Commit 302d0970 authored by Todd Nguyen's avatar Todd Nguyen Committed by Urvang Joshi
Browse files

Add experiment bgsprite

Work in progress to generate ARF with stitched background image.

Change-Id: I2fea75bbe5ac6f713f53eb5825776dadfc1d98c5
parent bda59df3
......@@ -21,6 +21,8 @@ AV1_CX_SRCS-yes += av1_cx_iface.c
AV1_CX_SRCS-yes += encoder/av1_quantize.c
AV1_CX_SRCS-yes += encoder/av1_quantize.h
AV1_CX_SRCS-yes += encoder/bitstream.c
AV1_CX_SRCS-$(CONFIG_BGSPRITE) += encoder/bgsprite.c
AV1_CX_SRCS-$(CONFIG_BGSPRITE) += encoder/bgsprite.h
AV1_CX_SRCS-yes += encoder/context_tree.c
AV1_CX_SRCS-yes += encoder/context_tree.h
AV1_CX_SRCS-yes += encoder/cost.h
......
/*
* Copyright (c) 2017, 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.
*/
#define _POSIX_C_SOURCE 200112L // rand_r()
#include <assert.h>
#include <float.h>
#include <limits.h>
#include <math.h>
#include <stdlib.h>
#include <time.h>
#include "av1/encoder/bgsprite.h"
#include "aom_mem/aom_mem.h"
#include "av1/common/mv.h"
#include "av1/common/warped_motion.h"
#include "av1/encoder/encoder.h"
#include "av1/encoder/global_motion.h"
#include "av1/encoder/mathutils.h"
#define TRANSFORM_MAT_DIM 3
typedef struct {
#if CONFIG_HIGHBITDEPTH
uint16_t y;
uint16_t u;
uint16_t v;
#else
uint8_t y;
uint8_t u;
uint8_t v;
#endif // CONFIG_HIGHBITDEPTH
} YuvPixel;
// Maps to convert from matrix form to param vector form.
static const int params_to_matrix_map[] = { 2, 3, 0, 4, 5, 1, 6, 7 };
static const int matrix_to_params_map[] = { 2, 5, 0, 1, 3, 4, 6, 7 };
// Convert the parameter array to a 3x3 matrix form.
static void params_to_matrix(const double *const params, double *target) {
for (int i = 0; i < MAX_PARAMDIM - 1; i++) {
assert(params_to_matrix_map[i] < MAX_PARAMDIM - 1);
target[i] = params[params_to_matrix_map[i]];
}
target[8] = 1;
}
// Convert a 3x3 matrix to a parameter array form.
static void matrix_to_params(const double *const matrix, double *target) {
for (int i = 0; i < MAX_PARAMDIM - 1; i++) {
assert(matrix_to_params_map[i] < MAX_PARAMDIM - 1);
target[i] = matrix[matrix_to_params_map[i]];
}
}
// Do matrix multiplication on params.
static void multiply_params(double *const m1, double *const m2,
double *target) {
double m1_matrix[MAX_PARAMDIM];
double m2_matrix[MAX_PARAMDIM];
double result[MAX_PARAMDIM];
params_to_matrix(m1, m1_matrix);
params_to_matrix(m2, m2_matrix);
multiply_mat(m2_matrix, m1_matrix, result, TRANSFORM_MAT_DIM,
TRANSFORM_MAT_DIM, TRANSFORM_MAT_DIM);
matrix_to_params(result, target);
}
// Finds x and y limits of a single transformed image.
// Width and height are the size of the input video.
static void find_frame_limit(int width, int height,
const double *const transform, int *x_min,
int *x_max, int *y_min, int *y_max) {
double transform_matrix[MAX_PARAMDIM];
double xy_matrix[3] = { 0, 0, 1 };
double uv_matrix[3] = { 0 };
// Macro used to update frame limits based on transformed coordinates.
