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/*
* Copyright (c) 2016, 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 <math.h>
#include <stdlib.h>
#include "av1/common/pred_common.h"
#include "av1/encoder/block.h"
#include "av1/encoder/cost.h"
#include "av1/encoder/encoder.h"
#include "av1/encoder/intra_mode_search.h"
#include "av1/encoder/intra_mode_search_utils.h"
#include "av1/encoder/palette.h"
#include "av1/encoder/random.h"
#include "av1/encoder/rdopt_utils.h"
#include "av1/encoder/tx_search.h"
#define AV1_K_MEANS_DIM 1
#include "av1/encoder/k_means_template.h"
#undef AV1_K_MEANS_DIM
#define AV1_K_MEANS_DIM 2
#include "av1/encoder/k_means_template.h"
#undef AV1_K_MEANS_DIM
static int int16_comparer(const void *a, const void *b) {
return (*(int16_t *)a - *(int16_t *)b);
}
/*!\brief Removes duplicated centroid indices.
*
* \ingroup palette_mode_search
* \param[in] centroids A list of centroids index.
* \param[in] num_centroids Number of centroids.
*
* \return Returns the number of unique centroids and saves the unique centroids
* in beginning of the centroids array.
*
* \attention The centroids should be rounded to integers before calling this
* method.
*/
static int remove_duplicates(int16_t *centroids, int num_centroids) {
int num_unique; // number of unique centroids
int i;
qsort(centroids, num_centroids, sizeof(*centroids), int16_comparer);
// Remove duplicates.
num_unique = 1;
for (i = 1; i < num_centroids; ++i) {
if (centroids[i] != centroids[i - 1]) { // found a new unique centroid
centroids[num_unique++] = centroids[i];
}
}
return num_unique;
}
static int delta_encode_cost(const int *colors, int num, int bit_depth,
int min_val) {
if (num <= 0) return 0;
int bits_cost = bit_depth;
if (num == 1) return bits_cost;
bits_cost += 2;
int max_delta = 0;
int deltas[PALETTE_MAX_SIZE];
const int min_bits = bit_depth - 3;
for (int i = 1; i < num; ++i) {
const int delta = colors[i] - colors[i - 1];
deltas[i - 1] = delta;
assert(delta >= min_val);
if (delta > max_delta) max_delta = delta;
}
int bits_per_delta = AOMMAX(av1_ceil_log2(max_delta + 1 - min_val), min_bits);
assert(bits_per_delta <= bit_depth);
int range = (1 << bit_depth) - colors[0] - min_val;
for (int i = 0; i < num - 1; ++i) {
bits_cost += bits_per_delta;
range -= deltas[i];
bits_per_delta = AOMMIN(bits_per_delta, av1_ceil_log2(range));
}
return bits_cost;
}
int av1_index_color_cache(const uint16_t *color_cache, int n_cache,
const uint16_t *colors, int n_colors,
uint8_t *cache_color_found, int *out_cache_colors) {
if (n_cache <= 0) {
for (int i = 0; i < n_colors; ++i) out_cache_colors[i] = colors[i];
return n_colors;
}
memset(cache_color_found, 0, n_cache * sizeof(*cache_color_found));
int n_in_cache = 0;
int in_cache_flags[PALETTE_MAX_SIZE];
memset(in_cache_flags, 0, sizeof(in_cache_flags));
for (int i = 0; i < n_cache && n_in_cache < n_colors; ++i) {
for (int j = 0; j < n_colors; ++j) {
if (colors[j] == color_cache[i]) {
in_cache_flags[j] = 1;
cache_color_found[i] = 1;
++n_in_cache;
break;
}
}
}
int j = 0;
for (int i = 0; i < n_colors; ++i)
if (!in_cache_flags[i]) out_cache_colors[j++] = colors[i];
assert(j == n_colors - n_in_cache);
return j;
}
int av1_get_palette_delta_bits_v(const PALETTE_MODE_INFO *const pmi,
int bit_depth, int *zero_count,
int *min_bits) {
const int n = pmi->palette_size[1];
const int max_val = 1 << bit_depth;
int max_d = 0;
*min_bits = bit_depth - 4;
*zero_count = 0;
for (int i = 1; i < n; ++i) {
const int delta = pmi->palette_colors[2 * PALETTE_MAX_SIZE + i] -
pmi->palette_colors[2 * PALETTE_MAX_SIZE + i - 1];
const int v = abs(delta);
const int d = AOMMIN(v, max_val - v);
if (d > max_d) max_d = d;
if (d == 0) ++(*zero_count);
}
return AOMMAX(av1_ceil_log2(max_d + 1), *min_bits);
}
int av1_palette_color_cost_y(const PALETTE_MODE_INFO *const pmi,
const uint16_t *color_cache, int n_cache,
int bit_depth) {
const int n = pmi->palette_size[0];
int out_cache_colors[PALETTE_MAX_SIZE];
uint8_t cache_color_found[2 * PALETTE_MAX_SIZE];
const int n_out_cache =
av1_index_color_cache(color_cache, n_cache, pmi->palette_colors, n,
cache_color_found, out_cache_colors);
const int total_bits =
n_cache + delta_encode_cost(out_cache_colors, n_out_cache, bit_depth, 1);
return av1_cost_literal(total_bits);
}
int av1_palette_color_cost_uv(const PALETTE_MODE_INFO *const pmi,
const uint16_t *color_cache, int n_cache,
int bit_depth) {
const int n = pmi->palette_size[1];
int total_bits = 0;
// U channel palette color cost.
