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Merge "Use bigdia search with pruned subpel search"

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This commit is contained in:
Deb Mukherjee 2014-09-12 16:42:18 -07:00 committed by Gerrit Code Review
commit c0dfecfb89
2 changed files with 317 additions and 19 deletions
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334
vp9/encoder/vp9_mcomp.c
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@ -319,25 +319,25 @@ int vp9_find_best_sub_pixel_tree_pruned(const MACROBLOCK *x,
(sad_list[2] < sad_list[4] ? 0 : 2);
switch (whichdir) {
case 0:
CHECK_BETTER(left, tr, tc - hstep);
CHECK_BETTER(up, tr - hstep, tc);
CHECK_BETTER(diag, tr - hstep, tc - hstep);
break;
case 1:
CHECK_BETTER(right, tr, tc + hstep);
CHECK_BETTER(up, tr - hstep, tc);
CHECK_BETTER(diag, tr - hstep, tc + hstep);
break;
case 2:
CHECK_BETTER(left, tr, tc - hstep);
CHECK_BETTER(down, tr + hstep, tc);
CHECK_BETTER(diag, tr + hstep, tc - hstep);
break;
case 3:
case 1:
CHECK_BETTER(right, tr, tc + hstep);
CHECK_BETTER(down, tr + hstep, tc);
CHECK_BETTER(diag, tr + hstep, tc + hstep);
break;
case 2:
CHECK_BETTER(left, tr, tc - hstep);
CHECK_BETTER(up, tr - hstep, tc);
CHECK_BETTER(diag, tr - hstep, tc - hstep);
break;
case 3:
CHECK_BETTER(right, tr, tc + hstep);
CHECK_BETTER(up, tr - hstep, tc);
CHECK_BETTER(diag, tr - hstep, tc + hstep);
break;
}
} else {
FIRST_LEVEL_CHECKS;
@ -648,11 +648,11 @@ static int vp9_pattern_search(const MACROBLOCK *x,
// Returns the one-away integer pel sad values around the best as follows:
// sad_list[0]: sad at the best integer pel
// sad_list[1]: sad at delta {0, -1} (left) from the best integer pel
// sad_list[2]: sad at delta {-1, 0} (top) from the best integer pel
// sad_list[2]: sad at delta { 1, 0} (bottom) from the best integer pel
// sad_list[3]: sad at delta { 0, 1} (right) from the best integer pel
// sad_list[4]: sad at delta { 1, 0} (bottom) from the best integer pel
// sad_list[4]: sad at delta {-1, 0} (top) from the best integer pel
if (sad_list) {
static const MV neighbors[4] = {{0, -1}, {-1, 0}, {0, 1}, {1, 0}};
static const MV neighbors[4] = {{0, -1}, {1, 0}, {0, 1}, {-1, 0}};
sad_list[0] = bestsad;
if (check_bounds(x, br, bc, 1)) {
for (i = 0; i < 4; i++) {
@ -660,7 +660,10 @@ static int vp9_pattern_search(const MACROBLOCK *x,
bc + neighbors[i].col};
sad_list[i + 1] = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
in_what->stride) +
(use_mvcost ?
mvsad_err_cost(x, &this_mv, &fcenter_mv, sad_per_bit) :
0);
}
} else {
for (i = 0; i < 4; i++) {
@ -669,9 +672,302 @@ static int vp9_pattern_search(const MACROBLOCK *x,
if (!is_mv_in(x, &this_mv))
sad_list[i + 1] = INT_MAX;
else
sad_list[i + 1] = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride) +
(use_mvcost ?
mvsad_err_cost(x, &this_mv, &fcenter_mv, sad_per_bit) :
0);
}
}
}
best_mv->row = br;
best_mv->col = bc;
return bestsad;
}
// A specialized function where the smallest scale search candidates
// are 4 1-away neighbors, and sad_list is non-null
// TODO(debargha): Merge this function with the one above. Also remove
// use_mvcost option since it is always 1, to save unnecessary branches.