#define UPDATELIMITS(u, v, x_min, x_max, y_min, y_max) \
{ \
if ((int)ceil(u) > *x_max) { \
*x_max = (int)ceil(u); \
} \
if ((int)floor(u) < *x_min) { \
*x_min = (int)floor(u); \
} \
if ((int)ceil(v) > *y_max) { \
*y_max = (int)ceil(v); \
} \
if ((int)floor(v) < *y_min) { \
*y_min = (int)floor(v); \
} \
}
params_to_matrix(transform, transform_matrix);
xy_matrix[0] = 0;
xy_matrix[1] = 0;
multiply_mat(transform_matrix, xy_matrix, uv_matrix, TRANSFORM_MAT_DIM,
TRANSFORM_MAT_DIM, 1);
*x_max = (int)ceil(uv_matrix[0]);
*x_min = (int)floor(uv_matrix[0]);
*y_max = (int)ceil(uv_matrix[1]);
*y_min = (int)floor(uv_matrix[1]);
xy_matrix[0] = width;
xy_matrix[1] = 0;
multiply_mat(transform_matrix, xy_matrix, uv_matrix, TRANSFORM_MAT_DIM,
TRANSFORM_MAT_DIM, 1);
UPDATELIMITS(uv_matrix[0], uv_matrix[1], x_min, x_max, y_min, y_max);
xy_matrix[0] = width;
xy_matrix[1] = height;
multiply_mat(transform_matrix, xy_matrix, uv_matrix, TRANSFORM_MAT_DIM,
TRANSFORM_MAT_DIM, 1);
UPDATELIMITS(uv_matrix[0], uv_matrix[1], x_min, x_max, y_min, y_max);
xy_matrix[0] = 0;
xy_matrix[1] = height;
multiply_mat(transform_matrix, xy_matrix, uv_matrix, TRANSFORM_MAT_DIM,
TRANSFORM_MAT_DIM, 1);
UPDATELIMITS(uv_matrix[0], uv_matrix[1], x_min, x_max, y_min, y_max);
#undef UPDATELIMITS
}
// Finds x and y limits for arrays. Also finds the overall max and minimums
static void find_limits(int width, int height, const double **const params,
int num_frames, int *x_min, int *x_max, int *y_min,
int *y_max, int *pano_x_min, int *pano_x_max,
int *pano_y_min, int *pano_y_max) {
*pano_x_max = INT_MIN;
*pano_x_min = INT_MAX;
*pano_y_max = INT_MIN;
*pano_y_min = INT_MAX;
for (int i = 0; i < num_frames; ++i) {
find_frame_limit(width, height, (const double *const)params[i], &x_min[i],
&x_max[i], &y_min[i], &y_max[i]);
if (x_max[i] > *pano_x_max) {
*pano_x_max = x_max[i];
}
if (x_min[i] < *pano_x_min) {
*pano_x_min = x_min[i];
}
if (y_max[i] > *pano_y_max) {
*pano_y_max = y_max[i];
}
if (y_min[i] < *pano_y_min) {
*pano_y_min = y_min[i];
}
}
}
// Inverts a 3x3 matrix that is in the parameter form.
static void invert_params(const double *const params, double *target) {
double temp[MAX_PARAMDIM] = { 0 };
params_to_matrix(params, temp);
// Find determinant of matrix (expansion by minors).
const double det = temp[0] * ((temp[4] * temp[8]) - (temp[5] * temp[7])) -
temp[1] * ((temp[3] * temp[8]) - (temp[5] * temp[6])) +
temp[2] * ((temp[3] * temp[7]) - (temp[4] * temp[6]));
assert(det != 0);
// inverse is transpose of cofactor * 1/det.
double inverse[MAX_PARAMDIM] = { 0 };
inverse[0] = (temp[4] * temp[8] - temp[7] * temp[5]) / det;
inverse[1] = (temp[2] * temp[7] - temp[1] * temp[8]) / det;
inverse[2] = (temp[1] * temp[5] - temp[2] * temp[4]) / det;
inverse[3] = (temp[5] * temp[6] - temp[3] * temp[8]) / det;
inverse[4] = (temp[0] * temp[8] - temp[2] * temp[6]) / det;
inverse[5] = (temp[3] * temp[2] - temp[0] * temp[5]) / det;
inverse[6] = (temp[3] * temp[7] - temp[6] * temp[4]) / det;
inverse[7] = (temp[6] * temp[1] - temp[0] * temp[7]) / det;
inverse[8] = (temp[0] * temp[4] - temp[3] * temp[1]) / det;
matrix_to_params(inverse, target);
}
// swap_yuvs two YuvPixels.
