ref: 4c1434e88c875544a83ca6b2cc6d18ac6ba4ffc8
parent: bb0e75463cf7ac1fd58711f0c54724261011f9aa
author: Angie Chiang <angiebird@google.com>
date: Wed Sep 19 12:44:40 EDT 2018
Add feature score for each block The feature score is used to indicate whether a block's mv is reliable or not. Now we use Harris Corner Detector method to compute the score. Change-Id: Ibbe7a1c1f3391d0bf4b03307eaabb5cc3cfb1360
--- a/tools/non_greedy_mv/non_greedy_mv.py
+++ b/tools/non_greedy_mv/non_greedy_mv.py
@@ -84,6 +84,14 @@
return rgb / 255.
+def read_feature_score(fp, mv_rows, mv_cols):
+ line = fp.readline()
+ word_ls = line.split()
+ feature_score = np.array([float(v) for v in word_ls])
+ feature_score = feature_score.reshape(mv_rows, mv_cols)
+ return feature_score
+
+
def read_frame_dpl_stats(fp):
line = fp.readline()
word_ls = line.split()
@@ -105,12 +113,13 @@
mv_ls.append([col, row, mv_col, mv_row])
mv_ls = np.array(mv_ls)
img = yuv_to_rgb(read_frame(fp))
+ feature_score = read_feature_score(fp, mv_rows, mv_cols)
ref = None
line = fp.readline()
word_ls = line.split()
if int(word_ls[1]):
ref = yuv_to_rgb(read_frame(fp))
- return frame_idx, mv_ls, img, ref, bs
+ return frame_idx, mv_ls, img, ref, bs, feature_score
def read_dpl_stats_file(filename, frame_num=0):
@@ -131,8 +140,8 @@
if __name__ == '__main__':
filename = sys.argv[1]
data_ls = read_dpl_stats_file(filename, frame_num=5)
- for frame_idx, mv_ls, img, ref, bs in data_ls:
- fig, axes = plt.subplots(1, 2)
+ for frame_idx, mv_ls, img, ref, bs, feature_score in data_ls:
+ fig, axes = plt.subplots(1, 3)
axes[0].imshow(img)
draw_mv_ls(axes[0], mv_ls)
@@ -148,6 +157,8 @@
#axes[1].grid(color='k', linestyle='-')
axes[1].set_ylim(ref.shape[0], 0)
axes[1].set_xlim(0, ref.shape[1])
+
+ axes[2].imshow(feature_score)
plt.show()
print frame_idx, len(mv_ls)
--- a/vp9/encoder/vp9_encoder.c
+++ b/vp9/encoder/vp9_encoder.c
@@ -5730,6 +5730,7 @@
tpl_ptr->sse_arr[rf_idx] = src_stats->sse_arr[rf_idx];
tpl_ptr->mv_arr[rf_idx].as_int = src_stats->mv_arr[rf_idx].as_int;
}
+ tpl_ptr->feature_score = src_stats->feature_score;
#endif
tpl_ptr->intra_cost = intra_cost;
tpl_ptr->inter_cost = inter_cost;
@@ -5845,6 +5846,31 @@
}
}
+#if CONFIG_NON_GREEDY_MV
+double get_feature_score(uint8_t *buf, ptrdiff_t stride, int rows, int cols) {
+ double IxIx = 0;
+ double IxIy = 0;
+ double IyIy = 0;
+ double score;
+ int r, c;
+ vpx_clear_system_state();
+ for (r = 0; r + 1 < rows; ++r) {
+ for (c = 0; c + 1 < cols; ++c) {
+ int diff_x = buf[r * stride + c] - buf[r * stride + c + 1];
+ int diff_y = buf[r * stride + c] - buf[(r + 1) * stride + c];
+ IxIx += diff_x * diff_x;
+ IxIy += diff_x * diff_y;
+ IyIy += diff_y * diff_y;
+ }
+ }
+ IxIx /= (rows - 1) * (cols - 1);
+ IxIy /= (rows - 1) * (cols - 1);
+ IyIy /= (rows - 1) * (cols - 1);
+ score = IxIx * IyIy - IxIy * IxIy - 0.04 * (IxIx + IyIy) * (IxIx + IyIy);
+ return score;
+}
+#endif
+
void mode_estimation(VP9_COMP *cpi, MACROBLOCK *x, MACROBLOCKD *xd,
struct scale_factors *sf, GF_PICTURE *gf_picture,
int frame_idx, int16_t *src_diff, tran_low_t *coeff,
@@ -5916,6 +5942,11 @@
x->mv_limits.col_max =
((cm->mi_cols - 1 - mi_col) * MI_SIZE) + (17 - 2 * VP9_INTERP_EXTEND);
+#if CONFIG_NON_GREEDY_MV
+ tpl_stats->feature_score = get_feature_score(
+ xd->cur_buf->y_buffer + mb_y_offset, xd->cur_buf->y_stride, bw, bh);
+#endif
+
for (rf_idx = 0; rf_idx < 3; ++rf_idx) {
int_mv mv;
if (ref_frame[rf_idx] == NULL) {
@@ -6133,6 +6164,17 @@
}
dump_frame_buf(gf_picture[frame_idx].frame);
+
+ for (mi_row = 0; mi_row < cm->mi_rows; ++mi_row) {
+ for (mi_col = 0; mi_col < cm->mi_cols; ++mi_col) {
+ if ((mi_row % mi_height) == 0 && (mi_col % mi_width) == 0) {
+ const TplDepStats *tpl_ptr =
+ &tpl_frame->tpl_stats_ptr[mi_row * tpl_frame->stride + mi_col];
+ printf("%f ", tpl_ptr->feature_score);
+ }
+ }
+ }
+ printf("\n");
rf_idx = gf_picture[frame_idx].ref_frame[idx];
printf("has_ref %d\n", rf_idx != -1);
--- a/vp9/encoder/vp9_encoder.h
+++ b/vp9/encoder/vp9_encoder.h
@@ -295,6 +295,7 @@
int64_t recon_error_arr[3];
int64_t sse_arr[3];
int_mv mv_arr[3];
+ double feature_score;
#endif
} TplDepStats;