ref: 0fdc9af7b2b3445ba72a8d9ae68383d0bbc1b929
parent: 181631ac16af6e58a11f228bb137d61e23ddc253
parent: 316e7f62dbd13ff6de6df2e82376f4033a9ff4d5
author: Angie Chiang <[email protected]>
date: Thu Mar 14 13:22:09 EDT 2019
Merge changes Ifc006890,I753920a6 * changes: Apply kmeans on log of wiener_variance Add vp9_kmeans()
--- a/vp9/encoder/vp9_encodeframe.c
+++ b/vp9/encoder/vp9_encodeframe.c
@@ -3583,6 +3583,8 @@
int row, col;
int64_t rdmult;
int64_t wiener_variance = 0;
+ KMEANS_DATA *kmeans_data;
+ vpx_clear_system_state();
assert(cpi->norm_wiener_variance > 0);
@@ -3590,10 +3592,12 @@
for (col = mb_col_start; col < mb_col_end; ++col)
wiener_variance += cpi->mb_wiener_variance[row * cm->mb_cols + col];
+ kmeans_data = &cpi->kmeans_data_arr[cpi->kmeans_data_size++];
+ kmeans_data->value = log(1 + wiener_variance);
+ kmeans_data->pos = mi_row * cpi->kmeans_data_stride + mi_col;
if (wiener_variance)
wiener_variance /=
(mb_row_end - mb_row_start) * (mb_col_end - mb_col_start);
-
rdmult = (orig_rdmult * wiener_variance) / cpi->norm_wiener_variance;
rdmult = VPXMIN(rdmult, orig_rdmult * 3);
@@ -5673,6 +5677,89 @@
}
#endif
+static int compare_kmeans_data(const void *a, const void *b) {+ if (((const KMEANS_DATA *)a)->value > ((const KMEANS_DATA *)b)->value) {+ return 1;
+ } else if (((const KMEANS_DATA *)a)->value <
+ ((const KMEANS_DATA *)b)->value) {+ return -1;
+ } else {+ return 0;
+ }
+}
+
+void vp9_kmeans(double *ctr_ls, int k, KMEANS_DATA *arr, int size) {+ double min, max;
+ double step;
+ int i, j;
+ int itr;
+ double boundary_ls[MAX_KMEANS_GROUPS] = { 0 };+ int group_idx;
+ double sum;
+ int count;
+
+ vpx_clear_system_state();
+
+ assert(k >= 2 && k <= MAX_KMEANS_GROUPS);
+
+ qsort(arr, size, sizeof(*arr), compare_kmeans_data);
+
+ min = arr[0].value;
+ max = arr[size - 1].value;
+
+ // initialize the center points
+ step = (max - min) * 1. / k;
+ for (j = 0; j < k; ++j) {+ ctr_ls[j] = min + j * step + step / 2;
+ }
+
+ for (itr = 0; itr < 10; ++itr) {+ for (j = 0; j < k - 1; ++j) {+ boundary_ls[j] = (ctr_ls[j] + ctr_ls[j + 1]) / 2.;
+ }
+ boundary_ls[k - 1] = max + 1;
+
+ group_idx = 0;
+ count = 0;
+ sum = 0;
+ for (i = 0; i < size; ++i) {+ while (arr[i].value >= boundary_ls[group_idx]) {+ ++group_idx;
+ if (group_idx == k - 1) {+ break;
+ }
+ }
+
+ sum += arr[i].value;
+ ++count;
+
+ if (i + 1 == size || arr[i + 1].value >= boundary_ls[group_idx]) {+ if (count > 0) {+ ctr_ls[group_idx] = sum / count;
+ }
+ count = 0;
+ sum = 0;
+ }
+ }
+ }
+
+ // compute group_idx
+ for (j = 0; j < k - 1; ++j) {+ boundary_ls[j] = (ctr_ls[j] + ctr_ls[j + 1]) / 2.;
+ }
+ boundary_ls[k - 1] = max + 1;
+ group_idx = 0;
+ for (i = 0; i < size; ++i) {+ while (arr[i].value >= boundary_ls[group_idx]) {+ ++group_idx;
+ if (group_idx == k - 1) {+ break;
+ }
+ }
+ arr[i].group_idx = group_idx;