int out_cache_colors[PALETTE_MAX_SIZE];
uint8_t cache_color_found[2 * PALETTE_MAX_SIZE];
const int n_out_cache = av1_index_color_cache(
color_cache, n_cache, pmi->palette_colors + PALETTE_MAX_SIZE, n,
cache_color_found, out_cache_colors);
total_bits +=
n_cache + delta_encode_cost(out_cache_colors, n_out_cache, bit_depth, 0);
// V channel palette color cost.
int zero_count = 0, min_bits_v = 0;
const int bits_v =
av1_get_palette_delta_bits_v(pmi, bit_depth, &zero_count, &min_bits_v);
const int bits_using_delta =
2 + bit_depth + (bits_v + 1) * (n - 1) - zero_count;
const int bits_using_raw = bit_depth * n;
total_bits += 1 + AOMMIN(bits_using_delta, bits_using_raw);
return av1_cost_literal(total_bits);
}
// Extends 'color_map' array from 'orig_width x orig_height' to 'new_width x
// new_height'. Extra rows and columns are filled in by copying last valid
// row/column.
static inline void extend_palette_color_map(uint8_t *const color_map,
int orig_width, int orig_height,
int new_width, int new_height) {
int j;
assert(new_width >= orig_width);
assert(new_height >= orig_height);
if (new_width == orig_width && new_height == orig_height) return;
for (j = orig_height - 1; j >= 0; --j) {
memmove(color_map + j * new_width, color_map + j * orig_width, orig_width);
// Copy last column to extra columns.
memset(color_map + j * new_width + orig_width,
color_map[j * new_width + orig_width - 1], new_width - orig_width);
}
// Copy last row to extra rows.
for (j = orig_height; j < new_height; ++j) {
memcpy(color_map + j * new_width, color_map + (orig_height - 1) * new_width,
new_width);
}
}
// Bias toward using colors in the cache.
// TODO(huisu): Try other schemes to improve compression.
static inline void optimize_palette_colors(uint16_t *color_cache, int n_cache,
int n_colors, int stride,
int16_t *centroids, int bit_depth) {
if (n_cache <= 0) return;
for (int i = 0; i < n_colors * stride; i += stride) {
int min_diff = abs((int)centroids[i] - (int)color_cache[0]);
int idx = 0;
for (int j = 1; j < n_cache; ++j) {
const int this_diff = abs((int)centroids[i] - (int)color_cache[j]);
if (this_diff < min_diff) {
min_diff = this_diff;
idx = j;
}
}
const int min_threshold = 4 << (bit_depth - 8);
if (min_diff <= min_threshold) centroids[i] = color_cache[idx];
}
}
/*!\brief Calculate the luma palette cost from a given color palette
*
* \ingroup palette_mode_search
* \callergraph
* Given the base colors as specified in centroids[], calculate the RD cost
* of palette mode.
*/
static inline void palette_rd_y(
const AV1_COMP *const cpi, MACROBLOCK *x, MB_MODE_INFO *mbmi,
BLOCK_SIZE bsize, int dc_mode_cost, const int16_t *data, int16_t *centroids,
int n, uint16_t *color_cache, int n_cache, bool do_header_rd_based_gating,
MB_MODE_INFO *best_mbmi, uint8_t *best_palette_color_map, int64_t *best_rd,
int *rate, int *rate_tokenonly, int64_t *distortion, uint8_t *skippable,
int *beat_best_rd, PICK_MODE_CONTEXT *ctx, uint8_t *blk_skip,
uint8_t *tx_type_map, int *beat_best_palette_rd,
bool *do_header_rd_based_breakout, int discount_color_cost) {
if (do_header_rd_based_breakout != NULL) *do_header_rd_based_breakout = false;
optimize_palette_colors(color_cache, n_cache, n, 1, centroids,
cpi->common.seq_params->bit_depth);
const int num_unique_colors = remove_duplicates(centroids, n);
if (num_unique_colors < PALETTE_MIN_SIZE) {
// Too few unique colors to create a palette. And DC_PRED will work
// well for that case anyway. So skip.
return;
}
PALETTE_MODE_INFO *const pmi = &mbmi->palette_mode_info;
if (cpi->common.seq_params->use_highbitdepth) {
for (int i = 0; i < num_unique_colors; ++i) {
pmi->palette_colors[i] = clip_pixel_highbd(
(int)centroids[i], cpi->common.seq_params->bit_depth);
}
} else {
for (int i = 0; i < num_unique_colors; ++i) {
pmi->palette_colors[i] = clip_pixel(centroids[i]);
}
}
pmi->palette_size[0] = num_unique_colors;
MACROBLOCKD *const xd = &x->e_mbd;
uint8_t *const color_map = xd->plane[0].color_index_map;
int block_width, block_height, rows, cols;
av1_get_block_dimensions(bsize, 0, xd, &block_width, &block_height, &rows,
&cols);
av1_calc_indices(data, centroids, color_map, rows * cols, num_unique_colors,
1);
extend_palette_color_map(color_map, cols, rows, block_width, block_height);
RD_STATS tokenonly_rd_stats;
int this_rate;
if (do_header_rd_based_gating) {
assert(do_header_rd_based_breakout != NULL);
const int palette_mode_rate = intra_mode_info_cost_y(
cpi, x, mbmi, bsize, dc_mode_cost, discount_color_cost);
const int64_t header_rd = RDCOST(x->rdmult, palette_mode_rate, 0);
// Less aggressive pruning when prune_luma_palette_size_search_level == 1.
const int header_rd_shift =
(cpi->sf.intra_sf.prune_luma_palette_size_search_level == 1) ? 1 : 0;
// Terminate further palette_size search, if the header cost corresponding
// to lower palette_size is more than *best_rd << header_rd_shift. This
// logic is implemented with a right shift in the LHS to prevent a possible
// overflow with the left shift in RHS.