static int vp9_pattern_search_sad(const MACROBLOCK *x,
MV *ref_mv,
int search_param,
int sad_per_bit,
int do_init_search,
int *sad_list,
const vp9_variance_fn_ptr_t *vfp,
int use_mvcost,
const MV *center_mv,
MV *best_mv,
const int num_candidates[MAX_PATTERN_SCALES],
const MV candidates[MAX_PATTERN_SCALES]
[MAX_PATTERN_CANDIDATES]) {
const MACROBLOCKD *const xd = &x->e_mbd;
static const int search_param_to_steps[MAX_MVSEARCH_STEPS] = {
10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0,
};
int i, s, t;
const struct buf_2d *const what = &x->plane[0].src;
const struct buf_2d *const in_what = &xd->plane[0].pre[0];
int br, bc;
int bestsad = INT_MAX;
int thissad;
int k = -1;
const MV fcenter_mv = {center_mv->row >> 3, center_mv->col >> 3};
int best_init_s = search_param_to_steps[search_param];
// adjust ref_mv to make sure it is within MV range
clamp_mv(ref_mv, x->mv_col_min, x->mv_col_max, x->mv_row_min, x->mv_row_max);
br = ref_mv->row;
bc = ref_mv->col;
if (sad_list != NULL) {
sad_list[0] = sad_list[1] = sad_list[2] = sad_list[3] = sad_list[4] =
INT_MAX;
}
// Work out the start point for the search
bestsad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, ref_mv), in_what->stride) +
mvsad_err_cost(x, ref_mv, &fcenter_mv, sad_per_bit);
// Search all possible scales upto the search param around the center point
// pick the scale of the point that is best as the starting scale of
// further steps around it.
if (do_init_search) {
s = best_init_s;
best_init_s = -1;
for (t = 0; t <= s; ++t) {
int best_site = -1;
if (check_bounds(x, br, bc, 1 << t)) {
for (i = 0; i < num_candidates[t]; i++) {
const MV this_mv = {br + candidates[t][i].row,
bc + candidates[t][i].col};
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
} else {
for (i = 0; i < num_candidates[t]; i++) {
const MV this_mv = {br + candidates[t][i].row,
bc + candidates[t][i].col};
if (!is_mv_in(x, &this_mv))
continue;
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
}
if (best_site == -1) {
continue;
} else {
best_init_s = t;
k = best_site;
}
}
if (best_init_s != -1) {
br += candidates[best_init_s][k].row;
bc += candidates[best_init_s][k].col;
}
}
// If the center point is still the best, just skip this and move to
// the refinement step.
if (best_init_s != -1) {
int do_sad = (num_candidates[0] == 4 && sad_list != NULL);
int best_site = -1;
s = best_init_s;
for (; s >= do_sad; s--) {
if (!do_init_search || s != best_init_s) {
if (check_bounds(x, br, bc, 1 << s)) {
for (i = 0; i < num_candidates[s]; i++) {
const MV this_mv = {br + candidates[s][i].row,
bc + candidates[s][i].col};
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
} else {
for (i = 0; i < num_candidates[s]; i++) {
const MV this_mv = {br + candidates[s][i].row,
bc + candidates[s][i].col};
if (!is_mv_in(x, &this_mv))
continue;
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
}
if (best_site == -1) {
continue;
} else {
br += candidates[s][best_site].row;
bc += candidates[s][best_site].col;
k = best_site;
}
}
do {
int next_chkpts_indices[PATTERN_CANDIDATES_REF];
best_site = -1;
next_chkpts_indices[0] = (k == 0) ? num_candidates[s] - 1 : k - 1;
next_chkpts_indices[1] = k;
next_chkpts_indices[2] = (k == num_candidates[s] - 1) ? 0 : k + 1;
if (check_bounds(x, br, bc, 1 << s)) {
for (i = 0; i < PATTERN_CANDIDATES_REF; i++) {
const MV this_mv = {br + candidates[s][next_chkpts_indices[i]].row,
bc + candidates[s][next_chkpts_indices[i]].col};
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
} else {
for (i = 0; i < PATTERN_CANDIDATES_REF; i++) {
const MV this_mv = {br + candidates[s][next_chkpts_indices[i]].row,
bc + candidates[s][next_chkpts_indices[i]].col};
if (!is_mv_in(x, &this_mv))
continue;
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
}
if (best_site != -1) {
k = next_chkpts_indices[best_site];
br += candidates[s][k].row;
bc += candidates[s][k].col;
}
} while (best_site != -1);
}
// Note: If we enter the if below, then sad_list must be non-NULL.
