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mlt/src/modules/motion_est/filter_motion_est.c

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/*
* /brief fast motion estimation filter
* /author Zachary Drew, Copyright 2005
*
* Currently only uses Gamma data for comparisonon (bug or feature?)
* SSE optimized where available.
*
* Vector orientation: The vector data that is generated for the current frame specifies
* the motion from the previous frame to the current frame. To know how a macroblock
* in the current frame will move in the future, the next frame is needed.
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
#include "filter_motion_est.h"
#include <framework/mlt.h>
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <string.h>
#include <sys/time.h>
#include <unistd.h>
#ifndef __DARWIN__
#include "sad_sse.h"
#endif
#define NDEBUG
#include <assert.h>
#undef DEBUG
#undef DEBUG_ASM
#undef BENCHMARK
#undef COUNT_COMPARES
#define DIAMOND_SEARCH 0x0
#define FULL_SEARCH 0x1
#define SHIFT 8
#define MIN(a,b) ((a) > (b) ? (b) : (a))
#define ABS(a) ((a) >= 0 ? (a) : (-(a)))
struct motion_est_context_s
{
int initialized; // true if filter has been initialized
#ifdef COUNT_COMPARES
int compares;
#endif
/* same as mlt_frame's parameters */
int width, height;
/* Operational details */
int mb_w, mb_h;
int xstride, ystride;
uint8_t *cache_image; // Copy of current frame
uint8_t *former_image; // Copy of former frame
int search_method;
int skip_prediction;
int shot_change;
int limit_x, limit_y; // max x and y of a motion vector
int initial_thresh;
int check_chroma; // if check_chroma == 1 then compare chroma
int denoise;
int previous_msad;
int show_reconstruction;
int toggle_when_paused;
int show_residual;
/* bounds */
struct mlt_geometry_item_s bounds; // Current bounds (from filters crop_detect, autotrack rectangle, or other)
/* bounds in macroblock units; macroblocks are completely contained within the boundry */
int left_mb, prev_left_mb, right_mb, prev_right_mb;
int top_mb, prev_top_mb, bottom_mb, prev_bottom_mb;
/* size of our vector buffers */
int mv_buffer_height, mv_buffer_width, mv_size;
/* vector buffers */
int former_vectors_valid; //<! true if the previous frame's buffered motion vector data is valid
motion_vector *former_vectors;
motion_vector *current_vectors;
motion_vector *denoise_vectors;
mlt_position former_frame_position, current_frame_position;
/* diagnostic metrics */
float predictive_misses; // How often do the prediction motion vectors fail?
int comparison_average; // How far does the best estimation deviate from a perfect comparison?
int bad_comparisons;
int average_length;
int average_x, average_y;
/* run-time configurable comparison functions */
int (*compare_reference)(uint8_t *, uint8_t *, int, int, int, int);
int (*compare_optimized)(uint8_t *, uint8_t *, int, int, int, int);
};
// This is used to constrains pixel operations between two blocks to be within the image boundry
inline static int constrain( int *x, int *y, int *w, int *h,
const int dx, const int dy,
const int left, const int right,
const int top, const int bottom)
{
uint32_t penalty = 1 << SHIFT; // Retain a few extra bits of precision
int x2 = *x + dx;
int y2 = *y + dy;
int w_remains = *w;
int h_remains = *h;
// Origin of macroblock moves left of image boundy
if( *x < left || x2 < left ) {
w_remains = *w - left + ((*x < x2) ? *x : x2);
*x += *w - w_remains;
}
// Portion of macroblock moves right of image boundry
else if( *x + *w > right || x2 + *w > right )
w_remains = right - ((*x > x2) ? *x : x2);
// Origin of macroblock moves above image boundy
if( *y < top || y2 < top ) {
h_remains = *h - top + ((*y < y2) ? *y : y2);
*y += *h - h_remains;
}
// Portion of macroblock moves bellow image boundry
else if( *y + *h > bottom || y2 + *h > bottom )
h_remains = bottom - ((*y > y2) ? *y : y2);
if( w_remains == *w && h_remains == *h ) return penalty;
if( w_remains <= 0 || h_remains <= 0) return 0; // Block is clipped out of existance
penalty = (*w * *h * penalty)
/ ( w_remains * h_remains); // Recipricol of the fraction of the block that remains
assert(*x >= left); assert(x2 + *w - w_remains >= left);
assert(*y >= top); assert(y2 + *h - h_remains >= top);
assert(*x + w_remains <= right); assert(x2 + w_remains <= right);
assert(*y + h_remains <= bottom); assert(y2 + h_remains <= bottom);
*w = w_remains; // Update the width and height
*h = h_remains;
return penalty;
}
/** /brief Reference Sum of Absolute Differences comparison function
*
*/
static int sad_reference( uint8_t *block1, uint8_t *block2, const int xstride, const int ystride, const int w, const int h )