if ((header_rd >> header_rd_shift) > *best_rd) {
*do_header_rd_based_breakout = true;
return;
}
av1_pick_uniform_tx_size_type_yrd(cpi, x, &tokenonly_rd_stats, bsize,
*best_rd);
if (tokenonly_rd_stats.rate == INT_MAX) return;
this_rate = tokenonly_rd_stats.rate + palette_mode_rate;
} else {
av1_pick_uniform_tx_size_type_yrd(cpi, x, &tokenonly_rd_stats, bsize,
*best_rd);
if (tokenonly_rd_stats.rate == INT_MAX) return;
this_rate = tokenonly_rd_stats.rate +
intra_mode_info_cost_y(cpi, x, mbmi, bsize, dc_mode_cost,
discount_color_cost);
}
int64_t this_rd = RDCOST(x->rdmult, this_rate, tokenonly_rd_stats.dist);
if (!xd->lossless[mbmi->segment_id] && block_signals_txsize(mbmi->bsize)) {
tokenonly_rd_stats.rate -= tx_size_cost(x, bsize, mbmi->tx_size);
}
// Collect mode stats for multiwinner mode processing
const int txfm_search_done = 1;
store_winner_mode_stats(
&cpi->common, x, mbmi, NULL, NULL, NULL, THR_DC, color_map, bsize,
this_rd, cpi->sf.winner_mode_sf.multi_winner_mode_type, txfm_search_done);
if (this_rd < *best_rd) {
*best_rd = this_rd;
// Setting beat_best_rd flag because current mode rd is better than best_rd.
// This flag need to be updated only for palette evaluation in key frames
if (beat_best_rd) *beat_best_rd = 1;
memcpy(best_palette_color_map, color_map,
block_width * block_height * sizeof(color_map[0]));
*best_mbmi = *mbmi;
memcpy(blk_skip, x->txfm_search_info.blk_skip,
sizeof(x->txfm_search_info.blk_skip[0]) * ctx->num_4x4_blk);
av1_copy_array(tx_type_map, xd->tx_type_map, ctx->num_4x4_blk);
if (rate) *rate = this_rate;
if (rate_tokenonly) *rate_tokenonly = tokenonly_rd_stats.rate;
if (distortion) *distortion = tokenonly_rd_stats.dist;
if (skippable) *skippable = tokenonly_rd_stats.skip_txfm;
if (beat_best_palette_rd) *beat_best_palette_rd = 1;
}
}
static inline int is_iter_over(int curr_idx, int end_idx, int step_size) {
assert(step_size != 0);
return (step_size > 0) ? curr_idx >= end_idx : curr_idx <= end_idx;
}
// Performs count-based palette search with number of colors in interval
// [start_n, end_n) with step size step_size. If step_size < 0, then end_n can
// be less than start_n. Saves the last numbers searched in last_n_searched and
// returns the best number of colors found.
static inline int perform_top_color_palette_search(
const AV1_COMP *const cpi, MACROBLOCK *x, MB_MODE_INFO *mbmi,
BLOCK_SIZE bsize, int dc_mode_cost, const int16_t *data,
int16_t *top_colors, int start_n, int end_n, int step_size,
bool do_header_rd_based_gating, int *last_n_searched, uint16_t *color_cache,
int n_cache, MB_MODE_INFO *best_mbmi, uint8_t *best_palette_color_map,
int64_t *best_rd, int *rate, int *rate_tokenonly, int64_t *distortion,
uint8_t *skippable, int *beat_best_rd, PICK_MODE_CONTEXT *ctx,
uint8_t *best_blk_skip, uint8_t *tx_type_map, int discount_color_cost) {
int16_t centroids[PALETTE_MAX_SIZE];
int n = start_n;
int top_color_winner = end_n;
/* clang-format off */
assert(IMPLIES(step_size < 0, start_n > end_n));
/* clang-format on */
assert(IMPLIES(step_size > 0, start_n < end_n));
while (!is_iter_over(n, end_n, step_size)) {
int beat_best_palette_rd = 0;
bool do_header_rd_based_breakout = false;
memcpy(centroids, top_colors, n * sizeof(top_colors[0]));
palette_rd_y(cpi, x, mbmi, bsize, dc_mode_cost, data, centroids, n,
color_cache, n_cache, do_header_rd_based_gating, best_mbmi,
best_palette_color_map, best_rd, rate, rate_tokenonly,
distortion, skippable, beat_best_rd, ctx, best_blk_skip,
tx_type_map, &beat_best_palette_rd,
&do_header_rd_based_breakout, discount_color_cost);
*last_n_searched = n;
if (do_header_rd_based_breakout) {
// Terminate palette_size search by setting last_n_searched to end_n.
*last_n_searched = end_n;
break;
}
if (beat_best_palette_rd) {
top_color_winner = n;
} else if (cpi->sf.intra_sf.prune_palette_search_level == 2) {
// At search level 2, we return immediately if we don't see an improvement
return top_color_winner;
}
n += step_size;
}
return top_color_winner;
}
// Performs k-means based palette search with number of colors in interval
// [start_n, end_n) with step size step_size. If step_size < 0, then end_n can
// be less than start_n. Saves the last numbers searched in last_n_searched and
// returns the best number of colors found.