+ }
+}
+
static void encode_frame_internal(VP9_COMP *cpi) {SPEED_FEATURES *const sf = &cpi->sf;
ThreadData *const td = &cpi->td;
@@ -5782,6 +5869,11 @@
}
#endif
+ if (cpi->sf.enable_wiener_variance && cm->show_frame) {+ cpi->kmeans_data_size = 0;
+ cpi->kmeans_ctr_num = 5;
+ }
+
if (!cpi->row_mt) {cpi->row_mt_sync_read_ptr = vp9_row_mt_sync_read_dummy;
cpi->row_mt_sync_write_ptr = vp9_row_mt_sync_write_dummy;
@@ -5795,6 +5887,11 @@
cpi->row_mt_sync_read_ptr = vp9_row_mt_sync_read;
cpi->row_mt_sync_write_ptr = vp9_row_mt_sync_write;
vp9_encode_tiles_row_mt(cpi);
+ }
+
+ if (cpi->sf.enable_wiener_variance && cm->show_frame) {+ vp9_kmeans(cpi->kmeans_ctr_ls, cpi->kmeans_ctr_num, cpi->kmeans_data_arr,
+ cpi->kmeans_data_size);
}
vpx_usec_timer_mark(&emr_timer);
--- a/vp9/encoder/vp9_encodeframe.h
+++ b/vp9/encoder/vp9_encodeframe.h
@@ -45,6 +45,9 @@
void vp9_set_variance_partition_thresholds(struct VP9_COMP *cpi, int q,
int content_state);
+struct KMEANS_DATA;
+void vp9_kmeans(double *ctr_ls, int k, struct KMEANS_DATA *arr, int size);
+
#ifdef __cplusplus
} // extern "C"
#endif
--- a/vp9/encoder/vp9_encoder.c
+++ b/vp9/encoder/vp9_encoder.c
@@ -2388,6 +2388,7 @@
sizeof(*cpi->mb_wiener_variance)));
}
+ cpi->kmeans_data_arr_alloc = 0;
#if CONFIG_NON_GREEDY_MV
cpi->feature_score_loc_alloc = 0;
cpi->tpl_ready = 0;
@@ -2591,6 +2592,10 @@
vp9_denoiser_free(&(cpi->denoiser));
#endif
+ if (cpi->kmeans_data_arr_alloc) {+ vpx_free(cpi->kmeans_data_arr);
+ }
+
#if CONFIG_NON_GREEDY_MV
vpx_free(cpi->feature_score_loc_arr);
vpx_free(cpi->feature_score_loc_sort);
@@ -7248,6 +7253,16 @@
if (cpi->oxcf.pass != 0 || cpi->use_svc || frame_is_intra_only(cm) == 1) {for (i = 0; i < REFS_PER_FRAME; ++i) cpi->scaled_ref_idx[i] = INVALID_IDX;
+ }
+
+ if (cpi->kmeans_data_arr_alloc == 0) {+ const int mi_cols = mi_cols_aligned_to_sb(cm->mi_cols);
+ const int mi_rows = mi_cols_aligned_to_sb(cm->mi_rows);
+ CHECK_MEM_ERROR(
+ cm, cpi->kmeans_data_arr,
+ vpx_calloc(mi_rows * mi_cols, sizeof(*cpi->kmeans_data_arr)));
+ cpi->kmeans_data_stride = mi_cols;
+ cpi->kmeans_data_arr_alloc = 1;
}
if (gf_group_index == 1 &&
--- a/vp9/encoder/vp9_encoder.h
+++ b/vp9/encoder/vp9_encoder.h
@@ -567,6 +567,14 @@
} FEATURE_SCORE_LOC;
#endif
+#define MAX_KMEANS_GROUPS 8
+
+typedef struct KMEANS_DATA {+ double value;
+ int pos;
+ int group_idx;
+} KMEANS_DATA;
+
typedef struct VP9_COMP {QUANTS quants;
ThreadData td;
@@ -594,6 +602,12 @@
TplDepFrame tpl_stats[MAX_ARF_GOP_SIZE];
YV12_BUFFER_CONFIG *tpl_recon_frames[REF_FRAMES];
EncFrameBuf enc_frame_buf[REF_FRAMES];
+ int kmeans_data_arr_alloc;
+ KMEANS_DATA *kmeans_data_arr;
+ int kmeans_data_size;
+ int kmeans_data_stride;
+ double kmeans_ctr_ls[MAX_KMEANS_GROUPS];
+ int kmeans_ctr_num;
#if CONFIG_NON_GREEDY_MV
int tpl_ready;
int feature_score_loc_alloc;