{
int i, j, score = 0;
for ( j = 0; j < h; j++ ){
for ( i = 0; i < w; i++ ){
score += ABS( block1[i*xstride] - block2[i*xstride] );
}
block1 += ystride;
block2 += ystride;
}
return score;
}
/** /brief Abstracted block comparison function
*/
inline static int block_compare( uint8_t *block1,
uint8_t *block2,
int x,
int y,
int dx,
int dy,
struct motion_est_context_s *c)
{
#ifdef COUNT_COMPARES
c->compares++;
#endif
int score;
// Default comparison may be overridden by the slower, more capable reference comparison
int (*cmp)(uint8_t *, uint8_t *, int, int, int, int) = c->compare_optimized;
// vector displacement limited has been exceeded
if( ABS( dx ) >= c->limit_x || ABS( dy ) >= c->limit_y )
return MAX_MSAD;
int mb_w = c->mb_w; // Some writeable local copies
int mb_h = c->mb_h;
// Determine if either macroblock got clipped
int penalty = constrain( &x, &y, &mb_w, &mb_h, dx, dy, 0, c->width, 0, c->height);
// Some gotchas
if( penalty == 0 ) // Clipped out of existance: Return worst score
return MAX_MSAD;
else if( penalty != 1<<SHIFT ) // Nonstandard macroblock dimensions: Disable SIMD optimizizations.
cmp = c->compare_reference;
// Calculate the memory locations of the macroblocks
block1 += x * c->xstride + y * c->ystride;
block2 += (x+dx) * c->xstride + (y+dy) * c->ystride;
#ifdef DEBUG_ASM
if( penalty == 1<<SHIFT ){
score = c->compare_reference( block1, block2, c->xstride, c->ystride, mb_w, mb_h );
int score2 = c->compare_optimized( block1, block2, c->xstride, c->ystride, mb_w, mb_h );
if ( score != score2 )
fprintf(stderr, "Your assembly doesn't work! Reference: %d Asm: %d\n", score, score2);
}
else
#endif
score = cmp( block1, block2, c->xstride, c->ystride, mb_w, mb_h );
return ( score * penalty ) >> SHIFT; // Ditch the extra precision
}
static inline void check_candidates ( uint8_t *ref,
uint8_t *candidate_base,
const int x,
const int y,
const motion_vector *candidates,// Contains to_x & to_y
const int count, // Number of candidates
const int unique, // Sometimes we know the candidates are unique
motion_vector *result,
struct motion_est_context_s *c )
{
int score, i, j;
/* Scan for the best candidate */
for ( i = 0; i < count; i++ )
{
// this little dohicky ignores duplicate candidates, if they are possible
if ( unique == 0 ) {
j = 0;
while ( j < i )
{
if ( candidates[j].dx == candidates[i].dx &&
candidates[j].dy == candidates[i].dy )
goto next_for_loop;
j++;
}
}
// Luma
score = block_compare( ref, candidate_base,
x, y,
candidates[i].dx, // from
candidates[i].dy,
c);
if ( score < result->msad ) { // New minimum
result->dx = candidates[i].dx;
result->dy = candidates[i].dy;
result->msad = score;
}
next_for_loop:;
}
}
/* /brief Diamond search
* Operates on a single macroblock
*/
static inline void diamond_search(
uint8_t *ref, //<! Image data from previous frame
uint8_t *candidate_base, //<! Image data in current frame
const int x, //<! X upper left corner of macroblock
const int y, //<! U upper left corner of macroblock
struct motion_vector_s *result, //<! Best predicted mv and eventual result
struct motion_est_context_s *c) //<! motion estimation context
{
// diamond search pattern
motion_vector candidates[4];
// Keep track of best and former best candidates
motion_vector best, former;
best.dx = 0;
best.dy = 0;
former.dx = 0;
former.dy = 0;
// The direction of the refinement needs to be known
motion_vector current;
int i, first = 1;
// Loop through the search pattern
while( 1 ) {
current.dx = result->dx;
current.dy = result->dy;
if ( first == 1 ) // Set the initial pattern
{
candidates[0].dx = result->dx + 1; candidates[0].dy = result->dy + 0;
candidates[1].dx = result->dx + 0; candidates[1].dy = result->dy + 1;
candidates[2].dx = result->dx - 1; candidates[2].dy = result->dy + 0;
candidates[3].dx = result->dx + 0; candidates[3].dy = result->dy - 1;
i = 4;
}
else // Construct the next portion of the search pattern
{
candidates[0].dx = result->dx + best.dx;
candidates[0].dy = result->dy + best.dy;
if (best.dx == former.dx && best.dy == former.dy) {
candidates[1].dx = result->dx + best.dy;
candidates[1].dy = result->dy + best.dx; // Yes, the wires
candidates[2].dx = result->dx - best.dy; // are crossed
candidates[2].dy = result->dy - best.dx;
i = 3;
} else {
candidates[1].dx = result->dx + former.dx;
candidates[1].dy = result->dy + former.dy;
i = 2;
}
former.dx = best.dx; former.dy = best.dy; // Keep track of new former best
}
check_candidates ( ref, candidate_base, x, y, candidates, i, 1, result, c );
// Which candidate was the best?