static inline int perform_k_means_palette_search(
const AV1_COMP *const cpi, MACROBLOCK *x, MB_MODE_INFO *mbmi,
BLOCK_SIZE bsize, int dc_mode_cost, const int16_t *data, int lower_bound,
int upper_bound, int start_n, int end_n, int step_size,
bool do_header_rd_based_gating, int *last_n_searched, uint16_t *color_cache,
int n_cache, MB_MODE_INFO *best_mbmi, uint8_t *best_palette_color_map,
int64_t *best_rd, int *rate, int *rate_tokenonly, int64_t *distortion,
uint8_t *skippable, int *beat_best_rd, PICK_MODE_CONTEXT *ctx,
uint8_t *best_blk_skip, uint8_t *tx_type_map, uint8_t *color_map,
int data_points, int discount_color_cost) {
int16_t centroids[PALETTE_MAX_SIZE];
const int max_itr = 50;
int n = start_n;
int top_color_winner = end_n;
/* clang-format off */
assert(IMPLIES(step_size < 0, start_n > end_n));
/* clang-format on */
assert(IMPLIES(step_size > 0, start_n < end_n));
while (!is_iter_over(n, end_n, step_size)) {
int beat_best_palette_rd = 0;
bool do_header_rd_based_breakout = false;
for (int i = 0; i < n; ++i) {
centroids[i] =
lower_bound + (2 * i + 1) * (upper_bound - lower_bound) / n / 2;
}
av1_k_means(data, centroids, color_map, data_points, n, 1, max_itr);
palette_rd_y(cpi, x, mbmi, bsize, dc_mode_cost, data, centroids, n,
color_cache, n_cache, do_header_rd_based_gating, best_mbmi,
best_palette_color_map, best_rd, rate, rate_tokenonly,
distortion, skippable, beat_best_rd, ctx, best_blk_skip,
tx_type_map, &beat_best_palette_rd,
&do_header_rd_based_breakout, discount_color_cost);
*last_n_searched = n;
if (do_header_rd_based_breakout) {
// Terminate palette_size search by setting last_n_searched to end_n.
*last_n_searched = end_n;
break;
}
if (beat_best_palette_rd) {
top_color_winner = n;
} else if (cpi->sf.intra_sf.prune_palette_search_level == 2) {
// At search level 2, we return immediately if we don't see an improvement
return top_color_winner;
}
n += step_size;
}
return top_color_winner;
}
// Sets the parameters to search the current number of colors +- 1
static inline void set_stage2_params(int *min_n, int *max_n, int *step_size,
int winner, int end_n) {
// Set min to winner - 1 unless we are already at the border, then we set it
// to winner + 1
*min_n = (winner == PALETTE_MIN_SIZE) ? (PALETTE_MIN_SIZE + 1)
: AOMMAX(winner - 1, PALETTE_MIN_SIZE);
// Set max to winner + 1 unless we are already at the border, then we set it
// to winner - 1
*max_n =
(winner == end_n) ? (winner - 1) : AOMMIN(winner + 1, PALETTE_MAX_SIZE);
// Set the step size to max_n - min_n so we only search those two values.
// If max_n == min_n, then set step_size to 1 to avoid infinite loop later.
*step_size = AOMMAX(1, *max_n - *min_n);
}
static inline void fill_data_and_get_bounds(const uint8_t *src,
const int src_stride,
const int rows, const int cols,
const int is_high_bitdepth,
int16_t *data, int *lower_bound,
int *upper_bound) {
if (is_high_bitdepth) {
const uint16_t *src_ptr = CONVERT_TO_SHORTPTR(src);
*lower_bound = *upper_bound = src_ptr[0];
for (int r = 0; r < rows; ++r) {
for (int c = 0; c < cols; ++c) {
const int val = src_ptr[c];
data[c] = (int16_t)val;
*lower_bound = AOMMIN(*lower_bound, val);
*upper_bound = AOMMAX(*upper_bound, val);
}
src_ptr += src_stride;
data += cols;
}
return;
}
// low bit depth
*lower_bound = *upper_bound = src[0];
for (int r = 0; r < rows; ++r) {
for (int c = 0; c < cols; ++c) {
const int val = src[c];
data[c] = (int16_t)val;
*lower_bound = AOMMIN(*lower_bound, val);
*upper_bound = AOMMAX(*upper_bound, val);
}
src += src_stride;
data += cols;
}
}
/*! \brief Colors are sorted by their count: the higher the better.
*/
struct ColorCount {
//! Color index in the histogram.
int index;
//! Histogram count.
int count;
};
static int color_count_comp(const void *c1, const void *c2) {
const struct ColorCount *color_count1 = (const struct ColorCount *)c1;
const struct ColorCount *color_count2 = (const struct ColorCount *)c2;
if (color_count1->count > color_count2->count) return -1;
if (color_count1->count < color_count2->count) return 1;
if (color_count1->index < color_count2->index) return -1;
return 1;
}
static void find_top_colors(const int *const count_buf, int bit_depth,
int n_colors, int16_t *top_colors) {
// Top color array, serving as a priority queue if more than n_colors are
// found.
struct ColorCount top_color_counts[PALETTE_MAX_SIZE] = { { 0 } };
int n_color_count = 0;
for (int i = 0; i < (1 << bit_depth); ++i) {
if (count_buf[i] > 0) {
if (n_color_count < n_colors) {
// Keep adding to the top colors.
top_color_counts[n_color_count].index = i;
top_color_counts[n_color_count].count = count_buf[i];
++n_color_count;
if (n_color_count == n_colors) {
qsort(top_color_counts, n_colors, sizeof(top_color_counts[0]),
color_count_comp);
}
} else {
// Check the worst in the sorted top.
if (count_buf[i] > top_color_counts[n_colors - 1].count) {
int j = n_colors - 1;
// Move up to the best one.
