diff options
Diffstat (limited to '')
| -rw-r--r-- | third_party/aom/av1/encoder/allintra_vis.c | 1055 |
1 files changed, 1055 insertions, 0 deletions
diff --git a/third_party/aom/av1/encoder/allintra_vis.c b/third_party/aom/av1/encoder/allintra_vis.c new file mode 100644 index 0000000000..8dcef5fc85 --- /dev/null +++ b/third_party/aom/av1/encoder/allintra_vis.c @@ -0,0 +1,1055 @@ +/* + * Copyright (c) 2021, 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 <assert.h> + +#include "config/aom_config.h" + +#if CONFIG_TFLITE +#include "tensorflow/lite/c/c_api.h" +#include "av1/encoder/deltaq4_model.c" +#endif + +#include "av1/common/common_data.h" +#include "av1/common/enums.h" +#include "av1/common/idct.h" +#include "av1/common/reconinter.h" +#include "av1/encoder/allintra_vis.h" +#include "av1/encoder/encoder.h" +#include "av1/encoder/ethread.h" +#include "av1/encoder/hybrid_fwd_txfm.h" +#include "av1/encoder/model_rd.h" +#include "av1/encoder/rdopt_utils.h" + +#define MB_WIENER_PRED_BLOCK_SIZE BLOCK_128X128 +#define MB_WIENER_PRED_BUF_STRIDE 128 + +void av1_alloc_mb_wiener_var_pred_buf(AV1_COMMON *cm, ThreadData *td) { + const int is_high_bitdepth = is_cur_buf_hbd(&td->mb.e_mbd); + assert(MB_WIENER_PRED_BLOCK_SIZE < BLOCK_SIZES_ALL); + const int buf_width = block_size_wide[MB_WIENER_PRED_BLOCK_SIZE]; + const int buf_height = block_size_high[MB_WIENER_PRED_BLOCK_SIZE]; + assert(buf_width == MB_WIENER_PRED_BUF_STRIDE); + const size_t buf_size = + (buf_width * buf_height * sizeof(*td->wiener_tmp_pred_buf)) + << is_high_bitdepth; + CHECK_MEM_ERROR(cm, td->wiener_tmp_pred_buf, aom_memalign(32, buf_size)); +} + +void av1_dealloc_mb_wiener_var_pred_buf(ThreadData *td) { + aom_free(td->wiener_tmp_pred_buf); + td->wiener_tmp_pred_buf = NULL; +} + +void av1_init_mb_wiener_var_buffer(AV1_COMP *cpi) { + AV1_COMMON *cm = &cpi->common; + + // This block size is also used to determine number of workers in + // multi-threading. If it is changed, one needs to change it accordingly in + // "compute_num_ai_workers()". + cpi->weber_bsize = BLOCK_8X8; + + if (cpi->oxcf.enable_rate_guide_deltaq) { + if (cpi->mb_weber_stats && cpi->prep_rate_estimates && + cpi->ext_rate_distribution) + return; + } else { + if (cpi->mb_weber_stats) return; + } + + CHECK_MEM_ERROR(cm, cpi->mb_weber_stats, + aom_calloc(cpi->frame_info.mi_rows * cpi->frame_info.mi_cols, + sizeof(*cpi->mb_weber_stats))); + + if (cpi->oxcf.enable_rate_guide_deltaq) { + CHECK_MEM_ERROR( + cm, cpi->prep_rate_estimates, + aom_calloc(cpi->frame_info.mi_rows * cpi->frame_info.mi_cols, + sizeof(*cpi->prep_rate_estimates))); + + CHECK_MEM_ERROR( + cm, cpi->ext_rate_distribution, + aom_calloc(cpi->frame_info.mi_rows * cpi->frame_info.mi_cols, + sizeof(*cpi->ext_rate_distribution))); + } +} + +static int64_t get_satd(AV1_COMP *const cpi, BLOCK_SIZE bsize, int mi_row, + int mi_col) { + AV1_COMMON *const cm = &cpi->common; + const int mi_wide = mi_size_wide[bsize]; + const int mi_high = mi_size_high[bsize]; + + const int mi_step = mi_size_wide[cpi->weber_bsize]; + int mb_stride = cpi->frame_info.mi_cols; + int mb_count = 0; + int64_t satd = 0; + + for (int row = mi_row; row < mi_row + mi_high; row += mi_step) { + for (int col = mi_col; col < mi_col + mi_wide; col += mi_step) { + if (row >= cm->mi_params.mi_rows || col >= cm->mi_params.mi_cols) + continue; + + satd += cpi->mb_weber_stats[(row / mi_step) * mb_stride + (col / mi_step)] + .satd; + ++mb_count; + } + } + + if (mb_count) satd = (int)(satd / mb_count); + satd = AOMMAX(1, satd); + + return (int)satd; +} + +static int64_t get_sse(AV1_COMP *const cpi, BLOCK_SIZE bsize, int mi_row, + int mi_col) { + AV1_COMMON *const cm = &cpi->common; + const int mi_wide = mi_size_wide[bsize]; + const int mi_high = mi_size_high[bsize]; + + const int mi_step = mi_size_wide[cpi->weber_bsize]; + int mb_stride = cpi->frame_info.mi_cols; + int mb_count = 0; + int64_t distortion = 0; + + for (int row = mi_row; row < mi_row + mi_high; row += mi_step) { + for (int col = mi_col; col < mi_col + mi_wide; col += mi_step) { + if (row >= cm->mi_params.mi_rows || col >= cm->mi_params.mi_cols) + continue; + + distortion += + cpi->mb_weber_stats[(row / mi_step) * mb_stride + (col / mi_step)] + .distortion; + ++mb_count; + } + } + + if (mb_count) distortion = (int)(distortion / mb_count); + distortion = AOMMAX(1, distortion); + + return (int)distortion; +} + +static double get_max_scale(AV1_COMP *const cpi, BLOCK_SIZE bsize, int mi_row, + int mi_col) { + AV1_COMMON *const cm = &cpi->common; + const int mi_wide = mi_size_wide[bsize]; + const int mi_high = mi_size_high[bsize]; + const int mi_step = mi_size_wide[cpi->weber_bsize]; + int mb_stride = cpi->frame_info.mi_cols; + double min_max_scale = 10.0; + + for (int row = mi_row; row < mi_row + mi_high; row += mi_step) { + for (int col = mi_col; col < mi_col + mi_wide; col += mi_step) { + if (row >= cm->mi_params.mi_rows || col >= cm->mi_params.mi_cols) + continue; + WeberStats *weber_stats = + &cpi->mb_weber_stats[(row / mi_step) * mb_stride + (col / mi_step)]; + if (weber_stats->max_scale < 1.0) continue; + if (weber_stats->max_scale < min_max_scale) + min_max_scale = weber_stats->max_scale; + } + } + return min_max_scale; +} + +static int get_window_wiener_var(AV1_COMP *const cpi, BLOCK_SIZE bsize, + int mi_row, int mi_col) { + AV1_COMMON *const cm = &cpi->common; + const int mi_wide = mi_size_wide[bsize]; + const int mi_high = mi_size_high[bsize]; + + const int mi_step = mi_size_wide[cpi->weber_bsize]; + int sb_wiener_var = 0; + int mb_stride = cpi->frame_info.mi_cols; + int mb_count = 0; + double base_num = 1; + double base_den = 1; + double base_reg = 1; + + for (int row = mi_row; row < mi_row + mi_high; row += mi_step) { + for (int col = mi_col; col < mi_col + mi_wide; col += mi_step) { + if (row >= cm->mi_params.mi_rows || col >= cm->mi_params.mi_cols) + continue; + + WeberStats *weber_stats = + &cpi->mb_weber_stats[(row / mi_step) * mb_stride + (col / mi_step)]; + + base_num += ((double)weber_stats->distortion) * + sqrt((double)weber_stats->src_variance) * + weber_stats->rec_pix_max; + + base_den += fabs( + weber_stats->rec_pix_max * sqrt((double)weber_stats->src_variance) - + weber_stats->src_pix_max * sqrt((double)weber_stats->rec_variance)); + + base_reg += sqrt((double)weber_stats->distortion) * + sqrt((double)weber_stats->src_pix_max) * 0.1; + ++mb_count; + } + } + + sb_wiener_var = + (int)(((base_num + base_reg) / (base_den + base_reg)) / mb_count); + sb_wiener_var = AOMMAX(1, sb_wiener_var); + + return (int)sb_wiener_var; +} + +static int get_var_perceptual_ai(AV1_COMP *const cpi, BLOCK_SIZE bsize, + int mi_row, int mi_col) { + AV1_COMMON *const cm = &cpi->common; + const int mi_wide = mi_size_wide[bsize]; + const int mi_high = mi_size_high[bsize]; + + int sb_wiener_var = get_window_wiener_var(cpi, bsize, mi_row, mi_col); + + if (mi_row >= (mi_high / 2)) { + sb_wiener_var = + AOMMIN(sb_wiener_var, + get_window_wiener_var(cpi, bsize, mi_row - mi_high / 2, mi_col)); + } + if (mi_row <= (cm->mi_params.mi_rows - mi_high - (mi_high / 2))) { + sb_wiener_var = + AOMMIN(sb_wiener_var, + get_window_wiener_var(cpi, bsize, mi_row + mi_high / 2, mi_col)); + } + if (mi_col >= (mi_wide / 2)) { + sb_wiener_var = + AOMMIN(sb_wiener_var, + get_window_wiener_var(cpi, bsize, mi_row, mi_col - mi_wide / 2)); + } + if (mi_col <= (cm->mi_params.mi_cols - mi_wide - (mi_wide / 2))) { + sb_wiener_var = + AOMMIN(sb_wiener_var, + get_window_wiener_var(cpi, bsize, mi_row, mi_col + mi_wide / 2)); + } + + return sb_wiener_var; +} + +static int rate_estimator(const tran_low_t *qcoeff, int eob, TX_SIZE tx_size) { + const SCAN_ORDER *const scan_order = &av1_scan_orders[tx_size][DCT_DCT]; + + assert((1 << num_pels_log2_lookup[txsize_to_bsize[tx_size]]) >= eob); + int rate_cost = 1; + + for (int idx = 0; idx < eob; ++idx) { + int abs_level = abs(qcoeff[scan_order->scan[idx]]); + rate_cost += (int)(log1p(abs_level) / log(2.0)) + 1 + (abs_level > 0); + } + + return (rate_cost << AV1_PROB_COST_SHIFT); +} + +void av1_calc_mb_wiener_var_row(AV1_COMP *const cpi, MACROBLOCK *x, + MACROBLOCKD *xd, const int mi_row, + int16_t *src_diff, tran_low_t *coeff, + tran_low_t *qcoeff, tran_low_t *dqcoeff, + double *sum_rec_distortion, + double *sum_est_rate, uint8_t *pred_buffer) { + AV1_COMMON *const cm = &cpi->common; + uint8_t *buffer = cpi->source->y_buffer; + int buf_stride = cpi->source->y_stride; + MB_MODE_INFO mbmi; + memset(&mbmi, 0, sizeof(mbmi)); + MB_MODE_INFO *mbmi_ptr = &mbmi; + xd->mi = &mbmi_ptr; + const BLOCK_SIZE bsize = cpi->weber_bsize; + const TX_SIZE tx_size = max_txsize_lookup[bsize]; + const int block_size = tx_size_wide[tx_size]; + const int coeff_count = block_size * block_size; + const int mb_step = mi_size_wide[bsize]; + const BitDepthInfo bd_info = get_bit_depth_info(xd); + const MultiThreadInfo *const mt_info = &cpi->mt_info; + const AV1EncAllIntraMultiThreadInfo *const intra_mt = &mt_info->intra_mt; + AV1EncRowMultiThreadSync *const intra_row_mt_sync = + &cpi->ppi->intra_row_mt_sync; + const int mi_cols = cm->mi_params.mi_cols; + const int mt_thread_id = mi_row / mb_step; + // TODO(chengchen): test different unit step size + const int mt_unit_step = mi_size_wide[MB_WIENER_MT_UNIT_SIZE]; + const int mt_unit_cols = (mi_cols + (mt_unit_step >> 1)) / mt_unit_step; + int mt_unit_col = 0; + const int is_high_bitdepth = is_cur_buf_hbd(xd); + + uint8_t *dst_buffer = pred_buffer; + const int dst_buffer_stride = MB_WIENER_PRED_BUF_STRIDE; + + if (is_high_bitdepth) { + uint16_t *pred_buffer_16 = (uint16_t *)pred_buffer; + dst_buffer = CONVERT_TO_BYTEPTR(pred_buffer_16); + } + + for (int mi_col = 0; mi_col < mi_cols; mi_col += mb_step) { + if (mi_col % mt_unit_step == 0) { + intra_mt->intra_sync_read_ptr(intra_row_mt_sync, mt_thread_id, + mt_unit_col); +#if CONFIG_MULTITHREAD + const int num_workers = + AOMMIN(mt_info->num_mod_workers[MOD_AI], mt_info->num_workers); + if (num_workers > 1) { + const AV1EncRowMultiThreadInfo *const enc_row_mt = &mt_info->enc_row_mt; + pthread_mutex_lock(enc_row_mt->mutex_); + const bool exit = enc_row_mt->mb_wiener_mt_exit; + pthread_mutex_unlock(enc_row_mt->mutex_); + // Stop further processing in case any worker has encountered an error. + if (exit) break; + } +#endif + } + + PREDICTION_MODE best_mode = DC_PRED; + int best_intra_cost = INT_MAX; + const int mi_width = mi_size_wide[bsize]; + const int mi_height = mi_size_high[bsize]; + set_mode_info_offsets(&cpi->common.mi_params, &cpi->mbmi_ext_info, x, xd, + mi_row, mi_col); + set_mi_row_col(xd, &xd->tile, mi_row, mi_height, mi_col, mi_width, + AOMMIN(mi_row + mi_height, cm->mi_params.mi_rows), + AOMMIN(mi_col + mi_width, cm->mi_params.mi_cols)); + set_plane_n4(xd, mi_size_wide[bsize], mi_size_high[bsize], + av1_num_planes(cm)); + xd->mi[0]->bsize = bsize; + xd->mi[0]->motion_mode = SIMPLE_TRANSLATION; + // Set above and left mbmi to NULL as they are not available in the + // preprocessing stage. + // They are used to detemine intra edge filter types in intra prediction. + if (xd->up_available) { + xd->above_mbmi = NULL; + } + if (xd->left_available) { + xd->left_mbmi = NULL; + } + uint8_t *mb_buffer = + buffer + mi_row * MI_SIZE * buf_stride + mi_col * MI_SIZE; + for (PREDICTION_MODE mode = INTRA_MODE_START; mode < INTRA_MODE_END; + ++mode) { + // TODO(chengchen): Here we use src instead of reconstructed frame as + // the intra predictor to make single and multithread version match. + // Ideally we want to use the reconstructed. + av1_predict_intra_block( + xd, cm->seq_params->sb_size, cm->seq_params->enable_intra_edge_filter, + block_size, block_size, tx_size, mode, 0, 0, FILTER_INTRA_MODES, + mb_buffer, buf_stride, dst_buffer, dst_buffer_stride, 0, 0, 0); + av1_subtract_block(bd_info, block_size, block_size, src_diff, block_size, + mb_buffer, buf_stride, dst_buffer, dst_buffer_stride); + av1_quick_txfm(0, tx_size, bd_info, src_diff, block_size, coeff); + int intra_cost = aom_satd(coeff, coeff_count); + if (intra_cost < best_intra_cost) { + best_intra_cost = intra_cost; + best_mode = mode; + } + } + + av1_predict_intra_block( + xd, cm->seq_params->sb_size, cm->seq_params->enable_intra_edge_filter, + block_size, block_size, tx_size, best_mode, 0, 0, FILTER_INTRA_MODES, + mb_buffer, buf_stride, dst_buffer, dst_buffer_stride, 0, 0, 0); + av1_subtract_block(bd_info, block_size, block_size, src_diff, block_size, + mb_buffer, buf_stride, dst_buffer, dst_buffer_stride); + av1_quick_txfm(0, tx_size, bd_info, src_diff, block_size, coeff); + + const struct macroblock_plane *const p = &x->plane[0]; + uint16_t eob; + const SCAN_ORDER *const scan_order = &av1_scan_orders[tx_size][DCT_DCT]; + QUANT_PARAM quant_param; + int pix_num = 1 << num_pels_log2_lookup[txsize_to_bsize[tx_size]]; + av1_setup_quant(tx_size, 0, AV1_XFORM_QUANT_FP, 0, &quant_param); +#if CONFIG_AV1_HIGHBITDEPTH + if (is_cur_buf_hbd(xd)) { + av1_highbd_quantize_fp_facade(coeff, pix_num, p, qcoeff, dqcoeff, &eob, + scan_order, &quant_param); + } else { + av1_quantize_fp_facade(coeff, pix_num, p, qcoeff, dqcoeff, &eob, + scan_order, &quant_param); + } +#else + av1_quantize_fp_facade(coeff, pix_num, p, qcoeff, dqcoeff, &eob, scan_order, + &quant_param); +#endif // CONFIG_AV1_HIGHBITDEPTH + + if (cpi->oxcf.enable_rate_guide_deltaq) { + const int rate_cost = rate_estimator(qcoeff, eob, tx_size); + cpi->prep_rate_estimates[(mi_row / mb_step) * cpi->frame_info.mi_cols + + (mi_col / mb_step)] = rate_cost; + } + + av1_inverse_transform_block(xd, dqcoeff, 0, DCT_DCT, tx_size, dst_buffer, + dst_buffer_stride, eob, 0); + WeberStats *weber_stats = + &cpi->mb_weber_stats[(mi_row / mb_step) * cpi->frame_info.mi_cols + + (mi_col / mb_step)]; + + weber_stats->rec_pix_max = 1; + weber_stats->rec_variance = 0; + weber_stats->src_pix_max = 1; + weber_stats->src_variance = 0; + weber_stats->distortion = 0; + + int64_t src_mean = 0; + int64_t rec_mean = 0; + int64_t dist_mean = 0; + + for (int pix_row = 0; pix_row < block_size; ++pix_row) { + for (int pix_col = 0; pix_col < block_size; ++pix_col) { + int src_pix, rec_pix; +#if CONFIG_AV1_HIGHBITDEPTH + if (is_cur_buf_hbd(xd)) { + uint16_t *src = CONVERT_TO_SHORTPTR(mb_buffer); + uint16_t *rec = CONVERT_TO_SHORTPTR(dst_buffer); + src_pix = src[pix_row * buf_stride + pix_col]; + rec_pix = rec[pix_row * dst_buffer_stride + pix_col]; + } else { + src_pix = mb_buffer[pix_row * buf_stride + pix_col]; + rec_pix = dst_buffer[pix_row * dst_buffer_stride + pix_col]; + } +#else + src_pix = mb_buffer[pix_row * buf_stride + pix_col]; + rec_pix = dst_buffer[pix_row * dst_buffer_stride + pix_col]; +#endif + src_mean += src_pix; + rec_mean += rec_pix; + dist_mean += src_pix - rec_pix; + weber_stats->src_variance += src_pix * src_pix; + weber_stats->rec_variance += rec_pix * rec_pix; + weber_stats->src_pix_max = AOMMAX(weber_stats->src_pix_max, src_pix); + weber_stats->rec_pix_max = AOMMAX(weber_stats->rec_pix_max, rec_pix); + weber_stats->distortion += (src_pix - rec_pix) * (src_pix - rec_pix); + } + } + + if (cpi->oxcf.intra_mode_cfg.auto_intra_tools_off) { + *sum_rec_distortion += weber_stats->distortion; + int est_block_rate = 0; + int64_t est_block_dist = 0; + model_rd_sse_fn[MODELRD_LEGACY](cpi, x, bsize, 0, weber_stats->distortion, + pix_num, &est_block_rate, + &est_block_dist); + *sum_est_rate += est_block_rate; + } + + weber_stats->src_variance -= (src_mean * src_mean) / pix_num; + weber_stats->rec_variance -= (rec_mean * rec_mean) / pix_num; + weber_stats->distortion -= (dist_mean * dist_mean) / pix_num; + weber_stats->satd = best_intra_cost; + + qcoeff[0] = 0; + int max_scale = 0; + for (int idx = 1; idx < coeff_count; ++idx) { + const int abs_qcoeff = abs(qcoeff[idx]); + max_scale = AOMMAX(max_scale, abs_qcoeff); + } + weber_stats->max_scale = max_scale; + + if ((mi_col + mb_step) % mt_unit_step == 0 || + (mi_col + mb_step) >= mi_cols) { + intra_mt->intra_sync_write_ptr(intra_row_mt_sync, mt_thread_id, + mt_unit_col, mt_unit_cols); + ++mt_unit_col; + } + } + // Set the pointer to null since mbmi is only allocated inside this function. + xd->mi = NULL; +} + +static void calc_mb_wiener_var(AV1_COMP *const cpi, double *sum_rec_distortion, + double *sum_est_rate) { + MACROBLOCK *x = &cpi->td.mb; + MACROBLOCKD *xd = &x->e_mbd; + const BLOCK_SIZE bsize = cpi->weber_bsize; + const int mb_step = mi_size_wide[bsize]; + DECLARE_ALIGNED(32, int16_t, src_diff[32 * 32]); + DECLARE_ALIGNED(32, tran_low_t, coeff[32 * 32]); + DECLARE_ALIGNED(32, tran_low_t, qcoeff[32 * 32]); + DECLARE_ALIGNED(32, tran_low_t, dqcoeff[32 * 32]); + for (int mi_row = 0; mi_row < cpi->frame_info.mi_rows; mi_row += mb_step) { + av1_calc_mb_wiener_var_row(cpi, x, xd, mi_row, src_diff, coeff, qcoeff, + dqcoeff, sum_rec_distortion, sum_est_rate, + cpi->td.wiener_tmp_pred_buf); + } +} + +static int64_t estimate_wiener_var_norm(AV1_COMP *const cpi, + const BLOCK_SIZE norm_block_size) { + const AV1_COMMON *const cm = &cpi->common; + int64_t norm_factor = 1; + assert(norm_block_size >= BLOCK_16X16 && norm_block_size <= BLOCK_128X128); + const int norm_step = mi_size_wide[norm_block_size]; + double sb_wiener_log = 0; + double sb_count = 0; + for (int mi_row = 0; mi_row < cm->mi_params.mi_rows; mi_row += norm_step) { + for (int mi_col = 0; mi_col < cm->mi_params.mi_cols; mi_col += norm_step) { + const int sb_wiener_var = + get_var_perceptual_ai(cpi, norm_block_size, mi_row, mi_col); + const int64_t satd = get_satd(cpi, norm_block_size, mi_row, mi_col); + const int64_t sse = get_sse(cpi, norm_block_size, mi_row, mi_col); + const double scaled_satd = (double)satd / sqrt((double)sse); + sb_wiener_log += scaled_satd * log(sb_wiener_var); + sb_count += scaled_satd; + } + } + if (sb_count > 0) norm_factor = (int64_t)(exp(sb_wiener_log / sb_count)); + norm_factor = AOMMAX(1, norm_factor); + + return norm_factor; +} + +static void automatic_intra_tools_off(AV1_COMP *cpi, + const double sum_rec_distortion, + const double sum_est_rate) { + if (!cpi->oxcf.intra_mode_cfg.auto_intra_tools_off) return; + + // Thresholds + const int high_quality_qindex = 128; + const double high_quality_bpp = 2.0; + const double high_quality_dist_per_pix = 4.0; + + AV1_COMMON *const cm = &cpi->common; + const int qindex = cm->quant_params.base_qindex; + const double dist_per_pix = + (double)sum_rec_distortion / (cm->width * cm->height); + // The estimate bpp is not accurate, an empirical constant 100 is divided. + const double estimate_bpp = sum_est_rate / (cm->width * cm->height * 100); + + if (qindex < high_quality_qindex && estimate_bpp > high_quality_bpp && + dist_per_pix < high_quality_dist_per_pix) { + cpi->oxcf.intra_mode_cfg.enable_smooth_intra = 0; + cpi->oxcf.intra_mode_cfg.enable_paeth_intra = 0; + cpi->oxcf.intra_mode_cfg.enable_cfl_intra = 0; + cpi->oxcf.intra_mode_cfg.enable_diagonal_intra = 0; + } +} + +static void ext_rate_guided_quantization(AV1_COMP *cpi) { + // Calculation uses 8x8. + const int mb_step = mi_size_wide[cpi->weber_bsize]; + // Accumulate to 16x16, step size is in the unit of mi. + const int block_step = 4; + + const char *filename = cpi->oxcf.rate_distribution_info; + FILE *pfile = fopen(filename, "r"); + if (pfile == NULL) { + assert(pfile != NULL); + return; + } + + double ext_rate_sum = 0.0; + for (int row = 0; row < cpi->frame_info.mi_rows; row += block_step) { + for (int col = 0; col < cpi->frame_info.mi_cols; col += block_step) { + float val; + const int fields_converted = fscanf(pfile, "%f", &val); + if (fields_converted != 1) { + assert(fields_converted == 1); + fclose(pfile); + return; + } + ext_rate_sum += val; + cpi->ext_rate_distribution[(row / mb_step) * cpi->frame_info.mi_cols + + (col / mb_step)] = val; + } + } + fclose(pfile); + + int uniform_rate_sum = 0; + for (int row = 0; row < cpi->frame_info.mi_rows; row += block_step) { + for (int col = 0; col < cpi->frame_info.mi_cols; col += block_step) { + int rate_sum = 0; + for (int r = 0; r < block_step; r += mb_step) { + for (int c = 0; c < block_step; c += mb_step) { + const int mi_row = row + r; + const int mi_col = col + c; + rate_sum += cpi->prep_rate_estimates[(mi_row / mb_step) * + cpi->frame_info.mi_cols + + (mi_col / mb_step)]; + } + } + uniform_rate_sum += rate_sum; + } + } + + const double scale = uniform_rate_sum / ext_rate_sum; + cpi->ext_rate_scale = scale; +} + +void av1_set_mb_wiener_variance(AV1_COMP *cpi) { + AV1_COMMON *const cm = &cpi->common; + const SequenceHeader *const seq_params = cm->seq_params; + if (aom_realloc_frame_buffer( + &cm->cur_frame->buf, cm->width, cm->height, seq_params->subsampling_x, + seq_params->subsampling_y, seq_params->use_highbitdepth, + cpi->oxcf.border_in_pixels, cm->features.byte_alignment, NULL, NULL, + NULL, cpi->image_pyramid_levels, 0)) + aom_internal_error(cm->error, AOM_CODEC_MEM_ERROR, + "Failed to allocate frame buffer"); + av1_alloc_mb_wiener_var_pred_buf(&cpi->common, &cpi->td); + cpi->norm_wiener_variance = 0; + + MACROBLOCK *x = &cpi->td.mb; + MACROBLOCKD *xd = &x->e_mbd; + // xd->mi needs to be setup since it is used in av1_frame_init_quantizer. + MB_MODE_INFO mbmi; + memset(&mbmi, 0, sizeof(mbmi)); + MB_MODE_INFO *mbmi_ptr = &mbmi; + xd->mi = &mbmi_ptr; + cm->quant_params.base_qindex = cpi->oxcf.rc_cfg.cq_level; + av1_frame_init_quantizer(cpi); + + double sum_rec_distortion = 0.0; + double sum_est_rate = 0.0; + + MultiThreadInfo *const mt_info = &cpi->mt_info; + const int num_workers = + AOMMIN(mt_info->num_mod_workers[MOD_AI], mt_info->num_workers); + AV1EncAllIntraMultiThreadInfo *const intra_mt = &mt_info->intra_mt; + intra_mt->intra_sync_read_ptr = av1_row_mt_sync_read_dummy; + intra_mt->intra_sync_write_ptr = av1_row_mt_sync_write_dummy; + // Calculate differential contrast for each block for the entire image. + // TODO(chengchen): properly accumulate the distortion and rate in + // av1_calc_mb_wiener_var_mt(). Until then, call calc_mb_wiener_var() if + // auto_intra_tools_off is true. + if (num_workers > 1 && !cpi->oxcf.intra_mode_cfg.auto_intra_tools_off) { + intra_mt->intra_sync_read_ptr = av1_row_mt_sync_read; + intra_mt->intra_sync_write_ptr = av1_row_mt_sync_write; + av1_calc_mb_wiener_var_mt(cpi, num_workers, &sum_rec_distortion, + &sum_est_rate); + } else { + calc_mb_wiener_var(cpi, &sum_rec_distortion, &sum_est_rate); + } + + // Determine whether to turn off several intra coding tools. + automatic_intra_tools_off(cpi, sum_rec_distortion, sum_est_rate); + + // Read external rate distribution and use it to guide delta quantization + if (cpi->oxcf.enable_rate_guide_deltaq) ext_rate_guided_quantization(cpi); + + const BLOCK_SIZE norm_block_size = cm->seq_params->sb_size; + cpi->norm_wiener_variance = estimate_wiener_var_norm(cpi, norm_block_size); + const int norm_step = mi_size_wide[norm_block_size]; + + double sb_wiener_log = 0; + double sb_count = 0; + for (int its_cnt = 0; its_cnt < 2; ++its_cnt) { + sb_wiener_log = 0; + sb_count = 0; + for (int mi_row = 0; mi_row < cm->mi_params.mi_rows; mi_row += norm_step) { + for (int mi_col = 0; mi_col < cm->mi_params.mi_cols; + mi_col += norm_step) { + int sb_wiener_var = + get_var_perceptual_ai(cpi, norm_block_size, mi_row, mi_col); + + double beta = (double)cpi->norm_wiener_variance / sb_wiener_var; + double min_max_scale = AOMMAX( + 1.0, get_max_scale(cpi, cm->seq_params->sb_size, mi_row, mi_col)); + + beta = AOMMIN(beta, 4); + beta = AOMMAX(beta, 0.25); + + if (beta < 1 / min_max_scale) continue; + + sb_wiener_var = (int)(cpi->norm_wiener_variance / beta); + + int64_t satd = get_satd(cpi, norm_block_size, mi_row, mi_col); + int64_t sse = get_sse(cpi, norm_block_size, mi_row, mi_col); + double scaled_satd = (double)satd / sqrt((double)sse); + sb_wiener_log += scaled_satd * log(sb_wiener_var); + sb_count += scaled_satd; + } + } + + if (sb_count > 0) + cpi->norm_wiener_variance = (int64_t)(exp(sb_wiener_log / sb_count)); + cpi->norm_wiener_variance = AOMMAX(1, cpi->norm_wiener_variance); + } + + // Set the pointer to null since mbmi is only allocated inside this function. + xd->mi = NULL; + aom_free_frame_buffer(&cm->cur_frame->buf); + av1_dealloc_mb_wiener_var_pred_buf(&cpi->td); +} + +static int get_rate_guided_quantizer(AV1_COMP *const cpi, BLOCK_SIZE bsize, + int mi_row, int mi_col) { + // Calculation uses 8x8. + const int mb_step = mi_size_wide[cpi->weber_bsize]; + // Accumulate to 16x16 + const int block_step = mi_size_wide[BLOCK_16X16]; + double sb_rate_hific = 0.0; + double sb_rate_uniform = 0.0; + for (int row = mi_row; row < mi_row + mi_size_wide[bsize]; + row += block_step) { + for (int col = mi_col; col < mi_col + mi_size_high[bsize]; + col += block_step) { + sb_rate_hific += + cpi->ext_rate_distribution[(row / mb_step) * cpi->frame_info.mi_cols + + (col / mb_step)]; + + for (int r = 0; r < block_step; r += mb_step) { + for (int c = 0; c < block_step; c += mb_step) { + const int this_row = row + r; + const int this_col = col + c; + sb_rate_uniform += + cpi->prep_rate_estimates[(this_row / mb_step) * + cpi->frame_info.mi_cols + + (this_col / mb_step)]; + } + } + } + } + sb_rate_hific *= cpi->ext_rate_scale; + + const double weight = 1.0; + const double rate_diff = + weight * (sb_rate_hific - sb_rate_uniform) / sb_rate_uniform; + double scale = pow(2, rate_diff); + + scale = scale * scale; + double min_max_scale = AOMMAX(1.0, get_max_scale(cpi, bsize, mi_row, mi_col)); + scale = 1.0 / AOMMIN(1.0 / scale, min_max_scale); + + AV1_COMMON *const cm = &cpi->common; + const int base_qindex = cm->quant_params.base_qindex; + int offset = + av1_get_deltaq_offset(cm->seq_params->bit_depth, base_qindex, scale); + const DeltaQInfo *const delta_q_info = &cm->delta_q_info; + const int max_offset = delta_q_info->delta_q_res * 10; + offset = AOMMIN(offset, max_offset - 1); + offset = AOMMAX(offset, -max_offset + 1); + int qindex = cm->quant_params.base_qindex + offset; + qindex = AOMMIN(qindex, MAXQ); + qindex = AOMMAX(qindex, MINQ); + if (base_qindex > MINQ) qindex = AOMMAX(qindex, MINQ + 1); + + return qindex; +} + +int av1_get_sbq_perceptual_ai(AV1_COMP *const cpi, BLOCK_SIZE bsize, int mi_row, + int mi_col) { + if (cpi->oxcf.enable_rate_guide_deltaq) { + return get_rate_guided_quantizer(cpi, bsize, mi_row, mi_col); + } + + AV1_COMMON *const cm = &cpi->common; + const int base_qindex = cm->quant_params.base_qindex; + int sb_wiener_var = get_var_perceptual_ai(cpi, bsize, mi_row, mi_col); + int offset = 0; + double beta = (double)cpi->norm_wiener_variance / sb_wiener_var; + double min_max_scale = AOMMAX(1.0, get_max_scale(cpi, bsize, mi_row, mi_col)); + beta = 1.0 / AOMMIN(1.0 / beta, min_max_scale); + + // Cap beta such that the delta q value is not much far away from the base q. + beta = AOMMIN(beta, 4); + beta = AOMMAX(beta, 0.25); + offset = av1_get_deltaq_offset(cm->seq_params->bit_depth, base_qindex, beta); + const DeltaQInfo *const delta_q_info = &cm->delta_q_info; + offset = AOMMIN(offset, delta_q_info->delta_q_res * 20 - 1); + offset = AOMMAX(offset, -delta_q_info->delta_q_res * 20 + 1); + int qindex = cm->quant_params.base_qindex + offset; + qindex = AOMMIN(qindex, MAXQ); + qindex = AOMMAX(qindex, MINQ); + if (base_qindex > MINQ) qindex = AOMMAX(qindex, MINQ + 1); + + return qindex; +} + +void av1_init_mb_ur_var_buffer(AV1_COMP *cpi) { + AV1_COMMON *cm = &cpi->common; + + if (cpi->mb_delta_q) return; + + CHECK_MEM_ERROR(cm, cpi->mb_delta_q, + aom_calloc(cpi->frame_info.mb_rows * cpi->frame_info.mb_cols, + sizeof(*cpi->mb_delta_q))); +} + +#if CONFIG_TFLITE +static int model_predict(BLOCK_SIZE block_size, int num_cols, int num_rows, + int bit_depth, uint8_t *y_buffer, int y_stride, + float *predicts0, float *predicts1) { + // Create the model and interpreter options. + TfLiteModel *model = + TfLiteModelCreate(av1_deltaq4_model_file, av1_deltaq4_model_fsize); + if (model == NULL) return 1; + + TfLiteInterpreterOptions *options = TfLiteInterpreterOptionsCreate(); + TfLiteInterpreterOptionsSetNumThreads(options, 2); + if (options == NULL) { + TfLiteModelDelete(model); + return 1; + } + + // Create the interpreter. + TfLiteInterpreter *interpreter = TfLiteInterpreterCreate(model, options); + if (interpreter == NULL) { + TfLiteInterpreterOptionsDelete(options); + TfLiteModelDelete(model); + return 1; + } + + // Allocate tensors and populate the input tensor data. + TfLiteInterpreterAllocateTensors(interpreter); + TfLiteTensor *input_tensor = TfLiteInterpreterGetInputTensor(interpreter, 0); + if (input_tensor == NULL) { + TfLiteInterpreterDelete(interpreter); + TfLiteInterpreterOptionsDelete(options); + TfLiteModelDelete(model); + return 1; + } + + size_t input_size = TfLiteTensorByteSize(input_tensor); + float *input_data = aom_calloc(input_size, 1); + if (input_data == NULL) { + TfLiteInterpreterDelete(interpreter); + TfLiteInterpreterOptionsDelete(options); + TfLiteModelDelete(model); + return 1; + } + + const int num_mi_w = mi_size_wide[block_size]; + const int num_mi_h = mi_size_high[block_size]; + for (int row = 0; row < num_rows; ++row) { + for (int col = 0; col < num_cols; ++col) { + const int row_offset = (row * num_mi_h) << 2; + const int col_offset = (col * num_mi_w) << 2; + + uint8_t *buf = y_buffer + row_offset * y_stride + col_offset; + int r = row_offset, pos = 0; + const float base = (float)((1 << bit_depth) - 1); + while (r < row_offset + (num_mi_h << 2)) { + for (int c = 0; c < (num_mi_w << 2); ++c) { + input_data[pos++] = bit_depth > 8 + ? (float)*CONVERT_TO_SHORTPTR(buf + c) / base + : (float)*(buf + c) / base; + } + buf += y_stride; + ++r; + } + TfLiteTensorCopyFromBuffer(input_tensor, input_data, input_size); + + // Execute inference. + if (TfLiteInterpreterInvoke(interpreter) != kTfLiteOk) { + TfLiteInterpreterDelete(interpreter); + TfLiteInterpreterOptionsDelete(options); + TfLiteModelDelete(model); + return 1; + } + + // Extract the output tensor data. + const TfLiteTensor *output_tensor = + TfLiteInterpreterGetOutputTensor(interpreter, 0); + if (output_tensor == NULL) { + TfLiteInterpreterDelete(interpreter); + TfLiteInterpreterOptionsDelete(options); + TfLiteModelDelete(model); + return 1; + } + + size_t output_size = TfLiteTensorByteSize(output_tensor); + float output_data[2]; + + TfLiteTensorCopyToBuffer(output_tensor, output_data, output_size); + predicts0[row * num_cols + col] = output_data[0]; + predicts1[row * num_cols + col] = output_data[1]; + } + } + + // Dispose of the model and interpreter objects. + TfLiteInterpreterDelete(interpreter); + TfLiteInterpreterOptionsDelete(options); + TfLiteModelDelete(model); + aom_free(input_data); + return 0; +} + +void av1_set_mb_ur_variance(AV1_COMP *cpi) { + const AV1_COMMON *cm = &cpi->common; + const CommonModeInfoParams *const mi_params = &cm->mi_params; + uint8_t *y_buffer = cpi->source->y_buffer; + const int y_stride = cpi->source->y_stride; + const int block_size = cpi->common.seq_params->sb_size; + const uint32_t bit_depth = cpi->td.mb.e_mbd.bd; + + const int num_mi_w = mi_size_wide[block_size]; + const int num_mi_h = mi_size_high[block_size]; + const int num_cols = (mi_params->mi_cols + num_mi_w - 1) / num_mi_w; + const int num_rows = (mi_params->mi_rows + num_mi_h - 1) / num_mi_h; + + // TODO(sdeng): fit a better model_1; disable it at this time. + float *mb_delta_q0, *mb_delta_q1, delta_q_avg0 = 0.0f; + CHECK_MEM_ERROR(cm, mb_delta_q0, + aom_calloc(num_rows * num_cols, sizeof(float))); + CHECK_MEM_ERROR(cm, mb_delta_q1, + aom_calloc(num_rows * num_cols, sizeof(float))); + + if (model_predict(block_size, num_cols, num_rows, bit_depth, y_buffer, + y_stride, mb_delta_q0, mb_delta_q1)) { + aom_internal_error(cm->error, AOM_CODEC_ERROR, + "Failed to call TFlite functions."); + } + + // Loop through each SB block. + for (int row = 0; row < num_rows; ++row) { + for (int col = 0; col < num_cols; ++col) { + const int index = row * num_cols + col; + delta_q_avg0 += mb_delta_q0[index]; + } + } + + delta_q_avg0 /= (float)(num_rows * num_cols); + + float scaling_factor; + const float cq_level = (float)cpi->oxcf.rc_cfg.cq_level / (float)MAXQ; + if (cq_level < delta_q_avg0) { + scaling_factor = cq_level / delta_q_avg0; + } else { + scaling_factor = 1.0f - (cq_level - delta_q_avg0) / (1.0f - delta_q_avg0); + } + + for (int row = 0; row < num_rows; ++row) { + for (int col = 0; col < num_cols; ++col) { + const int index = row * num_cols + col; + cpi->mb_delta_q[index] = + RINT((float)cpi->oxcf.q_cfg.deltaq_strength / 100.0f * (float)MAXQ * + scaling_factor * (mb_delta_q0[index] - delta_q_avg0)); + } + } + + aom_free(mb_delta_q0); + aom_free(mb_delta_q1); +} +#else // !CONFIG_TFLITE +void av1_set_mb_ur_variance(AV1_COMP *cpi) { + const AV1_COMMON *cm = &cpi->common; + const CommonModeInfoParams *const mi_params = &cm->mi_params; + const MACROBLOCKD *const xd = &cpi->td.mb.e_mbd; + uint8_t *y_buffer = cpi->source->y_buffer; + const int y_stride = cpi->source->y_stride; + const int block_size = cpi->common.seq_params->sb_size; + + const int num_mi_w = mi_size_wide[block_size]; + const int num_mi_h = mi_size_high[block_size]; + const int num_cols = (mi_params->mi_cols + num_mi_w - 1) / num_mi_w; + const int num_rows = (mi_params->mi_rows + num_mi_h - 1) / num_mi_h; + + int *mb_delta_q[2]; + CHECK_MEM_ERROR(cm, mb_delta_q[0], + aom_calloc(num_rows * num_cols, sizeof(*mb_delta_q[0]))); + CHECK_MEM_ERROR(cm, mb_delta_q[1], + aom_calloc(num_rows * num_cols, sizeof(*mb_delta_q[1]))); + + // Approximates the model change between current version (Spet 2021) and the + // baseline (July 2021). + const double model_change[] = { 3.0, 3.0 }; + // The following parameters are fitted from user labeled data. + const double a[] = { -24.50 * 4.0, -17.20 * 4.0 }; + const double b[] = { 0.004898, 0.003093 }; + const double c[] = { (29.932 + model_change[0]) * 4.0, + (42.100 + model_change[1]) * 4.0 }; + int delta_q_avg[2] = { 0, 0 }; + // Loop through each SB block. + for (int row = 0; row < num_rows; ++row) { + for (int col = 0; col < num_cols; ++col) { + double var = 0.0, num_of_var = 0.0; + const int index = row * num_cols + col; + + // Loop through each 8x8 block. + for (int mi_row = row * num_mi_h; + mi_row < mi_params->mi_rows && mi_row < (row + 1) * num_mi_h; + mi_row += 2) { + for (int mi_col = col * num_mi_w; + mi_col < mi_params->mi_cols && mi_col < (col + 1) * num_mi_w; + mi_col += 2) { + struct buf_2d buf; + const int row_offset_y = mi_row << 2; + const int col_offset_y = mi_col << 2; + + buf.buf = y_buffer + row_offset_y * y_stride + col_offset_y; + buf.stride = y_stride; + + unsigned int block_variance; + block_variance = av1_get_perpixel_variance_facade( + cpi, xd, &buf, BLOCK_8X8, AOM_PLANE_Y); + + block_variance = AOMMAX(block_variance, 1); + var += log((double)block_variance); + num_of_var += 1.0; + } + } + var = exp(var / num_of_var); + mb_delta_q[0][index] = RINT(a[0] * exp(-b[0] * var) + c[0]); + mb_delta_q[1][index] = RINT(a[1] * exp(-b[1] * var) + c[1]); + delta_q_avg[0] += mb_delta_q[0][index]; + delta_q_avg[1] += mb_delta_q[1][index]; + } + } + + delta_q_avg[0] = RINT((double)delta_q_avg[0] / (num_rows * num_cols)); + delta_q_avg[1] = RINT((double)delta_q_avg[1] / (num_rows * num_cols)); + + int model_idx; + double scaling_factor; + const int cq_level = cpi->oxcf.rc_cfg.cq_level; + if (cq_level < delta_q_avg[0]) { + model_idx = 0; + scaling_factor = (double)cq_level / delta_q_avg[0]; + } else if (cq_level < delta_q_avg[1]) { + model_idx = 2; + scaling_factor = + (double)(cq_level - delta_q_avg[0]) / (delta_q_avg[1] - delta_q_avg[0]); + } else { + model_idx = 1; + scaling_factor = (double)(MAXQ - cq_level) / (MAXQ - delta_q_avg[1]); + } + + const double new_delta_q_avg = + delta_q_avg[0] + scaling_factor * (delta_q_avg[1] - delta_q_avg[0]); + for (int row = 0; row < num_rows; ++row) { + for (int col = 0; col < num_cols; ++col) { + const int index = row * num_cols + col; + if (model_idx == 2) { + const double delta_q = + mb_delta_q[0][index] + + scaling_factor * (mb_delta_q[1][index] - mb_delta_q[0][index]); + cpi->mb_delta_q[index] = RINT((double)cpi->oxcf.q_cfg.deltaq_strength / + 100.0 * (delta_q - new_delta_q_avg)); + } else { + cpi->mb_delta_q[index] = RINT( + (double)cpi->oxcf.q_cfg.deltaq_strength / 100.0 * scaling_factor * + (mb_delta_q[model_idx][index] - delta_q_avg[model_idx])); + } + } + } + + aom_free(mb_delta_q[0]); + aom_free(mb_delta_q[1]); +} +#endif + +int av1_get_sbq_user_rating_based(AV1_COMP *const cpi, int mi_row, int mi_col) { + const BLOCK_SIZE bsize = cpi->common.seq_params->sb_size; + const CommonModeInfoParams *const mi_params = &cpi->common.mi_params; + AV1_COMMON *const cm = &cpi->common; + const int base_qindex = cm->quant_params.base_qindex; + if (base_qindex == MINQ || base_qindex == MAXQ) return base_qindex; + + const int num_mi_w = mi_size_wide[bsize]; + const int num_mi_h = mi_size_high[bsize]; + const int num_cols = (mi_params->mi_cols + num_mi_w - 1) / num_mi_w; + const int index = (mi_row / num_mi_h) * num_cols + (mi_col / num_mi_w); + const int delta_q = cpi->mb_delta_q[index]; + + int qindex = base_qindex + delta_q; + qindex = AOMMIN(qindex, MAXQ); + qindex = AOMMAX(qindex, MINQ + 1); + + return qindex; +} |