none.variance < threshold) {
set_block_size(cpi, x, xd, mi_row, mi_col, bsize);
return 1;
}
return 0;
} else if (bsize > bsize_min) {
// Variance already computed to set the force_split.
if (frame_is_intra_only(cm)) get_variance(&vt.part_variances->none);
// For key frame: take split for bsize above 32X32 or very high variance.
if (frame_is_intra_only(cm) &&
(bsize > BLOCK_32X32 ||
vt.part_variances->none.variance > (threshold << 4))) {
return 0;
}
// If variance is low, take the bsize (no split).
if (mi_col + block_width <= tile->mi_col_end &&
mi_row + block_height <= tile->mi_row_end &&
vt.part_variances->none.variance < threshold) {
set_block_size(cpi, x, xd, mi_row, mi_col, bsize);
return 1;
}
// Check vertical split.
if (mi_row + block_height <= tile->mi_row_end &&
mi_col + block_width / 2 <= tile->mi_col_end) {
BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_VERT);
get_variance(&vt.part_variances->vert[0]);
get_variance(&vt.part_variances->vert[1]);
if (vt.part_variances->vert[0].variance < threshold &&
vt.part_variances->vert[1].variance < threshold &&
get_plane_block_size(AOMMAX(BLOCK_8X8, subsize),
xd->plane[1].subsampling_x,
xd->plane[1].subsampling_y) < BLOCK_INVALID) {
set_block_size(cpi, x, xd, mi_row, mi_col, subsize);
set_block_size(cpi, x, xd, mi_row, mi_col + block_width / 2, subsize);
return 1;
}
}
// Check horizontal split.
if (mi_col + block_width <= tile->mi_col_end &&
mi_row + block_height / 2 <= tile->mi_row_end) {
BLOCK_SIZE subsize = get_partition_subsize(bsize, PARTITION_HORZ);
get_variance(&vt.part_variances->horz[0]);
get_variance(&vt.part_variances->horz[1]);
if (vt.part_variances->horz[0].variance < threshold &&
vt.part_variances->horz[1].variance < threshold &&
get_plane_block_size(AOMMAX(BLOCK_8X8, subsize),
xd->plane[1].subsampling_x,
xd->plane[1].subsampling_y) < BLOCK_INVALID) {
set_block_size(cpi, x, xd, mi_row, mi_col, subsize);
set_block_size(cpi, x, xd, mi_row + block_height / 2, mi_col, subsize);
return 1;
}
}
return 0;
}
return 0;
}
static void fill_variance_8x8avg(const uint8_t *s, int sp, const uint8_t *d,
int dp, int x16_idx, int y16_idx, v16x16 *vst,
int pixels_wide, int pixels_high,
int is_key_frame) {
int k;
for (k = 0; k < 4; k++) {
int x8_idx = x16_idx + ((k & 1) << 3);
int y8_idx = y16_idx + ((k >> 1) << 3);
unsigned int sse = 0;
int sum = 0;
if (x8_idx < pixels_wide && y8_idx < pixels_high) {
int s_avg;
int d_avg = 128;
s_avg = aom_avg_8x8(s + y8_idx * sp + x8_idx, sp);
if (!is_key_frame) d_avg = aom_avg_8x8(d + y8_idx * dp + x8_idx, dp);
sum = s_avg - d_avg;
sse = sum * sum;
}
fill_variance(sse, sum, 0, &vst->split[k].part_variances.none);
}
}
static int compute_minmax_8x8(const uint8_t *s, int sp, const uint8_t *d,
int dp, int x16_idx, int y16_idx, int pixels_wide,
int pixels_high) {
int k;
int minmax_max = 0;
int minmax_min = 255;
// Loop over the 4 8x8 subblocks.