best.dx = result->dx - current.dx;
best.dy = result->dy - current.dy;
// A better canidate was not found
if ( best.dx == 0 && best.dy == 0 )
return;
if ( first == 1 ){
first = 0;
former.dx = best.dx; former.dy = best.dy; // First iteration, sensible value for former.d*
}
}
}
/* /brief Full (brute) search
* Operates on a single macroblock
*/
__attribute__((used))
static void full_search(
uint8_t *ref, //<! Image data from previous frame
uint8_t *candidate_base, //<! Image data in current frame
int x, //<! X upper left corner of macroblock
int y, //<! U upper left corner of macroblock
struct motion_vector_s *result, //<! Best predicted mv and eventual result
struct motion_est_context_s *c) //<! motion estimation context
{
// Keep track of best candidate
int i,j,score;
// Go loopy
for( i = -c->mb_w; i <= c->mb_w; i++ ){
for( j = -c->mb_h; j <= c->mb_h; j++ ){
score = block_compare( ref, candidate_base,
x,
y,
x + i,
y + j,
c);
if ( score < result->msad ) {
result->dx = i;
result->dy = j;
result->msad = score;
}
}
}
}
// Macros for pointer calculations
#define CURRENT(i,j) ( c->current_vectors + (j)*c->mv_buffer_width + (i) )
#define FORMER(i,j) ( c->former_vectors + (j)*c->mv_buffer_width + (i) )
#define DENOISE(i,j) ( c->denoise_vectors + (j)*c->mv_buffer_width + (i) )
int ncompare (const void * a, const void * b)
{
return ( *(int*)a - *(int*)b );
}
// motion vector denoising
// for x and y components seperately,
// change the vector to be the median value of the 9 adjacent vectors
static void median_denoise( motion_vector *v, struct motion_est_context_s *c )
{
int xvalues[9], yvalues[9];
int i,j,n;
for( j = c->top_mb; j <= c->bottom_mb; j++ )
for( i = c->left_mb; i <= c->right_mb; i++ ){
{
n = 0;
xvalues[n ] = CURRENT(i,j)->dx; // Center
yvalues[n++] = CURRENT(i,j)->dy;
if( i > c->left_mb ) // Not in First Column
{
xvalues[n ] = CURRENT(i-1,j)->dx; // Left
yvalues[n++] = CURRENT(i-1,j)->dy;
if( j > c->top_mb ) {
xvalues[n ] = CURRENT(i-1,j-1)->dx; // Upper Left
yvalues[n++] = CURRENT(i-1,j-1)->dy;
}
if( j < c->bottom_mb ) {
xvalues[n ] = CURRENT(i-1,j+1)->dx; // Bottom Left
yvalues[n++] = CURRENT(i-1,j+1)->dy;
}
}
if( i < c->right_mb ) // Not in Last Column
{
xvalues[n ] = CURRENT(i+1,j)->dx; // Right
yvalues[n++] = CURRENT(i+1,j)->dy;
if( j > c->top_mb ) {
xvalues[n ] = CURRENT(i+1,j-1)->dx; // Upper Right
yvalues[n++] = CURRENT(i+1,j-1)->dy;
}
if( j < c->bottom_mb ) {
xvalues[n ] = CURRENT(i+1,j+1)->dx; // Bottom Right
yvalues[n++] = CURRENT(i+1,j+1)->dy;
}
}
if( j > c->top_mb ) // Not in First Row
{
xvalues[n ] = CURRENT(i,j-1)->dx; // Top
yvalues[n++] = CURRENT(i,j-1)->dy;
}
if( j < c->bottom_mb ) // Not in Last Row
{
xvalues[n ] = CURRENT(i,j+1)->dx; // Bottom
yvalues[n++] = CURRENT(i,j+1)->dy;
}
qsort (xvalues, n, sizeof(int), ncompare);
qsort (yvalues, n, sizeof(int), ncompare);
if( n % 2 == 1 ) {
DENOISE(i,j)->dx = xvalues[n/2];
DENOISE(i,j)->dy = yvalues[n/2];
}
else {
DENOISE(i,j)->dx = (xvalues[n/2] + xvalues[n/2+1])/2;
DENOISE(i,j)->dy = (yvalues[n/2] + yvalues[n/2+1])/2;
}
}
}
motion_vector *t = c->current_vectors;
c->current_vectors = c->denoise_vectors;
c->denoise_vectors = t;
}
// Credits: ffmpeg
// return the median
static inline int median_predictor(int a, int b, int c) {
if ( a > b ){
if ( c > b ){
if ( c > a ) b = a;
else b = c;
}
} else {
if ( b > c ){