while (j >= 1 && count_buf[i] > top_color_counts[j - 1].count) --j;
memmove(top_color_counts + j + 1, top_color_counts + j,
(n_colors - j - 1) * sizeof(top_color_counts[0]));
top_color_counts[j].index = i;
top_color_counts[j].count = count_buf[i];
}
}
}
}
assert(n_color_count == n_colors);
for (int i = 0; i < n_colors; ++i) {
top_colors[i] = top_color_counts[i].index;
}
}
void av1_rd_pick_palette_intra_sby(
const AV1_COMP *cpi, MACROBLOCK *x, BLOCK_SIZE bsize, int dc_mode_cost,
MB_MODE_INFO *best_mbmi, uint8_t *best_palette_color_map, int64_t *best_rd,
int *rate, int *rate_tokenonly, int64_t *distortion, uint8_t *skippable,
int *beat_best_rd, PICK_MODE_CONTEXT *ctx, uint8_t *best_blk_skip,
uint8_t *tx_type_map) {
MACROBLOCKD *const xd = &x->e_mbd;
MB_MODE_INFO *const mbmi = xd->mi[0];
assert(!is_inter_block(mbmi));
assert(av1_allow_palette(cpi->common.features.allow_screen_content_tools,
bsize));
assert(PALETTE_MAX_SIZE == 8);
assert(PALETTE_MIN_SIZE == 2);
const int src_stride = x->plane[0].src.stride;
const uint8_t *const src = x->plane[0].src.buf;
int block_width, block_height, rows, cols;
av1_get_block_dimensions(bsize, 0, xd, &block_width, &block_height, &rows,
&cols);
const SequenceHeader *const seq_params = cpi->common.seq_params;
const int is_hbd = seq_params->use_highbitdepth;
const int bit_depth = seq_params->bit_depth;
const int discount_color_cost = cpi->sf.rt_sf.use_nonrd_pick_mode;
int unused;
int count_buf[1 << 12]; // Maximum (1 << 12) color levels.
int colors, colors_threshold = 0;
if (is_hbd) {
int count_buf_8bit[1 << 8]; // Maximum (1 << 8) bins for hbd path.
av1_count_colors_highbd(src, src_stride, rows, cols, bit_depth, count_buf,
count_buf_8bit, &colors_threshold, &colors);
} else {
av1_count_colors(src, src_stride, rows, cols, count_buf, &colors);
colors_threshold = colors;
}
uint8_t *const color_map = xd->plane[0].color_index_map;
int color_thresh_palette = x->color_palette_thresh;
// Allow for larger color_threshold for palette search, based on color,
// scene_change, and block source variance.
// Since palette is Y based, only allow larger threshold if block
// color_dist is below threshold.
if (cpi->sf.rt_sf.use_nonrd_pick_mode &&
cpi->sf.rt_sf.increase_color_thresh_palette && cpi->rc.high_source_sad &&
x->source_variance > 50) {
int64_t norm_color_dist = 0;
if (x->color_sensitivity[0] || x->color_sensitivity[1]) {
norm_color_dist = x->min_dist_inter_uv >>
(mi_size_wide_log2[bsize] + mi_size_high_log2[bsize]);
if (x->color_sensitivity[0] && x->color_sensitivity[1])
norm_color_dist = norm_color_dist >> 1;
}
if (norm_color_dist < 8000) color_thresh_palette += 20;
}
if (colors_threshold > 1 && colors_threshold <= color_thresh_palette) {
int16_t *const data = x->palette_buffer->kmeans_data_buf;
int16_t centroids[PALETTE_MAX_SIZE];
int lower_bound, upper_bound;
fill_data_and_get_bounds(src, src_stride, rows, cols, is_hbd, data,
&lower_bound, &upper_bound);
mbmi->mode = DC_PRED;
mbmi->filter_intra_mode_info.use_filter_intra = 0;
uint16_t color_cache[2 * PALETTE_MAX_SIZE];
const int n_cache = av1_get_palette_cache(xd, 0, color_cache);
// Find the dominant colors, stored in top_colors[].
int16_t top_colors[PALETTE_MAX_SIZE] = { 0 };
find_top_colors(count_buf, bit_depth, AOMMIN(colors, PALETTE_MAX_SIZE),
top_colors);
// The following are the approaches used for header rdcost based gating
// for early termination for different values of prune_palette_search_level.
// 0: Pruning based on header rdcost for ascending order palette_size
// search.
// 1: When colors > PALETTE_MIN_SIZE, enabled only for coarse palette_size
// search and for finer search do_header_rd_based_gating parameter is
// explicitly passed as 'false'.
// 2: Enabled only for ascending order palette_size search and for
// descending order search do_header_rd_based_gating parameter is explicitly
// passed as 'false'.
const bool do_header_rd_based_gating =
cpi->sf.intra_sf.prune_luma_palette_size_search_level != 0;
// TODO(huisu@google.com): Try to avoid duplicate computation in cases
// where the dominant colors and the k-means results are similar.
if ((cpi->sf.intra_sf.prune_palette_search_level == 1) &&
(colors > PALETTE_MIN_SIZE)) {
// Start index and step size below are chosen to evaluate unique
// candidates in neighbor search, in case a winner candidate is found in
// coarse search. Example,
// 1) 8 colors (end_n = 8): 2,3,4,5,6,7,8. start_n is chosen as 2 and step
// size is chosen as 3. Therefore, coarse search will evaluate 2, 5 and 8.
// If winner is found at 5, then 4 and 6 are evaluated. Similarly, for 2
// (3) and 8 (7).
// 2) 7 colors (end_n = 7): 2,3,4,5,6,7. If start_n is chosen as 2 (same
// as for 8 colors) then step size should also be 2, to cover all
// candidates. Coarse search will evaluate 2, 4 and 6. If winner is either
// 2 or 4, 3 will be evaluated. Instead, if start_n=3 and step_size=3,
// coarse search will evaluate 3 and 6. For the winner, unique neighbors
// (3: 2,4 or 6: 5,7) would be evaluated.