for (k = 0; k < 4; k++) {
int x8_idx = x16_idx + ((k & 1) << 3);
int y8_idx = y16_idx + ((k >> 1) << 3);
int min = 0;
int max = 0;
if (x8_idx < pixels_wide && y8_idx < pixels_high) {
aom_minmax_8x8(s + y8_idx * sp + x8_idx, sp, d + y8_idx * dp + x8_idx, dp,
&min, &max);
if ((max - min) > minmax_max) minmax_max = (max - min);
if ((max - min) < minmax_min) minmax_min = (max - min);
}
}
return (minmax_max - minmax_min);
}
static void fill_variance_4x4avg(const uint8_t *s, int sp, const uint8_t *d,
int dp, int x8_idx, int y8_idx, v8x8 *vst,
int pixels_wide, int pixels_high,
int is_key_frame) {
int k;
for (k = 0; k < 4; k++) {
int x4_idx = x8_idx + ((k & 1) << 2);
int y4_idx = y8_idx + ((k >> 1) << 2);
unsigned int sse = 0;
int sum = 0;
if (x4_idx < pixels_wide && y4_idx < pixels_high) {
int s_avg;
int d_avg = 128;
s_avg = aom_avg_4x4(s + y4_idx * sp + x4_idx, sp);
if (!is_key_frame) d_avg = aom_avg_4x4(d + y4_idx * dp + x4_idx, dp);
sum = s_avg - d_avg;
sse = sum * sum;
}
fill_variance(sse, sum, 0, &vst->split[k].part_variances.none);
}
}
// TODO(kyslov) Bring back threshold adjustment based on content state
static int64_t scale_part_thresh_sumdiff(int64_t threshold_base, int speed,
int width, int height,
int content_state) {
(void)width;
(void)height;
(void)content_state;
if (speed >= 8) {
return (5 * threshold_base) >> 2;
}
return threshold_base;
}
// Set the variance split thresholds for following the block sizes:
// 0 - threshold_128x128, 1 - threshold_64x64, 2 - threshold_32x32,
// 3 - vbp_threshold_16x16. 4 - vbp_threshold_8x8 (to split to 4x4 partition) is
// currently only used on key frame.
static void set_vbp_thresholds(AV1_COMP *cpi, int64_t thresholds[], int q,
int content_state) {
AV1_COMMON *const cm = &cpi->common;
const int is_key_frame = frame_is_intra_only(cm);
const int threshold_multiplier = is_key_frame ? 40 : 1;
int64_t threshold_base = (int64_t)(
threshold_multiplier *
ROUND_POWER_OF_TWO(cpi->dequants.y_dequant_QTX[q][1], QUANT_TABLE_BITS));
if (is_key_frame) {
thresholds[0] = threshold_base;
thresholds[1] = threshold_base;
thresholds[2] = threshold_base >> 2;
thresholds[3] = threshold_base >> 2;
thresholds[4] = threshold_base << 2;
} else {
// Increase base variance threshold based on content_state/sum_diff level.
threshold_base = scale_part_thresh_sumdiff(
threshold_base, cpi->oxcf.speed, cm->width, cm->height, content_state);
thresholds[0] = threshold_base >> 1;
thresholds[1] = threshold_base;
thresholds[3] = threshold_base << cpi->oxcf.speed;
if (cm->width >= 1280 && cm->height >= 720)
thresholds[3] = thresholds[3] << 1;
if (cm->width <= 352 && cm->height <= 288) {
thresholds[1] = threshold_base >> 3;
thresholds[2] = threshold_base >> 1;
thresholds[3] = threshold_base << 3;
} else if (cm->width < 1280 && cm->height < 720) {
thresholds[2] = (5 * threshold_base) >> 2;
} else if (cm->width < 1920 && cm->height < 1080) {
thresholds[2] = threshold_base << 1;
} else {
thresholds[2] = (5 * threshold_base) >> 1;
}
}
}
void av1_set_variance_partition_thresholds(AV1_COMP *cpi, int q,
int content_state) {
AV1_COMMON *const cm = &cpi->common;
SPEED_FEATURES *const sf = &cpi->sf;
const int is_key_frame = frame_is_intra_only(cm);
if (sf->partition_search_type != VAR_BASED_PARTITION) {
return;
} else {
set_vbp_thresholds(cpi, cpi->vbp_thresholds, q, content_state);
// The thresholds below are not changed locally.