if ( c > a ) b = c;
else b = a;
}
}
return b;
}
/** /brief Motion search
*
* For each macroblock in the current frame, estimate the block from the last frame that
* matches best.
*
* Vocab: Colocated - the pixel in the previous frame at the current position
*
* Based on enhanced predictive zonal search. [Tourapis 2002]
*/
static void motion_search( uint8_t *from, //<! Image data.
uint8_t *to, //<! Image data. Rigid grid.
struct motion_est_context_s *c) //<! The context
{
#ifdef COUNT_COMPARES
compares = 0;
#endif
motion_vector candidates[10];
motion_vector *here; // This one gets used alot (about 30 times per macroblock)
int n = 0;
int i, j, count=0;
// For every macroblock, perform motion vector estimation
for( i = c->left_mb; i <= c->right_mb; i++ ){
for( j = c->top_mb; j <= c->bottom_mb; j++ ){
here = CURRENT(i,j);
here->valid = 1;
here->color = 100;
here->msad = MAX_MSAD;
count++;
n = 0;
/* Stack the predictors [i.e. checked in reverse order] */
/* Adjacent to collocated */
if( c->former_vectors_valid )
{
// Top of colocated
if( j > c->prev_top_mb ){// && COL_TOP->valid ){
candidates[n ].dx = FORMER(i,j-1)->dx;
candidates[n++].dy = FORMER(i,j-1)->dy;
}
// Left of colocated
if( i > c->prev_left_mb ){// && COL_LEFT->valid ){
candidates[n ].dx = FORMER(i-1,j)->dx;
candidates[n++].dy = FORMER(i-1,j)->dy;
}
// Right of colocated
if( i < c->prev_right_mb ){// && COL_RIGHT->valid ){
candidates[n ].dx = FORMER(i+1,j)->dx;
candidates[n++].dy = FORMER(i+1,j)->dy;
}
// Bottom of colocated
if( j < c->prev_bottom_mb ){// && COL_BOTTOM->valid ){
candidates[n ].dx = FORMER(i,j+1)->dx;
candidates[n++].dy = FORMER(i,j+1)->dy;
}
// And finally, colocated
candidates[n ].dx = FORMER(i,j)->dx;
candidates[n++].dy = FORMER(i,j)->dy;
}
// For macroblocks not in the top row
if ( j > c->top_mb) {
// Top if ( TOP->valid ) {
candidates[n ].dx = CURRENT(i,j-1)->dx;
candidates[n++].dy = CURRENT(i,j-1)->dy;
//}
// Top-Right, macroblocks not in the right row
if ( i < c->right_mb ){// && TOP_RIGHT->valid ) {
candidates[n ].dx = CURRENT(i+1,j-1)->dx;
candidates[n++].dy = CURRENT(i+1,j-1)->dy;
}
}
// Left, Macroblocks not in the left column
if ( i > c->left_mb ){// && LEFT->valid ) {
candidates[n ].dx = CURRENT(i-1,j)->dx;
candidates[n++].dy = CURRENT(i-1,j)->dy;
}
/* Median predictor vector (median of left, top, and top right adjacent vectors) */
if ( i > c->left_mb && j > c->top_mb && i < c->right_mb
)//&& LEFT->valid && TOP->valid && TOP_RIGHT->valid )
{
candidates[n ].dx = median_predictor( CURRENT(i-1,j)->dx, CURRENT(i,j-1)->dx, CURRENT(i+1,j-1)->dx);
candidates[n++].dy = median_predictor( CURRENT(i-1,j)->dy, CURRENT(i,j-1)->dy, CURRENT(i+1,j-1)->dy);
}
// Zero vector
candidates[n ].dx = 0;
candidates[n++].dy = 0;
int x = i * c->mb_w;
int y = j * c->mb_h;
check_candidates ( to, from, x, y, candidates, n, 0, here, c );
#ifndef FULLSEARCH
diamond_search( to, from, x, y, here, c);
#else
full_search( to, from, x, y, here, c);
#endif
assert( x + c->mb_w + here->dx > 0 ); // All macroblocks must have area > 0
assert( y + c->mb_h + here->dy > 0 );
assert( x + here->dx < c->width );
assert( y + here->dy < c->height );
} /* End column loop */
} /* End row loop */
#ifndef __DARWIN__
asm volatile ( "emms" );
#endif
#ifdef COUNT_COMPARES
fprintf(stderr, "%d comparisons per block were made", compares/count);
#endif
return;
}