// Start index for coarse palette search for dominant colors and k-means
const uint8_t start_n_lookup_table[PALETTE_MAX_SIZE + 1] = { 0, 0, 0,
3, 3, 2,
3, 3, 2 };
// Step size for coarse palette search for dominant colors and k-means
const uint8_t step_size_lookup_table[PALETTE_MAX_SIZE + 1] = { 0, 0, 0,
3, 3, 3,
3, 3, 3 };
// Choose the start index and step size for coarse search based on number
// of colors
const int max_n = AOMMIN(colors, PALETTE_MAX_SIZE);
const int min_n = start_n_lookup_table[max_n];
const int step_size = step_size_lookup_table[max_n];
assert(min_n >= PALETTE_MIN_SIZE);
// Perform top color coarse palette search to find the winner candidate
const int top_color_winner = perform_top_color_palette_search(
cpi, x, mbmi, bsize, dc_mode_cost, data, top_colors, min_n, max_n + 1,
step_size, do_header_rd_based_gating, &unused, color_cache, n_cache,
best_mbmi, best_palette_color_map, best_rd, rate, rate_tokenonly,
distortion, skippable, beat_best_rd, ctx, best_blk_skip, tx_type_map,
discount_color_cost);
// Evaluate neighbors for the winner color (if winner is found) in the
// above coarse search for dominant colors
if (top_color_winner <= max_n) {
int stage2_min_n, stage2_max_n, stage2_step_size;
set_stage2_params(&stage2_min_n, &stage2_max_n, &stage2_step_size,
top_color_winner, max_n);
// perform finer search for the winner candidate
perform_top_color_palette_search(
cpi, x, mbmi, bsize, dc_mode_cost, data, top_colors, stage2_min_n,
stage2_max_n + 1, stage2_step_size,
/*do_header_rd_based_gating=*/false, &unused, color_cache, n_cache,
best_mbmi, best_palette_color_map, best_rd, rate, rate_tokenonly,
distortion, skippable, beat_best_rd, ctx, best_blk_skip,
tx_type_map, discount_color_cost);
}
// K-means clustering.
// Perform k-means coarse palette search to find the winner candidate
const int k_means_winner = perform_k_means_palette_search(
cpi, x, mbmi, bsize, dc_mode_cost, data, lower_bound, upper_bound,
min_n, max_n + 1, step_size, do_header_rd_based_gating, &unused,
color_cache, n_cache, best_mbmi, best_palette_color_map, best_rd,
rate, rate_tokenonly, distortion, skippable, beat_best_rd, ctx,
best_blk_skip, tx_type_map, color_map, rows * cols,
discount_color_cost);
// Evaluate neighbors for the winner color (if winner is found) in the
// above coarse search for k-means
if (k_means_winner <= max_n) {
int start_n_stage2, end_n_stage2, step_size_stage2;
set_stage2_params(&start_n_stage2, &end_n_stage2, &step_size_stage2,
k_means_winner, max_n);
// perform finer search for the winner candidate
perform_k_means_palette_search(
cpi, x, mbmi, bsize, dc_mode_cost, data, lower_bound, upper_bound,
start_n_stage2, end_n_stage2 + 1, step_size_stage2,
/*do_header_rd_based_gating=*/false, &unused, color_cache, n_cache,
best_mbmi, best_palette_color_map, best_rd, rate, rate_tokenonly,
distortion, skippable, beat_best_rd, ctx, best_blk_skip,
tx_type_map, color_map, rows * cols, discount_color_cost);
}
} else {
const int max_n = AOMMIN(colors, PALETTE_MAX_SIZE),
min_n = PALETTE_MIN_SIZE;
// Perform top color palette search in ascending order
int last_n_searched = min_n;
perform_top_color_palette_search(
cpi, x, mbmi, bsize, dc_mode_cost, data, top_colors, min_n, max_n + 1,
1, do_header_rd_based_gating, &last_n_searched, color_cache, n_cache,
best_mbmi, best_palette_color_map, best_rd, rate, rate_tokenonly,
distortion, skippable, beat_best_rd, ctx, best_blk_skip, tx_type_map,
discount_color_cost);
if (last_n_searched < max_n) {
// Search in descending order until we get to the previous best
perform_top_color_palette_search(
cpi, x, mbmi, bsize, dc_mode_cost, data, top_colors, max_n,
last_n_searched, -1, /*do_header_rd_based_gating=*/false, &unused,
color_cache, n_cache, best_mbmi, best_palette_color_map, best_rd,
rate, rate_tokenonly, distortion, skippable, beat_best_rd, ctx,
best_blk_skip, tx_type_map, discount_color_cost);
}
// K-means clustering.
if (colors == PALETTE_MIN_SIZE) {
// Special case: These colors automatically become the centroids.