static void swap_yuv(YuvPixel *a, YuvPixel *b) {
const YuvPixel temp = *b;
*b = *a;
*a = temp;
}
// Partitions array to find pivot index in qselect.
static int partition(YuvPixel arr[], int left, int right, int pivot_idx) {
YuvPixel pivot = arr[pivot_idx];
// Move pivot to the end.
swap_yuv(&arr[pivot_idx], &arr[right]);
int p_idx = left;
for (int i = left; i < right; ++i) {
if (arr[i].y <= pivot.y) {
swap_yuv(&arr[i], &arr[p_idx]);
p_idx++;
}
}
swap_yuv(&arr[p_idx], &arr[right]);
return p_idx;
}
// Returns the kth element in array, partially sorted in place (quickselect).
static YuvPixel qselect(YuvPixel arr[], int left, int right, int k) {
if (left >= right) {
return arr[left];
}
unsigned int seed = time(NULL);
int pivot_idx = left + rand_r(&seed) % (right - left + 1);
pivot_idx = partition(arr, left, right, pivot_idx);
if (k == pivot_idx) {
return arr[k];
} else if (k < pivot_idx) {
return qselect(arr, left, pivot_idx - 1, k);
} else {
return qselect(arr, pivot_idx + 1, right, k);
}
}
// Stitches images together to create ARF and stores it in 'panorama'.
static void stitch_images(YV12_BUFFER_CONFIG **const frames,
const int num_frames, const double **const params,
const int *const x_min, const int *const x_max,
const int *const y_min, const int *const y_max,
int pano_x_min, int pano_x_max, int pano_y_min,
int pano_y_max, YV12_BUFFER_CONFIG *panorama) {
const int width = pano_x_max - pano_x_min + 1;
const int height = pano_y_max - pano_y_min + 1;
// Create temp_pano[y][x][num_frames] stack of pixel values
YuvPixel ***temp_pano = aom_malloc(height * sizeof(*temp_pano));
for (int i = 0; i < height; ++i) {
temp_pano[i] = aom_malloc(width * sizeof(**temp_pano));
for (int j = 0; j < width; ++j) {
temp_pano[i][j] = aom_malloc(num_frames * sizeof(***temp_pano));
}
}
// Create count[y][x] to count how many values in stack for median filtering
int **count = aom_malloc(height * sizeof(*count));
for (int i = 0; i < height; ++i) {
count[i] = aom_calloc(width, sizeof(**count)); // counts initialized to 0
}
// Re-sample images onto panorama (pre-median filtering).
const int x_offset = -pano_x_min;
const int y_offset = -pano_y_min;
const int frame_width = frames[0]->y_width;
const int frame_height = frames[0]->y_height;
for (int i = 0; i < num_frames; ++i) {
// Find transforms from panorama coordinate system back to single image
// coordinate system for sampling.
int transformed_width = x_max[i] - x_min[i] + 1;
int transformed_height = y_max[i] - y_min[i] + 1;
double transform_matrix[MAX_PARAMDIM];
double transform_params[MAX_PARAMDIM - 1];
invert_params(params[i], transform_params);
params_to_matrix(transform_params, transform_matrix);
#if CONFIG_HIGHBITDEPTH
const uint16_t *y_buffer16 = CONVERT_TO_SHORTPTR(frames[i]->y_buffer);
const uint16_t *u_buffer16 = CONVERT_TO_SHORTPTR(frames[i]->u_buffer);
const uint16_t *v_buffer16 = CONVERT_TO_SHORTPTR(frames[i]->v_buffer);
#endif
for (int y = 0; y < transformed_height; ++y) {
for (int x = 0; x < transformed_width; ++x) {
// Do transform.