if (is_key_frame) {
cpi->vbp_threshold_sad = 0;
cpi->vbp_threshold_copy = 0;
cpi->vbp_bsize_min = BLOCK_8X8;
} else {
const int y_dq = ROUND_POWER_OF_TWO(cpi->dequants.y_dequant_QTX[q][1],
QUANT_TABLE_BITS);
if (cm->width <= 352 && cm->height <= 288)
cpi->vbp_threshold_sad = 10;
else
cpi->vbp_threshold_sad = (y_dq << 1) > 1000 ? (y_dq << 1) : 1000;
cpi->vbp_bsize_min = BLOCK_16X16;
if (cm->width <= 352 && cm->height <= 288)
cpi->vbp_threshold_copy = 4000;
else if (cm->width <= 640 && cm->height <= 360)
cpi->vbp_threshold_copy = 8000;
else
cpi->vbp_threshold_copy = (y_dq << 3) > 8000 ? (y_dq << 3) : 8000;
}
cpi->vbp_threshold_minmax = 15 + (q >> 3);
}
}
// This function chooses partitioning based on the variance between source and
// reconstructed last, where variance is computed for down-sampled inputs.
// TODO(kyslov): lot of things. Bring back noise estimation, brush up partition
// selection and most of all - retune the thresholds
int av1_choose_var_based_partitioning(AV1_COMP *cpi, const TileInfo *const tile,
MACROBLOCK *x, int mi_row, int mi_col) {
AV1_COMMON *const cm = &cpi->common;
MACROBLOCKD *xd = &x->e_mbd;
int i, j, k, m;
v128x128 *vt;
v16x16 *vt2 = NULL;
unsigned char force_split[85];
int avg_32x32;
int max_var_32x32[4];
int min_var_32x32[4];
int var_32x32;
int var_64x64;
int min_var_64x64 = INT_MAX;
int max_var_64x64 = 0;
int avg_16x16[4][4];
int maxvar_16x16[4][4];
int minvar_16x16[4][4];
int64_t threshold_4x4avg;
int content_state = 0;
uint8_t *s;
const uint8_t *d;
int sp;
int dp;
// TODO(kyslov) Bring back compute_minmax_variance with content type detection
int compute_minmax_variance = 0;
int is_key_frame = frame_is_intra_only(cm);
int pixels_wide = 128, pixels_high = 128;
assert(cm->seq_params.sb_size == BLOCK_64X64 ||
cm->seq_params.sb_size == BLOCK_128X128);
const int is_small_sb = (cm->seq_params.sb_size == BLOCK_64X64);
const int num_64x64_blocks = is_small_sb ? 1 : 4;
CHECK_MEM_ERROR(cm, vt, aom_malloc(sizeof(*vt)));
int64_t thresholds[5] = { cpi->vbp_thresholds[0], cpi->vbp_thresholds[1],
cpi->vbp_thresholds[2], cpi->vbp_thresholds[3],
cpi->vbp_thresholds[4] };
const int low_res = (cm->width <= 352 && cm->height <= 288);
int variance4x4downsample[64];
int segment_id;
const int num_planes = av1_num_planes(cm);
segment_id = xd->mi[0]->segment_id;
set_vbp_thresholds(cpi, thresholds, cm->base_qindex, content_state);
if (is_small_sb) {
pixels_wide = 64;
pixels_high = 64;
}
// For non keyframes, disable 4x4 average for low resolution when speed = 8
threshold_4x4avg = INT64_MAX;
if (xd->mb_to_right_edge < 0) pixels_wide += (xd->mb_to_right_edge >> 3);
if (xd->mb_to_bottom_edge < 0) pixels_high += (xd->mb_to_bottom_edge >> 3);
s = x->plane[0].src.buf;
sp = x->plane[0].src.stride;
// Index for force_split: 0 for 64x64, 1-4 for 32x32 blocks,
// 5-20 for the 16x16 blocks.
force_split[0] = 0;
if (!is_key_frame) {
// TODO(kyslov): we are assuming that the ref is LAST_FRAME! Check if it
// is!!