void collect_post_statistics( struct motion_est_context_s *c ) {
c->comparison_average = 0;
c->average_length = 0;
c->average_x = 0;
c->average_y = 0;
int i, j, count = 0;
for ( i = c->left_mb; i <= c->right_mb; i++ ){
for ( j = c->top_mb; j <= c->bottom_mb; j++ ){
count++;
c->comparison_average += CURRENT(i,j)->msad;
c->average_x += CURRENT(i,j)->dx;
c->average_y += CURRENT(i,j)->dy;
}
}
if ( count > 0 )
{
c->comparison_average /= count;
c->average_x /= count;
c->average_y /= count;
c->average_length = sqrt( c->average_x * c->average_x + c->average_y * c->average_y );
}
}
static void init_optimizations( struct motion_est_context_s *c )
{
switch(c->mb_w){
#ifndef __DARWIN__
case 4: if(c->mb_h == 4) c->compare_optimized = sad_sse_422_luma_4x4;
else c->compare_optimized = sad_sse_422_luma_4w;
break;
case 8: if(c->mb_h == 8) c->compare_optimized = sad_sse_422_luma_8x8;
else c->compare_optimized = sad_sse_422_luma_8w;
break;
case 16: if(c->mb_h == 16) c->compare_optimized = sad_sse_422_luma_16x16;
else c->compare_optimized = sad_sse_422_luma_16w;
break;
case 32: if(c->mb_h == 32) c->compare_optimized = sad_sse_422_luma_32x32;
else c->compare_optimized = sad_sse_422_luma_32w;
break;
case 64: c->compare_optimized = sad_sse_422_luma_64w;
break;
#endif
default: c->compare_optimized = sad_reference;
break;
}
}
inline static void set_red(uint8_t *image, struct motion_est_context_s *c)
{
int n;
for( n = 0; n < c->width * c->height * 2; n+=4 )
{
image[n] = 79;
image[n+1] = 91;
image[n+2] = 79;
image[n+3] = 237;
}
}
static void show_residual( uint8_t *result, struct motion_est_context_s *c )
{
int i, j;
int x,y,w,h;
int dx, dy;
int tx,ty;
uint8_t *b, *r;
// set_red(result,c);
for( j = c->top_mb; j <= c->bottom_mb; j++ ){
for( i = c->left_mb; i <= c->right_mb; i++ ){
dx = CURRENT(i,j)->dx;
dy = CURRENT(i,j)->dy;
w = c->mb_w;
h = c->mb_h;
x = i * w;
y = j * h;
// Denoise function caused some blocks to be completely clipped, ignore them
if (constrain( &x, &y, &w, &h, dx, dy, 0, c->width, 0, c->height) == 0 )
continue;
for( ty = y; ty < y + h ; ty++ ){
for( tx = x; tx < x + w ; tx++ ){
b = c->former_image + (tx+dx)*c->xstride + (ty+dy)*c->ystride;
r = result + tx*c->xstride + ty*c->ystride;
r[0] = 16 + ABS( r[0] - b[0] );
if( dx % 2 == 0 )
r[1] = 128 + ABS( r[1] - b[1] );
else
// FIXME: may exceed boundies
r[1] = 128 + ABS( r[1] - ( *(b-1) + b[3] ) /2 );
}
}
}
}
}
static void show_reconstruction( uint8_t *result, struct motion_est_context_s *c )
{
int i, j;
int x,y,w,h;
int dx,dy;
uint8_t *r, *s;
int tx,ty;
for( i = c->left_mb; i <= c->right_mb; i++ ){
for( j = c->top_mb; j <= c->bottom_mb; j++ ){
dx = CURRENT(i,j)->dx;
dy = CURRENT(i,j)->dy;
w = c->mb_w;
h = c->mb_h;
x = i * w;
y = j * h;
// Denoise function caused some blocks to be completely clipped, ignore them
if (constrain( &x, &y, &w, &h, dx, dy, 0, c->width, 0, c->height) == 0 )
continue;
for( ty = y; ty < y + h ; ty++ ){
for( tx = x; tx < x + w ; tx++ ){
r = result + tx*c->xstride + ty*c->ystride;
s = c->former_image + (tx+dx)*c->xstride + (ty+dy)*c->ystride;
r[0] = s[0];
if( dx % 2 == 0 )
r[1] = s[1];
else
// FIXME: may exceed boundies
r[1] = ( *(s-1) + s[3] ) /2;
}
}
}
}
}
// Image stack(able) method
static int filter_get_image( mlt_frame frame, uint8_t **image, mlt_image_format *format, int *width, int *height, int writable )
{