double xy_matrix[3] = { x + x_min[i], y + y_min[i], 1 };
double uv_matrix[3] = { 0 };
multiply_mat(transform_matrix, xy_matrix, uv_matrix, TRANSFORM_MAT_DIM,
TRANSFORM_MAT_DIM, 1);
int image_x = (int)round(uv_matrix[0]);
int image_y = (int)round(uv_matrix[1]);
// Check if valid point in original image.
if (image_x >= 0 && image_x < frame_width && image_y >= 0 &&
image_y < frame_height) {
// Place in panorama stack.
int pano_x = x + x_min[i] + x_offset;
int pano_y = y + y_min[i] + y_offset;
int ychannel_idx = image_y * frames[i]->y_stride + image_x;
int uvchannel_idx =
(image_y >> frames[i]->subsampling_y) * frames[i]->uv_stride +
(image_x >> frames[i]->subsampling_x);
#if CONFIG_HIGHBITDEPTH
if (frames[i]->flags & YV12_FLAG_HIGHBITDEPTH) {
temp_pano[pano_y][pano_x][count[pano_y][pano_x]].y =
y_buffer16[ychannel_idx];
temp_pano[pano_y][pano_x][count[pano_y][pano_x]].u =
u_buffer16[uvchannel_idx];
temp_pano[pano_y][pano_x][count[pano_y][pano_x]].v =
v_buffer16[uvchannel_idx];
} else {
#endif // CONFIG_HIGHBITDEPTH
temp_pano[pano_y][pano_x][count[pano_y][pano_x]].y =
frames[i]->y_buffer[ychannel_idx];
temp_pano[pano_y][pano_x][count[pano_y][pano_x]].u =
frames[i]->u_buffer[uvchannel_idx];
temp_pano[pano_y][pano_x][count[pano_y][pano_x]].v =
frames[i]->v_buffer[uvchannel_idx];
// Update count.
count[pano_y][pano_x]++;
#if CONFIG_HIGHBITDEPTH
}
#endif // CONFIG_HIGHBITDEPTH
}
}
}
}
// Apply median filtering using quickselect.
for (int y = 0; y < height; ++y) {
for (int x = 0; x < width; ++x) {
if (count[y][x] == 0) {
// Just make the pixel black.
// TODO(toddnguyen): Color the pixel with nearest neighbor
} else {
// Find
const int median_idx = (int)floor(count[y][x] / 2);
YuvPixel median =
qselect(temp_pano[y][x], 0, count[y][x] - 1, median_idx);
// Make the median value the 0th index for UV subsampling later
temp_pano[y][x][0] = median;
assert(median.y == temp_pano[y][x][0].y &&
median.u == temp_pano[y][x][0].u &&
median.v == temp_pano[y][x][0].v);
}
}
}
// NOTE(toddnguyen): Right now the ARF in the cpi struct is fixed size at the
// same size as the frames. For now, we crop the generated panorama.
assert(panorama->y_width < width && panorama->y_height < height);
const int crop_x_offset = (width - panorama->y_width) / 2;
const int crop_y_offset = (height - panorama->y_height) / 2;
#if CONFIG_HIGHBITDEPTH
if (panorama->flags & YV12_FLAG_HIGHBITDEPTH) {
// Use median Y value.