MB_MODE_INFO *mi = xd->mi[0];
const YV12_BUFFER_CONFIG *yv12 = get_ref_frame_yv12_buf(cm, LAST_FRAME);
assert(yv12 != NULL);
av1_setup_pre_planes(xd, 0, yv12, mi_row, mi_col,
get_ref_scale_factors(cm, LAST_FRAME), num_planes,
NULL);
mi->ref_frame[0] = LAST_FRAME;
mi->ref_frame[1] = NONE_FRAME;
mi->sb_type = cm->seq_params.sb_size;
mi->mv[0].as_int = 0;
mi->interp_filters = av1_broadcast_interp_filter(BILINEAR);
if (cpi->sf.estimate_motion_for_var_based_partition) {
if (xd->mb_to_right_edge >= 0 && xd->mb_to_bottom_edge >= 0) {
const MV dummy_mv = { 0, 0 };
av1_int_pro_motion_estimation(cpi, x, cm->seq_params.sb_size, mi_row,
mi_col, &dummy_mv);
}
}
// TODO(kyslov): bring the small SAD functionality back
#if 0
y_sad = cpi->fn_ptr[bsize].sdf(x->plane[0].src.buf, x->plane[0].src.stride,
xd->plane[0].pre[0].buf,
xd->plane[0].pre[0].stride);
#endif
x->pred_mv[LAST_FRAME] = mi->mv[0].as_mv;
set_ref_ptrs(cm, xd, mi->ref_frame[0], mi->ref_frame[1]);
av1_enc_build_inter_predictor(cm, xd, mi_row, mi_col, NULL,
cm->seq_params.sb_size, AOM_PLANE_Y,
AOM_PLANE_Y);
d = xd->plane[0].dst.buf;
dp = xd->plane[0].dst.stride;
// If the y_sad is very small, take 64x64 as partition and exit.
// Don't check on boosted segment for now, as 64x64 is suppressed there.
#if 0
if (segment_id == CR_SEGMENT_ID_BASE && y_sad < cpi->vbp_threshold_sad)
{ const int block_width = num_8x8_blocks_wide_lookup[BLOCK_64X64]; const
int block_height = num_8x8_blocks_high_lookup[BLOCK_64X64]; if (mi_col +
block_width / 2 < cm->mi_cols && mi_row + block_height / 2 < cm->mi_rows)
{ set_block_size(cpi, x, xd, mi_row, mi_col, BLOCK_128X128);
x->variance_low[0] = 1;
return 0;
}
}
#endif
} else {
d = AV1_VAR_OFFS;
dp = 0;
}
if (low_res && threshold_4x4avg < INT64_MAX)
CHECK_MEM_ERROR(cm, vt2, aom_malloc(sizeof(*vt2)));
// Fill in the entire tree of 8x8 (or 4x4 under some conditions) variances
// for splits.
for (m = 0; m < num_64x64_blocks; m++) {
const int x64_idx = ((m & 1) << 6);
const int y64_idx = ((m >> 1) << 6);
const int m2 = m << 2;
force_split[m + 1] = 0;
max_var_32x32[m] = 0;
min_var_32x32[m] = INT_MAX;
for (i = 0; i < 4; i++) {
const int x32_idx = x64_idx + ((i & 1) << 5);
const int y32_idx = y64_idx + ((i >> 1) << 5);
const int i2 = (m2 + i) << 2;
force_split[5 + m2 + i] = 0;
avg_16x16[m][i] = 0;
maxvar_16x16[m][i] = 0;
minvar_16x16[m][i] = INT_MAX;
for (j = 0; j < 4; j++) {
const int x16_idx = x32_idx + ((j & 1) << 4);
const int y16_idx = y32_idx + ((j >> 1) << 4);
const int split_index = 21 + i2 + j;
v16x16 *vst = &vt->split[m].split[i].split[j];
force_split[split_index] = 0;
variance4x4downsample[i2 + j] = 0;
if (!is_key_frame) {
fill_variance_8x8avg(s, sp, d, dp, x16_idx, y16_idx, vst, pixels_wide,
pixels_high, is_key_frame);
fill_variance_tree(&vt->split[m].split[i].split[j], BLOCK_16X16);
get_variance(&vt->split[m].split[i].split[j].part_variances.none);
avg_16x16[m][i] +=
vt->split[m].split[i].split[j].part_variances.none.variance;
if (vt->split[m].split[i].split[j].part_variances.none.variance <
minvar_16x16[m][i])
minvar_16x16[m][i] =
vt->split[m].split[i].split[j].part_variances.none.variance;
if (vt->split[m].split[i].split[j].part_variances.none.variance >
maxvar_16x16[m][i])
maxvar_16x16[m][i] =
vt->split[m].split[i].split[j].part_variances.none.variance;
if (vt->split[m].split[i].split[j].part_variances.none.variance >
thresholds[3]) {
// 16X16 variance is above threshold for split, so force split to
// 8x8 for this 16x16 block (this also forces splits for upper
// levels).