assert(colors == 2);
centroids[0] = lower_bound;
centroids[1] = upper_bound;
palette_rd_y(cpi, x, mbmi, bsize, dc_mode_cost, data, centroids, colors,
color_cache, n_cache, /*do_header_rd_based_gating=*/false,
best_mbmi, best_palette_color_map, best_rd, rate,
rate_tokenonly, distortion, skippable, beat_best_rd, ctx,
best_blk_skip, tx_type_map, NULL, NULL,
discount_color_cost);
} else {
// Perform k-means palette search in ascending order
last_n_searched = min_n;
perform_k_means_palette_search(
cpi, x, mbmi, bsize, dc_mode_cost, data, lower_bound, upper_bound,
min_n, max_n + 1, 1, do_header_rd_based_gating, &last_n_searched,
color_cache, n_cache, best_mbmi, best_palette_color_map, best_rd,
rate, rate_tokenonly, distortion, skippable, beat_best_rd, ctx,
best_blk_skip, tx_type_map, color_map, rows * cols,
discount_color_cost);
if (last_n_searched < max_n) {
// Search in descending order until we get to the previous best
perform_k_means_palette_search(
cpi, x, mbmi, bsize, dc_mode_cost, data, lower_bound, upper_bound,
max_n, last_n_searched, -1, /*do_header_rd_based_gating=*/false,
&unused, color_cache, n_cache, best_mbmi, best_palette_color_map,
best_rd, rate, rate_tokenonly, distortion, skippable,
beat_best_rd, ctx, best_blk_skip, tx_type_map, color_map,
rows * cols, discount_color_cost);
}
}
}
}
if (best_mbmi->palette_mode_info.palette_size[0] > 0) {
memcpy(color_map, best_palette_color_map,
block_width * block_height * sizeof(best_palette_color_map[0]));
// Gather the stats to determine whether to use screen content tools in
// function av1_determine_sc_tools_with_encoding().
x->palette_pixels += (block_width * block_height);
}
*mbmi = *best_mbmi;
}
void av1_rd_pick_palette_intra_sbuv(const AV1_COMP *cpi, MACROBLOCK *x,
int dc_mode_cost,
uint8_t *best_palette_color_map,
MB_MODE_INFO *const best_mbmi,
int64_t *best_rd, int *rate,
int *rate_tokenonly, int64_t *distortion,
uint8_t *skippable) {
MACROBLOCKD *const xd = &x->e_mbd;
MB_MODE_INFO *const mbmi = xd->mi[0];
assert(!is_inter_block(mbmi));
assert(av1_allow_palette(cpi->common.features.allow_screen_content_tools,
mbmi->bsize));
PALETTE_MODE_INFO *const pmi = &mbmi->palette_mode_info;
const BLOCK_SIZE bsize = mbmi->bsize;
const SequenceHeader *const seq_params = cpi->common.seq_params;
int this_rate;
int64_t this_rd;
int colors_u, colors_v;
int colors_threshold_u = 0, colors_threshold_v = 0, colors_threshold = 0;
const int src_stride = x->plane[1].src.stride;
const uint8_t *const src_u = x->plane[1].src.buf;
const uint8_t *const src_v = x->plane[2].src.buf;
uint8_t *const color_map = xd->plane[1].color_index_map;
RD_STATS tokenonly_rd_stats;
int plane_block_width, plane_block_height, rows, cols;
av1_get_block_dimensions(bsize, 1, xd, &plane_block_width,
&plane_block_height, &rows, &cols);
mbmi->uv_mode = UV_DC_PRED;
if (seq_params->use_highbitdepth) {
int count_buf[1 << 12]; // Maximum (1 << 12) color levels.
int count_buf_8bit[1 << 8]; // Maximum (1 << 8) bins for hbd path.
av1_count_colors_highbd(src_u, src_stride, rows, cols,
seq_params->bit_depth, count_buf, count_buf_8bit,
&colors_threshold_u, &colors_u);
av1_count_colors_highbd(src_v, src_stride, rows, cols,
seq_params->bit_depth, count_buf, count_buf_8bit,
&colors_threshold_v, &colors_v);
} else {
int count_buf[1 << 8];
av1_count_colors(src_u, src_stride, rows, cols, count_buf, &colors_u);
av1_count_colors(src_v, src_stride, rows, cols, count_buf, &colors_v);
colors_threshold_u = colors_u;
colors_threshold_v = colors_v;
}
uint16_t color_cache[2 * PALETTE_MAX_SIZE];
const int n_cache = av1_get_palette_cache(xd, 1, color_cache);
colors_threshold = colors_threshold_u > colors_threshold_v
? colors_threshold_u
: colors_threshold_v;
if (colors_threshold > 1 && colors_threshold <= 64) {
int r, c, n, i, j;
const int max_itr = 50;
int lb_u, ub_u, val_u;
int lb_v, ub_v, val_v;
int16_t *const data = x->palette_buffer->kmeans_data_buf;
int16_t centroids[2 * PALETTE_MAX_SIZE];
uint16_t *src_u16 = CONVERT_TO_SHORTPTR(src_u);
uint16_t *src_v16 = CONVERT_TO_SHORTPTR(src_v);
if (seq_params->use_highbitdepth) {
lb_u = src_u16[0];
ub_u = src_u16[0];
lb_v = src_v16[0];
ub_v = src_v16[0];
} else {
lb_u = src_u[0];
ub_u = src_u[0];
lb_v = src_v[0];
ub_v = src_v[0];
}
for (r = 0; r < rows; ++r) {
for (c = 0; c < cols; ++c) {
if (seq_params->use_highbitdepth) {
val_u = src_u16[r * src_stride + c];
val_v = src_v16[r * src_stride + c];
data[(r * cols + c) * 2] = val_u;
data[(r * cols + c) * 2 + 1] = val_v;
} else {
val_u = src_u[r * src_stride + c];
val_v = src_v[r * src_stride + c];
data[(r * cols + c) * 2] = val_u;
data[(r * cols + c) * 2 + 1] = val_v;
}
if (val_u < lb_u)
lb_u = val_u;
else if (val_u > ub_u)
ub_u = val_u;
if (val_v < lb_v)
lb_v = val_v;
else if (val_v > ub_v)
ub_v = val_v;
}
}
const int colors = colors_u > colors_v ? colors_u : colors_v;
const int max_colors =
colors > PALETTE_MAX_SIZE ? PALETTE_MAX_SIZE : colors;
for (n = PALETTE_MIN_SIZE; n <= max_colors; ++n) {
for (i = 0; i < n; ++i) {
centroids[i * 2] = lb_u + (2 * i + 1) * (ub_u - lb_u) / n / 2;
centroids[i * 2 + 1] = lb_v + (2 * i + 1) * (ub_v - lb_v) / n / 2;
}
av1_k_means(data, centroids, color_map, rows * cols, n, 2, max_itr);
optimize_palette_colors(color_cache, n_cache, n, 2, centroids,
cpi->common.seq_params->bit_depth);
// Sort the U channel colors in ascending order.