uint16_t *pano_y_buffer16 = CONVERT_TO_SHORTPTR(panorama->y_buffer);
for (int y = 0; y < panorama->y_height; ++y) {
for (int x = 0; x < panorama->y_width; ++x) {
const int ychannel_idx = y * panorama->y_stride + x;
if (count[y + crop_y_offset][x + crop_x_offset] > 0) {
pano_y_buffer16[ychannel_idx] =
temp_pano[y + crop_y_offset][x + crop_x_offset][0].y;
} else {
pano_y_buffer16[ychannel_idx] = 0;
}
}
}
// UV subsampling with median UV values
uint16_t *pano_u_buffer16 = CONVERT_TO_SHORTPTR(panorama->u_buffer);
uint16_t *pano_v_buffer16 = CONVERT_TO_SHORTPTR(panorama->v_buffer);
for (int y = 0; y < panorama->uv_height; ++y) {
for (int x = 0; x < panorama->uv_width; ++x) {
uint32_t avg_count = 0;
uint32_t u_sum = 0;
uint32_t v_sum = 0;
// Look at surrounding pixels for subsampling
for (int s_x = 0; s_x < panorama->subsampling_x + 1; ++s_x) {
for (int s_y = 0; s_y < panorama->subsampling_y + 1; ++s_y) {
int y_sample = crop_y_offset + (y << panorama->subsampling_y) + s_y;
int x_sample = crop_x_offset + (x << panorama->subsampling_x) + s_x;
if (y_sample > 0 && y_sample < height && x_sample > 0 &&
x_sample < width && count[y_sample][x_sample] > 0) {
u_sum += temp_pano[y_sample][x_sample][0].u;
v_sum += temp_pano[y_sample][x_sample][0].v;
avg_count++;
}
}
}
const int uvchannel_idx = y * panorama->uv_stride + x;
if (avg_count != 0) {
pano_u_buffer16[uvchannel_idx] = (uint16_t)OD_DIVU(u_sum, avg_count);
pano_v_buffer16[uvchannel_idx] = (uint16_t)OD_DIVU(v_sum, avg_count);
} else {
pano_u_buffer16[uvchannel_idx] = 0;
pano_v_buffer16[uvchannel_idx] = 0;
}
}
}
} else {
#endif // CONFIG_HIGHBITDEPTH
// Use median Y value.
for (int y = 0; y < panorama->y_height; ++y) {
for (int x = 0; x < panorama->y_width; ++x) {
const int ychannel_idx = y * panorama->y_stride + x;
if (count[y + crop_y_offset][x + crop_x_offset] > 0) {
panorama->y_buffer[ychannel_idx] =
temp_pano[y + crop_y_offset][x + crop_x_offset][0].y;
} else {
panorama->y_buffer[ychannel_idx] = 0;
}
}
}
// UV subsampling with median UV values
for (int y = 0; y < panorama->uv_height; ++y) {
for (int x = 0; x < panorama->uv_width; ++x) {
uint16_t avg_count = 0;
uint16_t u_sum = 0;
uint16_t v_sum = 0;
// Look at surrounding pixels for subsampling
for (int s_x = 0; s_x < panorama->subsampling_x + 1; ++s_x) {
for (int s_y = 0; s_y < panorama->subsampling_y + 1; ++s_y) {
int y_sample = crop_y_offset + (y << panorama->subsampling_y) + s_y;
int x_sample = crop_x_offset + (x << panorama->subsampling_x) + s_x;
if (y_sample > 0 && y_sample < height && x_sample > 0 &&
x_sample < width && count[y_sample][x_sample] > 0) {
u_sum += temp_pano[y_sample][x_sample][0].u;
v_sum += temp_pano[y_sample][x_sample][0].v;
avg_count++;
}
}
}
const int uvchannel_idx = y * panorama->uv_stride + x;
if (avg_count != 0) {
panorama->u_buffer[uvchannel_idx] =
(uint8_t)OD_DIVU(u_sum, avg_count);
panorama->v_buffer[uvchannel_idx] =
(uint8_t)OD_DIVU(v_sum, avg_count);
} else {
panorama->u_buffer[uvchannel_idx] = 0;
panorama->v_buffer[uvchannel_idx] = 0;
}
}
}
#if CONFIG_HIGHBITDEPTH
}
#endif // CONFIG_HIGHBITDEPTH
for (int i = 0; i < height; ++i) {
for (int j = 0; j < width; ++j) {
aom_free(temp_pano[i][j]);
}
aom_free(temp_pano[i]);
aom_free(count[i]);
}
aom_free(count);
aom_free(temp_pano);
}
int av1_background_sprite(AV1_COMP *cpi, int distance) {
YV12_BUFFER_CONFIG *frames[MAX_LAG_BUFFERS] = { NULL };
int inliers_by_motion[RANSAC_NUM_MOTIONS];
static const double identity_params[MAX_PARAMDIM - 1] = {
0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 0.0
};
// Get frames to be included in background sprite.
frames[0] = cpi->source;
for (int frame = 0; frame < distance; ++frame) {
struct lookahead_entry *buf = av1_lookahead_peek(cpi->lookahead, frame);
frames[frame + 1] = &buf->img;
}
// Allocate empty arrays for parameters between frames.
double **params = aom_malloc((distance + 1) * sizeof(*params));
for (int i = 0; i < distance + 1; ++i) {
params[i] = aom_malloc(sizeof(identity_params));
memcpy(params[i], identity_params, sizeof(identity_params));
}
// Use global motion to find affine transformations between frames.