force_split[split_index] = 1;
force_split[5 + m2 + i] = 1;
force_split[m + 1] = 1;
force_split[0] = 1;
} else if (compute_minmax_variance &&
vt->split[m]
.split[i]
.split[j]
.part_variances.none.variance > thresholds[2] &&
!cyclic_refresh_segment_id_boosted(segment_id)) {
// We have some nominal amount of 16x16 variance (based on average),
// compute the minmax over the 8x8 sub-blocks, and if above
// threshold, force split to 8x8 block for this 16x16 block.
int minmax = compute_minmax_8x8(s, sp, d, dp, x16_idx, y16_idx,
pixels_wide, pixels_high);
int thresh_minmax = (int)cpi->vbp_threshold_minmax;
if (minmax > thresh_minmax) {
force_split[split_index] = 1;
force_split[5 + m2 + i] = 1;
force_split[m + 1] = 1;
force_split[0] = 1;
}
}
}
if (is_key_frame) {
force_split[split_index] = 0;
// Go down to 4x4 down-sampling for variance.
variance4x4downsample[i2 + j] = 1;
for (k = 0; k < 4; k++) {
int x8_idx = x16_idx + ((k & 1) << 3);
int y8_idx = y16_idx + ((k >> 1) << 3);
v8x8 *vst2 = is_key_frame ? &vst->split[k] : &vt2[i2 + j].split[k];
fill_variance_4x4avg(s, sp, d, dp, x8_idx, y8_idx, vst2,
pixels_wide, pixels_high, is_key_frame);
}
}
}
}
}
// Fill the rest of the variance tree by summing split partition values.
for (m = 0; m < num_64x64_blocks; ++m) {
avg_32x32 = 0;
const int m2 = m << 2;
for (i = 0; i < 4; i++) {
const int i2 = (m2 + i) << 2;
for (j = 0; j < 4; j++) {
const int split_index = 21 + i2 + j;
if (variance4x4downsample[i2 + j] == 1) {
v16x16 *vtemp =
(!is_key_frame) ? &vt2[i2 + j] : &vt->split[m].split[i].split[j];
for (k = 0; k < 4; k++)
fill_variance_tree(&vtemp->split[k], BLOCK_8X8);
fill_variance_tree(vtemp, BLOCK_16X16);
// If variance of this 16x16 block is above the threshold, force block
// to split. This also forces a split on the upper levels.
get_variance(&vtemp->part_variances.none);
if (vtemp->part_variances.none.variance > thresholds[3]) {
force_split[split_index] = 1;
force_split[5 + m2 + i] = 1;
force_split[m + 1] = 1;
force_split[0] = 1;
}
}
}
fill_variance_tree(&vt->split[m].split[i], BLOCK_32X32);
// If variance of this 32x32 block is above the threshold, or if its above
// (some threshold of) the average variance over the sub-16x16 blocks,
// then force this block to split. This also forces a split on the upper
// (64x64) level.
if (!force_split[5 + m2 + i]) {
get_variance(&vt->split[m].split[i].part_variances.none);
var_32x32 = vt->split[m].split[i].part_variances.none.variance;
max_var_32x32[m] = AOMMAX(var_32x32, max_var_32x32[m]);
min_var_32x32[m] = AOMMIN(var_32x32, min_var_32x32[m]);
if (vt->split[m].split[i].part_variances.none.variance >
thresholds[2] ||
(!is_key_frame &&
vt->split[m].split[i].part_variances.none.variance >
(thresholds[2] >> 1) &&
vt->split[m].split[i].part_variances.none.variance >
(avg_16x16[m][i] >> 1))) {
force_split[5 + m2 + i] = 1;
force_split[m + 1] = 1;
force_split[0] = 1;
} else if (!is_key_frame && cm->height <= 360 &&
(maxvar_16x16[m][i] - minvar_16x16[m][i]) >
(thresholds[2] >> 1) &&
maxvar_16x16[m][i] > thresholds[2]) {
force_split[5 + m2 + i] = 1;
force_split[m + 1] = 1;
force_split[0] = 1;
}
avg_32x32 += var_32x32;
}
}
if (!force_split[1 + m]) {
fill_variance_tree(&vt->split[m], BLOCK_64X64);
get_variance(&vt->split[m].part_variances.none);
var_64x64 = vt->split[m].part_variances.none.variance;
max_var_64x64 = AOMMAX(var_64x64, max_var_64x64);
min_var_64x64 = AOMMIN(var_64x64, min_var_64x64);
// If variance of this 64x64 block is above (some threshold of) the
// average variance over the sub-32x32 blocks, then force this block to
// split. Only checking this for noise level >= medium for now.