if (s == 0) {
sad_list[0] = bestsad;
if (!do_init_search || s != best_init_s) {
if (check_bounds(x, br, bc, 1 << s)) {
for (i = 0; i < num_candidates[s]; i++) {
const MV this_mv = {br + candidates[s][i].row,
bc + candidates[s][i].col};
sad_list[i + 1] =
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
} else {
for (i = 0; i < num_candidates[s]; i++) {
const MV this_mv = {br + candidates[s][i].row,
bc + candidates[s][i].col};
if (!is_mv_in(x, &this_mv))
continue;
sad_list[i + 1] =
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
}
if (best_site != -1) {
br += candidates[s][best_site].row;
bc += candidates[s][best_site].col;
k = best_site;
}
}
while (best_site != -1) {
int next_chkpts_indices[PATTERN_CANDIDATES_REF];
best_site = -1;
next_chkpts_indices[0] = (k == 0) ? num_candidates[s] - 1 : k - 1;
next_chkpts_indices[1] = k;
next_chkpts_indices[2] = (k == num_candidates[s] - 1) ? 0 : k + 1;
sad_list[1] = sad_list[2] = sad_list[3] = sad_list[4] = INT_MAX;
sad_list[((k + 2) % 4) + 1] = sad_list[0];
sad_list[0] = bestsad;
if (check_bounds(x, br, bc, 1 << s)) {
for (i = 0; i < PATTERN_CANDIDATES_REF; i++) {
const MV this_mv = {br + candidates[s][next_chkpts_indices[i]].row,
bc + candidates[s][next_chkpts_indices[i]].col};
sad_list[next_chkpts_indices[i] + 1] =
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
} else {
for (i = 0; i < PATTERN_CANDIDATES_REF; i++) {
const MV this_mv = {br + candidates[s][next_chkpts_indices[i]].row,
bc + candidates[s][next_chkpts_indices[i]].col};
if (!is_mv_in(x, &this_mv)) {
sad_list[next_chkpts_indices[i] + 1] = INT_MAX;
continue;
}
sad_list[next_chkpts_indices[i] + 1] =
thissad = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
CHECK_BETTER
}
}
if (best_site != -1) {
k = next_chkpts_indices[best_site];
br += candidates[s][k].row;
bc += candidates[s][k].col;
}
}
}
}
// Returns the one-away integer pel sad values around the best as follows:
// sad_list[0]: sad at the best integer pel
// sad_list[1]: sad at delta {0, -1} (left) from the best integer pel
// sad_list[2]: sad at delta { 1, 0} (bottom) from the best integer pel
// sad_list[3]: sad at delta { 0, 1} (right) from the best integer pel
// sad_list[4]: sad at delta {-1, 0} (top) from the best integer pel
if (sad_list) {
static const MV neighbors[4] = {{0, -1}, {1, 0}, {0, 1}, {-1, 0}};
if (sad_list[0] == INT_MAX) {
sad_list[0] = bestsad;
if (check_bounds(x, br, bc, 1)) {
for (i = 0; i < 4; i++) {
const MV this_mv = {br + neighbors[i].row,
bc + neighbors[i].col};
sad_list[i + 1] = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
}
} else {
for (i = 0; i < 4; i++) {
const MV this_mv = {br + neighbors[i].row,
bc + neighbors[i].col};
if (!is_mv_in(x, &this_mv))
sad_list[i + 1] = INT_MAX;
else
sad_list[i + 1] = vfp->sdf(what->buf, what->stride,
get_buf_from_mv(in_what, &this_mv),
in_what->stride);
}
}
} else {
if (use_mvcost) {
for (i = 0; i < 4; i++) {
const MV this_mv = {br + neighbors[i].row,
bc + neighbors[i].col};
if (sad_list[i + 1] != INT_MAX) {
sad_list[i + 1] +=
mvsad_err_cost(x, &this_mv, &fcenter_mv, sad_per_bit);
}
}
}
}
}
@ -784,10 +1080,10 @@ int vp9_bigdia_search(const MACROBLOCK *x,
{{-512, -512}, {0, -1024}, {512, -512}, {1024, 0}, {512, 512}, {0, 1024},
{-512, 512}, {-1024, 0}},
};
return vp9_pattern_search(x, ref_mv, search_param, sad_per_bit,
do_init_search, sad_list, vfp, use_mvcost,
center_mv, best_mv,
bigdia_num_candidates, bigdia_candidates);
return vp9_pattern_search_sad(x, ref_mv, search_param, sad_per_bit,
do_init_search, sad_list, vfp, use_mvcost,
center_mv, best_mv,
bigdia_num_candidates, bigdia_candidates);
}
int vp9_square_search(const MACROBLOCK *x,

2
vp9/encoder/vp9_speed_features.c
View File

@ -123,6 +123,8 @@ static void set_good_speed_feature(VP9_COMP *cpi, VP9_COMMON *cm,
sf->use_square_partition_only = 1;
sf->tx_size_search_method = USE_LARGESTALL;
sf->disable_split_mask = DISABLE_ALL_SPLIT;
sf->mv.search_method = BIGDIA;
sf->mv.subpel_search_method = SUBPEL_TREE_PRUNED;
sf->adaptive_rd_thresh = 4;
sf->mode_search_skip_flags |= FLAG_SKIP_COMP_REFMISMATCH |
FLAG_EARLY_TERMINATE;