// params[i] will have the transform from frame[i] to frame[i-1].
// params[0] will have the identity matrix because it has no previous frame.
TransformationType model = AFFINE;
for (int frame = 0; frame < distance; ++frame) {
const int global_motion_ret = compute_global_motion_feature_based(
model, frames[frame + 1], frames[frame],
#if CONFIG_HIGHBITDEPTH
cpi->common.bit_depth,
#endif // CONFIG_HIGHBITDEPTH
inliers_by_motion, params[frame + 1], RANSAC_NUM_MOTIONS);
// Quit if global motion had an error.
if (global_motion_ret == 0) {
for (int i = 0; i < distance + 1; ++i) {
aom_free(params[i]);
}
aom_free(params);
return 1;
}
}
// Compound the transformation parameters.
for (int i = 1; i < distance + 1; ++i) {
multiply_params(params[i - 1], params[i], params[i]);
}
// Compute frame limits for final stitched images.
int pano_x_max = INT_MIN;
int pano_x_min = INT_MAX;
int pano_y_max = INT_MIN;
int pano_y_min = INT_MAX;
int *x_max = aom_malloc((distance + 1) * sizeof(*x_max));
int *x_min = aom_malloc((distance + 1) * sizeof(*x_min));
int *y_max = aom_malloc((distance + 1) * sizeof(*y_max));
int *y_min = aom_malloc((distance + 1) * sizeof(*y_min));
find_limits(cpi->initial_width, cpi->initial_height,
(const double **const)params, distance + 1, x_min, x_max, y_min,
y_max, &pano_x_min, &pano_x_max, &pano_y_min, &pano_y_max);
// Estimate center image based on frame limits.
const double pano_center_x = (pano_x_max + pano_x_min) / 2;
const double pano_center_y = (pano_y_max + pano_y_min) / 2;
double nearest_distance = DBL_MAX;
int center_idx = -1;
for (int i = 0; i < distance + 1; ++i) {
const double image_center_x = (x_max[i] + x_min[i]) / 2;
const double image_center_y = (y_max[i] + y_min[i]) / 2;
const double distance_from_center = pow(pano_center_x - image_center_x, 2) +
pow(pano_center_y + image_center_y, 2);
if (distance_from_center < nearest_distance) {
center_idx = i;
nearest_distance = distance_from_center;
}
}
assert(center_idx != -1);
// Recompute transformations to adjust to center image.
// Invert center image's transform.
double inverse[MAX_PARAMDIM - 1] = { 0 };
invert_params(params[center_idx], inverse);
// Multiply the inverse to all transformation parameters.
for (int i = 0; i < distance + 1; ++i) {
multiply_params(inverse, params[i], params[i]);
}
// Recompute frame limits for new adjusted center.
find_limits(cpi->initial_width, cpi->initial_height,
(const double **const)params, distance + 1, x_min, x_max, y_min,
y_max, &pano_x_min, &pano_x_max, &pano_y_min, &pano_y_max);
// Stitch Images.
stitch_images(frames, distance + 1, (const double **const)params, x_min,
x_max, y_min, y_max, pano_x_min, pano_x_max, pano_y_min,
pano_y_max, &cpi->alt_ref_buffer);
// Free memory.
for (int i = 0; i < distance + 1; ++i) {
aom_free(params[i]);
}
aom_free(params);
aom_free(x_max);
aom_free(x_min);
aom_free(y_max);
aom_free(y_min);
return 0;
}
/*
* Copyright (c) 2017, 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