// Get the filter
mlt_filter filter = mlt_frame_pop_service( frame );
// Get the motion_est context object
struct motion_est_context_s *c = mlt_properties_get_data( MLT_FILTER_PROPERTIES( filter ), "context", NULL);
// Get the new image and frame number
int error = mlt_frame_get_image( frame, image, format, width, height, 1 );
#ifdef BENCHMARK
struct timeval start; gettimeofday(&start, NULL );
#endif
if( error != 0 )
mlt_properties_debug( MLT_FRAME_PROPERTIES(frame), "error after mlt_frame_get_image() in motion_est", stderr );
c->current_frame_position = mlt_frame_get_position( frame );
/* Context Initialization */
if ( c->initialized == 0 ) {
// Get the filter properties object
mlt_properties properties = mlt_filter_properties( filter );
c->width = *width;
c->height = *height;
/* Get parameters that may have been overridden */
if( mlt_properties_get( properties, "macroblock_width") != NULL )
c->mb_w = mlt_properties_get_int( properties, "macroblock_width");
if( mlt_properties_get( properties, "macroblock_height") != NULL )
c->mb_h = mlt_properties_get_int( properties, "macroblock_height");
if( mlt_properties_get( properties, "prediction_thresh") != NULL )
c->initial_thresh = mlt_properties_get_int( properties, "prediction_thresh" );
else
c->initial_thresh = c->mb_w * c->mb_h;
if( mlt_properties_get( properties, "search_method") != NULL )
c->search_method = mlt_properties_get_int( properties, "search_method");
if( mlt_properties_get( properties, "skip_prediction") != NULL )
c->skip_prediction = mlt_properties_get_int( properties, "skip_prediction");
if( mlt_properties_get( properties, "limit_x") != NULL )
c->limit_x = mlt_properties_get_int( properties, "limit_x");
if( mlt_properties_get( properties, "limit_y") != NULL )
c->limit_y = mlt_properties_get_int( properties, "limit_y");
if( mlt_properties_get( properties, "check_chroma" ) != NULL )
c->check_chroma = mlt_properties_get_int( properties, "check_chroma" );
if( mlt_properties_get( properties, "denoise" ) != NULL )
c->denoise = mlt_properties_get_int( properties, "denoise" );
if( mlt_properties_get( properties, "show_reconstruction" ) != NULL )
c->show_reconstruction = mlt_properties_get_int( properties, "show_reconstruction" );
if( mlt_properties_get( properties, "show_residual" ) != NULL )
c->show_residual = mlt_properties_get_int( properties, "show_residual" );
if( mlt_properties_get( properties, "toggle_when_paused" ) != NULL )
c->toggle_when_paused = mlt_properties_get_int( properties, "toggle_when_paused" );
init_optimizations( c );
// Calculate the dimensions in macroblock units
c->mv_buffer_width = (*width / c->mb_w);
c->mv_buffer_height = (*height / c->mb_h);
// Size of the motion vector buffer
c->mv_size = c->mv_buffer_width * c->mv_buffer_height * sizeof(struct motion_vector_s);
// Allocate the motion vector buffers
c->former_vectors = mlt_pool_alloc( c->mv_size );
c->current_vectors = mlt_pool_alloc( c->mv_size );
c->denoise_vectors = mlt_pool_alloc( c->mv_size );
// Register motion buffers for destruction
mlt_properties_set_data( properties, "current_motion_vectors", (void *)c->current_vectors, 0, mlt_pool_release, NULL );
mlt_properties_set_data( properties, "former_motion_vectors", (void *)c->former_vectors, 0, mlt_pool_release, NULL );
mlt_properties_set_data( properties, "denoise_motion_vectors", (void *)c->denoise_vectors, 0, mlt_pool_release, NULL );