if (!is_key_frame &&
(max_var_32x32[m] - min_var_32x32[m]) > 3 * (thresholds[1] >> 3) &&
max_var_32x32[m] > thresholds[1] >> 1)
force_split[1 + m] = 1;
}
if (is_small_sb) force_split[0] = 1;
}
if (!force_split[0]) {
fill_variance_tree(vt, BLOCK_128X128);
get_variance(&vt->part_variances.none);
if (!is_key_frame &&
(max_var_64x64 - min_var_64x64) > 3 * (thresholds[0] >> 3) &&
max_var_64x64 > thresholds[0] >> 1)
force_split[0] = 1;
}
if (mi_col + 32 > tile->mi_col_end || mi_row + 32 > tile->mi_row_end ||
!set_vt_partitioning(cpi, x, xd, tile, vt, BLOCK_128X128, mi_row, mi_col,
thresholds[0], BLOCK_16X16, force_split[0])) {
for (m = 0; m < num_64x64_blocks; ++m) {
const int x64_idx = ((m & 1) << 4);
const int y64_idx = ((m >> 1) << 4);
const int m2 = m << 2;
// Now go through the entire structure, splitting every block size until
// we get to one that's got a variance lower than our threshold.
if (!set_vt_partitioning(cpi, x, xd, tile, &vt->split[m], BLOCK_64X64,
mi_row + y64_idx, mi_col + x64_idx,
thresholds[1], BLOCK_16X16,
force_split[1 + m])) {
for (i = 0; i < 4; ++i) {
const int x32_idx = ((i & 1) << 3);
const int y32_idx = ((i >> 1) << 3);
const int i2 = (m2 + i) << 2;
if (!set_vt_partitioning(cpi, x, xd, tile, &vt->split[m].split[i],
BLOCK_32X32, (mi_row + y64_idx + y32_idx),
(mi_col + x64_idx + x32_idx), thresholds[2],
BLOCK_16X16, force_split[5 + m2 + i])) {
for (j = 0; j < 4; ++j) {
const int x16_idx = ((j & 1) << 2);
const int y16_idx = ((j >> 1) << 2);
const int split_index = 21 + i2 + j;
// For inter frames: if variance4x4downsample[] == 1 for this
// 16x16 block, then the variance is based on 4x4 down-sampling,
// so use vt2 in set_vt_partioning(), otherwise use vt.
v16x16 *vtemp =
(!is_key_frame && variance4x4downsample[i2 + j] == 1)
? &vt2[i2 + j]
: &vt->split[m].split[i].split[j];
if (!set_vt_partitioning(cpi, x, xd, tile, vtemp, BLOCK_16X16,
mi_row + y64_idx + y32_idx + y16_idx,
mi_col + x64_idx + x32_idx + x16_idx,
thresholds[3], BLOCK_8X8,
force_split[split_index])) {
for (k = 0; k < 4; ++k) {
const int x8_idx = (k & 1) << 1;
const int y8_idx = (k >> 1) << 1;
set_block_size(
cpi, x, xd,
(mi_row + y64_idx + y32_idx + y16_idx + y8_idx),
(mi_col + x64_idx + x32_idx + x16_idx + x8_idx),
BLOCK_8X8);
}
}
}
}
}
}
}
}
if (vt2) aom_free(vt2);
if (vt) aom_free(vt);
return 0;
}