for (i = 0; i < 2 * (n - 1); i += 2) {
int min_idx = i;
int min_val = centroids[i];
for (j = i + 2; j < 2 * n; j += 2)
if (centroids[j] < min_val) min_val = centroids[j], min_idx = j;
if (min_idx != i) {
int temp_u = centroids[i], temp_v = centroids[i + 1];
centroids[i] = centroids[min_idx];
centroids[i + 1] = centroids[min_idx + 1];
centroids[min_idx] = temp_u, centroids[min_idx + 1] = temp_v;
}
}
av1_calc_indices(data, centroids, color_map, rows * cols, n, 2);
extend_palette_color_map(color_map, cols, rows, plane_block_width,
plane_block_height);
pmi->palette_size[1] = n;
for (i = 1; i < 3; ++i) {
for (j = 0; j < n; ++j) {
if (seq_params->use_highbitdepth)
pmi->palette_colors[i * PALETTE_MAX_SIZE + j] = clip_pixel_highbd(
(int)centroids[j * 2 + i - 1], seq_params->bit_depth);
else
pmi->palette_colors[i * PALETTE_MAX_SIZE + j] =
clip_pixel((int)centroids[j * 2 + i - 1]);
}
}
if (cpi->sf.intra_sf.early_term_chroma_palette_size_search) {
const int palette_mode_rate =
intra_mode_info_cost_uv(cpi, x, mbmi, bsize, dc_mode_cost);
const int64_t header_rd = RDCOST(x->rdmult, palette_mode_rate, 0);
// Terminate further palette_size search, if header cost corresponding
// to lower palette_size is more than the best_rd.
if (header_rd >= *best_rd) break;
av1_txfm_uvrd(cpi, x, &tokenonly_rd_stats, bsize, *best_rd);
if (tokenonly_rd_stats.rate == INT_MAX) continue;
this_rate = tokenonly_rd_stats.rate + palette_mode_rate;
} else {
av1_txfm_uvrd(cpi, x, &tokenonly_rd_stats, bsize, *best_rd);
if (tokenonly_rd_stats.rate == INT_MAX) continue;
this_rate = tokenonly_rd_stats.rate +
intra_mode_info_cost_uv(cpi, x, mbmi, bsize, dc_mode_cost);
}
this_rd = RDCOST(x->rdmult, this_rate, tokenonly_rd_stats.dist);
if (this_rd < *best_rd) {
*best_rd = this_rd;
*best_mbmi = *mbmi;
memcpy(best_palette_color_map, color_map,
plane_block_width * plane_block_height *
sizeof(best_palette_color_map[0]));
*rate = this_rate;
*distortion = tokenonly_rd_stats.dist;
*rate_tokenonly = tokenonly_rd_stats.rate;
*skippable = tokenonly_rd_stats.skip_txfm;
}
}
}
if (best_mbmi->palette_mode_info.palette_size[1] > 0) {
memcpy(color_map, best_palette_color_map,
plane_block_width * plane_block_height *
sizeof(best_palette_color_map[0]));
}
}
void av1_restore_uv_color_map(const AV1_COMP *cpi, MACROBLOCK *x) {
MACROBLOCKD *const xd = &x->e_mbd;
MB_MODE_INFO *const mbmi = xd->mi[0];
PALETTE_MODE_INFO *const pmi = &mbmi->palette_mode_info;
const BLOCK_SIZE bsize = mbmi->bsize;
int src_stride = x->plane[1].src.stride;
const uint8_t *const src_u = x->plane[1].src.buf;
const uint8_t *const src_v = x->plane[2].src.buf;
int16_t *const data = x->palette_buffer->kmeans_data_buf;
int16_t centroids[2 * PALETTE_MAX_SIZE];
uint8_t *const color_map = xd->plane[1].color_index_map;
int r, c;
const uint16_t *const src_u16 = CONVERT_TO_SHORTPTR(src_u);
const uint16_t *const src_v16 = CONVERT_TO_SHORTPTR(src_v);
int plane_block_width, plane_block_height, rows, cols;
av1_get_block_dimensions(bsize, 1, xd, &plane_block_width,
&plane_block_height, &rows, &cols);
for (r = 0; r < rows; ++r) {
for (c = 0; c < cols; ++c) {
if (cpi->common.seq_params->use_highbitdepth) {
data[(r * cols + c) * 2] = src_u16[r * src_stride + c];
data[(r * cols + c) * 2 + 1] = src_v16[r * src_stride + c];
} else {
data[(r * cols + c) * 2] = src_u[r * src_stride + c];
data[(r * cols + c) * 2 + 1] = src_v[r * src_stride + c];
}
}
}
for (r = 1; r < 3; ++r) {
for (c = 0; c < pmi->palette_size[1]; ++c) {
centroids[c * 2 + r - 1] = pmi->palette_colors[r * PALETTE_MAX_SIZE + c];
}
}
av1_calc_indices(data, centroids, color_map, rows * cols,
pmi->palette_size[1], 2);
extend_palette_color_map(color_map, cols, rows, plane_block_width,
plane_block_height);
}