c->former_vectors_valid = 0;
memset( c->former_vectors, 0, c->mv_size );
// Calculate the size of our steps (the number of bytes that seperate adjacent pixels in X and Y direction)
switch( *format ) {
case mlt_image_yuv422:
c->xstride = 2;
c->ystride = c->xstride * *width;
break;
default:
// I don't know
fprintf(stderr, "\"I am unfamiliar with your new fangled pixel format!\" -filter_motion_est\n");
return -1;
}
// Allocate a cache for the previous frame's image
c->former_image = mlt_pool_alloc( *width * *height * 2 );
c->cache_image = mlt_pool_alloc( *width * *height * 2 );
// Register for destruction
mlt_properties_set_data( properties, "cache_image", (void *)c->cache_image, 0, mlt_pool_release, NULL );
mlt_properties_set_data( properties, "former_image", (void *)c->former_image, 0, mlt_pool_release, NULL );
c->former_frame_position = c->current_frame_position;
c->previous_msad = 0;
c->initialized = 1;
}
/* Check to see if somebody else has given us bounds */
struct mlt_geometry_item_s *bounds = mlt_properties_get_data( MLT_FRAME_PROPERTIES( frame ), "bounds", NULL );
if( bounds != NULL ) {
// translate pixel units (from bounds) to macroblock units
// make sure whole macroblock stays within bounds
c->left_mb = ( bounds->x + c->mb_w - 1 ) / c->mb_w;
c->top_mb = ( bounds->y + c->mb_h - 1 ) / c->mb_h;
c->right_mb = ( bounds->x + bounds->w ) / c->mb_w - 1;
c->bottom_mb = ( bounds->y + bounds->h ) / c->mb_h - 1;
c->bounds.x = bounds->x;
c->bounds.y = bounds->y;
c->bounds.w = bounds->w;
c->bounds.h = bounds->h;
} else {
c->left_mb = c->prev_left_mb = 0;
c->top_mb = c->prev_top_mb = 0;
c->right_mb = c->prev_right_mb = c->mv_buffer_width - 1; // Zero indexed
c->bottom_mb = c->prev_bottom_mb = c->mv_buffer_height - 1;
c->bounds.x = 0;
c->bounds.y = 0;
c->bounds.w = *width;
c->bounds.h = *height;
}
// If video is advancing, run motion vector algorithm and etc...
if( c->former_frame_position + 1 == c->current_frame_position )
{
// Swap the motion vector buffers and reuse allocated memory
struct motion_vector_s *temp = c->current_vectors;
c->current_vectors = c->former_vectors;
c->former_vectors = temp;
// This is done because filter_vismv doesn't pay attention to frame boundry
memset( c->current_vectors, 0, c->mv_size );
// Perform the motion search
motion_search( c->cache_image, *image, c );
collect_post_statistics( c );
// Detect shot changes
if( c->comparison_average > 10 * c->mb_w * c->mb_h &&
c->comparison_average > c->previous_msad * 2 )
{
fprintf(stderr, " - SAD: %d <<Shot change>>\n", c->comparison_average);
mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "shot_change", 1);
// c->former_vectors_valid = 0; // Invalidate the previous frame's predictors
c->shot_change = 1;
}
else {
c->former_vectors_valid = 1;
c->shot_change = 0;
//fprintf(stderr, " - SAD: %d\n", c->comparison_average);
}
c->previous_msad = c->comparison_average;
if( c->comparison_average != 0 ) { // If the frame is not a duplicate of the previous frame
// denoise the vector buffer
if( c->denoise )
median_denoise( c->current_vectors, c );
// Pass the new vector data into the frame
mlt_properties_set_data( MLT_FRAME_PROPERTIES( frame ), "motion_est.vectors",
(void*)c->current_vectors, c->mv_size, NULL, NULL );
// Cache the frame's image. Save the old cache. Reuse memory.
// After this block, exactly two unique frames will be cached
uint8_t *timg = c->cache_image;
c->cache_image = c->former_image;
c->former_image = timg;
memcpy( c->cache_image, *image, *width * *height * c->xstride );
}
else {
// Undo the Swap, This fixes the ugliness caused by a duplicate frame
temp = c->current_vectors;
c->current_vectors = c->former_vectors;
c->former_vectors = temp;
mlt_properties_set_data( MLT_FRAME_PROPERTIES( frame ), "motion_est.vectors",
(void*)c->former_vectors, c->mv_size, NULL, NULL );
}
if( c->shot_change == 1)
;
else if( c->show_reconstruction )
show_reconstruction( *image, c );
else if( c->show_residual )
show_residual( *image, c );
}
// paused
else if( c->former_frame_position == c->current_frame_position )
{
// Pass the old vector data into the frame if it's valid
if( c->former_vectors_valid == 1 ) {
mlt_properties_set_data( MLT_FRAME_PROPERTIES( frame ), "motion_est.vectors",
(void*)c->current_vectors, c->mv_size, NULL, NULL );
if( c->shot_change == 1)
;
else if( c->toggle_when_paused == 1 ) {
if( c->show_reconstruction )
show_reconstruction( *image, c );
else if( c->show_residual )
show_residual( *image, c );
c->toggle_when_paused = 2;
}
else if( c->toggle_when_paused == 2 )
c->toggle_when_paused = 1;
else {
if( c->show_reconstruction )
show_reconstruction( *image, c );
else if( c->show_residual )
show_residual( *image, c );
}
}
mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "shot_change", c->shot_change);
}
// there was jump in frame number
else {
// fprintf(stderr, "Warning: there was a frame number jumped from %d to %d.\n", c->former_frame_position, c->current_frame_position);
c->former_vectors_valid = 0;
}
// Cache our bounding geometry for the next frame's processing
c->prev_left_mb = c->left_mb;
c->prev_top_mb = c->top_mb;
c->prev_right_mb = c->right_mb;
c->prev_bottom_mb = c->bottom_mb;
// Remember which frame this is
c->former_frame_position = c->current_frame_position;
mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "motion_est.macroblock_width", c->mb_w );
mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "motion_est.macroblock_height", c->mb_h );
mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "motion_est.left_mb", c->left_mb );
mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "motion_est.right_mb", c->right_mb );
mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "motion_est.top_mb", c->top_mb );
mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "motion_est.bottom_mb", c->bottom_mb );
#ifdef BENCHMARK
struct timeval finish; gettimeofday(&finish, NULL ); int difference = (finish.tv_sec - start.tv_sec) * 1000000 + (finish.tv_usec - start.tv_usec);
fprintf(stderr, " in frame %d:%d usec\n", c->current_frame_position, difference);
#endif
return error;
}
/** filter processing.
*/
static mlt_frame filter_process( mlt_filter this, mlt_frame frame )
{
// Keeps tabs on the filter object
mlt_frame_push_service( frame, this);
// Push the frame filter
mlt_frame_push_get_image( frame, filter_get_image );
return frame;
}
/** Constructor for the filter.
*/
mlt_filter filter_motion_est_init( char *arg )
{
mlt_filter this = mlt_filter_new( );
if ( this != NULL )
{
// Get the properties object
mlt_properties properties = MLT_FILTER_PROPERTIES( this );
// Initialize the motion estimation context
struct motion_est_context_s *context;
context = mlt_pool_alloc( sizeof(struct motion_est_context_s) );
mlt_properties_set_data( properties, "context", (void *)context, sizeof( struct motion_est_context_s ),
mlt_pool_release, NULL );
// Register the filter
this->process = filter_process;
/* defaults that may be overridden */
context->mb_w = 16;
context->mb_h = 16;
context->skip_prediction = 0;
context->limit_x = 64;
context->limit_y = 64;
context->search_method = DIAMOND_SEARCH; // FIXME: not used
context->check_chroma = 0;
context->denoise = 1;
context->show_reconstruction = 0;
context->show_residual = 0;
context->toggle_when_paused = 0;
/* reference functions that may have optimized versions */
context->compare_reference = sad_reference;
// The rest of the buffers will be initialized when the filter is first processed
context->initialized = 0;
}
return this;
}
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